Postinstallation configuration


OpenShift Container Platform 4.17

Day 2 operations for OpenShift Container Platform

Red Hat OpenShift Documentation Team

Abstract

This document provides instructions and guidance on post installation activities for OpenShift Container Platform.

Chapter 1. Postinstallation configuration overview

After installing OpenShift Container Platform, a cluster administrator can configure and customize the following components:

  • Machine
  • Bare metal
  • Cluster
  • Node
  • Network
  • Storage
  • Users
  • Alerts and notifications

1.1. Post-installation configuration tasks

You can perform the post-installation configuration tasks to configure your environment to meet your need.

The following lists details these configurations:

  • Configure operating system features: The Machine Config Operator (MCO) manages MachineConfig objects. By using the MCO, you can configure nodes and custom resources.
  • Configure cluster features. You can modify the following features of an OpenShift Container Platform cluster:

    • Image registry
    • Networking configuration
    • Image build behavior
    • Identity provider
    • The etcd configuration
    • Machine set creation to handle the workloads
    • Cloud provider credential management
  • Configuring a private cluster: By default, the installation program provisions OpenShift Container Platform by using a publicly accessible DNS and endpoints. To make your cluster accessible only from within an internal network, configure the following components to make them private:

    • DNS
    • Ingress Controller
    • API server
  • Perform node operations: By default, OpenShift Container Platform uses Red Hat Enterprise Linux CoreOS (RHCOS) compute machines. You can perform the following node operations:

    • Add and remove compute machines.
    • Add and remove taints and tolerations.
    • Configure the maximum number of pods per node.
    • Enable Device Manager.
  • Configure users: OAuth access tokens allow users to authenticate themselves to the API. You can configure OAuth to perform the following tasks:
  • Specify an identity provider
  • Use role-based access control to define and supply permissions to users
  • Install an Operator from OperatorHub
  • Configuring alert notifications: By default, firing alerts are displayed on the Alerting UI of the web console. You can also configure OpenShift Container Platform to send alert notifications to external systems.

Chapter 2. Configuring a private cluster

After you install an OpenShift Container Platform version 4.17 cluster, you can set some of its core components to be private.

2.1. About private clusters

By default, OpenShift Container Platform is provisioned using publicly-accessible DNS and endpoints. You can set the DNS, Ingress Controller, and API server to private after you deploy your private cluster.

Important

If the cluster has any public subnets, load balancer services created by administrators might be publicly accessible. To ensure cluster security, verify that these services are explicitly annotated as private.

DNS

If you install OpenShift Container Platform on installer-provisioned infrastructure, the installation program creates records in a pre-existing public zone and, where possible, creates a private zone for the cluster’s own DNS resolution. In both the public zone and the private zone, the installation program or cluster creates DNS entries for *.apps, for the Ingress object, and api, for the API server.

The *.apps records in the public and private zone are identical, so when you delete the public zone, the private zone seamlessly provides all DNS resolution for the cluster.

Ingress Controller

Because the default Ingress object is created as public, the load balancer is internet-facing and in the public subnets.

The Ingress Operator generates a default certificate for an Ingress Controller to serve as a placeholder until you configure a custom default certificate. Do not use Operator-generated default certificates in production clusters. The Ingress Operator does not rotate its own signing certificate or the default certificates that it generates. Operator-generated default certificates are intended as placeholders for custom default certificates that you configure.

API server

By default, the installation program creates appropriate network load balancers for the API server to use for both internal and external traffic.

On Amazon Web Services (AWS), separate public and private load balancers are created. The load balancers are identical except that an additional port is available on the internal one for use within the cluster. Although the installation program automatically creates or destroys the load balancer based on API server requirements, the cluster does not manage or maintain them. As long as you preserve the cluster’s access to the API server, you can manually modify or move the load balancers. For the public load balancer, port 6443 is open and the health check is configured for HTTPS against the /readyz path.

On Google Cloud Platform, a single load balancer is created to manage both internal and external API traffic, so you do not need to modify the load balancer.

On Microsoft Azure, both public and private load balancers are created. However, because of limitations in current implementation, you just retain both load balancers in a private cluster.

2.2. Configuring DNS records to be published in a private zone

For all OpenShift Container Platform clusters, whether public or private, DNS records are published in a public zone by default.

You can remove the public zone from the cluster DNS configuration to avoid exposing DNS records to the public. You might want to avoid exposing sensitive information, such as internal domain names, internal IP addresses, or the number of clusters at an organization, or you might simply have no need to publish records publicly. If all the clients that should be able to connect to services within the cluster use a private DNS service that has the DNS records from the private zone, then there is no need to have a public DNS record for the cluster.

After you deploy a cluster, you can modify its DNS to use only a private zone by modifying the DNS custom resource (CR). Modifying the DNS CR in this way means that any DNS records that are subsequently created are not published to public DNS servers, which keeps knowledge of the DNS records isolated to internal users. This can be done when you configure the cluster to be private, or if you never want DNS records to be publicly resolvable.

Alternatively, even in a private cluster, you might keep the public zone for DNS records because it allows clients to resolve DNS names for applications running on that cluster. For example, an organization can have machines that connect to the public internet and then establish VPN connections for certain private IP ranges in order to connect to private IP addresses. The DNS lookups from these machines use the public DNS to determine the private addresses of those services, and then connect to the private addresses over the VPN.

Procedure

  1. Review the DNS CR for your cluster by running the following command and observing the output:

    $ oc get dnses.config.openshift.io/cluster -o yaml

    Example output

    apiVersion: config.openshift.io/v1
    kind: DNS
    metadata:
      creationTimestamp: "2019-10-25T18:27:09Z"
      generation: 2
      name: cluster
      resourceVersion: "37966"
      selfLink: /apis/config.openshift.io/v1/dnses/cluster
      uid: 0e714746-f755-11f9-9cb1-02ff55d8f976
    spec:
      baseDomain: <base_domain>
      privateZone:
        tags:
          Name: <infrastructure_id>-int
          kubernetes.io/cluster/<infrastructure_id>: owned
      publicZone:
        id: Z2XXXXXXXXXXA4
    status: {}

    Note that the spec section contains both a private and a public zone.

  2. Patch the DNS CR to remove the public zone by running the following command:

    $ oc patch dnses.config.openshift.io/cluster --type=merge --patch='{"spec": {"publicZone": null}}'

    Example output

    dns.config.openshift.io/cluster patched

    The Ingress Operator consults the DNS CR definition when it creates DNS records for IngressController objects. If only private zones are specified, only private records are created.

    Important

    Existing DNS records are not modified when you remove the public zone. You must manually delete previously published public DNS records if you no longer want them to be published publicly.

Verification

  • Review the DNS CR for your cluster and confirm that the public zone was removed, by running the following command and observing the output:

    $ oc get dnses.config.openshift.io/cluster -o yaml

    Example output

    apiVersion: config.openshift.io/v1
    kind: DNS
    metadata:
      creationTimestamp: "2019-10-25T18:27:09Z"
      generation: 2
      name: cluster
      resourceVersion: "37966"
      selfLink: /apis/config.openshift.io/v1/dnses/cluster
      uid: 0e714746-f755-11f9-9cb1-02ff55d8f976
    spec:
      baseDomain: <base_domain>
      privateZone:
        tags:
          Name: <infrastructure_id>-int
          kubernetes.io/cluster/<infrastructure_id>-wfpg4: owned
    status: {}

2.3. Setting the Ingress Controller to private

After you deploy a cluster, you can modify its Ingress Controller to use only a private zone.

Procedure

  1. Modify the default Ingress Controller to use only an internal endpoint:

    $ oc replace --force --wait --filename - <<EOF
    apiVersion: operator.openshift.io/v1
    kind: IngressController
    metadata:
      namespace: openshift-ingress-operator
      name: default
    spec:
      endpointPublishingStrategy:
        type: LoadBalancerService
        loadBalancer:
          scope: Internal
    EOF

    Example output

    ingresscontroller.operator.openshift.io "default" deleted
    ingresscontroller.operator.openshift.io/default replaced

    The public DNS entry is removed, and the private zone entry is updated.

2.4. Restricting the API server to private

After you deploy a cluster to Amazon Web Services (AWS) or Microsoft Azure, you can reconfigure the API server to use only the private zone.

Prerequisites

  • Install the OpenShift CLI (oc).
  • Have access to the web console as a user with admin privileges.

Procedure

  1. In the web portal or console for your cloud provider, take the following actions:

    1. Locate and delete the appropriate load balancer component:

      • For AWS, delete the external load balancer. The API DNS entry in the private zone already points to the internal load balancer, which uses an identical configuration, so you do not need to modify the internal load balancer.
      • For Azure, delete the api-internal-v4 rule for the public load balancer.
    2. For Azure, configure the Ingress Controller endpoint publishing scope to Internal. For more information, see "Configuring the Ingress Controller endpoint publishing scope to Internal".
    3. For the Azure public load balancer, if you configure the Ingress Controller endpoint publishing scope to Internal and there are no existing inbound rules in the public load balancer, you must create an outbound rule explicitly to provide outbound traffic for the backend address pool. For more information, see the Microsoft Azure documentation about adding outbound rules.
    4. Delete the api.$clustername.$yourdomain or api.$clustername DNS entry in the public zone.
  2. AWS clusters: Remove the external load balancers:

    Important

    You can run the following steps only for an installer-provisioned infrastructure (IPI) cluster. For a user-provisioned infrastructure (UPI) cluster, you must manually remove or disable the external load balancers.

    • If your cluster uses a control plane machine set, delete the lines in the control plane machine set custom resource that configure your public or external load balancer:

      # ...
      providerSpec:
        value:
      # ...
          loadBalancers:
          - name: lk4pj-ext 1
            type: network 2
          - name: lk4pj-int
            type: network
      # ...
      1
      Delete the name value for the external load balancer, which ends in -ext.
      2
      Delete the type value for the external load balancer.
    • If your cluster does not use a control plane machine set, you must delete the external load balancers from each control plane machine.

      1. From your terminal, list the cluster machines by running the following command:

        $ oc get machine -n openshift-machine-api

        Example output

        NAME                            STATE     TYPE        REGION      ZONE         AGE
        lk4pj-master-0                  running   m4.xlarge   us-east-1   us-east-1a   17m
        lk4pj-master-1                  running   m4.xlarge   us-east-1   us-east-1b   17m
        lk4pj-master-2                  running   m4.xlarge   us-east-1   us-east-1a   17m
        lk4pj-worker-us-east-1a-5fzfj   running   m4.xlarge   us-east-1   us-east-1a   15m
        lk4pj-worker-us-east-1a-vbghs   running   m4.xlarge   us-east-1   us-east-1a   15m
        lk4pj-worker-us-east-1b-zgpzg   running   m4.xlarge   us-east-1   us-east-1b   15m

        The control plane machines contain master in the name.

      2. Remove the external load balancer from each control plane machine:

        1. Edit a control plane machine object to by running the following command:

          $ oc edit machines -n openshift-machine-api <control_plane_name> 1
          1
          Specify the name of the control plane machine object to modify.
        2. Remove the lines that describe the external load balancer, which are marked in the following example:

          # ...
          providerSpec:
            value:
          # ...
              loadBalancers:
              - name: lk4pj-ext 1
                type: network 2
              - name: lk4pj-int
                type: network
          # ...
          1
          Delete the name value for the external load balancer, which ends in -ext.
          2
          Delete the type value for the external load balancer.
        3. Save your changes and exit the object specification.
        4. Repeat this process for each of the control plane machines.

2.5. Configuring a private storage endpoint on Azure

You can leverage the Image Registry Operator to use private endpoints on Azure, which enables seamless configuration of private storage accounts when OpenShift Container Platform is deployed on private Azure clusters. This allows you to deploy the image registry without exposing public-facing storage endpoints.

Important

Do not configure a private storage endpoint on Microsoft Azure Red Hat OpenShift (ARO), because the endpoint can put your Microsoft Azure Red Hat OpenShift cluster in an unrecoverable state.

You can configure the Image Registry Operator to use private storage endpoints on Azure in one of two ways:

  • By configuring the Image Registry Operator to discover the VNet and subnet names
  • With user-provided Azure Virtual Network (VNet) and subnet names

2.5.1. Limitations for configuring a private storage endpoint on Azure

The following limitations apply when configuring a private storage endpoint on Azure:

  • When configuring the Image Registry Operator to use a private storage endpoint, public network access to the storage account is disabled. Consequently, pulling images from the registry outside of OpenShift Container Platform only works by setting disableRedirect: true in the registry Operator configuration. With redirect enabled, the registry redirects the client to pull images directly from the storage account, which will no longer work due to disabled public network access. For more information, see "Disabling redirect when using a private storage endpoint on Azure".
  • This operation cannot be undone by the Image Registry Operator.

2.5.2. Configuring a private storage endpoint on Azure by enabling the Image Registry Operator to discover VNet and subnet names

The following procedure shows you how to set up a private storage endpoint on Azure by configuring the Image Registry Operator to discover VNet and subnet names.

Prerequisites

  • You have configured the image registry to run on Azure.
  • Your network has been set up using the Installer Provisioned Infrastructure installation method.

    For users with a custom network setup, see "Configuring a private storage endpoint on Azure with user-provided VNet and subnet names".

Procedure

  1. Edit the Image Registry Operator config object and set networkAccess.type to Internal:

    $ oc edit configs.imageregistry/cluster
    # ...
    spec:
      # ...
       storage:
          azure:
            # ...
            networkAccess:
              type: Internal
    # ...
  2. Optional: Enter the following command to confirm that the Operator has completed provisioning. This might take a few minutes.

    $ oc get configs.imageregistry/cluster -o=jsonpath="{.spec.storage.azure.privateEndpointName}" -w
  3. Optional: If the registry is exposed by a route, and you are configuring your storage account to be private, you must disable redirect if you want pulls external to the cluster to continue to work. Enter the following command to disable redirect on the Image Operator configuration:

    $ oc patch configs.imageregistry cluster --type=merge -p '{"spec":{"disableRedirect": true}}'
    Note

    When redirect is enabled, pulling images from outside of the cluster will not work.

Verification

  1. Fetch the registry service name by running the following command:

    $ oc get imagestream -n openshift

    Example output

    NAME   IMAGE REPOSITORY                                                 TAGS     UPDATED
    cli    image-registry.openshift-image-registry.svc:5000/openshift/cli   latest   8 hours ago
    ...

  2. Enter debug mode by running the following command:

    $ oc debug node/<node_name>
  3. Run the suggested chroot command. For example:

    $ chroot /host
  4. Enter the following command to log in to your container registry:

    $ podman login --tls-verify=false -u unused -p $(oc whoami -t) image-registry.openshift-image-registry.svc:5000

    Example output

    Login Succeeded!

  5. Enter the following command to verify that you can pull an image from the registry:

    $ podman pull --tls-verify=false image-registry.openshift-image-registry.svc:5000/openshift/tools

    Example output

    Trying to pull image-registry.openshift-image-registry.svc:5000/openshift/tools/openshift/tools...
    Getting image source signatures
    Copying blob 6b245f040973 done
    Copying config 22667f5368 done
    Writing manifest to image destination
    Storing signatures
    22667f53682a2920948d19c7133ab1c9c3f745805c14125859d20cede07f11f9

2.5.3. Configuring a private storage endpoint on Azure with user-provided VNet and subnet names

Use the following procedure to configure a storage account that has public network access disabled and is exposed behind a private storage endpoint on Azure.

Prerequisites

  • You have configured the image registry to run on Azure.
  • You must know the VNet and subnet names used for your Azure environment.
  • If your network was configured in a separate resource group in Azure, you must also know its name.

Procedure

  1. Edit the Image Registry Operator config object and configure the private endpoint using your VNet and subnet names:

    $ oc edit configs.imageregistry/cluster
    # ...
    spec:
      # ...
       storage:
          azure:
            # ...
            networkAccess:
              type: Internal
              internal:
                subnetName: <subnet_name>
                vnetName: <vnet_name>
                networkResourceGroupName: <network_resource_group_name>
    # ...
  2. Optional: Enter the following command to confirm that the Operator has completed provisioning. This might take a few minutes.

    $ oc get configs.imageregistry/cluster -o=jsonpath="{.spec.storage.azure.privateEndpointName}" -w
    Note

    When redirect is enabled, pulling images from outside of the cluster will not work.

Verification

  1. Fetch the registry service name by running the following command:

    $ oc get imagestream -n openshift

    Example output

    NAME   IMAGE REPOSITORY                                                 TAGS     UPDATED
    cli    image-registry.openshift-image-registry.svc:5000/openshift/cli   latest   8 hours ago
    ...

  2. Enter debug mode by running the following command:

    $ oc debug node/<node_name>
  3. Run the suggested chroot command. For example:

    $ chroot /host
  4. Enter the following command to log in to your container registry:

    $ podman login --tls-verify=false -u unused -p $(oc whoami -t) image-registry.openshift-image-registry.svc:5000

    Example output

    Login Succeeded!

  5. Enter the following command to verify that you can pull an image from the registry:

    $ podman pull --tls-verify=false image-registry.openshift-image-registry.svc:5000/openshift/tools

    Example output

    Trying to pull image-registry.openshift-image-registry.svc:5000/openshift/tools/openshift/tools...
    Getting image source signatures
    Copying blob 6b245f040973 done
    Copying config 22667f5368 done
    Writing manifest to image destination
    Storing signatures
    22667f53682a2920948d19c7133ab1c9c3f745805c14125859d20cede07f11f9

2.5.4. Optional: Disabling redirect when using a private storage endpoint on Azure

By default, redirect is enabled when using the image registry. Redirect allows off-loading of traffic from the registry pods into the object storage, which makes pull faster. When redirect is enabled and the storage account is private, users from outside of the cluster are unable to pull images from the registry.

In some cases, users might want to disable redirect so that users from outside of the cluster can pull images from the registry.

Use the following procedure to disable redirect.

Prerequisites

  • You have configured the image registry to run on Azure.
  • You have configured a route.

Procedure

  • Enter the following command to disable redirect on the image registry configuration:

    $ oc patch configs.imageregistry cluster --type=merge -p '{"spec":{"disableRedirect": true}}'

Verification

  1. Fetch the registry service name by running the following command:

    $ oc get imagestream -n openshift

    Example output

    NAME   IMAGE REPOSITORY                                           TAGS     UPDATED
    cli    default-route-openshift-image-registry.<cluster_dns>/cli   latest   8 hours ago
    ...

  2. Enter the following command to log in to your container registry:

    $ podman login --tls-verify=false -u unused -p $(oc whoami -t) default-route-openshift-image-registry.<cluster_dns>

    Example output

    Login Succeeded!

  3. Enter the following command to verify that you can pull an image from the registry:

    $ podman pull --tls-verify=false default-route-openshift-image-registry.<cluster_dns>
    /openshift/tools

    Example output

    Trying to pull default-route-openshift-image-registry.<cluster_dns>/openshift/tools...
    Getting image source signatures
    Copying blob 6b245f040973 done
    Copying config 22667f5368 done
    Writing manifest to image destination
    Storing signatures
    22667f53682a2920948d19c7133ab1c9c3f745805c14125859d20cede07f11f9

Chapter 3. Configuring multi-architecture compute machines on an OpenShift cluster

3.1. About clusters with multi-architecture compute machines

An OpenShift Container Platform cluster with multi-architecture compute machines is a cluster that supports compute machines with different architectures.

Note

When there are nodes with multiple architectures in your cluster, the architecture of your image must be consistent with the architecture of the node. You need to ensure that the pod is assigned to the node with the appropriate architecture and that it matches the image architecture. For more information on assigning pods to nodes, see Assigning pods to nodes.

Important

The Cluster Samples Operator is not supported on clusters with multi-architecture compute machines. Your cluster can be created without this capability. For more information, see Cluster capabilities.

For information on migrating your single-architecture cluster to a cluster that supports multi-architecture compute machines, see Migrating to a cluster with multi-architecture compute machines.

3.1.1. Configuring your cluster with multi-architecture compute machines

To create a cluster with multi-architecture compute machines with different installation options and platforms, you can use the documentation in the following table:

Table 3.1. Cluster with multi-architecture compute machine installation options
Documentation sectionPlatformUser-provisioned installationInstaller-provisioned installationControl PlaneCompute node

Creating a cluster with multi-architecture compute machines on Azure

Microsoft Azure

 

aarch64 or x86_64

aarch64, x86_64

Creating a cluster with multi-architecture compute machines on AWS

Amazon Web Services (AWS)

 

aarch64 or x86_64

aarch64, x86_64

Creating a cluster with multi-architecture compute machines on GCP

Google Cloud Platform (GCP)

 

aarch64 or x86_64

aarch64, x86_64

Creating a cluster with multi-architecture compute machines on bare metal, IBM Power, or IBM Z

Bare metal

 

aarch64 or x86_64

aarch64, x86_64

IBM Power

 

x86_64 or ppc64le

x86_64, ppc64le

IBM Z

 

x86_64 or s390x

x86_64, s390x

Creating a cluster with multi-architecture compute machines on IBM Z® and IBM® LinuxONE with z/VM

IBM Z® and IBM® LinuxONE

 

x86_64

x86_64, s390x

Creating a cluster with multi-architecture compute machines on IBM Z® and IBM® LinuxONE with RHEL KVM

IBM Z® and IBM® LinuxONE

 

x86_64

x86_64, s390x

Creating a cluster with multi-architecture compute machines on IBM Power®

IBM Power®

 

x86_64

x86_64, ppc64le

Important

Autoscaling from zero is currently not supported on Google Cloud Platform (GCP).

3.2. Creating a cluster with multi-architecture compute machine on Azure

To deploy an Azure cluster with multi-architecture compute machines, you must first create a single-architecture Azure installer-provisioned cluster that uses the multi-architecture installer binary. For more information on Azure installations, see Installing a cluster on Azure with customizations.

You can also migrate your current cluster with single-architecture compute machines to a cluster with multi-architecture compute machines. For more information, see Migrating to a cluster with multi-architecture compute machines.

After creating a multi-architecture cluster, you can add nodes with different architectures to the cluster.

3.2.1. Verifying cluster compatibility

Before you can start adding compute nodes of different architectures to your cluster, you must verify that your cluster is multi-architecture compatible.

Prerequisites

  • You installed the OpenShift CLI (oc).

Procedure

  1. Log in to the OpenShift CLI (oc).
  2. You can check that your cluster uses the architecture payload by running the following command:

    $ oc adm release info -o jsonpath="{ .metadata.metadata}"

Verification

  • If you see the following output, your cluster is using the multi-architecture payload:

    {
     "release.openshift.io/architecture": "multi",
     "url": "https://access.redhat.com/errata/<errata_version>"
    }

    You can then begin adding multi-arch compute nodes to your cluster.

  • If you see the following output, your cluster is not using the multi-architecture payload:

    {
     "url": "https://access.redhat.com/errata/<errata_version>"
    }
    Important

    To migrate your cluster so the cluster supports multi-architecture compute machines, follow the procedure in Migrating to a cluster with multi-architecture compute machines.

3.2.2. Creating a 64-bit ARM boot image using the Azure image gallery

The following procedure describes how to manually generate a 64-bit ARM boot image.

Prerequisites

  • You installed the Azure CLI (az).
  • You created a single-architecture Azure installer-provisioned cluster with the multi-architecture installer binary.

Procedure

  1. Log in to your Azure account:

    $ az login
  2. Create a storage account and upload the aarch64 virtual hard disk (VHD) to your storage account. The OpenShift Container Platform installation program creates a resource group, however, the boot image can also be uploaded to a custom named resource group:

    $ az storage account create -n ${STORAGE_ACCOUNT_NAME} -g ${RESOURCE_GROUP} -l westus --sku Standard_LRS 1
    1
    The westus object is an example region.
  3. Create a storage container using the storage account you generated:

    $ az storage container create -n ${CONTAINER_NAME} --account-name ${STORAGE_ACCOUNT_NAME}
  4. You must use the OpenShift Container Platform installation program JSON file to extract the URL and aarch64 VHD name:

    1. Extract the URL field and set it to RHCOS_VHD_ORIGIN_URL as the file name by running the following command:

      $ RHCOS_VHD_ORIGIN_URL=$(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' | jq -r '.architectures.aarch64."rhel-coreos-extensions"."azure-disk".url')
    2. Extract the aarch64 VHD name and set it to BLOB_NAME as the file name by running the following command:

      $ BLOB_NAME=rhcos-$(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' | jq -r '.architectures.aarch64."rhel-coreos-extensions"."azure-disk".release')-azure.aarch64.vhd
  5. Generate a shared access signature (SAS) token. Use this token to upload the RHCOS VHD to your storage container with the following commands:

    $ end=`date -u -d "30 minutes" '+%Y-%m-%dT%H:%MZ'`
    $ sas=`az storage container generate-sas -n ${CONTAINER_NAME} --account-name ${STORAGE_ACCOUNT_NAME} --https-only --permissions dlrw --expiry $end -o tsv`
  6. Copy the RHCOS VHD into the storage container:

    $ az storage blob copy start --account-name ${STORAGE_ACCOUNT_NAME} --sas-token "$sas" \
     --source-uri "${RHCOS_VHD_ORIGIN_URL}" \
     --destination-blob "${BLOB_NAME}" --destination-container ${CONTAINER_NAME}

    You can check the status of the copying process with the following command:

    $ az storage blob show -c ${CONTAINER_NAME} -n ${BLOB_NAME} --account-name ${STORAGE_ACCOUNT_NAME} | jq .properties.copy

    Example output

    {
     "completionTime": null,
     "destinationSnapshot": null,
     "id": "1fd97630-03ca-489a-8c4e-cfe839c9627d",
     "incrementalCopy": null,
     "progress": "17179869696/17179869696",
     "source": "https://rhcos.blob.core.windows.net/imagebucket/rhcos-411.86.202207130959-0-azure.aarch64.vhd",
     "status": "success", 1
     "statusDescription": null
    }

    1
    If the status parameter displays the success object, the copying process is complete.
  7. Create an image gallery using the following command:

    $ az sig create --resource-group ${RESOURCE_GROUP} --gallery-name ${GALLERY_NAME}

    Use the image gallery to create an image definition. In the following example command, rhcos-arm64 is the name of the image definition.

    $ az sig image-definition create --resource-group ${RESOURCE_GROUP} --gallery-name ${GALLERY_NAME} --gallery-image-definition rhcos-arm64 --publisher RedHat --offer arm --sku arm64 --os-type linux --architecture Arm64 --hyper-v-generation V2
  8. To get the URL of the VHD and set it to RHCOS_VHD_URL as the file name, run the following command:

    $ RHCOS_VHD_URL=$(az storage blob url --account-name ${STORAGE_ACCOUNT_NAME} -c ${CONTAINER_NAME} -n "${BLOB_NAME}" -o tsv)
  9. Use the RHCOS_VHD_URL file, your storage account, resource group, and image gallery to create an image version. In the following example, 1.0.0 is the image version.

    $ az sig image-version create --resource-group ${RESOURCE_GROUP} --gallery-name ${GALLERY_NAME} --gallery-image-definition rhcos-arm64 --gallery-image-version 1.0.0 --os-vhd-storage-account ${STORAGE_ACCOUNT_NAME} --os-vhd-uri ${RHCOS_VHD_URL}
  10. Your arm64 boot image is now generated. You can access the ID of your image with the following command:

    $ az sig image-version show -r $GALLERY_NAME -g $RESOURCE_GROUP -i rhcos-arm64 -e 1.0.0

    The following example image ID is used in the recourseID parameter of the compute machine set:

    Example resourceID

    /resourceGroups/${RESOURCE_GROUP}/providers/Microsoft.Compute/galleries/${GALLERY_NAME}/images/rhcos-arm64/versions/1.0.0

3.2.3. Creating a 64-bit x86 boot image using the Azure image gallery

The following procedure describes how to manually generate a 64-bit x86 boot image.

Prerequisites

  • You installed the Azure CLI (az).
  • You created a single-architecture Azure installer-provisioned cluster with the multi-architecture installer binary.

Procedure

  1. Log in to your Azure account by running the following command:

    $ az login
  2. Create a storage account and upload the x86_64 virtual hard disk (VHD) to your storage account by running the following command. The OpenShift Container Platform installation program creates a resource group. However, the boot image can also be uploaded to a custom named resource group:

    $ az storage account create -n ${STORAGE_ACCOUNT_NAME} -g ${RESOURCE_GROUP} -l westus --sku Standard_LRS 1
    1
    The westus object is an example region.
  3. Create a storage container using the storage account you generated by running the following command:

    $ az storage container create -n ${CONTAINER_NAME} --account-name ${STORAGE_ACCOUNT_NAME}
  4. Use the OpenShift Container Platform installation program JSON file to extract the URL and x86_64 VHD name:

    1. Extract the URL field and set it to RHCOS_VHD_ORIGIN_URL as the file name by running the following command:

      $ RHCOS_VHD_ORIGIN_URL=$(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' | jq -r '.architectures.x86_64."rhel-coreos-extensions"."azure-disk".url')
    2. Extract the x86_64 VHD name and set it to BLOB_NAME as the file name by running the following command:

      $ BLOB_NAME=rhcos-$(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' | jq -r '.architectures.x86_64."rhel-coreos-extensions"."azure-disk".release')-azure.x86_64.vhd
  5. Generate a shared access signature (SAS) token. Use this token to upload the RHCOS VHD to your storage container by running the following commands:

    $ end=`date -u -d "30 minutes" '+%Y-%m-%dT%H:%MZ'`
    $ sas=`az storage container generate-sas -n ${CONTAINER_NAME} --account-name ${STORAGE_ACCOUNT_NAME} --https-only --permissions dlrw --expiry $end -o tsv`
  6. Copy the RHCOS VHD into the storage container by running the following command:

    $ az storage blob copy start --account-name ${STORAGE_ACCOUNT_NAME} --sas-token "$sas" \
     --source-uri "${RHCOS_VHD_ORIGIN_URL}" \
     --destination-blob "${BLOB_NAME}" --destination-container ${CONTAINER_NAME}

    You can check the status of the copying process by running the following command:

    $ az storage blob show -c ${CONTAINER_NAME} -n ${BLOB_NAME} --account-name ${STORAGE_ACCOUNT_NAME} | jq .properties.copy

    Example output

    {
     "completionTime": null,
     "destinationSnapshot": null,
     "id": "1fd97630-03ca-489a-8c4e-cfe839c9627d",
     "incrementalCopy": null,
     "progress": "17179869696/17179869696",
     "source": "https://rhcos.blob.core.windows.net/imagebucket/rhcos-411.86.202207130959-0-azure.aarch64.vhd",
     "status": "success", 1
     "statusDescription": null
    }

    1
    If the status parameter displays the success object, the copying process is complete.
  7. Create an image gallery by running the following command:

    $ az sig create --resource-group ${RESOURCE_GROUP} --gallery-name ${GALLERY_NAME}
  8. Use the image gallery to create an image definition by running the following command:

    $ az sig image-definition create --resource-group ${RESOURCE_GROUP} --gallery-name ${GALLERY_NAME} --gallery-image-definition rhcos-x86_64 --publisher RedHat --offer x86_64 --sku x86_64 --os-type linux --architecture x64 --hyper-v-generation V2

    In this example command, rhcos-x86_64 is the name of the image definition.

  9. To get the URL of the VHD and set it to RHCOS_VHD_URL as the file name, run the following command:

    $ RHCOS_VHD_URL=$(az storage blob url --account-name ${STORAGE_ACCOUNT_NAME} -c ${CONTAINER_NAME} -n "${BLOB_NAME}" -o tsv)
  10. Use the RHCOS_VHD_URL file, your storage account, resource group, and image gallery to create an image version by running the following command:

    $ az sig image-version create --resource-group ${RESOURCE_GROUP} --gallery-name ${GALLERY_NAME} --gallery-image-definition rhcos-arm64 --gallery-image-version 1.0.0 --os-vhd-storage-account ${STORAGE_ACCOUNT_NAME} --os-vhd-uri ${RHCOS_VHD_URL}

    In this example, 1.0.0 is the image version.

  11. Optional: Access the ID of the generated x86_64 boot image by running the following command:

    $ az sig image-version show -r $GALLERY_NAME -g $RESOURCE_GROUP -i rhcos-x86_64 -e 1.0.0

    The following example image ID is used in the recourseID parameter of the compute machine set:

    Example resourceID

    /resourceGroups/${RESOURCE_GROUP}/providers/Microsoft.Compute/galleries/${GALLERY_NAME}/images/rhcos-x86_64/versions/1.0.0

3.2.4. Adding a multi-architecture compute machine set to your Azure cluster

After creating a multi-architecture cluster, you can add nodes with different architectures.

You can add multi-architecture compute machines to a multi-architecture cluster in the following ways:

  • Adding 64-bit x86 compute machines to a cluster that uses 64-bit ARM control plane machines and already includes 64-bit ARM compute machines. In this case, 64-bit x86 is considered the secondary architecture.
  • Adding 64-bit ARM compute machines to a cluster that uses 64-bit x86 control plane machines and already includes 64-bit x86 compute machines. In this case, 64-bit ARM is considered the secondary architecture.

To create a custom compute machine set on Azure, see "Creating a compute machine set on Azure".

Note

Before adding a secondary architecture node to your cluster, it is recommended to install the Multiarch Tuning Operator, and deploy a ClusterPodPlacementConfig custom resource. For more information, see "Managing workloads on multi-architecture clusters by using the Multiarch Tuning Operator".

Prerequisites

  • You installed the OpenShift CLI (oc).
  • You created a 64-bit ARM or 64-bit x86 boot image.
  • You used the installation program to create a 64-bit ARM or 64-bit x86 single-architecture Azure cluster with the multi-architecture installer binary.

Procedure

  1. Log in to the OpenShift CLI (oc).
  2. Create a YAML file, and add the configuration to create a compute machine set to control the 64-bit ARM or 64-bit x86 compute nodes in your cluster.

    Example MachineSet object for an Azure 64-bit ARM or 64-bit x86 compute node

    apiVersion: machine.openshift.io/v1beta1
    kind: MachineSet
    metadata:
      labels:
        machine.openshift.io/cluster-api-cluster: <infrastructure_id>
        machine.openshift.io/cluster-api-machine-role: worker
        machine.openshift.io/cluster-api-machine-type: worker
      name: <infrastructure_id>-machine-set-0
      namespace: openshift-machine-api
    spec:
      replicas: 2
      selector:
        matchLabels:
          machine.openshift.io/cluster-api-cluster: <infrastructure_id>
          machine.openshift.io/cluster-api-machineset: <infrastructure_id>-machine-set-0
      template:
        metadata:
          labels:
            machine.openshift.io/cluster-api-cluster: <infrastructure_id>
            machine.openshift.io/cluster-api-machine-role: worker
            machine.openshift.io/cluster-api-machine-type: worker
            machine.openshift.io/cluster-api-machineset: <infrastructure_id>-machine-set-0
        spec:
          lifecycleHooks: {}
          metadata: {}
          providerSpec:
            value:
              acceleratedNetworking: true
              apiVersion: machine.openshift.io/v1beta1
              credentialsSecret:
                name: azure-cloud-credentials
                namespace: openshift-machine-api
              image:
                offer: ""
                publisher: ""
                resourceID: /resourceGroups/${RESOURCE_GROUP}/providers/Microsoft.Compute/galleries/${GALLERY_NAME}/images/rhcos-arm64/versions/1.0.0 1
                sku: ""
                version: ""
              kind: AzureMachineProviderSpec
              location: <region>
              managedIdentity: <infrastructure_id>-identity
              networkResourceGroup: <infrastructure_id>-rg
              osDisk:
                diskSettings: {}
                diskSizeGB: 128
                managedDisk:
                  storageAccountType: Premium_LRS
                osType: Linux
              publicIP: false
              publicLoadBalancer: <infrastructure_id>
              resourceGroup: <infrastructure_id>-rg
              subnet: <infrastructure_id>-worker-subnet
              userDataSecret:
                name: worker-user-data
              vmSize: Standard_D4ps_v5 2
              vnet: <infrastructure_id>-vnet
              zone: "<zone>"

    1
    Set the resourceID parameter to either arm64 or amd64 boot image.
    2
    Set the vmSize parameter to the instance type used in your installation. Some example instance types are Standard_D4ps_v5 or D8ps.
  3. Create the compute machine set by running the following command:

    $ oc create -f <file_name> 1
    1
    Replace <file_name> with the name of the YAML file with compute machine set configuration. For example: arm64-machine-set-0.yaml, or amd64-machine-set-0.yaml.

Verification

  1. Verify that the new machines are running by running the following command:

    $ oc get machineset -n openshift-machine-api

    The output must include the machine set that you created.

    Example output

    NAME                                                DESIRED  CURRENT  READY  AVAILABLE  AGE
    <infrastructure_id>-machine-set-0                   2        2      2          2  10m

  2. You can check if the nodes are ready and schedulable by running the following command:

    $ oc get nodes

3.3. Creating a cluster with multi-architecture compute machines on AWS

To create an AWS cluster with multi-architecture compute machines, you must first create a single-architecture AWS installer-provisioned cluster with the multi-architecture installer binary. For more information on AWS installations, see Installing a cluster on AWS with customizations.

You can also migrate your current cluster with single-architecture compute machines to a cluster with multi-architecture compute machines. For more information, see Migrating to a cluster with multi-architecture compute machines.

After creating a multi-architecture cluster, you can add nodes with different architectures to the cluster.

3.3.1. Verifying cluster compatibility

Before you can start adding compute nodes of different architectures to your cluster, you must verify that your cluster is multi-architecture compatible.

Prerequisites

  • You installed the OpenShift CLI (oc).

Procedure

  1. Log in to the OpenShift CLI (oc).
  2. You can check that your cluster uses the architecture payload by running the following command:

    $ oc adm release info -o jsonpath="{ .metadata.metadata}"

Verification

  • If you see the following output, your cluster is using the multi-architecture payload:

    {
     "release.openshift.io/architecture": "multi",
     "url": "https://access.redhat.com/errata/<errata_version>"
    }

    You can then begin adding multi-arch compute nodes to your cluster.

  • If you see the following output, your cluster is not using the multi-architecture payload:

    {
     "url": "https://access.redhat.com/errata/<errata_version>"
    }
    Important

    To migrate your cluster so the cluster supports multi-architecture compute machines, follow the procedure in Migrating to a cluster with multi-architecture compute machines.

3.3.2. Adding a multi-architecture compute machine set to your AWS cluster

After creating a multi-architecture cluster, you can add nodes with different architectures.

You can add multi-architecture compute machines to a multi-architecture cluster in the following ways:

  • Adding 64-bit x86 compute machines to a cluster that uses 64-bit ARM control plane machines and already includes 64-bit ARM compute machines. In this case, 64-bit x86 is considered the secondary architecture.
  • Adding 64-bit ARM compute machines to a cluster that uses 64-bit x86 control plane machines and already includes 64-bit x86 compute machines. In this case, 64-bit ARM is considered the secondary architecture.
Note

Before adding a secondary architecture node to your cluster, it is recommended to install the Multiarch Tuning Operator, and deploy a ClusterPodPlacementConfig custom resource. For more information, see "Managing workloads on multi-architecture clusters by using the Multiarch Tuning Operator".

Prerequisites

  • You installed the OpenShift CLI (oc).
  • You used the installation program to create an 64-bit ARM or 64-bit x86 single-architecture AWS cluster with the multi-architecture installer binary.

Procedure

  1. Log in to the OpenShift CLI (oc).
  2. Create a YAML file, and add the configuration to create a compute machine set to control the 64-bit ARM or 64-bit x86 compute nodes in your cluster.

    Example MachineSet object for an AWS 64-bit ARM or x86 compute node

    apiVersion: machine.openshift.io/v1beta1
    kind: MachineSet
    metadata:
      labels:
        machine.openshift.io/cluster-api-cluster: <infrastructure_id> 1
      name: <infrastructure_id>-aws-machine-set-0 2
      namespace: openshift-machine-api
    spec:
      replicas: 1
      selector:
        matchLabels:
          machine.openshift.io/cluster-api-cluster: <infrastructure_id> 3
          machine.openshift.io/cluster-api-machineset: <infrastructure_id>-<role>-<zone> 4
      template:
        metadata:
          labels:
            machine.openshift.io/cluster-api-cluster: <infrastructure_id>
            machine.openshift.io/cluster-api-machine-role: <role> 5
            machine.openshift.io/cluster-api-machine-type: <role> 6
            machine.openshift.io/cluster-api-machineset: <infrastructure_id>-<role>-<zone> 7
        spec:
          metadata:
            labels:
              node-role.kubernetes.io/<role>: ""
          providerSpec:
            value:
              ami:
                id: ami-02a574449d4f4d280 8
              apiVersion: awsproviderconfig.openshift.io/v1beta1
              blockDevices:
                - ebs:
                    iops: 0
                    volumeSize: 120
                    volumeType: gp2
              credentialsSecret:
                name: aws-cloud-credentials
              deviceIndex: 0
              iamInstanceProfile:
                id: <infrastructure_id>-worker-profile 9
              instanceType: m6g.xlarge 10
              kind: AWSMachineProviderConfig
              placement:
                availabilityZone: us-east-1a 11
                region: <region> 12
              securityGroups:
                - filters:
                    - name: tag:Name
                      values:
                        - <infrastructure_id>-worker-sg 13
              subnet:
                filters:
                  - name: tag:Name
                    values:
                      - <infrastructure_id>-private-<zone>
              tags:
                - name: kubernetes.io/cluster/<infrastructure_id> 14
                  value: owned
                - name: <custom_tag_name>
                  value: <custom_tag_value>
              userDataSecret:
                name: worker-user-data

    1 2 3 9 13 14
    Specify the infrastructure ID that is based on the cluster ID that you set when you provisioned the cluster. If you have the OpenShift CLI (oc) installed, you can obtain the infrastructure ID by running the following command:
    $ oc get -o jsonpath=‘{.status.infrastructureName}{“\n”}’ infrastructure cluster
    4 7
    Specify the infrastructure ID, role node label, and zone.
    5 6
    Specify the role node label to add.
    8
    Specify a Red Hat Enterprise Linux CoreOS (RHCOS) Amazon Machine Image (AMI) for your AWS zone for the nodes. The RHCOS AMI must be compatible with the machine architecture.
    $ oc get configmap/coreos-bootimages \
    	  -n openshift-machine-config-operator \
    	  -o jsonpath='{.data.stream}' | jq \
    	  -r '.architectures.<arch>.images.aws.regions."<region>".image'
    10
    Specify a machine type that aligns with the CPU architecture of the chosen AMI. For more information, see "Tested instance types for AWS 64-bit ARM"
    11
    Specify the zone. For example, us-east-1a. Ensure that the zone you select has machines with the required architecture.
    12
    Specify the region. For example, us-east-1. Ensure that the zone you select has machines with the required architecture.
  3. Create the compute machine set by running the following command:

    $ oc create -f <file_name> 1
    1
    Replace <file_name> with the name of the YAML file with compute machine set configuration. For example: aws-arm64-machine-set-0.yaml, or aws-amd64-machine-set-0.yaml.

Verification

  1. View the list of compute machine sets by running the following command:

    $ oc get machineset -n openshift-machine-api

    The output must include the machine set that you created.

    Example output

    NAME                                                DESIRED  CURRENT  READY  AVAILABLE  AGE
    <infrastructure_id>-aws-machine-set-0                   2        2      2          2  10m

  2. You can check if the nodes are ready and schedulable by running the following command:

    $ oc get nodes

3.4. Creating a cluster with multi-architecture compute machines on GCP

To create a Google Cloud Platform (GCP) cluster with multi-architecture compute machines, you must first create a single-architecture GCP installer-provisioned cluster with the multi-architecture installer binary. For more information on AWS installations, see Installing a cluster on GCP with customizations.

You can also migrate your current cluster with single-architecture compute machines to a cluster with multi-architecture compute machines. For more information, see Migrating to a cluster with multi-architecture compute machines.

After creating a multi-architecture cluster, you can add nodes with different architectures to the cluster.

Note

Secure booting is currently not supported on 64-bit ARM machines for GCP

3.4.1. Verifying cluster compatibility

Before you can start adding compute nodes of different architectures to your cluster, you must verify that your cluster is multi-architecture compatible.

Prerequisites

  • You installed the OpenShift CLI (oc).

Procedure

  1. Log in to the OpenShift CLI (oc).
  2. You can check that your cluster uses the architecture payload by running the following command:

    $ oc adm release info -o jsonpath="{ .metadata.metadata}"

Verification

  • If you see the following output, your cluster is using the multi-architecture payload:

    {
     "release.openshift.io/architecture": "multi",
     "url": "https://access.redhat.com/errata/<errata_version>"
    }

    You can then begin adding multi-arch compute nodes to your cluster.

  • If you see the following output, your cluster is not using the multi-architecture payload:

    {
     "url": "https://access.redhat.com/errata/<errata_version>"
    }
    Important

    To migrate your cluster so the cluster supports multi-architecture compute machines, follow the procedure in Migrating to a cluster with multi-architecture compute machines.

3.4.2. Adding a multi-architecture compute machine set to your GCP cluster

After creating a multi-architecture cluster, you can add nodes with different architectures.

You can add multi-architecture compute machines to a multi-architecture cluster in the following ways:

  • Adding 64-bit x86 compute machines to a cluster that uses 64-bit ARM control plane machines and already includes 64-bit ARM compute machines. In this case, 64-bit x86 is considered the secondary architecture.
  • Adding 64-bit ARM compute machines to a cluster that uses 64-bit x86 control plane machines and already includes 64-bit x86 compute machines. In this case, 64-bit ARM is considered the secondary architecture.
Note

Before adding a secondary architecture node to your cluster, it is recommended to install the Multiarch Tuning Operator, and deploy a ClusterPodPlacementConfig custom resource. For more information, see "Managing workloads on multi-architecture clusters by using the Multiarch Tuning Operator".

Prerequisites

  • You installed the OpenShift CLI (oc).
  • You used the installation program to create a 64-bit x86 or 64-bit ARM single-architecture GCP cluster with the multi-architecture installer binary.

Procedure

  1. Log in to the OpenShift CLI (oc).
  2. Create a YAML file, and add the configuration to create a compute machine set to control the 64-bit ARM or 64-bit x86 compute nodes in your cluster.

    Example MachineSet object for a GCP 64-bit ARM or 64-bit x86 compute node

    apiVersion: machine.openshift.io/v1beta1
    kind: MachineSet
    metadata:
      labels:
        machine.openshift.io/cluster-api-cluster: <infrastructure_id> 1
      name: <infrastructure_id>-w-a
      namespace: openshift-machine-api
    spec:
      replicas: 1
      selector:
        matchLabels:
          machine.openshift.io/cluster-api-cluster: <infrastructure_id>
          machine.openshift.io/cluster-api-machineset: <infrastructure_id>-w-a
      template:
        metadata:
          creationTimestamp: null
          labels:
            machine.openshift.io/cluster-api-cluster: <infrastructure_id>
            machine.openshift.io/cluster-api-machine-role: <role> 2
            machine.openshift.io/cluster-api-machine-type: <role>
            machine.openshift.io/cluster-api-machineset: <infrastructure_id>-w-a
        spec:
          metadata:
            labels:
              node-role.kubernetes.io/<role>: ""
          providerSpec:
            value:
              apiVersion: gcpprovider.openshift.io/v1beta1
              canIPForward: false
              credentialsSecret:
                name: gcp-cloud-credentials
              deletionProtection: false
              disks:
              - autoDelete: true
                boot: true
                image: <path_to_image> 3
                labels: null
                sizeGb: 128
                type: pd-ssd
              gcpMetadata: 4
              - key: <custom_metadata_key>
                value: <custom_metadata_value>
              kind: GCPMachineProviderSpec
              machineType: n1-standard-4 5
              metadata:
                creationTimestamp: null
              networkInterfaces:
              - network: <infrastructure_id>-network
                subnetwork: <infrastructure_id>-worker-subnet
              projectID: <project_name> 6
              region: us-central1 7
              serviceAccounts:
              - email: <infrastructure_id>-w@<project_name>.iam.gserviceaccount.com
                scopes:
                - https://www.googleapis.com/auth/cloud-platform
              tags:
                - <infrastructure_id>-worker
              userDataSecret:
                name: worker-user-data
              zone: us-central1-a

    1
    Specify the infrastructure ID that is based on the cluster ID that you set when you provisioned the cluster. You can obtain the infrastructure ID by running the following command:
    $ oc get -o jsonpath='{.status.infrastructureName}{"\n"}' infrastructure cluster
    2
    Specify the role node label to add.
    3
    Specify the path to the image that is used in current compute machine sets. You need the project and image name for your path to image.

    To access the project and image name, run the following command:

    $ oc get configmap/coreos-bootimages \
      -n openshift-machine-config-operator \
      -o jsonpath='{.data.stream}' | jq \
      -r '.architectures.aarch64.images.gcp'

    Example output

      "gcp": {
        "release": "415.92.202309142014-0",
        "project": "rhcos-cloud",
        "name": "rhcos-415-92-202309142014-0-gcp-aarch64"
      }

    Use the project and name parameters from the output to create the path to image field in your machine set. The path to the image should follow the following format:

    $ projects/<project>/global/images/<image_name>
    4
    Optional: Specify custom metadata in the form of a key:value pair. For example use cases, see the GCP documentation for setting custom metadata.
    5
    Specify a machine type that aligns with the CPU architecture of the chosen OS image. For more information, see "Tested instance types for GCP on 64-bit ARM infrastructures".
    6
    Specify the name of the GCP project that you use for your cluster.
    7
    Specify the region. For example, us-central1. Ensure that the zone you select has machines with the required architecture.
  3. Create the compute machine set by running the following command:

    $ oc create -f <file_name> 1
    1
    Replace <file_name> with the name of the YAML file with compute machine set configuration. For example: gcp-arm64-machine-set-0.yaml, or gcp-amd64-machine-set-0.yaml.

Verification

  1. View the list of compute machine sets by running the following command:

    $ oc get machineset -n openshift-machine-api

    The output must include the machine set that you created.

    Example output

    NAME                                                DESIRED  CURRENT  READY  AVAILABLE  AGE
    <infrastructure_id>-gcp-machine-set-0                   2        2      2          2  10m

  2. You can check if the nodes are ready and schedulable by running the following command:

    $ oc get nodes

3.5. Creating a cluster with multi-architecture compute machines on bare metal, IBM Power, or IBM Z

To create a cluster with multi-architecture compute machines on bare metal (x86_64 or aarch64), IBM Power® (ppc64le), or IBM Z® (s390x) you must have an existing single-architecture cluster on one of these platforms. Follow the installations procedures for your platform:

Important

The bare metal installer-provisioned infrastructure and the Bare Metal Operator do not support adding secondary architecture nodes during the initial cluster setup. You can add secondary architecture nodes manually only after the initial cluster setup.

Before you can add additional compute nodes to your cluster, you must upgrade your cluster to one that uses the multi-architecture payload. For more information on migrating to the multi-architecture payload, see Migrating to a cluster with multi-architecture compute machines.

The following procedures explain how to create a RHCOS compute machine using an ISO image or network PXE booting. This allows you to add additional nodes to your cluster and deploy a cluster with multi-architecture compute machines.

Note

Before adding a secondary architecture node to your cluster, it is recommended to install the Multiarch Tuning Operator, and deploy a ClusterPodPlacementConfig object. For more information, see Managing workloads on multi-architecture clusters by using the Multiarch Tuning Operator.

3.5.1. Verifying cluster compatibility

Before you can start adding compute nodes of different architectures to your cluster, you must verify that your cluster is multi-architecture compatible.

Prerequisites

  • You installed the OpenShift CLI (oc).

Procedure

  1. Log in to the OpenShift CLI (oc).
  2. You can check that your cluster uses the architecture payload by running the following command:

    $ oc adm release info -o jsonpath="{ .metadata.metadata}"

Verification

  • If you see the following output, your cluster is using the multi-architecture payload:

    {
     "release.openshift.io/architecture": "multi",
     "url": "https://access.redhat.com/errata/<errata_version>"
    }

    You can then begin adding multi-arch compute nodes to your cluster.

  • If you see the following output, your cluster is not using the multi-architecture payload:

    {
     "url": "https://access.redhat.com/errata/<errata_version>"
    }
    Important

    To migrate your cluster so the cluster supports multi-architecture compute machines, follow the procedure in Migrating to a cluster with multi-architecture compute machines.

3.5.2. Creating RHCOS machines using an ISO image

You can create more Red Hat Enterprise Linux CoreOS (RHCOS) compute machines for your bare metal cluster by using an ISO image to create the machines.

Prerequisites

  • Obtain the URL of the Ignition config file for the compute machines for your cluster. You uploaded this file to your HTTP server during installation.
  • You must have the OpenShift CLI (oc) installed.

Procedure

  1. Extract the Ignition config file from the cluster by running the following command:

    $ oc extract -n openshift-machine-api secret/worker-user-data-managed --keys=userData --to=- > worker.ign
  2. Upload the worker.ign Ignition config file you exported from your cluster to your HTTP server. Note the URLs of these files.
  3. You can validate that the ignition files are available on the URLs. The following example gets the Ignition config files for the compute node:

    $ curl -k http://<HTTP_server>/worker.ign
  4. You can access the ISO image for booting your new machine by running to following command:

    RHCOS_VHD_ORIGIN_URL=$(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' | jq -r '.architectures.<architecture>.artifacts.metal.formats.iso.disk.location')
  5. Use the ISO file to install RHCOS on more compute machines. Use the same method that you used when you created machines before you installed the cluster:

    • Burn the ISO image to a disk and boot it directly.
    • Use ISO redirection with a LOM interface.
  6. Boot the RHCOS ISO image without specifying any options, or interrupting the live boot sequence. Wait for the installer to boot into a shell prompt in the RHCOS live environment.

    Note

    You can interrupt the RHCOS installation boot process to add kernel arguments. However, for this ISO procedure you must use the coreos-installer command as outlined in the following steps, instead of adding kernel arguments.

  7. Run the coreos-installer command and specify the options that meet your installation requirements. At a minimum, you must specify the URL that points to the Ignition config file for the node type, and the device that you are installing to:

    $ sudo coreos-installer install --ignition-url=http://<HTTP_server>/<node_type>.ign <device> --ignition-hash=sha512-<digest> 12
    1
    You must run the coreos-installer command by using sudo, because the core user does not have the required root privileges to perform the installation.
    2
    The --ignition-hash option is required when the Ignition config file is obtained through an HTTP URL to validate the authenticity of the Ignition config file on the cluster node. <digest> is the Ignition config file SHA512 digest obtained in a preceding step.
    Note

    If you want to provide your Ignition config files through an HTTPS server that uses TLS, you can add the internal certificate authority (CA) to the system trust store before running coreos-installer.

    The following example initializes a bootstrap node installation to the /dev/sda device. The Ignition config file for the bootstrap node is obtained from an HTTP web server with the IP address 192.168.1.2:

    $ sudo coreos-installer install --ignition-url=http://192.168.1.2:80/installation_directory/bootstrap.ign /dev/sda --ignition-hash=sha512-a5a2d43879223273c9b60af66b44202a1d1248fc01cf156c46d4a79f552b6bad47bc8cc78ddf0116e80c59d2ea9e32ba53bc807afbca581aa059311def2c3e3b
  8. Monitor the progress of the RHCOS installation on the console of the machine.

    Important

    Ensure that the installation is successful on each node before commencing with the OpenShift Container Platform installation. Observing the installation process can also help to determine the cause of RHCOS installation issues that might arise.

  9. Continue to create more compute machines for your cluster.

3.5.3. Creating RHCOS machines by PXE or iPXE booting

You can create more Red Hat Enterprise Linux CoreOS (RHCOS) compute machines for your bare metal cluster by using PXE or iPXE booting.

Prerequisites

  • Obtain the URL of the Ignition config file for the compute machines for your cluster. You uploaded this file to your HTTP server during installation.
  • Obtain the URLs of the RHCOS ISO image, compressed metal BIOS, kernel, and initramfs files that you uploaded to your HTTP server during cluster installation.
  • You have access to the PXE booting infrastructure that you used to create the machines for your OpenShift Container Platform cluster during installation. The machines must boot from their local disks after RHCOS is installed on them.
  • If you use UEFI, you have access to the grub.conf file that you modified during OpenShift Container Platform installation.

Procedure

  1. Confirm that your PXE or iPXE installation for the RHCOS images is correct.

    • For PXE:

      DEFAULT pxeboot
      TIMEOUT 20
      PROMPT 0
      LABEL pxeboot
          KERNEL http://<HTTP_server>/rhcos-<version>-live-kernel-<architecture> 1
          APPEND initrd=http://<HTTP_server>/rhcos-<version>-live-initramfs.<architecture>.img coreos.inst.install_dev=/dev/sda coreos.inst.ignition_url=http://<HTTP_server>/worker.ign coreos.live.rootfs_url=http://<HTTP_server>/rhcos-<version>-live-rootfs.<architecture>.img 2
      1
      Specify the location of the live kernel file that you uploaded to your HTTP server.
      2
      Specify locations of the RHCOS files that you uploaded to your HTTP server. The initrd parameter value is the location of the live initramfs file, the coreos.inst.ignition_url parameter value is the location of the worker Ignition config file, and the coreos.live.rootfs_url parameter value is the location of the live rootfs file. The coreos.inst.ignition_url and coreos.live.rootfs_url parameters only support HTTP and HTTPS.
      Note

      This configuration does not enable serial console access on machines with a graphical console. To configure a different console, add one or more console= arguments to the APPEND line. For example, add console=tty0 console=ttyS0 to set the first PC serial port as the primary console and the graphical console as a secondary console. For more information, see How does one set up a serial terminal and/or console in Red Hat Enterprise Linux?.

    • For iPXE (x86_64 + aarch64):

      kernel http://<HTTP_server>/rhcos-<version>-live-kernel-<architecture> initrd=main coreos.live.rootfs_url=http://<HTTP_server>/rhcos-<version>-live-rootfs.<architecture>.img coreos.inst.install_dev=/dev/sda coreos.inst.ignition_url=http://<HTTP_server>/worker.ign 1 2
      initrd --name main http://<HTTP_server>/rhcos-<version>-live-initramfs.<architecture>.img 3
      boot
      1
      Specify the locations of the RHCOS files that you uploaded to your HTTP server. The kernel parameter value is the location of the kernel file, the initrd=main argument is needed for booting on UEFI systems, the coreos.live.rootfs_url parameter value is the location of the rootfs file, and the coreos.inst.ignition_url parameter value is the location of the worker Ignition config file.
      2
      If you use multiple NICs, specify a single interface in the ip option. For example, to use DHCP on a NIC that is named eno1, set ip=eno1:dhcp.
      3
      Specify the location of the initramfs file that you uploaded to your HTTP server.
      Note

      This configuration does not enable serial console access on machines with a graphical console To configure a different console, add one or more console= arguments to the kernel line. For example, add console=tty0 console=ttyS0 to set the first PC serial port as the primary console and the graphical console as a secondary console. For more information, see How does one set up a serial terminal and/or console in Red Hat Enterprise Linux? and "Enabling the serial console for PXE and ISO installation" in the "Advanced RHCOS installation configuration" section.

      Note

      To network boot the CoreOS kernel on aarch64 architecture, you need to use a version of iPXE build with the IMAGE_GZIP option enabled. See IMAGE_GZIP option in iPXE.

    • For PXE (with UEFI and GRUB as second stage) on aarch64:

      menuentry 'Install CoreOS' {
          linux rhcos-<version>-live-kernel-<architecture>  coreos.live.rootfs_url=http://<HTTP_server>/rhcos-<version>-live-rootfs.<architecture>.img coreos.inst.install_dev=/dev/sda coreos.inst.ignition_url=http://<HTTP_server>/worker.ign 1 2
          initrd rhcos-<version>-live-initramfs.<architecture>.img 3
      }
      1
      Specify the locations of the RHCOS files that you uploaded to your HTTP/TFTP server. The kernel parameter value is the location of the kernel file on your TFTP server. The coreos.live.rootfs_url parameter value is the location of the rootfs file, and the coreos.inst.ignition_url parameter value is the location of the worker Ignition config file on your HTTP Server.
      2
      If you use multiple NICs, specify a single interface in the ip option. For example, to use DHCP on a NIC that is named eno1, set ip=eno1:dhcp.
      3
      Specify the location of the initramfs file that you uploaded to your TFTP server.
  2. Use the PXE or iPXE infrastructure to create the required compute machines for your cluster.

3.5.4. Approving the certificate signing requests for your machines

When you add machines to a cluster, two pending certificate signing requests (CSRs) are generated for each machine that you added. You must confirm that these CSRs are approved or, if necessary, approve them yourself. The client requests must be approved first, followed by the server requests.

Prerequisites

  • You added machines to your cluster.

Procedure

  1. Confirm that the cluster recognizes the machines:

    $ oc get nodes

    Example output

    NAME      STATUS    ROLES   AGE  VERSION
    master-0  Ready     master  63m  v1.30.3
    master-1  Ready     master  63m  v1.30.3
    master-2  Ready     master  64m  v1.30.3

    The output lists all of the machines that you created.

    Note

    The preceding output might not include the compute nodes, also known as worker nodes, until some CSRs are approved.

  2. Review the pending CSRs and ensure that you see the client requests with the Pending or Approved status for each machine that you added to the cluster:

    $ oc get csr

    Example output

    NAME        AGE     REQUESTOR                                                                   CONDITION
    csr-8b2br   15m     system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending
    csr-8vnps   15m     system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending
    ...

    In this example, two machines are joining the cluster. You might see more approved CSRs in the list.

  3. If the CSRs were not approved, after all of the pending CSRs for the machines you added are in Pending status, approve the CSRs for your cluster machines:

    Note

    Because the CSRs rotate automatically, approve your CSRs within an hour of adding the machines to the cluster. If you do not approve them within an hour, the certificates will rotate, and more than two certificates will be present for each node. You must approve all of these certificates. After the client CSR is approved, the Kubelet creates a secondary CSR for the serving certificate, which requires manual approval. Then, subsequent serving certificate renewal requests are automatically approved by the machine-approver if the Kubelet requests a new certificate with identical parameters.

    Note

    For clusters running on platforms that are not machine API enabled, such as bare metal and other user-provisioned infrastructure, you must implement a method of automatically approving the kubelet serving certificate requests (CSRs). If a request is not approved, then the oc exec, oc rsh, and oc logs commands cannot succeed, because a serving certificate is required when the API server connects to the kubelet. Any operation that contacts the Kubelet endpoint requires this certificate approval to be in place. The method must watch for new CSRs, confirm that the CSR was submitted by the node-bootstrapper service account in the system:node or system:admin groups, and confirm the identity of the node.

    • To approve them individually, run the following command for each valid CSR:

      $ oc adm certificate approve <csr_name> 1
      1
      <csr_name> is the name of a CSR from the list of current CSRs.
    • To approve all pending CSRs, run the following command:

      $ oc get csr -o go-template='{{range .items}}{{if not .status}}{{.metadata.name}}{{"\n"}}{{end}}{{end}}' | xargs --no-run-if-empty oc adm certificate approve
      Note

      Some Operators might not become available until some CSRs are approved.

  4. Now that your client requests are approved, you must review the server requests for each machine that you added to the cluster:

    $ oc get csr

    Example output

    NAME        AGE     REQUESTOR                                                                   CONDITION
    csr-bfd72   5m26s   system:node:ip-10-0-50-126.us-east-2.compute.internal                       Pending
    csr-c57lv   5m26s   system:node:ip-10-0-95-157.us-east-2.compute.internal                       Pending
    ...

  5. If the remaining CSRs are not approved, and are in the Pending status, approve the CSRs for your cluster machines:

    • To approve them individually, run the following command for each valid CSR:

      $ oc adm certificate approve <csr_name> 1
      1
      <csr_name> is the name of a CSR from the list of current CSRs.
    • To approve all pending CSRs, run the following command:

      $ oc get csr -o go-template='{{range .items}}{{if not .status}}{{.metadata.name}}{{"\n"}}{{end}}{{end}}' | xargs oc adm certificate approve
  6. After all client and server CSRs have been approved, the machines have the Ready status. Verify this by running the following command:

    $ oc get nodes

    Example output

    NAME      STATUS    ROLES   AGE  VERSION
    master-0  Ready     master  73m  v1.30.3
    master-1  Ready     master  73m  v1.30.3
    master-2  Ready     master  74m  v1.30.3
    worker-0  Ready     worker  11m  v1.30.3
    worker-1  Ready     worker  11m  v1.30.3

    Note

    It can take a few minutes after approval of the server CSRs for the machines to transition to the Ready status.

Additional information

3.6. Creating a cluster with multi-architecture compute machines on IBM Z and IBM LinuxONE with z/VM

To create a cluster with multi-architecture compute machines on IBM Z® and IBM® LinuxONE (s390x) with z/VM, you must have an existing single-architecture x86_64 cluster. You can then add s390x compute machines to your OpenShift Container Platform cluster.

Before you can add s390x nodes to your cluster, you must upgrade your cluster to one that uses the multi-architecture payload. For more information on migrating to the multi-architecture payload, see Migrating to a cluster with multi-architecture compute machines.

The following procedures explain how to create a RHCOS compute machine using a z/VM instance. This will allow you to add s390x nodes to your cluster and deploy a cluster with multi-architecture compute machines.

To create an IBM Z® or IBM® LinuxONE (s390x) cluster with multi-architecture compute machines on x86_64, follow the instructions for Installing a cluster on IBM Z® and IBM® LinuxONE. You can then add x86_64 compute machines as described in Creating a cluster with multi-architecture compute machines on bare metal, IBM Power, or IBM Z.

Note

Before adding a secondary architecture node to your cluster, it is recommended to install the Multiarch Tuning Operator, and deploy a ClusterPodPlacementConfig object. For more information, see Managing workloads on multi-architecture clusters by using the Multiarch Tuning Operator.

3.6.1. Verifying cluster compatibility

Before you can start adding compute nodes of different architectures to your cluster, you must verify that your cluster is multi-architecture compatible.

Prerequisites

  • You installed the OpenShift CLI (oc).

Procedure

  1. Log in to the OpenShift CLI (oc).
  2. You can check that your cluster uses the architecture payload by running the following command:

    $ oc adm release info -o jsonpath="{ .metadata.metadata}"

Verification

  • If you see the following output, your cluster is using the multi-architecture payload:

    {
     "release.openshift.io/architecture": "multi",
     "url": "https://access.redhat.com/errata/<errata_version>"
    }

    You can then begin adding multi-arch compute nodes to your cluster.

  • If you see the following output, your cluster is not using the multi-architecture payload:

    {
     "url": "https://access.redhat.com/errata/<errata_version>"
    }
    Important

    To migrate your cluster so the cluster supports multi-architecture compute machines, follow the procedure in Migrating to a cluster with multi-architecture compute machines.

3.6.2. Creating RHCOS machines on IBM Z with z/VM

You can create more Red Hat Enterprise Linux CoreOS (RHCOS) compute machines running on IBM Z® with z/VM and attach them to your existing cluster.

Prerequisites

  • You have a domain name server (DNS) that can perform hostname and reverse lookup for the nodes.
  • You have an HTTP or HTTPS server running on your provisioning machine that is accessible to the machines you create.

Procedure

  1. Disable UDP aggregation.

    Currently, UDP aggregation is not supported on IBM Z® and is not automatically deactivated on multi-architecture compute clusters with an x86_64 control plane and additional s390x compute machines. To ensure that the addtional compute nodes are added to the cluster correctly, you must manually disable UDP aggregation.

    1. Create a YAML file udp-aggregation-config.yaml with the following content:

      apiVersion: v1
      kind: ConfigMap
      data:
        disable-udp-aggregation: "true"
      metadata:
        name: udp-aggregation-config
        namespace: openshift-network-operator
    2. Create the ConfigMap resource by running the following command:

      $ oc create -f udp-aggregation-config.yaml
  2. Extract the Ignition config file from the cluster by running the following command:

    $ oc extract -n openshift-machine-api secret/worker-user-data-managed --keys=userData --to=- > worker.ign
  3. Upload the worker.ign Ignition config file you exported from your cluster to your HTTP server. Note the URL of this file.
  4. You can validate that the Ignition file is available on the URL. The following example gets the Ignition config file for the compute node:

    $ curl -k http://<http_server>/worker.ign
  5. Download the RHEL live kernel, initramfs, and rootfs files by running the following commands:

    $ curl -LO $(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' \
    | jq -r '.architectures.s390x.artifacts.metal.formats.pxe.kernel.location')
    $ curl -LO $(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' \
    | jq -r '.architectures.s390x.artifacts.metal.formats.pxe.initramfs.location')
    $ curl -LO $(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' \
    | jq -r '.architectures.s390x.artifacts.metal.formats.pxe.rootfs.location')
  6. Move the downloaded RHEL live kernel, initramfs, and rootfs files to an HTTP or HTTPS server that is accessible from the z/VM guest you want to add.
  7. Create a parameter file for the z/VM guest. The following parameters are specific for the virtual machine:

    • Optional: To specify a static IP address, add an ip= parameter with the following entries, with each separated by a colon:

      1. The IP address for the machine.
      2. An empty string.
      3. The gateway.
      4. The netmask.
      5. The machine host and domain name in the form hostname.domainname. Omit this value to let RHCOS decide.
      6. The network interface name. Omit this value to let RHCOS decide.
      7. The value none.
    • For coreos.inst.ignition_url=, specify the URL to the worker.ign file. Only HTTP and HTTPS protocols are supported.
    • For coreos.live.rootfs_url=, specify the matching rootfs artifact for the kernel and initramfs you are booting. Only HTTP and HTTPS protocols are supported.
    • For installations on DASD-type disks, complete the following tasks:

      1. For coreos.inst.install_dev=, specify /dev/dasda.
      2. Use rd.dasd= to specify the DASD where RHCOS is to be installed.
      3. You can adjust further parameters if required.

        The following is an example parameter file, additional-worker-dasd.parm:

        cio_ignore=all,!condev rd.neednet=1 \
        console=ttysclp0 \
        coreos.inst.install_dev=/dev/dasda \
        coreos.inst.ignition_url=http://<http_server>/worker.ign \
        coreos.live.rootfs_url=http://<http_server>/rhcos-<version>-live-rootfs.<architecture>.img \
        ip=<ip>::<gateway>:<netmask>:<hostname>::none nameserver=<dns> \
        rd.znet=qeth,0.0.bdf0,0.0.bdf1,0.0.bdf2,layer2=1,portno=0 \
        rd.dasd=0.0.3490 \
        zfcp.allow_lun_scan=0

        Write all options in the parameter file as a single line and make sure that you have no newline characters.

    • For installations on FCP-type disks, complete the following tasks:

      1. Use rd.zfcp=<adapter>,<wwpn>,<lun> to specify the FCP disk where RHCOS is to be installed. For multipathing, repeat this step for each additional path.

        Note

        When you install with multiple paths, you must enable multipathing directly after the installation, not at a later point in time, as this can cause problems.

      2. Set the install device as: coreos.inst.install_dev=/dev/sda.

        Note

        If additional LUNs are configured with NPIV, FCP requires zfcp.allow_lun_scan=0. If you must enable zfcp.allow_lun_scan=1 because you use a CSI driver, for example, you must configure your NPIV so that each node cannot access the boot partition of another node.

      3. You can adjust further parameters if required.

        Important

        Additional postinstallation steps are required to fully enable multipathing. For more information, see “Enabling multipathing with kernel arguments on RHCOS" in Postinstallation machine configuration tasks.

        The following is an example parameter file, additional-worker-fcp.parm for a worker node with multipathing:

        cio_ignore=all,!condev rd.neednet=1 \
        console=ttysclp0 \
        coreos.inst.install_dev=/dev/sda \
        coreos.live.rootfs_url=http://<http_server>/rhcos-<version>-live-rootfs.<architecture>.img \
        coreos.inst.ignition_url=http://<http_server>/worker.ign \
        ip=<ip>::<gateway>:<netmask>:<hostname>::none nameserver=<dns> \
        rd.znet=qeth,0.0.bdf0,0.0.bdf1,0.0.bdf2,layer2=1,portno=0 \
        zfcp.allow_lun_scan=0 \
        rd.zfcp=0.0.1987,0x50050763070bc5e3,0x4008400B00000000 \
        rd.zfcp=0.0.19C7,0x50050763070bc5e3,0x4008400B00000000 \
        rd.zfcp=0.0.1987,0x50050763071bc5e3,0x4008400B00000000 \
        rd.zfcp=0.0.19C7,0x50050763071bc5e3,0x4008400B00000000

        Write all options in the parameter file as a single line and make sure that you have no newline characters.

  8. Transfer the initramfs, kernel, parameter files, and RHCOS images to z/VM, for example, by using FTP. For details about how to transfer the files with FTP and boot from the virtual reader, see Installing under Z/VM.
  9. Punch the files to the virtual reader of the z/VM guest virtual machine.

    See PUNCH in IBM® Documentation.

    Tip

    You can use the CP PUNCH command or, if you use Linux, the vmur command to transfer files between two z/VM guest virtual machines.

  10. Log in to CMS on the bootstrap machine.
  11. IPL the bootstrap machine from the reader by running the following command:

    $ ipl c

    See IPL in IBM® Documentation.

3.6.3. Approving the certificate signing requests for your machines

When you add machines to a cluster, two pending certificate signing requests (CSRs) are generated for each machine that you added. You must confirm that these CSRs are approved or, if necessary, approve them yourself. The client requests must be approved first, followed by the server requests.

Prerequisites

  • You added machines to your cluster.

Procedure

  1. Confirm that the cluster recognizes the machines:

    $ oc get nodes

    Example output

    NAME      STATUS    ROLES   AGE  VERSION
    master-0  Ready     master  63m  v1.30.3
    master-1  Ready     master  63m  v1.30.3
    master-2  Ready     master  64m  v1.30.3

    The output lists all of the machines that you created.

    Note

    The preceding output might not include the compute nodes, also known as worker nodes, until some CSRs are approved.

  2. Review the pending CSRs and ensure that you see the client requests with the Pending or Approved status for each machine that you added to the cluster:

    $ oc get csr

    Example output

    NAME        AGE     REQUESTOR                                                                   CONDITION
    csr-8b2br   15m     system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending
    csr-8vnps   15m     system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending
    ...

    In this example, two machines are joining the cluster. You might see more approved CSRs in the list.

  3. If the CSRs were not approved, after all of the pending CSRs for the machines you added are in Pending status, approve the CSRs for your cluster machines:

    Note

    Because the CSRs rotate automatically, approve your CSRs within an hour of adding the machines to the cluster. If you do not approve them within an hour, the certificates will rotate, and more than two certificates will be present for each node. You must approve all of these certificates. After the client CSR is approved, the Kubelet creates a secondary CSR for the serving certificate, which requires manual approval. Then, subsequent serving certificate renewal requests are automatically approved by the machine-approver if the Kubelet requests a new certificate with identical parameters.

    Note

    For clusters running on platforms that are not machine API enabled, such as bare metal and other user-provisioned infrastructure, you must implement a method of automatically approving the kubelet serving certificate requests (CSRs). If a request is not approved, then the oc exec, oc rsh, and oc logs commands cannot succeed, because a serving certificate is required when the API server connects to the kubelet. Any operation that contacts the Kubelet endpoint requires this certificate approval to be in place. The method must watch for new CSRs, confirm that the CSR was submitted by the node-bootstrapper service account in the system:node or system:admin groups, and confirm the identity of the node.

    • To approve them individually, run the following command for each valid CSR:

      $ oc adm certificate approve <csr_name> 1
      1
      <csr_name> is the name of a CSR from the list of current CSRs.
    • To approve all pending CSRs, run the following command:

      $ oc get csr -o go-template='{{range .items}}{{if not .status}}{{.metadata.name}}{{"\n"}}{{end}}{{end}}' | xargs --no-run-if-empty oc adm certificate approve
      Note

      Some Operators might not become available until some CSRs are approved.

  4. Now that your client requests are approved, you must review the server requests for each machine that you added to the cluster:

    $ oc get csr

    Example output

    NAME        AGE     REQUESTOR                                                                   CONDITION
    csr-bfd72   5m26s   system:node:ip-10-0-50-126.us-east-2.compute.internal                       Pending
    csr-c57lv   5m26s   system:node:ip-10-0-95-157.us-east-2.compute.internal                       Pending
    ...

  5. If the remaining CSRs are not approved, and are in the Pending status, approve the CSRs for your cluster machines:

    • To approve them individually, run the following command for each valid CSR:

      $ oc adm certificate approve <csr_name> 1
      1
      <csr_name> is the name of a CSR from the list of current CSRs.
    • To approve all pending CSRs, run the following command:

      $ oc get csr -o go-template='{{range .items}}{{if not .status}}{{.metadata.name}}{{"\n"}}{{end}}{{end}}' | xargs oc adm certificate approve
  6. After all client and server CSRs have been approved, the machines have the Ready status. Verify this by running the following command:

    $ oc get nodes

    Example output

    NAME      STATUS    ROLES   AGE  VERSION
    master-0  Ready     master  73m  v1.30.3
    master-1  Ready     master  73m  v1.30.3
    master-2  Ready     master  74m  v1.30.3
    worker-0  Ready     worker  11m  v1.30.3
    worker-1  Ready     worker  11m  v1.30.3

    Note

    It can take a few minutes after approval of the server CSRs for the machines to transition to the Ready status.

Additional information

3.7. Creating a cluster with multi-architecture compute machines on IBM Z and IBM LinuxONE in an LPAR

To create a cluster with multi-architecture compute machines on IBM Z® and IBM® LinuxONE (s390x) in an LPAR, you must have an existing single-architecture x86_64 cluster. You can then add s390x compute machines to your OpenShift Container Platform cluster.

Before you can add s390x nodes to your cluster, you must upgrade your cluster to one that uses the multi-architecture payload. For more information on migrating to the multi-architecture payload, see Migrating to a cluster with multi-architecture compute machines.

The following procedures explain how to create a RHCOS compute machine using an LPAR instance. This will allow you to add s390x nodes to your cluster and deploy a cluster with multi-architecture compute machines.

Note

To create an IBM Z® or IBM® LinuxONE (s390x) cluster with multi-architecture compute machines on x86_64, follow the instructions for Installing a cluster on IBM Z® and IBM® LinuxONE. You can then add x86_64 compute machines as described in Creating a cluster with multi-architecture compute machines on bare metal, IBM Power, or IBM Z.

3.7.1. Verifying cluster compatibility

Before you can start adding compute nodes of different architectures to your cluster, you must verify that your cluster is multi-architecture compatible.

Prerequisites

  • You installed the OpenShift CLI (oc).

Procedure

  1. Log in to the OpenShift CLI (oc).
  2. You can check that your cluster uses the architecture payload by running the following command:

    $ oc adm release info -o jsonpath="{ .metadata.metadata}"

Verification

  • If you see the following output, your cluster is using the multi-architecture payload:

    {
     "release.openshift.io/architecture": "multi",
     "url": "https://access.redhat.com/errata/<errata_version>"
    }

    You can then begin adding multi-arch compute nodes to your cluster.

  • If you see the following output, your cluster is not using the multi-architecture payload:

    {
     "url": "https://access.redhat.com/errata/<errata_version>"
    }
    Important

    To migrate your cluster so the cluster supports multi-architecture compute machines, follow the procedure in Migrating to a cluster with multi-architecture compute machines.

3.7.2. Creating RHCOS machines on IBM Z with z/VM

You can create more Red Hat Enterprise Linux CoreOS (RHCOS) compute machines running on IBM Z® with z/VM and attach them to your existing cluster.

Prerequisites

  • You have a domain name server (DNS) that can perform hostname and reverse lookup for the nodes.
  • You have an HTTP or HTTPS server running on your provisioning machine that is accessible to the machines you create.

Procedure

  1. Disable UDP aggregation.

    Currently, UDP aggregation is not supported on IBM Z® and is not automatically deactivated on multi-architecture compute clusters with an x86_64 control plane and additional s390x compute machines. To ensure that the addtional compute nodes are added to the cluster correctly, you must manually disable UDP aggregation.

    1. Create a YAML file udp-aggregation-config.yaml with the following content:

      apiVersion: v1
      kind: ConfigMap
      data:
        disable-udp-aggregation: "true"
      metadata:
        name: udp-aggregation-config
        namespace: openshift-network-operator
    2. Create the ConfigMap resource by running the following command:

      $ oc create -f udp-aggregation-config.yaml
  2. Extract the Ignition config file from the cluster by running the following command:

    $ oc extract -n openshift-machine-api secret/worker-user-data-managed --keys=userData --to=- > worker.ign
  3. Upload the worker.ign Ignition config file you exported from your cluster to your HTTP server. Note the URL of this file.
  4. You can validate that the Ignition file is available on the URL. The following example gets the Ignition config file for the compute node:

    $ curl -k http://<http_server>/worker.ign
  5. Download the RHEL live kernel, initramfs, and rootfs files by running the following commands:

    $ curl -LO $(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' \
    | jq -r '.architectures.s390x.artifacts.metal.formats.pxe.kernel.location')
    $ curl -LO $(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' \
    | jq -r '.architectures.s390x.artifacts.metal.formats.pxe.initramfs.location')
    $ curl -LO $(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' \
    | jq -r '.architectures.s390x.artifacts.metal.formats.pxe.rootfs.location')
  6. Move the downloaded RHEL live kernel, initramfs, and rootfs files to an HTTP or HTTPS server that is accessible from the z/VM guest you want to add.
  7. Create a parameter file for the z/VM guest. The following parameters are specific for the virtual machine:

    • Optional: To specify a static IP address, add an ip= parameter with the following entries, with each separated by a colon:

      1. The IP address for the machine.
      2. An empty string.
      3. The gateway.
      4. The netmask.
      5. The machine host and domain name in the form hostname.domainname. Omit this value to let RHCOS decide.
      6. The network interface name. Omit this value to let RHCOS decide.
      7. The value none.
    • For coreos.inst.ignition_url=, specify the URL to the worker.ign file. Only HTTP and HTTPS protocols are supported.
    • For coreos.live.rootfs_url=, specify the matching rootfs artifact for the kernel and initramfs you are booting. Only HTTP and HTTPS protocols are supported.
    • For installations on DASD-type disks, complete the following tasks:

      1. For coreos.inst.install_dev=, specify /dev/dasda.
      2. Use rd.dasd= to specify the DASD where RHCOS is to be installed.
      3. You can adjust further parameters if required.

        The following is an example parameter file, additional-worker-dasd.parm:

        cio_ignore=all,!condev rd.neednet=1 \
        console=ttysclp0 \
        coreos.inst.install_dev=/dev/dasda \
        coreos.inst.ignition_url=http://<http_server>/worker.ign \
        coreos.live.rootfs_url=http://<http_server>/rhcos-<version>-live-rootfs.<architecture>.img \
        ip=<ip>::<gateway>:<netmask>:<hostname>::none nameserver=<dns> \
        rd.znet=qeth,0.0.bdf0,0.0.bdf1,0.0.bdf2,layer2=1,portno=0 \
        rd.dasd=0.0.3490 \
        zfcp.allow_lun_scan=0

        Write all options in the parameter file as a single line and make sure that you have no newline characters.

    • For installations on FCP-type disks, complete the following tasks:

      1. Use rd.zfcp=<adapter>,<wwpn>,<lun> to specify the FCP disk where RHCOS is to be installed. For multipathing, repeat this step for each additional path.

        Note

        When you install with multiple paths, you must enable multipathing directly after the installation, not at a later point in time, as this can cause problems.

      2. Set the install device as: coreos.inst.install_dev=/dev/sda.

        Note

        If additional LUNs are configured with NPIV, FCP requires zfcp.allow_lun_scan=0. If you must enable zfcp.allow_lun_scan=1 because you use a CSI driver, for example, you must configure your NPIV so that each node cannot access the boot partition of another node.

      3. You can adjust further parameters if required.

        Important

        Additional postinstallation steps are required to fully enable multipathing. For more information, see “Enabling multipathing with kernel arguments on RHCOS" in Postinstallation machine configuration tasks.

        The following is an example parameter file, additional-worker-fcp.parm for a worker node with multipathing:

        cio_ignore=all,!condev rd.neednet=1 \
        console=ttysclp0 \
        coreos.inst.install_dev=/dev/sda \
        coreos.live.rootfs_url=http://<http_server>/rhcos-<version>-live-rootfs.<architecture>.img \
        coreos.inst.ignition_url=http://<http_server>/worker.ign \
        ip=<ip>::<gateway>:<netmask>:<hostname>::none nameserver=<dns> \
        rd.znet=qeth,0.0.bdf0,0.0.bdf1,0.0.bdf2,layer2=1,portno=0 \
        zfcp.allow_lun_scan=0 \
        rd.zfcp=0.0.1987,0x50050763070bc5e3,0x4008400B00000000 \
        rd.zfcp=0.0.19C7,0x50050763070bc5e3,0x4008400B00000000 \
        rd.zfcp=0.0.1987,0x50050763071bc5e3,0x4008400B00000000 \
        rd.zfcp=0.0.19C7,0x50050763071bc5e3,0x4008400B00000000

        Write all options in the parameter file as a single line and make sure that you have no newline characters.

  8. Transfer the initramfs, kernel, parameter files, and RHCOS images to z/VM, for example, by using FTP. For details about how to transfer the files with FTP and boot from the virtual reader, see Installing under Z/VM.
  9. Punch the files to the virtual reader of the z/VM guest virtual machine.

    See PUNCH in IBM® Documentation.

    Tip

    You can use the CP PUNCH command or, if you use Linux, the vmur command to transfer files between two z/VM guest virtual machines.

  10. Log in to CMS on the bootstrap machine.
  11. IPL the bootstrap machine from the reader by running the following command:

    $ ipl c

    See IPL in IBM® Documentation.

3.7.3. Approving the certificate signing requests for your machines

When you add machines to a cluster, two pending certificate signing requests (CSRs) are generated for each machine that you added. You must confirm that these CSRs are approved or, if necessary, approve them yourself. The client requests must be approved first, followed by the server requests.

Prerequisites

  • You added machines to your cluster.

Procedure

  1. Confirm that the cluster recognizes the machines:

    $ oc get nodes

    Example output

    NAME      STATUS    ROLES   AGE  VERSION
    master-0  Ready     master  63m  v1.30.3
    master-1  Ready     master  63m  v1.30.3
    master-2  Ready     master  64m  v1.30.3

    The output lists all of the machines that you created.

    Note

    The preceding output might not include the compute nodes, also known as worker nodes, until some CSRs are approved.

  2. Review the pending CSRs and ensure that you see the client requests with the Pending or Approved status for each machine that you added to the cluster:

    $ oc get csr

    Example output

    NAME        AGE     REQUESTOR                                                                   CONDITION
    csr-8b2br   15m     system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending
    csr-8vnps   15m     system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending
    ...

    In this example, two machines are joining the cluster. You might see more approved CSRs in the list.

  3. If the CSRs were not approved, after all of the pending CSRs for the machines you added are in Pending status, approve the CSRs for your cluster machines:

    Note

    Because the CSRs rotate automatically, approve your CSRs within an hour of adding the machines to the cluster. If you do not approve them within an hour, the certificates will rotate, and more than two certificates will be present for each node. You must approve all of these certificates. After the client CSR is approved, the Kubelet creates a secondary CSR for the serving certificate, which requires manual approval. Then, subsequent serving certificate renewal requests are automatically approved by the machine-approver if the Kubelet requests a new certificate with identical parameters.

    Note

    For clusters running on platforms that are not machine API enabled, such as bare metal and other user-provisioned infrastructure, you must implement a method of automatically approving the kubelet serving certificate requests (CSRs). If a request is not approved, then the oc exec, oc rsh, and oc logs commands cannot succeed, because a serving certificate is required when the API server connects to the kubelet. Any operation that contacts the Kubelet endpoint requires this certificate approval to be in place. The method must watch for new CSRs, confirm that the CSR was submitted by the node-bootstrapper service account in the system:node or system:admin groups, and confirm the identity of the node.

    • To approve them individually, run the following command for each valid CSR:

      $ oc adm certificate approve <csr_name> 1
      1
      <csr_name> is the name of a CSR from the list of current CSRs.
    • To approve all pending CSRs, run the following command:

      $ oc get csr -o go-template='{{range .items}}{{if not .status}}{{.metadata.name}}{{"\n"}}{{end}}{{end}}' | xargs --no-run-if-empty oc adm certificate approve
      Note

      Some Operators might not become available until some CSRs are approved.

  4. Now that your client requests are approved, you must review the server requests for each machine that you added to the cluster:

    $ oc get csr

    Example output

    NAME        AGE     REQUESTOR                                                                   CONDITION
    csr-bfd72   5m26s   system:node:ip-10-0-50-126.us-east-2.compute.internal                       Pending
    csr-c57lv   5m26s   system:node:ip-10-0-95-157.us-east-2.compute.internal                       Pending
    ...

  5. If the remaining CSRs are not approved, and are in the Pending status, approve the CSRs for your cluster machines:

    • To approve them individually, run the following command for each valid CSR:

      $ oc adm certificate approve <csr_name> 1
      1
      <csr_name> is the name of a CSR from the list of current CSRs.
    • To approve all pending CSRs, run the following command:

      $ oc get csr -o go-template='{{range .items}}{{if not .status}}{{.metadata.name}}{{"\n"}}{{end}}{{end}}' | xargs oc adm certificate approve
  6. After all client and server CSRs have been approved, the machines have the Ready status. Verify this by running the following command:

    $ oc get nodes

    Example output

    NAME      STATUS    ROLES   AGE  VERSION
    master-0  Ready     master  73m  v1.30.3
    master-1  Ready     master  73m  v1.30.3
    master-2  Ready     master  74m  v1.30.3
    worker-0  Ready     worker  11m  v1.30.3
    worker-1  Ready     worker  11m  v1.30.3

    Note

    It can take a few minutes after approval of the server CSRs for the machines to transition to the Ready status.

Additional information

3.8. Creating a cluster with multi-architecture compute machines on IBM Z and IBM LinuxONE with RHEL KVM

To create a cluster with multi-architecture compute machines on IBM Z® and IBM® LinuxONE (s390x) with RHEL KVM, you must have an existing single-architecture x86_64 cluster. You can then add s390x compute machines to your OpenShift Container Platform cluster.

Before you can add s390x nodes to your cluster, you must upgrade your cluster to one that uses the multi-architecture payload. For more information on migrating to the multi-architecture payload, see Migrating to a cluster with multi-architecture compute machines.

The following procedures explain how to create a RHCOS compute machine using a RHEL KVM instance. This will allow you to add s390x nodes to your cluster and deploy a cluster with multi-architecture compute machines.

To create an IBM Z® or IBM® LinuxONE (s390x) cluster with multi-architecture compute machines on x86_64, follow the instructions for Installing a cluster on IBM Z® and IBM® LinuxONE. You can then add x86_64 compute machines as described in Creating a cluster with multi-architecture compute machines on bare metal, IBM Power, or IBM Z.

Note

Before adding a secondary architecture node to your cluster, it is recommended to install the Multiarch Tuning Operator, and deploy a ClusterPodPlacementConfig object. For more information, see Managing workloads on multi-architecture clusters by using the Multiarch Tuning Operator.

3.8.1. Verifying cluster compatibility

Before you can start adding compute nodes of different architectures to your cluster, you must verify that your cluster is multi-architecture compatible.

Prerequisites

  • You installed the OpenShift CLI (oc).

Procedure

  1. Log in to the OpenShift CLI (oc).
  2. You can check that your cluster uses the architecture payload by running the following command:

    $ oc adm release info -o jsonpath="{ .metadata.metadata}"

Verification

  • If you see the following output, your cluster is using the multi-architecture payload:

    {
     "release.openshift.io/architecture": "multi",
     "url": "https://access.redhat.com/errata/<errata_version>"
    }

    You can then begin adding multi-arch compute nodes to your cluster.

  • If you see the following output, your cluster is not using the multi-architecture payload:

    {
     "url": "https://access.redhat.com/errata/<errata_version>"
    }
    Important

    To migrate your cluster so the cluster supports multi-architecture compute machines, follow the procedure in Migrating to a cluster with multi-architecture compute machines.

3.8.2. Creating RHCOS machines using virt-install

You can create more Red Hat Enterprise Linux CoreOS (RHCOS) compute machines for your cluster by using virt-install.

Prerequisites

  • You have at least one LPAR running on RHEL 8.7 or later with KVM, referred to as RHEL KVM host in this procedure.
  • The KVM/QEMU hypervisor is installed on the RHEL KVM host.
  • You have a domain name server (DNS) that can perform hostname and reverse lookup for the nodes.
  • An HTTP or HTTPS server is set up.

Procedure

  1. Disable UDP aggregation.

    Currently, UDP aggregation is not supported on IBM Z® and is not automatically deactivated on multi-architecture compute clusters with an x86_64 control plane and additional s390x compute machines. To ensure that the addtional compute nodes are added to the cluster correctly, you must manually disable UDP aggregation.

    1. Create a YAML file udp-aggregation-config.yaml with the following content:

      apiVersion: v1
      kind: ConfigMap
      data:
        disable-udp-aggregation: "true"
      metadata:
        name: udp-aggregation-config
        namespace: openshift-network-operator
    2. Create the ConfigMap resource by running the following command:

      $ oc create -f udp-aggregation-config.yaml
  2. Extract the Ignition config file from the cluster by running the following command:

    $ oc extract -n openshift-machine-api secret/worker-user-data-managed --keys=userData --to=- > worker.ign
  3. Upload the worker.ign Ignition config file you exported from your cluster to your HTTP server. Note the URL of this file.
  4. You can validate that the Ignition file is available on the URL. The following example gets the Ignition config file for the compute node:

    $ curl -k http://<HTTP_server>/worker.ign
  5. Download the RHEL live kernel, initramfs, and rootfs files by running the following commands:

     $ curl -LO $(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' \
    | jq -r '.architectures.s390x.artifacts.metal.formats.pxe.kernel.location')
    $ curl -LO $(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' \
    | jq -r '.architectures.s390x.artifacts.metal.formats.pxe.initramfs.location')
    $ curl -LO $(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' \
    | jq -r '.architectures.s390x.artifacts.metal.formats.pxe.rootfs.location')
  6. Move the downloaded RHEL live kernel, initramfs and rootfs files to an HTTP or HTTPS server before you launch virt-install.
  7. Create the new KVM guest nodes using the RHEL kernel, initramfs, and Ignition files; the new disk image; and adjusted parm line arguments.

    $ virt-install \
       --connect qemu:///system \
       --name <vm_name> \
       --autostart \
       --os-variant rhel9.4 \ 1
       --cpu host \
       --vcpus <vcpus> \
       --memory <memory_mb> \
       --disk <vm_name>.qcow2,size=<image_size> \
       --network network=<virt_network_parm> \
       --location <media_location>,kernel=<rhcos_kernel>,initrd=<rhcos_initrd> \ 2
       --extra-args "rd.neednet=1" \
       --extra-args "coreos.inst.install_dev=/dev/vda" \
       --extra-args "coreos.inst.ignition_url=http://<http_server>/worker.ign " \ 3
       --extra-args "coreos.live.rootfs_url=http://<http_server>/rhcos-<version>-live-rootfs.<architecture>.img" \ 4
       --extra-args "ip=<ip>::<gateway>:<netmask>:<hostname>::none" \ 5
       --extra-args "nameserver=<dns>" \
       --extra-args "console=ttysclp0" \
       --noautoconsole \
       --wait
    1
    For os-variant, specify the RHEL version for the RHCOS compute machine. rhel9.4 is the recommended version. To query the supported RHEL version of your operating system, run the following command:
    $ osinfo-query os -f short-id
    Note

    The os-variant is case sensitive.

    2
    For --location, specify the location of the kernel/initrd on the HTTP or HTTPS server.
    3
    Specify the location of the worker.ign config file. Only HTTP and HTTPS protocols are supported.
    4
    Specify the location of the rootfs artifact for the kernel and initramfs you are booting. Only HTTP and HTTPS protocols are supported
    5
    Optional: For hostname, specify the fully qualified hostname of the client machine.
    Note

    If you are using HAProxy as a load balancer, update your HAProxy rules for ingress-router-443 and ingress-router-80 in the /etc/haproxy/haproxy.cfg configuration file.

  8. Continue to create more compute machines for your cluster.

3.8.3. Approving the certificate signing requests for your machines

When you add machines to a cluster, two pending certificate signing requests (CSRs) are generated for each machine that you added. You must confirm that these CSRs are approved or, if necessary, approve them yourself. The client requests must be approved first, followed by the server requests.

Prerequisites

  • You added machines to your cluster.

Procedure

  1. Confirm that the cluster recognizes the machines:

    $ oc get nodes

    Example output

    NAME      STATUS    ROLES   AGE  VERSION
    master-0  Ready     master  63m  v1.30.3
    master-1  Ready     master  63m  v1.30.3
    master-2  Ready     master  64m  v1.30.3

    The output lists all of the machines that you created.

    Note

    The preceding output might not include the compute nodes, also known as worker nodes, until some CSRs are approved.

  2. Review the pending CSRs and ensure that you see the client requests with the Pending or Approved status for each machine that you added to the cluster:

    $ oc get csr

    Example output

    NAME        AGE     REQUESTOR                                                                   CONDITION
    csr-8b2br   15m     system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending
    csr-8vnps   15m     system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending
    ...

    In this example, two machines are joining the cluster. You might see more approved CSRs in the list.

  3. If the CSRs were not approved, after all of the pending CSRs for the machines you added are in Pending status, approve the CSRs for your cluster machines:

    Note

    Because the CSRs rotate automatically, approve your CSRs within an hour of adding the machines to the cluster. If you do not approve them within an hour, the certificates will rotate, and more than two certificates will be present for each node. You must approve all of these certificates. After the client CSR is approved, the Kubelet creates a secondary CSR for the serving certificate, which requires manual approval. Then, subsequent serving certificate renewal requests are automatically approved by the machine-approver if the Kubelet requests a new certificate with identical parameters.

    Note

    For clusters running on platforms that are not machine API enabled, such as bare metal and other user-provisioned infrastructure, you must implement a method of automatically approving the kubelet serving certificate requests (CSRs). If a request is not approved, then the oc exec, oc rsh, and oc logs commands cannot succeed, because a serving certificate is required when the API server connects to the kubelet. Any operation that contacts the Kubelet endpoint requires this certificate approval to be in place. The method must watch for new CSRs, confirm that the CSR was submitted by the node-bootstrapper service account in the system:node or system:admin groups, and confirm the identity of the node.

    • To approve them individually, run the following command for each valid CSR:

      $ oc adm certificate approve <csr_name> 1
      1
      <csr_name> is the name of a CSR from the list of current CSRs.
    • To approve all pending CSRs, run the following command:

      $ oc get csr -o go-template='{{range .items}}{{if not .status}}{{.metadata.name}}{{"\n"}}{{end}}{{end}}' | xargs --no-run-if-empty oc adm certificate approve
      Note

      Some Operators might not become available until some CSRs are approved.

  4. Now that your client requests are approved, you must review the server requests for each machine that you added to the cluster:

    $ oc get csr

    Example output

    NAME        AGE     REQUESTOR                                                                   CONDITION
    csr-bfd72   5m26s   system:node:ip-10-0-50-126.us-east-2.compute.internal                       Pending
    csr-c57lv   5m26s   system:node:ip-10-0-95-157.us-east-2.compute.internal                       Pending
    ...

  5. If the remaining CSRs are not approved, and are in the Pending status, approve the CSRs for your cluster machines:

    • To approve them individually, run the following command for each valid CSR:

      $ oc adm certificate approve <csr_name> 1
      1
      <csr_name> is the name of a CSR from the list of current CSRs.
    • To approve all pending CSRs, run the following command:

      $ oc get csr -o go-template='{{range .items}}{{if not .status}}{{.metadata.name}}{{"\n"}}{{end}}{{end}}' | xargs oc adm certificate approve
  6. After all client and server CSRs have been approved, the machines have the Ready status. Verify this by running the following command:

    $ oc get nodes

    Example output

    NAME      STATUS    ROLES   AGE  VERSION
    master-0  Ready     master  73m  v1.30.3
    master-1  Ready     master  73m  v1.30.3
    master-2  Ready     master  74m  v1.30.3
    worker-0  Ready     worker  11m  v1.30.3
    worker-1  Ready     worker  11m  v1.30.3

    Note

    It can take a few minutes after approval of the server CSRs for the machines to transition to the Ready status.

Additional information

3.9. Creating a cluster with multi-architecture compute machines on IBM Power

To create a cluster with multi-architecture compute machines on IBM Power® (ppc64le), you must have an existing single-architecture (x86_64) cluster. You can then add ppc64le compute machines to your OpenShift Container Platform cluster.

Important

Before you can add ppc64le nodes to your cluster, you must upgrade your cluster to one that uses the multi-architecture payload. For more information on migrating to the multi-architecture payload, see Migrating to a cluster with multi-architecture compute machines.

The following procedures explain how to create a RHCOS compute machine using an ISO image or network PXE booting. This will allow you to add ppc64le nodes to your cluster and deploy a cluster with multi-architecture compute machines.

To create an IBM Power® (ppc64le) cluster with multi-architecture compute machines on x86_64, follow the instructions for Installing a cluster on IBM Power®. You can then add x86_64 compute machines as described in Creating a cluster with multi-architecture compute machines on bare metal, IBM Power, or IBM Z.

Note

Before adding a secondary architecture node to your cluster, it is recommended to install the Multiarch Tuning Operator, and deploy a ClusterPodPlacementConfig object. For more information, see Managing workloads on multi-architecture clusters by using the Multiarch Tuning Operator.

3.9.1. Verifying cluster compatibility

Before you can start adding compute nodes of different architectures to your cluster, you must verify that your cluster is multi-architecture compatible.

Prerequisites

  • You installed the OpenShift CLI (oc).
Note

When using multiple architectures, hosts for OpenShift Container Platform nodes must share the same storage layer. If they do not have the same storage layer, use a storage provider such as nfs-provisioner.

Note

You should limit the number of network hops between the compute and control plane as much as possible.

Procedure

  1. Log in to the OpenShift CLI (oc).
  2. You can check that your cluster uses the architecture payload by running the following command:

    $ oc adm release info -o jsonpath="{ .metadata.metadata}"

Verification

  • If you see the following output, your cluster is using the multi-architecture payload:

    {
     "release.openshift.io/architecture": "multi",
     "url": "https://access.redhat.com/errata/<errata_version>"
    }

    You can then begin adding multi-arch compute nodes to your cluster.

  • If you see the following output, your cluster is not using the multi-architecture payload:

    {
     "url": "https://access.redhat.com/errata/<errata_version>"
    }
    Important

    To migrate your cluster so the cluster supports multi-architecture compute machines, follow the procedure in Migrating to a cluster with multi-architecture compute machines.

3.9.2. Creating RHCOS machines using an ISO image

You can create more Red Hat Enterprise Linux CoreOS (RHCOS) compute machines for your cluster by using an ISO image to create the machines.

Prerequisites

  • Obtain the URL of the Ignition config file for the compute machines for your cluster. You uploaded this file to your HTTP server during installation.
  • You must have the OpenShift CLI (oc) installed.

Procedure

  1. Extract the Ignition config file from the cluster by running the following command:

    $ oc extract -n openshift-machine-api secret/worker-user-data-managed --keys=userData --to=- > worker.ign
  2. Upload the worker.ign Ignition config file you exported from your cluster to your HTTP server. Note the URLs of these files.
  3. You can validate that the ignition files are available on the URLs. The following example gets the Ignition config files for the compute node:

    $ curl -k http://<HTTP_server>/worker.ign
  4. You can access the ISO image for booting your new machine by running to following command:

    RHCOS_VHD_ORIGIN_URL=$(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' | jq -r '.architectures.<architecture>.artifacts.metal.formats.iso.disk.location')
  5. Use the ISO file to install RHCOS on more compute machines. Use the same method that you used when you created machines before you installed the cluster:

    • Burn the ISO image to a disk and boot it directly.
    • Use ISO redirection with a LOM interface.
  6. Boot the RHCOS ISO image without specifying any options, or interrupting the live boot sequence. Wait for the installer to boot into a shell prompt in the RHCOS live environment.

    Note

    You can interrupt the RHCOS installation boot process to add kernel arguments. However, for this ISO procedure you must use the coreos-installer command as outlined in the following steps, instead of adding kernel arguments.

  7. Run the coreos-installer command and specify the options that meet your installation requirements. At a minimum, you must specify the URL that points to the Ignition config file for the node type, and the device that you are installing to:

    $ sudo coreos-installer install --ignition-url=http://<HTTP_server>/<node_type>.ign <device> --ignition-hash=sha512-<digest> 12
    1
    You must run the coreos-installer command by using sudo, because the core user does not have the required root privileges to perform the installation.
    2
    The --ignition-hash option is required when the Ignition config file is obtained through an HTTP URL to validate the authenticity of the Ignition config file on the cluster node. <digest> is the Ignition config file SHA512 digest obtained in a preceding step.
    Note

    If you want to provide your Ignition config files through an HTTPS server that uses TLS, you can add the internal certificate authority (CA) to the system trust store before running coreos-installer.

    The following example initializes a bootstrap node installation to the /dev/sda device. The Ignition config file for the bootstrap node is obtained from an HTTP web server with the IP address 192.168.1.2:

    $ sudo coreos-installer install --ignition-url=http://192.168.1.2:80/installation_directory/bootstrap.ign /dev/sda --ignition-hash=sha512-a5a2d43879223273c9b60af66b44202a1d1248fc01cf156c46d4a79f552b6bad47bc8cc78ddf0116e80c59d2ea9e32ba53bc807afbca581aa059311def2c3e3b
  8. Monitor the progress of the RHCOS installation on the console of the machine.

    Important

    Ensure that the installation is successful on each node before commencing with the OpenShift Container Platform installation. Observing the installation process can also help to determine the cause of RHCOS installation issues that might arise.

  9. Continue to create more compute machines for your cluster.

3.9.3. Creating RHCOS machines by PXE or iPXE booting

You can create more Red Hat Enterprise Linux CoreOS (RHCOS) compute machines for your bare metal cluster by using PXE or iPXE booting.

Prerequisites

  • Obtain the URL of the Ignition config file for the compute machines for your cluster. You uploaded this file to your HTTP server during installation.
  • Obtain the URLs of the RHCOS ISO image, compressed metal BIOS, kernel, and initramfs files that you uploaded to your HTTP server during cluster installation.
  • You have access to the PXE booting infrastructure that you used to create the machines for your OpenShift Container Platform cluster during installation. The machines must boot from their local disks after RHCOS is installed on them.
  • If you use UEFI, you have access to the grub.conf file that you modified during OpenShift Container Platform installation.

Procedure

  1. Confirm that your PXE or iPXE installation for the RHCOS images is correct.

    • For PXE:

      DEFAULT pxeboot
      TIMEOUT 20
      PROMPT 0
      LABEL pxeboot
          KERNEL http://<HTTP_server>/rhcos-<version>-live-kernel-<architecture> 1
          APPEND initrd=http://<HTTP_server>/rhcos-<version>-live-initramfs.<architecture>.img coreos.inst.install_dev=/dev/sda coreos.inst.ignition_url=http://<HTTP_server>/worker.ign coreos.live.rootfs_url=http://<HTTP_server>/rhcos-<version>-live-rootfs.<architecture>.img 2
      1
      Specify the location of the live kernel file that you uploaded to your HTTP server.
      2
      Specify locations of the RHCOS files that you uploaded to your HTTP server. The initrd parameter value is the location of the live initramfs file, the coreos.inst.ignition_url parameter value is the location of the worker Ignition config file, and the coreos.live.rootfs_url parameter value is the location of the live rootfs file. The coreos.inst.ignition_url and coreos.live.rootfs_url parameters only support HTTP and HTTPS.
      Note

      This configuration does not enable serial console access on machines with a graphical console. To configure a different console, add one or more console= arguments to the APPEND line. For example, add console=tty0 console=ttyS0 to set the first PC serial port as the primary console and the graphical console as a secondary console. For more information, see How does one set up a serial terminal and/or console in Red Hat Enterprise Linux?.

    • For iPXE (x86_64 + ppc64le):

      kernel http://<HTTP_server>/rhcos-<version>-live-kernel-<architecture> initrd=main coreos.live.rootfs_url=http://<HTTP_server>/rhcos-<version>-live-rootfs.<architecture>.img coreos.inst.install_dev=/dev/sda coreos.inst.ignition_url=http://<HTTP_server>/worker.ign 1 2
      initrd --name main http://<HTTP_server>/rhcos-<version>-live-initramfs.<architecture>.img 3
      boot
      1
      Specify the locations of the RHCOS files that you uploaded to your HTTP server. The kernel parameter value is the location of the kernel file, the initrd=main argument is needed for booting on UEFI systems, the coreos.live.rootfs_url parameter value is the location of the rootfs file, and the coreos.inst.ignition_url parameter value is the location of the worker Ignition config file.
      2
      If you use multiple NICs, specify a single interface in the ip option. For example, to use DHCP on a NIC that is named eno1, set ip=eno1:dhcp.
      3
      Specify the location of the initramfs file that you uploaded to your HTTP server.
      Note

      This configuration does not enable serial console access on machines with a graphical console To configure a different console, add one or more console= arguments to the kernel line. For example, add console=tty0 console=ttyS0 to set the first PC serial port as the primary console and the graphical console as a secondary console. For more information, see How does one set up a serial terminal and/or console in Red Hat Enterprise Linux? and "Enabling the serial console for PXE and ISO installation" in the "Advanced RHCOS installation configuration" section.

      Note

      To network boot the CoreOS kernel on ppc64le architecture, you need to use a version of iPXE build with the IMAGE_GZIP option enabled. See IMAGE_GZIP option in iPXE.

    • For PXE (with UEFI and GRUB as second stage) on ppc64le:

      menuentry 'Install CoreOS' {
          linux rhcos-<version>-live-kernel-<architecture>  coreos.live.rootfs_url=http://<HTTP_server>/rhcos-<version>-live-rootfs.<architecture>.img coreos.inst.install_dev=/dev/sda coreos.inst.ignition_url=http://<HTTP_server>/worker.ign 1 2
          initrd rhcos-<version>-live-initramfs.<architecture>.img 3
      }
      1
      Specify the locations of the RHCOS files that you uploaded to your HTTP/TFTP server. The kernel parameter value is the location of the kernel file on your TFTP server. The coreos.live.rootfs_url parameter value is the location of the rootfs file, and the coreos.inst.ignition_url parameter value is the location of the worker Ignition config file on your HTTP Server.
      2
      If you use multiple NICs, specify a single interface in the ip option. For example, to use DHCP on a NIC that is named eno1, set ip=eno1:dhcp.
      3
      Specify the location of the initramfs file that you uploaded to your TFTP server.
  2. Use the PXE or iPXE infrastructure to create the required compute machines for your cluster.

3.9.4. Approving the certificate signing requests for your machines

When you add machines to a cluster, two pending certificate signing requests (CSRs) are generated for each machine that you added. You must confirm that these CSRs are approved or, if necessary, approve them yourself. The client requests must be approved first, followed by the server requests.

Prerequisites

  • You added machines to your cluster.

Procedure

  1. Confirm that the cluster recognizes the machines:

    $ oc get nodes

    Example output

    NAME      STATUS    ROLES   AGE  VERSION
    master-0  Ready     master  63m  v1.30.3
    master-1  Ready     master  63m  v1.30.3
    master-2  Ready     master  64m  v1.30.3

    The output lists all of the machines that you created.

    Note

    The preceding output might not include the compute nodes, also known as worker nodes, until some CSRs are approved.

  2. Review the pending CSRs and ensure that you see the client requests with the Pending or Approved status for each machine that you added to the cluster:

    $ oc get csr

    Example output

    NAME        AGE     REQUESTOR                                                                   CONDITION
    csr-8b2br   15m     system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending
    csr-8vnps   15m     system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending
    ...

    In this example, two machines are joining the cluster. You might see more approved CSRs in the list.

  3. If the CSRs were not approved, after all of the pending CSRs for the machines you added are in Pending status, approve the CSRs for your cluster machines:

    Note

    Because the CSRs rotate automatically, approve your CSRs within an hour of adding the machines to the cluster. If you do not approve them within an hour, the certificates will rotate, and more than two certificates will be present for each node. You must approve all of these certificates. After the client CSR is approved, the Kubelet creates a secondary CSR for the serving certificate, which requires manual approval. Then, subsequent serving certificate renewal requests are automatically approved by the machine-approver if the Kubelet requests a new certificate with identical parameters.

    Note

    For clusters running on platforms that are not machine API enabled, such as bare metal and other user-provisioned infrastructure, you must implement a method of automatically approving the kubelet serving certificate requests (CSRs). If a request is not approved, then the oc exec, oc rsh, and oc logs commands cannot succeed, because a serving certificate is required when the API server connects to the kubelet. Any operation that contacts the Kubelet endpoint requires this certificate approval to be in place. The method must watch for new CSRs, confirm that the CSR was submitted by the node-bootstrapper service account in the system:node or system:admin groups, and confirm the identity of the node.

    • To approve them individually, run the following command for each valid CSR:

      $ oc adm certificate approve <csr_name> 1
      1
      <csr_name> is the name of a CSR from the list of current CSRs.
    • To approve all pending CSRs, run the following command:

      $ oc get csr -o go-template='{{range .items}}{{if not .status}}{{.metadata.name}}{{"\n"}}{{end}}{{end}}' | xargs --no-run-if-empty oc adm certificate approve
      Note

      Some Operators might not become available until some CSRs are approved.

  4. Now that your client requests are approved, you must review the server requests for each machine that you added to the cluster:

    $ oc get csr

    Example output

    NAME        AGE     REQUESTOR                                                                   CONDITION
    csr-bfd72   5m26s   system:node:ip-10-0-50-126.us-east-2.compute.internal                       Pending
    csr-c57lv   5m26s   system:node:ip-10-0-95-157.us-east-2.compute.internal                       Pending
    ...

  5. If the remaining CSRs are not approved, and are in the Pending status, approve the CSRs for your cluster machines:

    • To approve them individually, run the following command for each valid CSR:

      $ oc adm certificate approve <csr_name> 1
      1
      <csr_name> is the name of a CSR from the list of current CSRs.
    • To approve all pending CSRs, run the following command:

      $ oc get csr -o go-template='{{range .items}}{{if not .status}}{{.metadata.name}}{{"\n"}}{{end}}{{end}}' | xargs oc adm certificate approve
  6. After all client and server CSRs have been approved, the machines have the Ready status. Verify this by running the following command:

    $ oc get nodes -o wide

    Example output

    NAME               STATUS   ROLES                  AGE   VERSION   INTERNAL-IP      EXTERNAL-IP   OS-IMAGE                                                       KERNEL-VERSION                  CONTAINER-RUNTIME
    worker-0-ppc64le   Ready    worker                 42d   v1.30.3   192.168.200.21   <none>        Red Hat Enterprise Linux CoreOS 415.92.202309261919-0 (Plow)   5.14.0-284.34.1.el9_2.ppc64le   cri-o://1.30.3-3.rhaos4.15.gitb36169e.el9
    worker-1-ppc64le   Ready    worker                 42d   v1.30.3   192.168.200.20   <none>        Red Hat Enterprise Linux CoreOS 415.92.202309261919-0 (Plow)   5.14.0-284.34.1.el9_2.ppc64le   cri-o://1.30.3-3.rhaos4.15.gitb36169e.el9
    master-0-x86       Ready    control-plane,master   75d   v1.30.3   10.248.0.38      10.248.0.38   Red Hat Enterprise Linux CoreOS 415.92.202309261919-0 (Plow)   5.14.0-284.34.1.el9_2.x86_64    cri-o://1.30.3-3.rhaos4.15.gitb36169e.el9
    master-1-x86       Ready    control-plane,master   75d   v1.30.3   10.248.0.39      10.248.0.39   Red Hat Enterprise Linux CoreOS 415.92.202309261919-0 (Plow)   5.14.0-284.34.1.el9_2.x86_64    cri-o://1.30.3-3.rhaos4.15.gitb36169e.el9
    master-2-x86       Ready    control-plane,master   75d   v1.30.3   10.248.0.40      10.248.0.40   Red Hat Enterprise Linux CoreOS 415.92.202309261919-0 (Plow)   5.14.0-284.34.1.el9_2.x86_64    cri-o://1.30.3-3.rhaos4.15.gitb36169e.el9
    worker-0-x86       Ready    worker                 75d   v1.30.3   10.248.0.43      10.248.0.43   Red Hat Enterprise Linux CoreOS 415.92.202309261919-0 (Plow)   5.14.0-284.34.1.el9_2.x86_64    cri-o://1.30.3-3.rhaos4.15.gitb36169e.el9
    worker-1-x86       Ready    worker                 75d   v1.30.3   10.248.0.44      10.248.0.44   Red Hat Enterprise Linux CoreOS 415.92.202309261919-0 (Plow)   5.14.0-284.34.1.el9_2.x86_64    cri-o://1.30.3-3.rhaos4.15.gitb36169e.el9

    Note

    It can take a few minutes after approval of the server CSRs for the machines to transition to the Ready status.

Additional information

3.10. Managing a cluster with multi-architecture compute machines

Managing a cluster that has nodes with multiple architectures requires you to consider node architecture as you monitor the cluster and manage your workloads. This requires you to take additional considerations into account when you configure cluster resource requirements and behavior, or schedule workloads in a multi-architecture cluster.

3.10.1. Scheduling workloads on clusters with multi-architecture compute machines

When you deploy workloads on a cluster with compute nodes that use different architectures, you must align pod architecture with the architecture of the underlying node. Your workload may also require additional configuration to particular resources depending on the underlying node architecture.

You can use the Multiarch Tuning Operator to enable architecture-aware scheduling of workloads on clusters with multi-architecture compute machines. The Multiarch Tuning Operator implements additional scheduler predicates in the pods specifications based on the architectures that the pods can support at creation time.

3.10.1.1. Sample multi-architecture node workload deployments

Scheduling a workload to an appropriate node based on architecture works in the same way as scheduling based on any other node characteristic. Consider the following options when determining how to schedule your workloads.

Using nodeAffinity to schedule nodes with specific architectures

You can allow a workload to be scheduled on only a set of nodes with architectures supported by its images, you can set the spec.affinity.nodeAffinity field in your pod’s template specification.

apiVersion: apps/v1
kind: Deployment
metadata: # ...
spec:
   # ...
  template:
     # ...
    spec:
      affinity:
        nodeAffinity:
          requiredDuringSchedulingIgnoredDuringExecution:
            nodeSelectorTerms:
            - matchExpressions:
              - key: kubernetes.io/arch
                operator: In
                values: 1
                - amd64
                - arm64
1
Specify the supported architectures. Valid values include amd64,arm64, or both values.
Tainting each node for a specific architecture

You can taint a node to avoid the node scheduling workloads that are incompatible with its architecture. When your cluster uses a MachineSet object, you can add parameters to the .spec.template.spec.taints field to avoid workloads being scheduled on nodes with non-supported architectures.

Before you add a taint to a node, you must scale down the MachineSet object or remove existing available machines. For more information, see Modifying a compute machine set.

apiVersion: machine.openshift.io/v1beta1
kind: MachineSet
metadata: # ...
spec:
  # ...
  template:
    # ...
    spec:
      # ...
      taints:
      - effect: NoSchedule
        key: multiarch.openshift.io/arch
        value: arm64

You can also set a taint on a specific node by running the following command:

$ oc adm taint nodes <node-name> multiarch.openshift.io/arch=arm64:NoSchedule
Creating a default toleration in a namespace

When a node or machine set has a taint, only workloads that tolerate that taint can be scheduled. You can annotate a namespace so all of the workloads get the same default toleration by running the following command:

$ oc annotate namespace my-namespace \
  'scheduler.alpha.kubernetes.io/defaultTolerations'='[{"operator": "Exists", "effect": "NoSchedule", "key": "multiarch.openshift.io/arch"}]'
Tolerating architecture taints in workloads

When a node or machine set has a taint, only workloads that tolerate that taint can be scheduled. You can configure your workload with a toleration so that it is scheduled on nodes with specific architecture taints.

apiVersion: apps/v1
kind: Deployment
metadata: # ...
spec:
  # ...
  template:
    # ...
    spec:
      tolerations:
      - key: "multiarch.openshift.io/arch"
        value: "arm64"
        operator: "Equal"
        effect: "NoSchedule"

This example deployment can be scheduled on nodes and machine sets that have the multiarch.openshift.io/arch=arm64 taint specified.

Using node affinity with taints and tolerations

When a scheduler computes the set of nodes to schedule a pod, tolerations can broaden the set while node affinity restricts the set. If you set a taint on nodes that have a specific architecture, you must also add a toleration to workloads that you want to be scheduled there.

apiVersion: apps/v1
kind: Deployment
metadata: # ...
spec:
  # ...
  template:
    # ...
    spec:
      affinity:
        nodeAffinity:
          requiredDuringSchedulingIgnoredDuringExecution:
            nodeSelectorTerms:
            - matchExpressions:
              - key: kubernetes.io/arch
                operator: In
                values:
                - amd64
                - arm64
      tolerations:
      - key: "multiarch.openshift.io/arch"
        value: "arm64"
        operator: "Equal"
        effect: "NoSchedule"

3.10.2. Enabling 64k pages on the Red Hat Enterprise Linux CoreOS (RHCOS) kernel

You can enable the 64k memory page in the Red Hat Enterprise Linux CoreOS (RHCOS) kernel on the 64-bit ARM compute machines in your cluster. The 64k page size kernel specification can be used for large GPU or high memory workloads. This is done using the Machine Config Operator (MCO) which uses a machine config pool to update the kernel. To enable 64k page sizes, you must dedicate a machine config pool for ARM64 to enable on the kernel.

Important

Using 64k pages is exclusive to 64-bit ARM architecture compute nodes or clusters installed on 64-bit ARM machines. If you configure the 64k pages kernel on a machine config pool using 64-bit x86 machines, the machine config pool and MCO will degrade.

Prerequisites

  • You installed the OpenShift CLI (oc).
  • You created a cluster with compute nodes of different architecture on one of the supported platforms.

Procedure

  1. Label the nodes where you want to run the 64k page size kernel:

    $ oc label node <node_name> <label>

    Example command

    $ oc label node worker-arm64-01 node-role.kubernetes.io/worker-64k-pages=

  2. Create a machine config pool that contains the worker role that uses the ARM64 architecture and the worker-64k-pages role:

    apiVersion: machineconfiguration.openshift.io/v1
    kind: MachineConfigPool
    metadata:
      name: worker-64k-pages
    spec:
      machineConfigSelector:
        matchExpressions:
          - key: machineconfiguration.openshift.io/role
            operator: In
            values:
            - worker
            - worker-64k-pages
      nodeSelector:
        matchLabels:
          node-role.kubernetes.io/worker-64k-pages: ""
          kubernetes.io/arch: arm64
  3. Create a machine config on your compute node to enable 64k-pages with the 64k-pages parameter.

    $ oc create -f <filename>.yaml

    Example MachineConfig

    apiVersion: machineconfiguration.openshift.io/v1
    kind: MachineConfig
    metadata:
      labels:
        machineconfiguration.openshift.io/role: "worker-64k-pages" 1
      name: 99-worker-64kpages
    spec:
      kernelType: 64k-pages 2

    1
    Specify the value of the machineconfiguration.openshift.io/role label in the custom machine config pool. The example MachineConfig uses the worker-64k-pages label to enable 64k pages in the worker-64k-pages pool.
    2
    Specify your desired kernel type. Valid values are 64k-pages and default
    Note

    The 64k-pages type is supported on only 64-bit ARM architecture based compute nodes. The realtime type is supported on only 64-bit x86 architecture based compute nodes.

Verification

  • To view your new worker-64k-pages machine config pool, run the following command:

    $ oc get mcp

    Example output

    NAME     CONFIG                                                                UPDATED   UPDATING   DEGRADED   MACHINECOUNT   READYMACHINECOUNT   UPDATEDMACHINECOUNT   DEGRADEDMACHINECOUNT   AGE
    master   rendered-master-9d55ac9a91127c36314e1efe7d77fbf8                      True      False      False      3              3                   3                     0                      361d
    worker   rendered-worker-e7b61751c4a5b7ff995d64b967c421ff                      True      False      False      7              7                   7                     0                      361d
    worker-64k-pages  rendered-worker-64k-pages-e7b61751c4a5b7ff995d64b967c421ff   True      False      False      2              2                   2                     0                      35m

3.10.3. Importing manifest lists in image streams on your multi-architecture compute machines

On an OpenShift Container Platform 4.17 cluster with multi-architecture compute machines, the image streams in the cluster do not import manifest lists automatically. You must manually change the default importMode option to the PreserveOriginal option in order to import the manifest list.

Prerequisites

  • You installed the OpenShift Container Platform CLI (oc).

Procedure

  • The following example command shows how to patch the ImageStream cli-artifacts so that the cli-artifacts:latest image stream tag is imported as a manifest list.

    $ oc patch is/cli-artifacts -n openshift -p '{"spec":{"tags":[{"name":"latest","importPolicy":{"importMode":"PreserveOriginal"}}]}}'

Verification

  • You can check that the manifest lists imported properly by inspecting the image stream tag. The following command will list the individual architecture manifests for a particular tag.

    $ oc get istag cli-artifacts:latest -n openshift -oyaml

    If the dockerImageManifests object is present, then the manifest list import was successful.

    Example output of the dockerImageManifests object

    dockerImageManifests:
      - architecture: amd64
        digest: sha256:16d4c96c52923a9968fbfa69425ec703aff711f1db822e4e9788bf5d2bee5d77
        manifestSize: 1252
        mediaType: application/vnd.docker.distribution.manifest.v2+json
        os: linux
      - architecture: arm64
        digest: sha256:6ec8ad0d897bcdf727531f7d0b716931728999492709d19d8b09f0d90d57f626
        manifestSize: 1252
        mediaType: application/vnd.docker.distribution.manifest.v2+json
        os: linux
      - architecture: ppc64le
        digest: sha256:65949e3a80349cdc42acd8c5b34cde6ebc3241eae8daaeea458498fedb359a6a
        manifestSize: 1252
        mediaType: application/vnd.docker.distribution.manifest.v2+json
        os: linux
      - architecture: s390x
        digest: sha256:75f4fa21224b5d5d511bea8f92dfa8e1c00231e5c81ab95e83c3013d245d1719
        manifestSize: 1252
        mediaType: application/vnd.docker.distribution.manifest.v2+json
        os: linux

3.11. Managing workloads on multi-architecture clusters by using the Multiarch Tuning Operator

The Multiarch Tuning Operator optimizes workload management within multi-architecture clusters and in single-architecture clusters transitioning to multi-architecture environments.

Architecture-aware workload scheduling allows the scheduler to place pods onto nodes that match the architecture of the pod images.

By default, the scheduler does not consider the architecture of a pod’s container images when determining the placement of new pods onto nodes.

To enable architecture-aware workload scheduling, you must create the ClusterPodPlacementConfig object. When you create the ClusterPodPlacementConfig object, the Multiarch Tuning Operator deploys the necessary operands to support architecture-aware workload scheduling.

When a pod is created, the operands perform the following actions:

  1. Add the multiarch.openshift.io/scheduling-gate scheduling gate that prevents the scheduling of the pod.
  2. Compute a scheduling predicate that includes the supported architecture values for the kubernetes.io/arch label.
  3. Integrate the scheduling predicate as a nodeAffinity requirement in the pod specification.
  4. Remove the scheduling gate from the pod.
Important

Note the following operand behaviors:

  • If the nodeSelector field is already configured with the kubernetes.io/arch label for a workload, the operand does not update the nodeAffinity field for that workload.
  • If the nodeSelector field is not configured with the kubernetes.io/arch label for a workload, the operand updates the nodeAffinity field for that workload. However, in that nodeAffinity field, the operand updates only the node selector terms that are not configured with the kubernetes.io/arch label.
  • If the nodeName field is already set, the Multiarch Tuning Operator does not process the pod.

3.11.1. Installing the Multiarch Tuning Operator by using the CLI

You can install the Multiarch Tuning Operator by using the OpenShift CLI (oc).

Prerequisites

  • You have installed oc.
  • You have logged in to oc as a user with cluster-admin privileges.

Procedure

  1. Create a new project named openshift-multiarch-tuning-operator by running the following command:

    $ oc create ns openshift-multiarch-tuning-operator
  2. Create an OperatorGroup object:

    1. Create a YAML file with the configuration for creating an OperatorGroup object.

      Example YAML configuration for creating an OperatorGroup object

      apiVersion: operators.coreos.com/v1
      kind: OperatorGroup
      metadata:
        name: openshift-multiarch-tuning-operator
        namespace: openshift-multiarch-tuning-operator
      spec: {}

    2. Create the OperatorGroup object by running the following command:

      $ oc create -f <file_name> 1
      1
      Replace <file_name> with the name of the YAML file that contains the OperatorGroup object configuration.
  3. Create a Subscription object:

    1. Create a YAML file with the configuration for creating a Subscription object.

      Example YAML configuration for creating a Subscription object

      apiVersion: operators.coreos.com/v1alpha1
      kind: Subscription
      metadata:
        name: openshift-multiarch-tuning-operator
        namespace: openshift-multiarch-tuning-operator
      spec:
        channel: stable
        name: multiarch-tuning-operator
        source: redhat-operators
        sourceNamespace: openshift-marketplace
        installPlanApproval: Automatic
        startingCSV: multiarch-tuning-operator.v1.0.0

    2. Create the Subscription object by running the following command:

      $ oc create -f <file_name> 1
      1
      Replace <file_name> with the name of the YAML file that contains the Subscription object configuration.
Note

For more details about configuring the Subscription object and OperatorGroup object, see "Installing from OperatorHub using the CLI".

Verification

  1. To verify that the Multiarch Tuning Operator is installed, run the following command:

    $ oc get csv -n openshift-multiarch-tuning-operator

    Example output

    NAME                               DISPLAY                     VERSION   REPLACES                              PHASE
    multiarch-tuning-operator.v1.0.0   Multiarch Tuning Operator   1.0.0     multiarch-tuning-operator.v0.9.0      Succeeded

    The installation is successful if the Operator is in Succeeded phase.

  2. Optional: To verify that the OperatorGroup object is created, run the following command:

    $ oc get operatorgroup -n openshift-multiarch-tuning-operator

    Example output

    NAME                                        AGE
    openshift-multiarch-tuning-operator-q8zbb   133m

  3. Optional: To verify that the Subscription object is created, run the following command:

    $ oc get subscription -n openshift-multiarch-tuning-operator

    Example output

    NAME                        PACKAGE                     SOURCE                  CHANNEL
    multiarch-tuning-operator   multiarch-tuning-operator   redhat-operators        stable

3.11.2. Installing the Multiarch Tuning Operator by using the web console

You can install the Multiarch Tuning Operator by using the OpenShift Container Platform web console.

Prerequisites

  • You have access to the cluster with cluster-admin privileges.
  • You have access to the OpenShift Container Platform web console.

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. Navigate to Operators → OperatorHub.
  3. Enter Multiarch Tuning Operator in the search field.
  4. Click Multiarch Tuning Operator.
  5. Select the Multiarch Tuning Operator version from the Version list.
  6. Click Install
  7. Set the following options on the Operator Installation page:

    1. Set Update Channel to stable.
    2. Set Installation Mode to All namespaces on the cluster.
    3. Set Installed Namespace to Operator recommended Namespace or Select a Namespace.

      The recommended Operator namespace is openshift-multiarch-tuning-operator. If the openshift-multiarch-tuning-operator namespace does not exist, it is created during the operator installation.

      If you select Select a namespace, you must select a namespace for the Operator from the Select Project list.

    4. Update approval as Automatic or Manual.

      If you select Automatic updates, Operator Lifecycle Manager (OLM) automatically updates the running instance of the Multiarch Tuning Operator without any intervention.

      If you select Manual updates, OLM creates an update request. As a cluster administrator, you must manually approve the update request to update the Multiarch Tuning Operator to a newer version.

  8. Optional: Select the Enable Operator recommended cluster monitoring on this Namespace checkbox.
  9. Click Install.

Verification

  1. Navigate to OperatorsInstalled Operators.
  2. Verify that the Multiarch Tuning Operator is listed with the Status field as Succeeded in the openshift-multiarch-tuning-operator namespace.

3.11.3. Multiarch Tuning Operator pod labels and architecture support overview

After installing the Multiarch Tuning Operator, you can verify the multi-architecture support for workloads in your cluster. You can identify and manage pods based on their architecture compatibility by using the pod labels. These labels are automatically set on the newly created pods to provide insights into their architecture support.

The following table describes the labels that the Multiarch Tuning Operator adds when you create a pod:

Table 3.2. Pod labels that the Multiarch Tuning Operator adds when you create a pod
LabelDescription

multiarch.openshift.io/multi-arch: ""

The pod supports multiple architectures.

multiarch.openshift.io/single-arch: ""

The pod supports only a single architecture.

multiarch.openshift.io/arm64: ""

The pod supports the arm64 architecture.

multiarch.openshift.io/amd64: ""

The pod supports the amd64 architecture.

multiarch.openshift.io/ppc64le: ""

The pod supports the ppc64le architecture.

multiarch.openshift.io/s390x: ""

The pod supports the s390x architecture.

multirach.openshift.io/node-affinity: set

The Operator has set the node affinity requirement for the architecture.

multirach.openshift.io/node-affinity: not-set

The Operator did not set the node affinity requirement. For example, when the pod already has a node affinity for the architecture, the Multiarch Tuning Operator adds this label to the pod.

multiarch.openshift.io/scheduling-gate: gated

The pod is gated.

multiarch.openshift.io/scheduling-gate: removed

The pod gate has been removed.

multiarch.openshift.io/inspection-error: ""

An error has occurred while building the node affinity requirements.

3.11.4. Creating the ClusterPodPlacementConfig object

After installing the Multiarch Tuning Operator, you must create the ClusterPodPlacementConfig object. When you create this object, the Multiarch Tuning Operator deploys an operand that enables architecture-aware workload scheduling.

Note

You can create only one instance of the ClusterPodPlacementConfig object.

Example ClusterPodPlacementConfig object configuration

apiVersion: multiarch.openshift.io/v1beta1
kind: ClusterPodPlacementConfig
metadata:
  name: cluster 1
spec:
  logVerbosityLevel: Normal 2
  namespaceSelector: 3
    matchExpressions:
      - key: multiarch.openshift.io/exclude-pod-placement
        operator: DoesNotExist

1
You must set this field value to cluster.
2
Optional: You can set the field value to Normal, Debug, Trace, or TraceAll. The value is set to Normal by default.
3
Optional: You can configure the namespaceSelector to select the namespaces in which the Multiarch Tuning Operator’s pod placement operand must process the nodeAffinity of the pods. All namespaces are considered by default.

In this example, the operator field value is set to DoesNotExist. Therefore, if the key field value (multiarch.openshift.io/exclude-pod-placement) is set as a label in a namespace, the operand does not process the nodeAffinity of the pods in that namespace. Instead, the operand processes the nodeAffinity of the pods in namespaces that do not contain the label.

If you want the operand to process the nodeAffinity of the pods only in specific namespaces, you can configure the namespaceSelector as follows:

namespaceSelector:
  matchExpressions:
    - key: multiarch.openshift.io/include-pod-placement
      operator: Exists

In this example, the operator field value is set to Exists. Therefore, the operand processes the nodeAffinity of the pods only in namespaces that contain the multiarch.openshift.io/include-pod-placement label.

Important

This Operator excludes pods in namespaces starting with kube-. It also excludes pods that are expected to be scheduled on control plane nodes.

3.11.4.1. Creating the ClusterPodPlacementConfig object by using the CLI

To deploy the pod placement operand that enables architecture-aware workload scheduling, you can create the ClusterPodPlacementConfig object by using the OpenShift CLI (oc).

Prerequisites

  • You have installed oc.
  • You have logged in to oc as a user with cluster-admin privileges.
  • You have installed the Multiarch Tuning Operator.

Procedure

  1. Create a ClusterPodPlacementConfig object YAML file:

    Example ClusterPodPlacementConfig object configuration

    apiVersion: multiarch.openshift.io/v1beta1
    kind: ClusterPodPlacementConfig
    metadata:
      name: cluster
    spec:
      logVerbosityLevel: Normal
      namespaceSelector:
        matchExpressions:
          - key: multiarch.openshift.io/exclude-pod-placement
            operator: DoesNotExist

  2. Create the ClusterPodPlacementConfig object by running the following command:

    $ oc create -f <file_name> 1
    1
    Replace <file_name> with the name of the ClusterPodPlacementConfig object YAML file.

Verification

  • To check that the ClusterPodPlacementConfig object is created, run the following command:

    $ oc get clusterpodplacementconfig

    Example output

    NAME      AGE
    cluster   29s

3.11.4.2. Creating the ClusterPodPlacementConfig object by using the web console

To deploy the pod placement operand that enables architecture-aware workload scheduling, you can create the ClusterPodPlacementConfig object by using the OpenShift Container Platform web console.

Prerequisites

  • You have access to the cluster with cluster-admin privileges.
  • You have access to the OpenShift Container Platform web console.
  • You have installed the Multiarch Tuning Operator.

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. Navigate to OperatorsInstalled Operators.
  3. On the Installed Operators page, click Multiarch Tuning Operator.
  4. Click the Cluster Pod Placement Config tab.
  5. Select either Form view or YAML view.
  6. Configure the ClusterPodPlacementConfig object parameters.
  7. Click Create.
  8. Optional: If you want to edit the ClusterPodPlacementConfig object, perform the following actions:

    1. Click the Cluster Pod Placement Config tab.
    2. Select Edit ClusterPodPlacementConfig from the options menu.
    3. Click YAML and edit the ClusterPodPlacementConfig object parameters.
    4. Click Save.

Verification

  • On the Cluster Pod Placement Config page, check that the ClusterPodPlacementConfig object is in the Ready state.

3.11.5. Deleting the ClusterPodPlacementConfig object by using the CLI

You can create only one instance of the ClusterPodPlacementConfig object. If you want to re-create this object, you must first delete the existing instance.

You can delete this object by using the OpenShift CLI (oc).

Prerequisites

  • You have installed oc.
  • You have logged in to oc as a user with cluster-admin privileges.

Procedure

  1. Log in to the OpenShift CLI (oc).
  2. Delete the ClusterPodPlacementConfig object by running the following command:

    $ oc delete clusterpodplacementconfig cluster

Verification

  • To check that the ClusterPodPlacementConfig object is deleted, run the following command:

    $ oc get clusterpodplacementconfig

    Example output

    No resources found

3.11.6. Deleting the ClusterPodPlacementConfig object by using the web console

You can create only one instance of the ClusterPodPlacementConfig object. If you want to re-create this object, you must first delete the existing instance.

You can delete this object by using the OpenShift Container Platform web console.

Prerequisites

  • You have access to the cluster with cluster-admin privileges.
  • You have access to the OpenShift Container Platform web console.
  • You have created the ClusterPodPlacementConfig object.

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. Navigate to OperatorsInstalled Operators.
  3. On the Installed Operators page, click Multiarch Tuning Operator.
  4. Click the Cluster Pod Placement Config tab.
  5. Select Delete ClusterPodPlacementConfig from the options menu.
  6. Click Delete.

Verification

  • On the Cluster Pod Placement Config page, check that the ClusterPodPlacementConfig object has been deleted.

3.11.7. Uninstalling the Multiarch Tuning Operator by using the CLI

You can uninstall the Multiarch Tuning Operator by using the OpenShift CLI (oc).

Prerequisites

  • You have installed oc.
  • You have logged in to oc as a user with cluster-admin privileges.
  • You deleted the ClusterPodPlacementConfig object.

    Important

    You must delete the ClusterPodPlacementConfig object before uninstalling the Multiarch Tuning Operator. Uninstalling the Operator without deleting the ClusterPodPlacementConfig object can lead to unexpected behavior.

Procedure

  1. Get the Subscription object name for the Multiarch Tuning Operator by running the following command:

    $ oc get subscription.operators.coreos.com -n <namespace> 1
    1
    Replace <namespace> with the name of the namespace where you want to uninstall the Multiarch Tuning Operator.

    Example output

    NAME                                  PACKAGE                     SOURCE             CHANNEL
    openshift-multiarch-tuning-operator   multiarch-tuning-operator   redhat-operators   stable

  2. Get the currentCSV value for the Multiarch Tuning Operator by running the following command:

    $ oc get subscription.operators.coreos.com <subscription_name> -n <namespace> -o yaml | grep currentCSV 1
    1
    Replace <subscription_name> with the Subscription object name. For example: openshift-multiarch-tuning-operator. Replace <namespace> with the name of the namespace where you want to uninstall the Multiarch Tuning Operator.

    Example output

    currentCSV: multiarch-tuning-operator.v1.0.0

  3. Delete the Subscription object by running the following command:

    $ oc delete subscription.operators.coreos.com <subscription_name> -n <namespace> 1
    1
    Replace <subscription_name> with the Subscription object name. Replace <namespace> with the name of the namespace where you want to uninstall the Multiarch Tuning Operator.

    Example output

    subscription.operators.coreos.com "openshift-multiarch-tuning-operator" deleted

  4. Delete the CSV for the Multiarch Tuning Operator in the target namespace using the currentCSV value by running the following command:

    $ oc delete clusterserviceversion <currentCSV_value> -n <namespace> 1
    1
    Replace <currentCSV> with the currentCSV value for the Multiarch Tuning Operator. For example: multiarch-tuning-operator.v1.0.0. Replace <namespace> with the name of the namespace where you want to uninstall the Multiarch Tuning Operator.

    Example output

    clusterserviceversion.operators.coreos.com "multiarch-tuning-operator.v1.0.0" deleted

Verification

  • To verify that the Multiarch Tuning Operator is uninstalled, run the following command:

    $ oc get csv -n <namespace> 1
    1
    Replace <namespace> with the name of the namespace where you have uninstalled the Multiarch Tuning Operator.

    Example output

    No resources found in openshift-multiarch-tuning-operator namespace.

3.11.8. Uninstalling the Multiarch Tuning Operator by using the web console

You can uninstall the Multiarch Tuning Operator by using the OpenShift Container Platform web console.

Prerequisites

  • You have access to the cluster with cluster-admin permissions.
  • You deleted the ClusterPodPlacementConfig object.

    Important

    You must delete the ClusterPodPlacementConfig object before uninstalling the Multiarch Tuning Operator. Uninstalling the Operator without deleting the ClusterPodPlacementConfig object can lead to unexpected behavior.

Procedure

  1. Log in to the OpenShift Container Platform web console.
  2. Navigate to Operators → OperatorHub.
  3. Enter Multiarch Tuning Operator in the search field.
  4. Click Multiarch Tuning Operator.
  5. Click the Details tab.
  6. From the Actions menu, select Uninstall Operator.
  7. When prompted, click Uninstall.

Verification

  1. Navigate to OperatorsInstalled Operators.
  2. On the Installed Operators page, verify that the Multiarch Tuning Operator is not listed.

3.12. Multiarch Tuning Operator release notes

The Multiarch Tuning Operator optimizes workload management within multi-architecture clusters and in single-architecture clusters transitioning to multi-architecture environments.

These release notes track the development of the Multiarch Tuning Operator.

For more information, see Managing workloads on multi-architecture clusters by using the Multiarch Tuning Operator.

3.12.1. Release notes for the Multiarch Tuning Operator 1.0.0

Issued: 31 October 2024

3.12.1.1. New features and enhancements
  • With this release, the Multiarch Tuning Operator supports custom network scenarios and cluster-wide custom registries configurations.
  • With this release, you can identify pods based on their architecture compatibility by using the pod labels that the Multiarch Tuning Operator adds to newly created pods.
  • With this release, you can monitor the behavior of the Multiarch Tuning Operator by using the metrics and alerts that are registered in the Cluster Monitoring Operator.

Chapter 4. Postinstallation cluster tasks

After installing OpenShift Container Platform, you can further expand and customize your cluster to your requirements.

4.1. Available cluster customizations

You complete most of the cluster configuration and customization after you deploy your OpenShift Container Platform cluster. A number of configuration resources are available.

Note

If you install your cluster on IBM Z®, not all features and functions are available.

You modify the configuration resources to configure the major features of the cluster, such as the image registry, networking configuration, image build behavior, and the identity provider.

For current documentation of the settings that you control by using these resources, use the oc explain command, for example oc explain builds --api-version=config.openshift.io/v1

4.1.1. Cluster configuration resources

All cluster configuration resources are globally scoped (not namespaced) and named cluster.

Resource nameDescription

apiserver.config.openshift.io

Provides API server configuration such as certificates and certificate authorities.

authentication.config.openshift.io

Controls the identity provider and authentication configuration for the cluster.

build.config.openshift.io

Controls default and enforced configuration for all builds on the cluster.

console.config.openshift.io

Configures the behavior of the web console interface, including the logout behavior.

featuregate.config.openshift.io

Enables FeatureGates so that you can use Tech Preview features.

image.config.openshift.io

Configures how specific image registries should be treated (allowed, disallowed, insecure, CA details).

ingress.config.openshift.io

Configuration details related to routing such as the default domain for routes.

oauth.config.openshift.io

Configures identity providers and other behavior related to internal OAuth server flows.

project.config.openshift.io

Configures how projects are created including the project template.

proxy.config.openshift.io

Defines proxies to be used by components needing external network access. Note: not all components currently consume this value.

scheduler.config.openshift.io

Configures scheduler behavior such as profiles and default node selectors.

4.1.2. Operator configuration resources

These configuration resources are cluster-scoped instances, named cluster, which control the behavior of a specific component as owned by a particular Operator.

Resource nameDescription

consoles.operator.openshift.io

Controls console appearance such as branding customizations

config.imageregistry.operator.openshift.io

Configures OpenShift image registry settings such as public routing, log levels, proxy settings, resource constraints, replica counts, and storage type.

config.samples.operator.openshift.io

Configures the Samples Operator to control which example image streams and templates are installed on the cluster.

4.1.3. Additional configuration resources

These configuration resources represent a single instance of a particular component. In some cases, you can request multiple instances by creating multiple instances of the resource. In other cases, the Operator can use only a specific resource instance name in a specific namespace. Reference the component-specific documentation for details on how and when you can create additional resource instances.

Resource nameInstance nameNamespaceDescription

alertmanager.monitoring.coreos.com

main

openshift-monitoring

Controls the Alertmanager deployment parameters.

ingresscontroller.operator.openshift.io

default

openshift-ingress-operator

Configures Ingress Operator behavior such as domain, number of replicas, certificates, and controller placement.

4.1.4. Informational Resources

You use these resources to retrieve information about the cluster. Some configurations might require you to edit these resources directly.

Resource nameInstance nameDescription

clusterversion.config.openshift.io

version

In OpenShift Container Platform 4.17, you must not customize the ClusterVersion resource for production clusters. Instead, follow the process to update a cluster.

dns.config.openshift.io

cluster

You cannot modify the DNS settings for your cluster. You can check the DNS Operator status.

infrastructure.config.openshift.io

cluster

Configuration details allowing the cluster to interact with its cloud provider.

network.config.openshift.io

cluster

You cannot modify your cluster networking after installation. To customize your network, follow the process to customize networking during installation.

4.2. Adding worker nodes

After you deploy your OpenShift Container Platform cluster, you can add worker nodes to scale cluster resources. There are different ways you can add worker nodes depending on the installation method and the environment of your cluster.

4.2.1. Adding worker nodes to an on-premise cluster

For on-premise clusters, you can add worker nodes by using the OpenShift Container Platform CLI (oc) to generate an ISO image, which can then be used to boot one or more nodes in your target cluster. This process can be used regardless of how you installed your cluster.

You can add one or more nodes at a time while customizing each node with more complex configurations, such as static network configuration, or you can specify only the MAC address of each node. Any configurations that are not specified during ISO generation are retrieved from the target cluster and applied to the new nodes.

Preflight validation checks are also performed when booting the ISO image to inform you of failure-causing issues before you attempt to boot each node.

Adding worker nodes to an on-premise cluster

4.2.2. Adding worker nodes to installer-provisioned infrastructure clusters

For installer-provisioned infrastructure clusters, you can manually or automatically scale the MachineSet object to match the number of available bare-metal hosts.

To add a bare-metal host, you must configure all network prerequisites, configure an associated baremetalhost object, then provision the worker node to the cluster. You can add a bare-metal host manually or by using the web console.

4.2.3. Adding worker nodes to user-provisioned infrastructure clusters

For user-provisioned infrastructure clusters, you can add worker nodes by using a RHEL or RHCOS ISO image and connecting it to your cluster using cluster Ignition config files. For RHEL worker nodes, the following example uses Ansible playbooks to add worker nodes to the cluster. For RHCOS worker nodes, the following example uses an ISO image and network booting to add worker nodes to the cluster.

4.2.4. Adding worker nodes to clusters managed by the Assisted Installer

For clusters managed by the Assisted Installer, you can add worker nodes by using the Red Hat OpenShift Cluster Manager console, the Assisted Installer REST API or you can manually add worker nodes using an ISO image and cluster Ignition config files.

4.2.5. Adding worker nodes to clusters managed by the multicluster engine for Kubernetes

For clusters managed by the multicluster engine for Kubernetes, you can add worker nodes by using the dedicated multicluster engine console.

4.3. Adjust worker nodes

If you incorrectly sized the worker nodes during deployment, adjust them by creating one or more new compute machine sets, scale them up, then scale the original compute machine set down before removing them.

4.3.1. Understanding the difference between compute machine sets and the machine config pool

MachineSet objects describe OpenShift Container Platform nodes with respect to the cloud or machine provider.

The MachineConfigPool object allows MachineConfigController components to define and provide the status of machines in the context of upgrades.

The MachineConfigPool object allows users to configure how upgrades are rolled out to the OpenShift Container Platform nodes in the machine config pool.

The NodeSelector object can be replaced with a reference to the MachineSet object.

4.3.2. Scaling a compute machine set manually

To add or remove an instance of a machine in a compute machine set, you can manually scale the compute machine set.

This guidance is relevant to fully automated, installer-provisioned infrastructure installations. Customized, user-provisioned infrastructure installations do not have compute machine sets.

Prerequisites

  • Install an OpenShift Container Platform cluster and the oc command line.
  • Log in to oc as a user with cluster-admin permission.

Procedure

  1. View the compute machine sets that are in the cluster by running the following command:

    $ oc get machinesets.machine.openshift.io -n openshift-machine-api

    The compute machine sets are listed in the form of <clusterid>-worker-<aws-region-az>.

  2. View the compute machines that are in the cluster by running the following command:

    $ oc get machines.machine.openshift.io -n openshift-machine-api
  3. Set the annotation on the compute machine that you want to delete by running the following command:

    $ oc annotate machines.machine.openshift.io/<machine_name> -n openshift-machine-api machine.openshift.io/delete-machine="true"
  4. Scale the compute machine set by running one of the following commands:

    $ oc scale --replicas=2 machinesets.machine.openshift.io <machineset> -n openshift-machine-api

    Or:

    $ oc edit machinesets.machine.openshift.io <machineset> -n openshift-machine-api
    Tip

    You can alternatively apply the following YAML to scale the compute machine set:

    apiVersion: machine.openshift.io/v1beta1
    kind: MachineSet
    metadata:
      name: <machineset>
      namespace: openshift-machine-api
    spec:
      replicas: 2

    You can scale the compute machine set up or down. It takes several minutes for the new machines to be available.

    Important

    By default, the machine controller tries to drain the node that is backed by the machine until it succeeds. In some situations, such as with a misconfigured pod disruption budget, the drain operation might not be able to succeed. If the drain operation fails, the machine controller cannot proceed removing the machine.

    You can skip draining the node by annotating machine.openshift.io/exclude-node-draining in a specific machine.

Verification

  • Verify the deletion of the intended machine by running the following command:

    $ oc get machines.machine.openshift.io

4.3.3. The compute machine set deletion policy

Random, Newest, and Oldest are the three supported deletion options. The default is Random, meaning that random machines are chosen and deleted when scaling compute machine sets down. The deletion policy can be set according to the use case by modifying the particular compute machine set:

spec:
  deletePolicy: <delete_policy>
  replicas: <desired_replica_count>

Specific machines can also be prioritized for deletion by adding the annotation machine.openshift.io/delete-machine=true to the machine of interest, regardless of the deletion policy.

Important

By default, the OpenShift Container Platform router pods are deployed on workers. Because the router is required to access some cluster resources, including the web console, do not scale the worker compute machine set to 0 unless you first relocate the router pods.

Note

Custom compute machine sets can be used for use cases requiring that services run on specific nodes and that those services are ignored by the controller when the worker compute machine sets are scaling down. This prevents service disruption.

4.3.4. Creating default cluster-wide node selectors

You can use default cluster-wide node selectors on pods together with labels on nodes to constrain all pods created in a cluster to specific nodes.

With cluster-wide node selectors, when you create a pod in that cluster, OpenShift Container Platform adds the default node selectors to the pod and schedules the pod on nodes with matching labels.

You configure cluster-wide node selectors by editing the Scheduler Operator custom resource (CR). You add labels to a node, a compute machine set, or a machine config. Adding the label to the compute machine set ensures that if the node or machine goes down, new nodes have the label. Labels added to a node or machine config do not persist if the node or machine goes down.

Note

You can add additional key/value pairs to a pod. But you cannot add a different value for a default key.

Procedure

To add a default cluster-wide node selector:

  1. Edit the Scheduler Operator CR to add the default cluster-wide node selectors:

    $ oc edit scheduler cluster

    Example Scheduler Operator CR with a node selector

    apiVersion: config.openshift.io/v1
    kind: Scheduler
    metadata:
      name: cluster
    ...
    spec:
      defaultNodeSelector: type=user-node,region=east 1
      mastersSchedulable: false

    1
    Add a node selector with the appropriate <key>:<value> pairs.

    After making this change, wait for the pods in the openshift-kube-apiserver project to redeploy. This can take several minutes. The default cluster-wide node selector does not take effect until the pods redeploy.

  2. Add labels to a node by using a compute machine set or editing the node directly:

    • Use a compute machine set to add labels to nodes managed by the compute machine set when a node is created:

      1. Run the following command to add labels to a MachineSet object:

        $ oc patch MachineSet <name> --type='json' -p='[{"op":"add","path":"/spec/template/spec/metadata/labels", "value":{"<key>"="<value>","<key>"="<value>"}}]'  -n openshift-machine-api 1
        1
        Add a <key>/<value> pair for each label.

        For example:

        $ oc patch MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c --type='json' -p='[{"op":"add","path":"/spec/template/spec/metadata/labels", "value":{"type":"user-node","region":"east"}}]'  -n openshift-machine-api
        Tip

        You can alternatively apply the following YAML to add labels to a compute machine set:

        apiVersion: machine.openshift.io/v1beta1
        kind: MachineSet
        metadata:
          name: <machineset>
          namespace: openshift-machine-api
        spec:
          template:
            spec:
              metadata:
                labels:
                  region: "east"
                  type: "user-node"
      2. Verify that the labels are added to the MachineSet object by using the oc edit command:

        For example:

        $ oc edit MachineSet abc612-msrtw-worker-us-east-1c -n openshift-machine-api

        Example MachineSet object

        apiVersion: machine.openshift.io/v1beta1
        kind: MachineSet
          ...
        spec:
          ...
          template:
            metadata:
          ...
            spec:
              metadata:
                labels:
                  region: east
                  type: user-node
          ...

      3. Redeploy the nodes associated with that compute machine set by scaling down to 0 and scaling up the nodes:

        For example:

        $ oc scale --replicas=0 MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c -n openshift-machine-api
        $ oc scale --replicas=1 MachineSet ci-ln-l8nry52-f76d1-hl7m7-worker-c -n openshift-machine-api
      4. When the nodes are ready and available, verify that the label is added to the nodes by using the oc get command:

        $ oc get nodes -l <key>=<value>

        For example:

        $ oc get nodes -l type=user-node

        Example output

        NAME                                       STATUS   ROLES    AGE   VERSION
        ci-ln-l8nry52-f76d1-hl7m7-worker-c-vmqzp   Ready    worker   61s   v1.30.3

    • Add labels directly to a node:

      1. Edit the Node object for the node:

        $ oc label nodes <name> <key>=<value>

        For example, to label a node:

        $ oc label nodes ci-ln-l8nry52-f76d1-hl7m7-worker-b-tgq49 type=user-node region=east
        Tip

        You can alternatively apply the following YAML to add labels to a node:

        kind: Node
        apiVersion: v1
        metadata:
          name: <node_name>
          labels:
            type: "user-node"
            region: "east"
      2. Verify that the labels are added to the node using the oc get command:

        $ oc get nodes -l <key>=<value>,<key>=<value>

        For example:

        $ oc get nodes -l type=user-node,region=east

        Example output

        NAME                                       STATUS   ROLES    AGE   VERSION
        ci-ln-l8nry52-f76d1-hl7m7-worker-b-tgq49   Ready    worker   17m   v1.30.3

4.4. Improving cluster stability in high latency environments using worker latency profiles

If the cluster administrator has performed latency tests for platform verification, they can discover the need to adjust the operation of the cluster to ensure stability in cases of high latency. The cluster administrator needs to change only one parameter, recorded in a file, which controls four parameters affecting how supervisory processes read status and interpret the health of the cluster. Changing only the one parameter provides cluster tuning in an easy, supportable manner.

The Kubelet process provides the starting point for monitoring cluster health. The Kubelet sets status values for all nodes in the OpenShift Container Platform cluster. The Kubernetes Controller Manager (kube controller) reads the status values every 10 seconds, by default. If the kube controller cannot read a node status value, it loses contact with that node after a configured period. The default behavior is:

  1. The node controller on the control plane updates the node health to Unhealthy and marks the node Ready condition`Unknown`.
  2. In response, the scheduler stops scheduling pods to that node.
  3. The Node Lifecycle Controller adds a node.kubernetes.io/unreachable taint with a NoExecute effect to the node and schedules any pods on the node for eviction after five minutes, by default.

This behavior can cause problems if your network is prone to latency issues, especially if you have nodes at the network edge. In some cases, the Kubernetes Controller Manager might not receive an update from a healthy node due to network latency. The Kubelet evicts pods from the node even though the node is healthy.

To avoid this problem, you can use worker latency profiles to adjust the frequency that the Kubelet and the Kubernetes Controller Manager wait for status updates before taking action. These adjustments help to ensure that your cluster runs properly if network latency between the control plane and the worker nodes is not optimal.

These worker latency profiles contain three sets of parameters that are predefined with carefully tuned values to control the reaction of the cluster to increased latency. There is no need to experimentally find the best values manually.

You can configure worker latency profiles when installing a cluster or at any time you notice increased latency in your cluster network.

4.4.1. Understanding worker latency profiles

Worker latency profiles are four different categories of carefully-tuned parameters. The four parameters which implement these values are node-status-update-frequency, node-monitor-grace-period, default-not-ready-toleration-seconds and default-unreachable-toleration-seconds. These parameters can use values which allow you to control the reaction of the cluster to latency issues without needing to determine the best values by using manual methods.

Important

Setting these parameters manually is not supported. Incorrect parameter settings adversely affect cluster stability.

All worker latency profiles configure the following parameters:

node-status-update-frequency
Specifies how often the kubelet posts node status to the API server.
node-monitor-grace-period
Specifies the amount of time in seconds that the Kubernetes Controller Manager waits for an update from a kubelet before marking the node unhealthy and adding the node.kubernetes.io/not-ready or node.kubernetes.io/unreachable taint to the node.
default-not-ready-toleration-seconds
Specifies the amount of time in seconds after marking a node unhealthy that the Kube API Server Operator waits before evicting pods from that node.
default-unreachable-toleration-seconds
Specifies the amount of time in seconds after marking a node unreachable that the Kube API Server Operator waits before evicting pods from that node.

The following Operators monitor the changes to the worker latency profiles and respond accordingly:

  • The Machine Config Operator (MCO) updates the node-status-update-frequency parameter on the worker nodes.
  • The Kubernetes Controller Manager updates the node-monitor-grace-period parameter on the control plane nodes.
  • The Kubernetes API Server Operator updates the default-not-ready-toleration-seconds and default-unreachable-toleration-seconds parameters on the control plane nodes.

Although the default configuration works in most cases, OpenShift Container Platform offers two other worker latency profiles for situations where the network is experiencing higher latency than usual. The three worker latency profiles are described in the following sections:

Default worker latency profile

With the Default profile, each Kubelet updates its status every 10 seconds (node-status-update-frequency). The Kube Controller Manager checks the statuses of Kubelet every 5 seconds.

The Kubernetes Controller Manager waits 40 seconds (node-monitor-grace-period) for a status update from Kubelet before considering the Kubelet unhealthy. If no status is made available to the Kubernetes Controller Manager, it then marks the node with the node.kubernetes.io/not-ready or node.kubernetes.io/unreachable taint and evicts the pods on that node.

If a pod is on a node that has the NoExecute taint, the pod runs according to tolerationSeconds. If the node has no taint, it will be evicted in 300 seconds (default-not-ready-toleration-seconds and default-unreachable-toleration-seconds settings of the Kube API Server).

ProfileComponentParameterValue

Default

kubelet

node-status-update-frequency

10s

Kubelet Controller Manager

node-monitor-grace-period

40s

Kubernetes API Server Operator

default-not-ready-toleration-seconds

300s

Kubernetes API Server Operator

default-unreachable-toleration-seconds

300s

Medium worker latency profile

Use the MediumUpdateAverageReaction profile if the network latency is slightly higher than usual.

The MediumUpdateAverageReaction profile reduces the frequency of kubelet updates to 20 seconds and changes the period that the Kubernetes Controller Manager waits for those updates to 2 minutes. The pod eviction period for a pod on that node is reduced to 60 seconds. If the pod has the tolerationSeconds parameter, the eviction waits for the period specified by that parameter.

The Kubernetes Controller Manager waits for 2 minutes to consider a node unhealthy. In another minute, the eviction process starts.

ProfileComponentParameterValue

MediumUpdateAverageReaction

kubelet

node-status-update-frequency

20s

Kubelet Controller Manager

node-monitor-grace-period

2m

Kubernetes API Server Operator

default-not-ready-toleration-seconds

60s

Kubernetes API Server Operator

default-unreachable-toleration-seconds

60s

Low worker latency profile

Use the LowUpdateSlowReaction profile if the network latency is extremely high.

The LowUpdateSlowReaction profile reduces the frequency of kubelet updates to 1 minute and changes the period that the Kubernetes Controller Manager waits for those updates to 5 minutes. The pod eviction period for a pod on that node is reduced to 60 seconds. If the pod has the tolerationSeconds parameter, the eviction waits for the period specified by that parameter.

The Kubernetes Controller Manager waits for 5 minutes to consider a node unhealthy. In another minute, the eviction process starts.

ProfileComponentParameterValue

LowUpdateSlowReaction

kubelet

node-status-update-frequency

1m

Kubelet Controller Manager

node-monitor-grace-period

5m

Kubernetes API Server Operator

default-not-ready-toleration-seconds

60s

Kubernetes API Server Operator

default-unreachable-toleration-seconds

60s

4.4.2. Using and changing worker latency profiles

To change a worker latency profile to deal with network latency, edit the node.config object to add the name of the profile. You can change the profile at any time as latency increases or decreases.

You must move one worker latency profile at a time. For example, you cannot move directly from the Default profile to the LowUpdateSlowReaction worker latency profile. You must move from the Default worker latency profile to the MediumUpdateAverageReaction profile first, then to LowUpdateSlowReaction. Similarly, when returning to the Default profile, you must move from the low profile to the medium profile first, then to Default.

Note

You can also configure worker latency profiles upon installing an OpenShift Container Platform cluster.

Procedure

To move from the default worker latency profile:

  1. Move to the medium worker latency profile:

    1. Edit the node.config object:

      $ oc edit nodes.config/cluster
    2. Add spec.workerLatencyProfile: MediumUpdateAverageReaction:

      Example node.config object

      apiVersion: config.openshift.io/v1
      kind: Node
      metadata:
        annotations:
          include.release.openshift.io/ibm-cloud-managed: "true"
          include.release.openshift.io/self-managed-high-availability: "true"
          include.release.openshift.io/single-node-developer: "true"
          release.openshift.io/create-only: "true"
        creationTimestamp: "2022-07-08T16:02:51Z"
        generation: 1
        name: cluster
        ownerReferences:
        - apiVersion: config.openshift.io/v1
          kind: ClusterVersion
          name: version
          uid: 36282574-bf9f-409e-a6cd-3032939293eb
        resourceVersion: "1865"
        uid: 0c0f7a4c-4307-4187-b591-6155695ac85b
      spec:
        workerLatencyProfile: MediumUpdateAverageReaction 1
      
      # ...

      1
      Specifies the medium worker latency policy.

      Scheduling on each worker node is disabled as the change is being applied.

  2. Optional: Move to the low worker latency profile:

    1. Edit the node.config object:

      $ oc edit nodes.config/cluster
    2. Change the spec.workerLatencyProfile value to LowUpdateSlowReaction:

      Example node.config object

      apiVersion: config.openshift.io/v1
      kind: Node
      metadata:
        annotations:
          include.release.openshift.io/ibm-cloud-managed: "true"
          include.release.openshift.io/self-managed-high-availability: "true"
          include.release.openshift.io/single-node-developer: "true"
          release.openshift.io/create-only: "true"
        creationTimestamp: "2022-07-08T16:02:51Z"
        generation: 1
        name: cluster
        ownerReferences:
        - apiVersion: config.openshift.io/v1
          kind: ClusterVersion
          name: version
          uid: 36282574-bf9f-409e-a6cd-3032939293eb
        resourceVersion: "1865"
        uid: 0c0f7a4c-4307-4187-b591-6155695ac85b
      spec:
        workerLatencyProfile: LowUpdateSlowReaction 1
      
      # ...

      1
      Specifies use of the low worker latency policy.

Scheduling on each worker node is disabled as the change is being applied.

Verification

  • When all nodes return to the Ready condition, you can use the following command to look in the Kubernetes Controller Manager to ensure it was applied:

    $ oc get KubeControllerManager -o yaml | grep -i workerlatency -A 5 -B 5

    Example output

    # ...
        - lastTransitionTime: "2022-07-11T19:47:10Z"
          reason: ProfileUpdated
          status: "False"
          type: WorkerLatencyProfileProgressing
        - lastTransitionTime: "2022-07-11T19:47:10Z" 1
          message: all static pod revision(s) have updated latency profile
          reason: ProfileUpdated
          status: "True"
          type: WorkerLatencyProfileComplete
        - lastTransitionTime: "2022-07-11T19:20:11Z"
          reason: AsExpected
          status: "False"
          type: WorkerLatencyProfileDegraded
        - lastTransitionTime: "2022-07-11T19:20:36Z"
          status: "False"
    # ...

    1
    Specifies that the profile is applied and active.

To change the medium profile to default or change the default to medium, edit the node.config object and set the spec.workerLatencyProfile parameter to the appropriate value.

4.5. Managing control plane machines

Control plane machine sets provide management capabilities for control plane machines that are similar to what compute machine sets provide for compute machines. The availability and initial status of control plane machine sets on your cluster depend on your cloud provider and the version of OpenShift Container Platform that you installed. For more information, see Getting started with control plane machine sets.

4.6. Creating infrastructure machine sets for production environments

You can create a compute machine set to create machines that host only infrastructure components, such as the default router, the integrated container image registry, and components for cluster metrics and monitoring. These infrastructure machines are not counted toward the total number of subscriptions that are required to run the environment.

In a production deployment, it is recommended that you deploy at least three compute machine sets to hold infrastructure components. Both OpenShift Logging and Red Hat OpenShift Service Mesh deploy Elasticsearch, which requires three instances to be installed on different nodes. Each of these nodes can be deployed to different availability zones for high availability. A configuration like this requires three different compute machine sets, one for each availability zone. In global Azure regions that do not have multiple availability zones, you can use availability sets to ensure high availability.

For information on infrastructure nodes and which components can run on infrastructure nodes, see Creating infrastructure machine sets.

To create an infrastructure node, you can use a machine set, assign a label to the nodes, or use a machine config pool.

For sample machine sets that you can use with these procedures, see Creating machine sets for different clouds.

Applying a specific node selector to all infrastructure components causes OpenShift Container Platform to schedule those workloads on nodes with that label.

4.6.1. Creating a compute machine set

In addition to the compute machine sets created by the installation program, you can create your own to dynamically manage the machine compute resources for specific workloads of your choice.

Prerequisites

  • Deploy an OpenShift Container Platform cluster.
  • Install the OpenShift CLI (oc).
  • Log in to oc as a user with cluster-admin permission.

Procedure

  1. Create a new YAML file that contains the compute machine set custom resource (CR) sample and is named <file_name>.yaml.

    Ensure that you set the <clusterID> and <role> parameter values.

  2. Optional: If you are not sure which value to set for a specific field, you can check an existing compute machine set from your cluster.

    1. To list the compute machine sets in your cluster, run the following command:

      $ oc get machinesets -n openshift-machine-api

      Example output

      NAME                                DESIRED   CURRENT   READY   AVAILABLE   AGE
      agl030519-vplxk-worker-us-east-1a   1         1         1       1           55m
      agl030519-vplxk-worker-us-east-1b   1         1         1       1           55m
      agl030519-vplxk-worker-us-east-1c   1         1         1       1           55m
      agl030519-vplxk-worker-us-east-1d   0         0                             55m
      agl030519-vplxk-worker-us-east-1e   0         0                             55m
      agl030519-vplxk-worker-us-east-1f   0         0                             55m

    2. To view values of a specific compute machine set custom resource (CR), run the following command:

      $ oc get machineset <machineset_name> \
        -n openshift-machine-api -o yaml

      Example output

      apiVersion: machine.openshift.io/v1beta1
      kind: MachineSet
      metadata:
        labels:
          machine.openshift.io/cluster-api-cluster: <infrastructure_id> 1
        name: <infrastructure_id>-<role> 2
        namespace: openshift-machine-api
      spec:
        replicas: 1
        selector:
          matchLabels:
            machine.openshift.io/cluster-api-cluster: <infrastructure_id>
            machine.openshift.io/cluster-api-machineset: <infrastructure_id>-<role>
        template:
          metadata:
            labels:
              machine.openshift.io/cluster-api-cluster: <infrastructure_id>
              machine.openshift.io/cluster-api-machine-role: <role>
              machine.openshift.io/cluster-api-machine-type: <role>
              machine.openshift.io/cluster-api-machineset: <infrastructure_id>-<role>
          spec:
            providerSpec: 3
              ...

      1
      The cluster infrastructure ID.
      2
      A default node label.
      Note

      For clusters that have user-provisioned infrastructure, a compute machine set can only create worker and infra type machines.

      3
      The values in the <providerSpec> section of the compute machine set CR are platform-specific. For more information about <providerSpec> parameters in the CR, see the sample compute machine set CR configuration for your provider.
  3. Create a MachineSet CR by running the following command:

    $ oc create -f <file_name>.yaml

Verification

  • View the list of compute machine sets by running the following command:

    $ oc get machineset -n openshift-machine-api

    Example output

    NAME                                DESIRED   CURRENT   READY   AVAILABLE   AGE
    agl030519-vplxk-infra-us-east-1a    1         1         1       1           11m
    agl030519-vplxk-worker-us-east-1a   1         1         1       1           55m
    agl030519-vplxk-worker-us-east-1b   1         1         1       1           55m
    agl030519-vplxk-worker-us-east-1c   1         1         1       1           55m
    agl030519-vplxk-worker-us-east-1d   0         0                             55m
    agl030519-vplxk-worker-us-east-1e   0         0                             55m
    agl030519-vplxk-worker-us-east-1f   0         0                             55m

    When the new compute machine set is available, the DESIRED and CURRENT values match. If the compute machine set is not available, wait a few minutes and run the command again.

4.6.2. Creating an infrastructure node

Important

See Creating infrastructure machine sets for installer-provisioned infrastructure environments or for any cluster where the control plane nodes are managed by the machine API.

Requirements of the cluster dictate that infrastructure, also called infra nodes, be provisioned. The installer only provides provisions for control plane and worker nodes. Worker nodes can be designated as infrastructure nodes or application, also called app, nodes through labeling.

Procedure

  1. Add a label to the worker node that you want to act as application node:

    $ oc label node <node-name> node-role.kubernetes.io/app=""
  2. Add a label to the worker nodes that you want to act as infrastructure nodes:

    $ oc label node <node-name> node-role.kubernetes.io/infra=""
  3. Check to see if applicable nodes now have the infra role and app roles:

    $ oc get nodes
  4. Create a default cluster-wide node selector. The default node selector is applied to pods created in all namespaces. This creates an intersection with any existing node selectors on a pod, which additionally constrains the pod’s selector.

    Important

    If the default node selector key conflicts with the key of a pod’s label, then the default node selector is not applied.

    However, do not set a default node selector that might cause a pod to become unschedulable. For example, setting the default node selector to a specific node role, such as node-role.kubernetes.io/infra="", when a pod’s label is set to a different node role, such as node-role.kubernetes.io/master="", can cause the pod to become unschedulable. For this reason, use caution when setting the default node selector to specific node roles.

    You can alternatively use a project node selector to avoid cluster-wide node selector key conflicts.

    1. Edit the Scheduler object:

      $ oc edit scheduler cluster
    2. Add the defaultNodeSelector field with the appropriate node selector:

      apiVersion: config.openshift.io/v1
      kind: Scheduler
      metadata:
        name: cluster
      spec:
        defaultNodeSelector: node-role.kubernetes.io/infra="" 1
      # ...
      1
      This example node selector deploys pods on infrastructure nodes by default.
    3. Save the file to apply the changes.

You can now move infrastructure resources to the newly labeled infra nodes.

Additional resources

  • For information on how to configure project node selectors to avoid cluster-wide node selector key conflicts, see Project node selectors.

4.6.3. Creating a machine config pool for infrastructure machines

If you need infrastructure machines to have dedicated configurations, you must create an infra pool.

Important

Creating a custom machine configuration pool overrides default worker pool configurations if they refer to the same file or unit.

Procedure

  1. Add a label to the node you want to assign as the infra node with a specific label:

    $ oc label node <node_name> <label>
    $ oc label node ci-ln-n8mqwr2-f76d1-xscn2-worker-c-6fmtx node-role.kubernetes.io/infra=
  2. Create a machine config pool that contains both the worker role and your custom role as machine config selector:

    $ cat infra.mcp.yaml

    Example output

    apiVersion: machineconfiguration.openshift.io/v1
    kind: MachineConfigPool
    metadata:
      name: infra
    spec:
      machineConfigSelector:
        matchExpressions:
          - {key: machineconfiguration.openshift.io/role, operator: In, values: [worker,infra]} 1
      nodeSelector:
        matchLabels:
          node-role.kubernetes.io/infra: "" 2

    1
    Add the worker role and your custom role.
    2
    Add the label you added to the node as a nodeSelector.
    Note

    Custom machine config pools inherit machine configs from the worker pool. Custom pools use any machine config targeted for the worker pool, but add the ability to also deploy changes that are targeted at only the custom pool. Because a custom pool inherits resources from the worker pool, any change to the worker pool also affects the custom pool.

  3. After you have the YAML file, you can create the machine config pool:

    $ oc create -f infra.mcp.yaml
  4. Check the machine configs to ensure that the infrastructure configuration rendered successfully:

    $ oc get machineconfig

    Example output

    NAME                                                        GENERATEDBYCONTROLLER                      IGNITIONVERSION   CREATED
    00-master                                                   365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
    00-worker                                                   365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
    01-master-container-runtime                                 365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
    01-master-kubelet                                           365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
    01-worker-container-runtime                                 365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
    01-worker-kubelet                                           365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
    99-master-1ae2a1e0-a115-11e9-8f14-005056899d54-registries   365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
    99-master-ssh                                                                                          3.2.0             31d
    99-worker-1ae64748-a115-11e9-8f14-005056899d54-registries   365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             31d
    99-worker-ssh                                                                                          3.2.0             31d
    rendered-infra-4e48906dca84ee702959c71a53ee80e7             365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             23m
    rendered-master-072d4b2da7f88162636902b074e9e28e            5b6fb8349a29735e48446d435962dec4547d3090   3.2.0             31d
    rendered-master-3e88ec72aed3886dec061df60d16d1af            02c07496ba0417b3e12b78fb32baf6293d314f79   3.2.0             31d
    rendered-master-419bee7de96134963a15fdf9dd473b25            365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             17d
    rendered-master-53f5c91c7661708adce18739cc0f40fb            365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             13d
    rendered-master-a6a357ec18e5bce7f5ac426fc7c5ffcd            365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             7d3h
    rendered-master-dc7f874ec77fc4b969674204332da037            5b6fb8349a29735e48446d435962dec4547d3090   3.2.0             31d
    rendered-worker-1a75960c52ad18ff5dfa6674eb7e533d            5b6fb8349a29735e48446d435962dec4547d3090   3.2.0             31d
    rendered-worker-2640531be11ba43c61d72e82dc634ce6            5b6fb8349a29735e48446d435962dec4547d3090   3.2.0             31d
    rendered-worker-4e48906dca84ee702959c71a53ee80e7            365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             7d3h
    rendered-worker-4f110718fe88e5f349987854a1147755            365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             17d
    rendered-worker-afc758e194d6188677eb837842d3b379            02c07496ba0417b3e12b78fb32baf6293d314f79   3.2.0             31d
    rendered-worker-daa08cc1e8f5fcdeba24de60cd955cc3            365c1cfd14de5b0e3b85e0fc815b0060f36ab955   3.2.0             13d

    You should see a new machine config, with the rendered-infra-* prefix.

  5. Optional: To deploy changes to a custom pool, create a machine config that uses the custom pool name as the label, such as infra. Note that this is not required and only shown for instructional purposes. In this manner, you can apply any custom configurations specific to only your infra nodes.

    Note

    After you create the new machine config pool, the MCO generates a new rendered config for that pool, and associated nodes of that pool reboot to apply the new configuration.

    1. Create a machine config:

      $ cat infra.mc.yaml

      Example output

      apiVersion: machineconfiguration.openshift.io/v1
      kind: MachineConfig
      metadata:
        name: 51-infra
        labels:
          machineconfiguration.openshift.io/role: infra 1
      spec:
        config:
          ignition:
            version: 3.2.0
          storage:
            files:
            - path: /etc/infratest
              mode: 0644
              contents:
                source: data:,infra

      1
      Add the label you added to the node as a nodeSelector.
    2. Apply the machine config to the infra-labeled nodes:

      $ oc create -f infra.mc.yaml
  6. Confirm that your new machine config pool is available:

    $ oc get mcp

    Example output

    NAME     CONFIG                                             UPDATED   UPDATING   DEGRADED   MACHINECOUNT   READYMACHINECOUNT   UPDATEDMACHINECOUNT   DEGRADEDMACHINECOUNT   AGE
    infra    rendered-infra-60e35c2e99f42d976e084fa94da4d0fc    True      False      False      1              1                   1                     0                      4m20s
    master   rendered-master-9360fdb895d4c131c7c4bebbae099c90   True      False      False      3              3                   3                     0                      91m
    worker   rendered-worker-60e35c2e99f42d976e084fa94da4d0fc   True      False      False      2              2                   2                     0                      91m

    In this example, a worker node was changed to an infra node.

Additional resources

4.7. Assigning machine set resources to infrastructure nodes

After creating an infrastructure machine set, the worker and infra roles are applied to new infra nodes. Nodes with the infra role are not counted toward the total number of subscriptions that are required to run the environment, even when the worker role is also applied.

However, when an infra node is assigned the worker role, there is a chance that user workloads can get assigned inadvertently to the infra node. To avoid this, you can apply a taint to the infra node and tolerations for the pods that you want to control.

4.7.1. Binding infrastructure node workloads using taints and tolerations

If you have an infra node that has the infra and worker roles assigned, you must configure the node so that user workloads are not assigned to it.

Important

It is recommended that you preserve the dual infra,worker label that is created for infra nodes and use taints and tolerations to manage nodes that user workloads are scheduled on. If you remove the worker label from the node, you must create a custom pool to manage it. A node with a label other than master or worker is not recognized by the MCO without a custom pool. Maintaining the worker label allows the node to be managed by the default worker machine config pool, if no custom pools that select the custom label exists. The infra label communicates to the cluster that it does not count toward the total number of subscriptions.

Prerequisites

  • Configure additional MachineSet objects in your OpenShift Container Platform cluster.

Procedure

  1. Add a taint to the infra node to prevent scheduling user workloads on it:

    1. Determine if the node has the taint:

      $ oc describe nodes <node_name>

      Sample output

      oc describe node ci-ln-iyhx092-f76d1-nvdfm-worker-b-wln2l
      Name:               ci-ln-iyhx092-f76d1-nvdfm-worker-b-wln2l
      Roles:              worker
       ...
      Taints:             node-role.kubernetes.io/infra:NoSchedule
       ...

      This example shows that the node has a taint. You can proceed with adding a toleration to your pod in the next step.

    2. If you have not configured a taint to prevent scheduling user workloads on it:

      $ oc adm taint nodes <node_name> <key>=<value>:<effect>

      For example:

      $ oc adm taint nodes node1 node-role.kubernetes.io/infra=reserved:NoSchedule
      Tip

      You can alternatively apply the following YAML to add the taint:

      kind: Node
      apiVersion: v1
      metadata:
        name: <node_name>
        labels:
          ...
      spec:
        taints:
          - key: node-role.kubernetes.io/infra
            effect: NoSchedule
            value: reserved
        ...

      This example places a taint on node1 that has key node-role.kubernetes.io/infra and taint effect NoSchedule. Nodes with the NoSchedule effect schedule only pods that tolerate the taint, but allow existing pods to remain scheduled on the node.

      Note

      If a descheduler is used, pods violating node taints could be evicted from the cluster.

    3. Add the taint with NoExecute Effect along with the above taint with NoSchedule Effect:

      $ oc adm taint nodes <node_name> <key>=<value>:<effect>

      For example:

      $ oc adm taint nodes node1 node-role.kubernetes.io/infra=reserved:NoExecute
      Tip

      You can alternatively apply the following YAML to add the taint:

      kind: Node
      apiVersion: v1
      metadata:
        name: <node_name>
        labels:
          ...
      spec:
        taints:
          - key: node-role.kubernetes.io/infra
            effect: NoExecute
            value: reserved
        ...

      This example places a taint on node1 that has the key node-role.kubernetes.io/infra and taint effect NoExecute. Nodes with the NoExecute effect schedule only pods that tolerate the taint. The effect will remove any existing pods from the node that do not have a matching toleration.

  2. Add tolerations for the pod configurations you want to schedule on the infra node, like router, registry, and monitoring workloads. Add the following code to the Pod object specification:

    tolerations:
      - effect: NoSchedule 1
        key: node-role.kubernetes.io/infra 2
        value: reserved 3
      - effect: NoExecute 4
        key: node-role.kubernetes.io/infra 5
        operator: Exists 6
        value: reserved 7
    1
    Specify the effect that you added to the node.
    2
    Specify the key that you added to the node.
    3
    Specify the value of the key-value pair taint that you added to the node.
    4
    Specify the effect that you added to the node.
    5
    Specify the key that you added to the node.
    6
    Specify the Exists Operator to require a taint with the key node-role.kubernetes.io/infra to be present on the node.
    7
    Specify the value of the key-value pair taint that you added to the node.

    This toleration matches the taint created by the oc adm taint command. A pod with this toleration can be scheduled onto the infra node.

    Note

    Moving pods for an Operator installed via OLM to an infra node is not always possible. The capability to move Operator pods depends on the configuration of each Operator.

  3. Schedule the pod to the infra node using a scheduler. See the documentation for Controlling pod placement onto nodes for details.

Additional resources

4.8. Moving resources to infrastructure machine sets

Some of the infrastructure resources are deployed in your cluster by default. You can move them to the infrastructure machine sets that you created.

4.8.1. Moving the router

You can deploy the router pod to a different compute machine set. By default, the pod is deployed to a worker node.

Prerequisites

  • Configure additional compute machine sets in your OpenShift Container Platform cluster.

Procedure

  1. View the IngressController custom resource for the router Operator:

    $ oc get ingresscontroller default -n openshift-ingress-operator -o yaml

    The command output resembles the following text:

    apiVersion: operator.openshift.io/v1
    kind: IngressController
    metadata:
      creationTimestamp: 2019-04-18T12:35:39Z
      finalizers:
      - ingresscontroller.operator.openshift.io/finalizer-ingresscontroller
      generation: 1
      name: default
      namespace: openshift-ingress-operator
      resourceVersion: "11341"
      selfLink: /apis/operator.openshift.io/v1/namespaces/openshift-ingress-operator/ingresscontrollers/default
      uid: 79509e05-61d6-11e9-bc55-02ce4781844a
    spec: {}
    status:
      availableReplicas: 2
      conditions:
      - lastTransitionTime: 2019-04-18T12:36:15Z
        status: "True"
        type: Available
      domain: apps.<cluster>.example.com
      endpointPublishingStrategy:
        type: LoadBalancerService
      selector: ingresscontroller.operator.openshift.io/deployment-ingresscontroller=default
  2. Edit the ingresscontroller resource and change the nodeSelector to use the infra label:

    $ oc edit ingresscontroller default -n openshift-ingress-operator
      spec:
        nodePlacement:
          nodeSelector: 1
            matchLabels:
              node-role.kubernetes.io/infra: ""
          tolerations:
          - effect: NoSchedule
            key: node-role.kubernetes.io/infra
            value: reserved
          - effect: NoExecute
            key: node-role.kubernetes.io/infra
            value: reserved
    1
    Add a nodeSelector parameter with the appropriate value to the component you want to move. You can use a nodeSelector in the format shown or use <key>: <value> pairs, based on the value specified for the node. If you added a taint to the infrastructure node, also add a matching toleration.
  3. Confirm that the router pod is running on the infra node.

    1. View the list of router pods and note the node name of the running pod:

      $ oc get pod -n openshift-ingress -o wide

      Example output

      NAME                              READY     STATUS        RESTARTS   AGE       IP           NODE                           NOMINATED NODE   READINESS GATES
      router-default-86798b4b5d-bdlvd   1/1      Running       0          28s       10.130.2.4   ip-10-0-217-226.ec2.internal   <none>           <none>
      router-default-955d875f4-255g8    0/1      Terminating   0          19h       10.129.2.4   ip-10-0-148-172.ec2.internal   <none>           <none>

      In this example, the running pod is on the ip-10-0-217-226.ec2.internal node.

    2. View the node status of the running pod:

      $ oc get node <node_name> 1
      1
      Specify the <node_name> that you obtained from the pod list.

      Example output

      NAME                          STATUS  ROLES         AGE   VERSION
      ip-10-0-217-226.ec2.internal  Ready   infra,worker  17h   v1.30.3

      Because the role list includes infra, the pod is running on the correct node.

4.8.2. Moving the default registry

You configure the registry Operator to deploy its pods to different nodes.

Prerequisites

  • Configure additional compute machine sets in your OpenShift Container Platform cluster.

Procedure

  1. View the config/instance object:

    $ oc get configs.imageregistry.operator.openshift.io/cluster -o yaml

    Example output

    apiVersion: imageregistry.operator.openshift.io/v1
    kind: Config
    metadata:
      creationTimestamp: 2019-02-05T13:52:05Z
      finalizers:
      - imageregistry.operator.openshift.io/finalizer
      generation: 1
      name: cluster
      resourceVersion: "56174"
      selfLink: /apis/imageregistry.operator.openshift.io/v1/configs/cluster
      uid: 36fd3724-294d-11e9-a524-12ffeee2931b
    spec:
      httpSecret: d9a012ccd117b1e6616ceccb2c3bb66a5fed1b5e481623
      logging: 2
      managementState: Managed
      proxy: {}
      replicas: 1
      requests:
        read: {}
        write: {}
      storage:
        s3:
          bucket: image-registry-us-east-1-c92e88cad85b48ec8b312344dff03c82-392c
          region: us-east-1
    status:
    ...

  2. Edit the config/instance object:

    $ oc edit configs.imageregistry.operator.openshift.io/cluster
    spec:
      affinity:
        podAntiAffinity:
          preferredDuringSchedulingIgnoredDuringExecution:
          - podAffinityTerm:
              namespaces:
              - openshift-image-registry
              topologyKey: kubernetes.io/hostname
            weight: 100
      logLevel: Normal
      managementState: Managed
      nodeSelector: 1
        node-role.kubernetes.io/infra: ""
      tolerations:
      - effect: NoSchedule
        key: node-role.kubernetes.io/infra
        value: reserved
      - effect: NoExecute
        key: node-role.kubernetes.io/infra
        value: reserved
    1
    Add a nodeSelector parameter with the appropriate value to the component you want to move. You can use a nodeSelector in the format shown or use <key>: <value> pairs, based on the value specified for the node. If you added a taint to the infrasructure node, also add a matching toleration.
  3. Verify the registry pod has been moved to the infrastructure node.

    1. Run the following command to identify the node where the registry pod is located:

      $ oc get pods -o wide -n openshift-image-registry
    2. Confirm the node has the label you specified:

      $ oc describe node <node_name>

      Review the command output and confirm that node-role.kubernetes.io/infra is in the LABELS list.

4.8.3. Moving the monitoring solution

The monitoring stack includes multiple components, including Prometheus, Thanos Querier, and Alertmanager. The Cluster Monitoring Operator manages this stack. To redeploy the monitoring stack to infrastructure nodes, you can create and apply a custom config map.

Procedure

  1. Edit the cluster-monitoring-config config map and change the nodeSelector to use the infra label:

    $ oc edit configmap cluster-monitoring-config -n openshift-monitoring
    apiVersion: v1
    kind: ConfigMap
    metadata:
      name: cluster-monitoring-config
      namespace: openshift-monitoring
    data:
      config.yaml: |+
        alertmanagerMain:
          nodeSelector: 1
            node-role.kubernetes.io/infra: ""
          tolerations:
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoSchedule
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoExecute
        prometheusK8s:
          nodeSelector:
            node-role.kubernetes.io/infra: ""
          tolerations:
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoSchedule
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoExecute
        prometheusOperator:
          nodeSelector:
            node-role.kubernetes.io/infra: ""
          tolerations:
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoSchedule
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoExecute
        metricsServer:
          nodeSelector:
            node-role.kubernetes.io/infra: ""
          tolerations:
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoSchedule
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoExecute
        kubeStateMetrics:
          nodeSelector:
            node-role.kubernetes.io/infra: ""
          tolerations:
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoSchedule
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoExecute
        telemeterClient:
          nodeSelector:
            node-role.kubernetes.io/infra: ""
          tolerations:
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoSchedule
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoExecute
        openshiftStateMetrics:
          nodeSelector:
            node-role.kubernetes.io/infra: ""
          tolerations:
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoSchedule
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoExecute
        thanosQuerier:
          nodeSelector:
            node-role.kubernetes.io/infra: ""
          tolerations:
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoSchedule
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoExecute
        monitoringPlugin:
          nodeSelector:
            node-role.kubernetes.io/infra: ""
          tolerations:
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoSchedule
          - key: node-role.kubernetes.io/infra
            value: reserved
            effect: NoExecute
    1
    Add a nodeSelector parameter with the appropriate value to the component you want to move. You can use a nodeSelector in the format shown or use <key>: <value> pairs, based on the value specified for the node. If you added a taint to the infrastructure node, also add a matching toleration.
  2. Watch the monitoring pods move to the new machines:

    $ watch 'oc get pod -n openshift-monitoring -o wide'
  3. If a component has not moved to the infra node, delete the pod with this component:

    $ oc delete pod -n openshift-monitoring <pod>

    The component from the deleted pod is re-created on the infra node.

4.9. Applying autoscaling to your cluster

Applying autoscaling to an OpenShift Container Platform cluster involves deploying a cluster autoscaler and then deploying machine autoscalers for each machine type in your cluster.

For more information, see Applying autoscaling to an OpenShift Container Platform cluster.

4.10. Configuring Linux cgroup

As of OpenShift Container Platform 4.14, OpenShift Container Platform uses Linux control group version 2 (cgroup v2) in your cluster. If you are using cgroup v1 on OpenShift Container Platform 4.13 or earlier, migrating to OpenShift Container Platform 4.14 or later will not automatically update your cgroup configuration to version 2. A fresh installation of OpenShift Container Platform 4.14 or later will use cgroup v2 by default. However, you can enable Linux control group version 1 (cgroup v1) upon installation.

cgroup v2 is the current version of the Linux cgroup API. cgroup v2 offers several improvements over cgroup v1, including a unified hierarchy, safer sub-tree delegation, new features such as Pressure Stall Information, and enhanced resource management and isolation. However, cgroup v2 has different CPU, memory, and I/O management characteristics than cgroup v1. Therefore, some workloads might experience slight differences in memory or CPU usage on clusters that run cgroup v2.

You can change between cgroup v1 and cgroup v2, as needed. Enabling cgroup v1 in OpenShift Container Platform disables all cgroup v2 controllers and hierarchies in your cluster.

Important

cgroup v1 is a deprecated feature. Deprecated functionality is still included in OpenShift Container Platform and continues to be supported; however, it will be removed in a future release of this product and is not recommended for new deployments.

For the most recent list of major functionality that has been deprecated or removed within OpenShift Container Platform, refer to the Deprecated and removed features section of the OpenShift Container Platform release notes.

Prerequisites

  • You have a running OpenShift Container Platform cluster that uses version 4.12 or later.
  • You are logged in to the cluster as a user with administrative privileges.

Procedure

  1. Enable cgroup v1 on nodes:

    1. Edit the node.config object:

      $ oc edit nodes.config/cluster
    2. Add spec.cgroupMode: "v1":

      Example node.config object

      apiVersion: config.openshift.io/v2
      kind: Node
      metadata:
        annotations:
          include.release.openshift.io/ibm-cloud-managed: "true"
          include.release.openshift.io/self-managed-high-availability: "true"
          include.release.openshift.io/single-node-developer: "true"
          release.openshift.io/create-only: "true"
        creationTimestamp: "2022-07-08T16:02:51Z"
        generation: 1
        name: cluster
        ownerReferences:
        - apiVersion: config.openshift.io/v2
          kind: ClusterVersion
          name: version
          uid: 36282574-bf9f-409e-a6cd-3032939293eb
        resourceVersion: "1865"
        uid: 0c0f7a4c-4307-4187-b591-6155695ac85b
      spec:
        cgroupMode: "v1" 1
      ...

      1
      Enables cgroup v1.

Verification

  1. Check the machine configs to see that the new machine configs were added:

    $ oc get mc

    Example output

    NAME                                               GENERATEDBYCONTROLLER                      IGNITIONVERSION   AGE
    00-master                                          52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
    00-worker                                          52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
    01-master-container-runtime                        52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
    01-master-kubelet                                  52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
    01-worker-container-runtime                        52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
    01-worker-kubelet                                  52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
    97-master-generated-kubelet                        52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
    99-worker-generated-kubelet                        52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
    99-master-generated-registries                     52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
    99-master-ssh                                                                                 3.2.0             40m
    99-worker-generated-registries                     52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
    99-worker-ssh                                                                                 3.2.0             40m
    rendered-master-23d4317815a5f854bd3553d689cfe2e9   52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             10s 1
    rendered-master-23e785de7587df95a4b517e0647e5ab7   52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
    rendered-worker-5d596d9293ca3ea80c896a1191735bb1   52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             33m
    rendered-worker-dcc7f1b92892d34db74d6832bcc9ccd4   52dd3ba6a9a527fc3ab42afac8d12b693534c8c9   3.2.0             10s

    1
    New machine configs are created, as expected.
  2. Check that the new kernelArguments were added to the new machine configs:

    $ oc describe mc <name>

    Example output for cgroup v1

    apiVersion: machineconfiguration.openshift.io/v2
    kind: MachineConfig
    metadata:
      labels:
        machineconfiguration.openshift.io/role: worker
      name: 05-worker-kernelarg-selinuxpermissive
    spec:
      kernelArguments:
        systemd.unified_cgroup_hierarchy=0 1
        systemd.legacy_systemd_cgroup_controller=1 2

    1
    Disables cgroup v2.
    2
    Enables cgroup v1 in systemd.
  3. Check the nodes to see that scheduling on the nodes is disabled. This indicates that the change is being applied:

    $ oc get nodes

    Example output

    NAME                                       STATUS                     ROLES    AGE   VERSION
    ci-ln-fm1qnwt-72292-99kt6-master-0         Ready,SchedulingDisabled   master   58m   v1.30.3
    ci-ln-fm1qnwt-72292-99kt6-master-1         Ready                      master   58m   v1.30.3
    ci-ln-fm1qnwt-72292-99kt6-master-2         Ready                      master   58m   v1.30.3
    ci-ln-fm1qnwt-72292-99kt6-worker-a-h5gt4   Ready,SchedulingDisabled   worker   48m   v1.30.3
    ci-ln-fm1qnwt-72292-99kt6-worker-b-7vtmd   Ready                      worker   48m   v1.30.3
    ci-ln-fm1qnwt-72292-99kt6-worker-c-rhzkv   Ready                      worker   48m   v1.30.3

  4. After a node returns to the Ready state, start a debug session for that node:

    $ oc debug node/<node_name>
  5. Set /host as the root directory within the debug shell:

    sh-4.4# chroot /host
  6. Check that the sys/fs/cgroup/cgroup2fs file is present on your nodes. This file is created by cgroup v1:

    $ stat -c %T -f /sys/fs/cgroup

    Example output

    cgroup2fs

4.11. Enabling Technology Preview features using FeatureGates

You can turn on a subset of the current Technology Preview features on for all nodes in the cluster by editing the FeatureGate custom resource (CR).

4.11.1. Understanding feature gates

You can use the FeatureGate custom resource (CR) to enable specific feature sets in your cluster. A feature set is a collection of OpenShift Container Platform features that are not enabled by default.

You can activate the following feature set by using the FeatureGate CR:

  • TechPreviewNoUpgrade. This feature set is a subset of the current Technology Preview features. This feature set allows you to enable these Technology Preview features on test clusters, where you can fully test them, while leaving the features disabled on production clusters.

    Warning

    Enabling the TechPreviewNoUpgrade feature set on your cluster cannot be undone and prevents minor version updates. You should not enable this feature set on production clusters.

    The following Technology Preview features are enabled by this feature set:

    • External cloud providers. Enables support for external cloud providers for clusters on vSphere, AWS, Azure, and GCP. Support for OpenStack is GA. This is an internal feature that most users do not need to interact with. (ExternalCloudProvider)
    • Swap memory on nodes. Enables swap memory use for OpenShift Container Platform workloads on a per-node basis. (NodeSwap)
    • OpenStack Machine API Provider. This gate has no effect and is planned to be removed from this feature set in a future release. (MachineAPIProviderOpenStack)
    • Insights Operator. Enables the InsightsDataGather CRD, which allows users to configure some Insights data gathering options. The feature set also enables the DataGather CRD, which allows users to run Insights data gathering on-demand. (InsightsConfigAPI)
    • Dynamic Resource Allocation API. Enables a new API for requesting and sharing resources between pods and containers. This is an internal feature that most users do not need to interact with. (DynamicResourceAllocation)
    • Pod security admission enforcement. Enables the restricted enforcement mode for pod security admission. Instead of only logging a warning, pods are rejected if they violate pod security standards. (OpenShiftPodSecurityAdmission)
    • StatefulSet pod availability upgrading limits. Enables users to define the maximum number of statefulset pods unavailable during updates which reduces application downtime. (MaxUnavailableStatefulSet)
    • gcpLabelsTags
    • vSphereStaticIPs
    • routeExternalCertificate
    • automatedEtcdBackup
    • gcpClusterHostedDNS
    • vSphereControlPlaneMachineset
    • dnsNameResolver
    • machineConfigNodes
    • metricsServer
    • installAlternateInfrastructureAWS
    • mixedCPUsAllocation
    • managedBootImages
    • onClusterBuild
    • signatureStores
    • SigstoreImageVerification
    • DisableKubeletCloudCredentialProviders
    • BareMetalLoadBalancer
    • ClusterAPIInstallAWS
    • ClusterAPIInstallAzure
    • ClusterAPIInstallNutanix
    • ClusterAPIInstallOpenStack
    • ClusterAPIInstallVSphere
    • HardwareSpeed
    • KMSv1
    • NetworkDiagnosticsConfig
    • VSphereDriverConfiguration
    • ExternalOIDC
    • ChunkSizeMiB
    • ClusterAPIInstallGCP
    • ClusterAPIInstallPowerVS
    • EtcdBackendQuota
    • InsightsConfig
    • InsightsOnDemandDataGather
    • MetricsCollectionProfiles
    • NewOLM
    • NodeDisruptionPolicy
    • PinnedImages
    • PlatformOperators
    • ServiceAccountTokenNodeBinding
    • TranslateStreamCloseWebsocketRequests
    • UpgradeStatus
    • VSphereMultiVCenters
    • VolumeGroupSnapshot
    • AdditionalRoutingCapabilities
    • BootcNodeManagement
    • ClusterMonitoringConfig
    • DNSNameResolver
    • ManagedBootImagesAWS
    • NetworkSegmentation
    • OVNObservability
    • PersistentIPsForVirtualization
    • ProcMountType
    • RouteAdvertisements
    • UserNamespacesSupport
    • AWSEFSDriverVolumeMetrics
    • AlibabaPlatform
    • AzureWorkloadIdentity
    • BuildCSIVolumes
    • CloudDualStackNodeIPs
    • ExternalCloudProviderAzure
    • ExternalCloudProviderExternal
    • ExternalCloudProviderGCP
    • IngressControllerLBSubnetsAWS
    • MultiArchInstallAWS
    • MultiArchInstallGCP
    • NetworkLiveMigration
    • PrivateHostedZoneAWS
    • SetEIPForNLBIngressController
    • ValidatingAdmissionPolicy

4.11.2. Enabling feature sets using the web console

You can use the OpenShift Container Platform web console to enable feature sets for all of the nodes in a cluster by editing the FeatureGate custom resource (CR).

Procedure

To enable feature sets:

  1. In the OpenShift Container Platform web console, switch to the AdministrationCustom Resource Definitions page.
  2. On the Custom Resource Definitions page, click FeatureGate.
  3. On the Custom Resource Definition Details page, click the Instances tab.
  4. Click the cluster feature gate, then click the YAML tab.
  5. Edit the cluster instance to add specific feature sets:

    Warning

    Enabling the TechPreviewNoUpgrade feature set on your cluster cannot be undone and prevents minor version updates. You should not enable this feature set on production clusters.

    Sample Feature Gate custom resource

    apiVersion: config.openshift.io/v1
    kind: FeatureGate
    metadata:
      name: cluster 1
    # ...
    spec:
      featureSet: TechPreviewNoUpgrade 2

    1
    The name of the FeatureGate CR must be cluster.
    2
    Add the feature set that you want to enable:
    • TechPreviewNoUpgrade enables specific Technology Preview features.

    After you save the changes, new machine configs are created, the machine config pools are updated, and scheduling on each node is disabled while the change is being applied.

Verification

You can verify that the feature gates are enabled by looking at the kubelet.conf file on a node after the nodes return to the ready state.

  1. From the Administrator perspective in the web console, navigate to ComputeNodes.
  2. Select a node.
  3. In the Node details page, click Terminal.
  4. In the terminal window, change your root directory to /host:

    sh-4.2# chroot /host
  5. View the kubelet.conf file:

    sh-4.2# cat /etc/kubernetes/kubelet.conf

    Sample output

    # ...
    featureGates:
      InsightsOperatorPullingSCA: true,
      LegacyNodeRoleBehavior: false
    # ...

    The features that are listed as true are enabled on your cluster.

    Note

    The features listed vary depending upon the OpenShift Container Platform version.

4.11.3. Enabling feature sets using the CLI

You can use the OpenShift CLI (oc) to enable feature sets for all of the nodes in a cluster by editing the FeatureGate custom resource (CR).

Prerequisites

  • You have installed the OpenShift CLI (oc).

Procedure

To enable feature sets:

  1. Edit the FeatureGate CR named cluster:

    $ oc edit featuregate cluster
    Warning

    Enabling the TechPreviewNoUpgrade feature set on your cluster cannot be undone and prevents minor version updates. You should not enable this feature set on production clusters.

    Sample FeatureGate custom resource

    apiVersion: config.openshift.io/v1
    kind: FeatureGate
    metadata:
      name: cluster 1
    # ...
    spec:
      featureSet: TechPreviewNoUpgrade 2

    1
    The name of the FeatureGate CR must be cluster.
    2
    Add the feature set that you want to enable:
    • TechPreviewNoUpgrade enables specific Technology Preview features.

    After you save the changes, new machine configs are created, the machine config pools are updated, and scheduling on each node is disabled while the change is being applied.

Verification

You can verify that the feature gates are enabled by looking at the kubelet.conf file on a node after the nodes return to the ready state.

  1. From the Administrator perspective in the web console, navigate to ComputeNodes.
  2. Select a node.
  3. In the Node details page, click Terminal.
  4. In the terminal window, change your root directory to /host:

    sh-4.2# chroot /host
  5. View the kubelet.conf file:

    sh-4.2# cat /etc/kubernetes/kubelet.conf

    Sample output

    # ...
    featureGates:
      InsightsOperatorPullingSCA: true,
      LegacyNodeRoleBehavior: false
    # ...

    The features that are listed as true are enabled on your cluster.

    Note

    The features listed vary depending upon the OpenShift Container Platform version.

4.12. etcd tasks

Back up etcd, enable or disable etcd encryption, or defragment etcd data.

Note

If you deployed a bare-metal cluster, you can scale the cluster up to 5 nodes as part of your post-installation tasks. For more information, see Node scaling for etcd.

4.12.1. About etcd encryption

By default, etcd data is not encrypted in OpenShift Container Platform. You can enable etcd encryption for your cluster to provide an additional layer of data security. For example, it can help protect the loss of sensitive data if an etcd backup is exposed to the incorrect parties.

When you enable etcd encryption, the following OpenShift API server and Kubernetes API server resources are encrypted:

  • Secrets
  • Config maps
  • Routes
  • OAuth access tokens
  • OAuth authorize tokens

When you enable etcd encryption, encryption keys are created. You must have these keys to restore from an etcd backup.

Note

Etcd encryption only encrypts values, not keys. Resource types, namespaces, and object names are unencrypted.

If etcd encryption is enabled during a backup, the static_kuberesources_<datetimestamp>.tar.gz file contains the encryption keys for the etcd snapshot. For security reasons, store this file separately from the etcd snapshot. However, this file is required to restore a previous state of etcd from the respective etcd snapshot.

4.12.2. Supported encryption types

The following encryption types are supported for encrypting etcd data in OpenShift Container Platform:

AES-CBC
Uses AES-CBC with PKCS#7 padding and a 32 byte key to perform the encryption. The encryption keys are rotated weekly.
AES-GCM
Uses AES-GCM with a random nonce and a 32 byte key to perform the encryption. The encryption keys are rotated weekly.

4.12.3. Enabling etcd encryption

You can enable etcd encryption to encrypt sensitive resources in your cluster.

Warning

Do not back up etcd resources until the initial encryption process is completed. If the encryption process is not completed, the backup might be only partially encrypted.

After you enable etcd encryption, several changes can occur:

  • The etcd encryption might affect the memory consumption of a few resources.
  • You might notice a transient affect on backup performance because the leader must serve the backup.
  • A disk I/O can affect the node that receives the backup state.

You can encrypt the etcd database in either AES-GCM or AES-CBC encryption.

Note

To migrate your etcd database from one encryption type to the other, you can modify the API server’s spec.encryption.type field. Migration of the etcd data to the new encryption type occurs automatically.

Prerequisites

  • Access to the cluster as a user with the cluster-admin role.

Procedure

  1. Modify the APIServer object:

    $ oc edit apiserver
  2. Set the spec.encryption.type field to aesgcm or aescbc:

    spec:
      encryption:
        type: aesgcm 1
    1
    Set to aesgcm for AES-GCM encryption or aescbc for AES-CBC encryption.
  3. Save the file to apply the changes.

    The encryption process starts. It can take 20 minutes or longer for this process to complete, depending on the size of the etcd database.

  4. Verify that etcd encryption was successful.

    1. Review the Encrypted status condition for the OpenShift API server to verify that its resources were successfully encrypted:

      $ oc get openshiftapiserver -o=jsonpath='{range .items[0].status.conditions[?(@.type=="Encrypted")]}{.reason}{"\n"}{.message}{"\n"}'

      The output shows EncryptionCompleted upon successful encryption:

      EncryptionCompleted
      All resources encrypted: routes.route.openshift.io

      If the output shows EncryptionInProgress, encryption is still in progress. Wait a few minutes and try again.

    2. Review the Encrypted status condition for the Kubernetes API server to verify that its resources were successfully encrypted:

      $ oc get kubeapiserver -o=jsonpath='{range .items[0].status.conditions[?(@.type=="Encrypted")]}{.reason}{"\n"}{.message}{"\n"}'

      The output shows EncryptionCompleted upon successful encryption:

      EncryptionCompleted
      All resources encrypted: secrets, configmaps

      If the output shows EncryptionInProgress, encryption is still in progress. Wait a few minutes and try again.

    3. Review the Encrypted status condition for the OpenShift OAuth API server to verify that its resources were successfully encrypted:

      $ oc get authentication.operator.openshift.io -o=jsonpath='{range .items[0].status.conditions[?(@.type=="Encrypted")]}{.reason}{"\n"}{.message}{"\n"}'

      The output shows EncryptionCompleted upon successful encryption:

      EncryptionCompleted
      All resources encrypted: oauthaccesstokens.oauth.openshift.io, oauthauthorizetokens.oauth.openshift.io

      If the output shows EncryptionInProgress, encryption is still in progress. Wait a few minutes and try again.

4.12.4. Disabling etcd encryption

You can disable encryption of etcd data in your cluster.

Prerequisites

  • Access to the cluster as a user with the cluster-admin role.

Procedure

  1. Modify the APIServer object:

    $ oc edit apiserver
  2. Set the encryption field type to identity:

    spec:
      encryption:
        type: identity 1
    1
    The identity type is the default value and means that no encryption is performed.
  3. Save the file to apply the changes.

    The decryption process starts. It can take 20 minutes or longer for this process to complete, depending on the size of your cluster.

  4. Verify that etcd decryption was successful.

    1. Review the Encrypted status condition for the OpenShift API server to verify that its resources were successfully decrypted:

      $ oc get openshiftapiserver -o=jsonpath='{range .items[0].status.conditions[?(@.type=="Encrypted")]}{.reason}{"\n"}{.message}{"\n"}'

      The output shows DecryptionCompleted upon successful decryption:

      DecryptionCompleted
      Encryption mode set to identity and everything is decrypted

      If the output shows DecryptionInProgress, decryption is still in progress. Wait a few minutes and try again.

    2. Review the Encrypted status condition for the Kubernetes API server to verify that its resources were successfully decrypted:

      $ oc get kubeapiserver -o=jsonpath='{range .items[0].status.conditions[?(@.type=="Encrypted")]}{.reason}{"\n"}{.message}{"\n"}'

      The output shows DecryptionCompleted upon successful decryption:

      DecryptionCompleted
      Encryption mode set to identity and everything is decrypted

      If the output shows DecryptionInProgress, decryption is still in progress. Wait a few minutes and try again.

    3. Review the Encrypted status condition for the OpenShift OAuth API server to verify that its resources were successfully decrypted:

      $ oc get authentication.operator.openshift.io -o=jsonpath='{range .items[0].status.conditions[?(@.type=="Encrypted")]}{.reason}{"\n"}{.message}{"\n"}'

      The output shows DecryptionCompleted upon successful decryption:

      DecryptionCompleted
      Encryption mode set to identity and everything is decrypted

      If the output shows DecryptionInProgress, decryption is still in progress. Wait a few minutes and try again.

4.12.5. Backing up etcd data

Follow these steps to back up etcd data by creating an etcd snapshot and backing up the resources for the static pods. This backup can be saved and used at a later time if you need to restore etcd.

Important

Only save a backup from a single control plane host. Do not take a backup from each control plane host in the cluster.

Prerequisites

  • You have access to the cluster as a user with the cluster-admin role.
  • You have checked whether the cluster-wide proxy is enabled.

    Tip

    You can check whether the proxy is enabled by reviewing the output of oc get proxy cluster -o yaml. The proxy is enabled if the httpProxy, httpsProxy, and noProxy fields have values set.

Procedure

  1. Start a debug session as root for a control plane node:

    $ oc debug --as-root node/<node_name>
  2. Change your root directory to /host in the debug shell:

    sh-4.4# chroot /host
  3. If the cluster-wide proxy is enabled, export the NO_PROXY, HTTP_PROXY, and HTTPS_PROXY environment variables by running the following commands:

    $ export HTTP_PROXY=http://<your_proxy.example.com>:8080
    $ export HTTPS_PROXY=https://<your_proxy.example.com>:8080
    $ export NO_PROXY=<example.com>
  4. Run the cluster-backup.sh script in the debug shell and pass in the location to save the backup to.

    Tip

    The cluster-backup.sh script is maintained as a component of the etcd Cluster Operator and is a wrapper around the etcdctl snapshot save command.

    sh-4.4# /usr/local/bin/cluster-backup.sh /home/core/assets/backup

    Example script output

    found latest kube-apiserver: /etc/kubernetes/static-pod-resources/kube-apiserver-pod-6
    found latest kube-controller-manager: /etc/kubernetes/static-pod-resources/kube-controller-manager-pod-7
    found latest kube-scheduler: /etc/kubernetes/static-pod-resources/kube-scheduler-pod-6
    found latest etcd: /etc/kubernetes/static-pod-resources/etcd-pod-3
    ede95fe6b88b87ba86a03c15e669fb4aa5bf0991c180d3c6895ce72eaade54a1
    etcdctl version: 3.4.14
    API version: 3.4
    {"level":"info","ts":1624647639.0188997,"caller":"snapshot/v3_snapshot.go:119","msg":"created temporary db file","path":"/home/core/assets/backup/snapshot_2021-06-25_190035.db.part"}
    {"level":"info","ts":"2021-06-25T19:00:39.030Z","caller":"clientv3/maintenance.go:200","msg":"opened snapshot stream; downloading"}
    {"level":"info","ts":1624647639.0301006,"caller":"snapshot/v3_snapshot.go:127","msg":"fetching snapshot","endpoint":"https://10.0.0.5:2379"}
    {"level":"info","ts":"2021-06-25T19:00:40.215Z","caller":"clientv3/maintenance.go:208","msg":"completed snapshot read; closing"}
    {"level":"info","ts":1624647640.6032252,"caller":"snapshot/v3_snapshot.go:142","msg":"fetched snapshot","endpoint":"https://10.0.0.5:2379","size":"114 MB","took":1.584090459}
    {"level":"info","ts":1624647640.6047094,"caller":"snapshot/v3_snapshot.go:152","msg":"saved","path":"/home/core/assets/backup/snapshot_2021-06-25_190035.db"}
    Snapshot saved at /home/core/assets/backup/snapshot_2021-06-25_190035.db
    {"hash":3866667823,"revision":31407,"totalKey":12828,"totalSize":114446336}
    snapshot db and kube resources are successfully saved to /home/core/assets/backup

    In this example, two files are created in the /home/core/assets/backup/ directory on the control plane host:

    • snapshot_<datetimestamp>.db: This file is the etcd snapshot. The cluster-backup.sh script confirms its validity.
    • static_kuberesources_<datetimestamp>.tar.gz: This file contains the resources for the static pods. If etcd encryption is enabled, it also contains the encryption keys for the etcd snapshot.

      Note

      If etcd encryption is enabled, it is recommended to store this second file separately from the etcd snapshot for security reasons. However, this file is required to restore from the etcd snapshot.

      Keep in mind that etcd encryption only encrypts values, not keys. This means that resource types, namespaces, and object names are unencrypted.

4.12.6. Defragmenting etcd data

For large and dense clusters, etcd can suffer from poor performance if the keyspace grows too large and exceeds the space quota. Periodically maintain and defragment etcd to free up space in the data store. Monitor Prometheus for etcd metrics and defragment it when required; otherwise, etcd can raise a cluster-wide alarm that puts the cluster into a maintenance mode that accepts only key reads and deletes.

Monitor these key metrics:

  • etcd_server_quota_backend_bytes, which is the current quota limit
  • etcd_mvcc_db_total_size_in_use_in_bytes, which indicates the actual database usage after a history compaction
  • etcd_mvcc_db_total_size_in_bytes, which shows the database size, including free space waiting for defragmentation

Defragment etcd data to reclaim disk space after events that cause disk fragmentation, such as etcd history compaction.

History compaction is performed automatically every five minutes and leaves gaps in the back-end database. This fragmented space is available for use by etcd, but is not available to the host file system. You must defragment etcd to make this space available to the host file system.

Defragmentation occurs automatically, but you can also trigger it manually.

Note

Automatic defragmentation is good for most cases, because the etcd operator uses cluster information to determine the most efficient operation for the user.

4.12.6.1. Automatic defragmentation

The etcd Operator automatically defragments disks. No manual intervention is needed.

Verify that the defragmentation process is successful by viewing one of these logs:

  • etcd logs
  • cluster-etcd-operator pod
  • operator status error log
Warning

Automatic defragmentation can cause leader election failure in various OpenShift core components, such as the Kubernetes controller manager, which triggers a restart of the failing component. The restart is harmless and either triggers failover to the next running instance or the component resumes work again after the restart.

Example log output for successful defragmentation

etcd member has been defragmented: <member_name>, memberID: <member_id>

Example log output for unsuccessful defragmentation

failed defrag on member: <member_name>, memberID: <member_id>: <error_message>

4.12.6.2. Manual defragmentation

A Prometheus alert indicates when you need to use manual defragmentation. The alert is displayed in two cases:

  • When etcd uses more than 50% of its available space for more than 10 minutes
  • When etcd is actively using less than 50% of its total database size for more than 10 minutes

You can also determine whether defragmentation is needed by checking the etcd database size in MB that will be freed by defragmentation with the PromQL expression: (etcd_mvcc_db_total_size_in_bytes - etcd_mvcc_db_total_size_in_use_in_bytes)/1024/1024

Warning

Defragmenting etcd is a blocking action. The etcd member will not respond until defragmentation is complete. For this reason, wait at least one minute between defragmentation actions on each of the pods to allow the cluster to recover.

Follow this procedure to defragment etcd data on each etcd member.

Prerequisites

  • You have access to the cluster as a user with the cluster-admin role.

Procedure

  1. Determine which etcd member is the leader, because the leader should be defragmented last.

    1. Get the list of etcd pods:

      $ oc -n openshift-etcd get pods -l k8s-app=etcd -o wide

      Example output

      etcd-ip-10-0-159-225.example.redhat.com                3/3     Running     0          175m   10.0.159.225   ip-10-0-159-225.example.redhat.com   <none>           <none>
      etcd-ip-10-0-191-37.example.redhat.com                 3/3     Running     0          173m   10.0.191.37    ip-10-0-191-37.example.redhat.com    <none>           <none>
      etcd-ip-10-0-199-170.example.redhat.com                3/3     Running     0          176m   10.0.199.170   ip-10-0-199-170.example.redhat.com   <none>           <none>

    2. Choose a pod and run the following command to determine which etcd member is the leader:

      $ oc rsh -n openshift-etcd etcd-ip-10-0-159-225.example.redhat.com etcdctl endpoint status --cluster -w table

      Example output

      Defaulting container name to etcdctl.
      Use 'oc describe pod/etcd-ip-10-0-159-225.example.redhat.com -n openshift-etcd' to see all of the containers in this pod.
      +---------------------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+
      |         ENDPOINT          |        ID        | VERSION | DB SIZE | IS LEADER | IS LEARNER | RAFT TERM | RAFT INDEX | RAFT APPLIED INDEX | ERRORS |
      +---------------------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+
      |  https://10.0.191.37:2379 | 251cd44483d811c3 |   3.5.9 |  104 MB |     false |      false |         7 |      91624 |              91624 |        |
      | https://10.0.159.225:2379 | 264c7c58ecbdabee |   3.5.9 |  104 MB |     false |      false |         7 |      91624 |              91624 |        |
      | https://10.0.199.170:2379 | 9ac311f93915cc79 |   3.5.9 |  104 MB |      true |      false |         7 |      91624 |              91624 |        |
      +---------------------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+

      Based on the IS LEADER column of this output, the https://10.0.199.170:2379 endpoint is the leader. Matching this endpoint with the output of the previous step, the pod name of the leader is etcd-ip-10-0-199-170.example.redhat.com.

  2. Defragment an etcd member.

    1. Connect to the running etcd container, passing in the name of a pod that is not the leader:

      $ oc rsh -n openshift-etcd etcd-ip-10-0-159-225.example.redhat.com
    2. Unset the ETCDCTL_ENDPOINTS environment variable:

      sh-4.4# unset ETCDCTL_ENDPOINTS
    3. Defragment the etcd member:

      sh-4.4# etcdctl --command-timeout=30s --endpoints=https://localhost:2379 defrag

      Example output

      Finished defragmenting etcd member[https://localhost:2379]

      If a timeout error occurs, increase the value for --command-timeout until the command succeeds.

    4. Verify that the database size was reduced:

      sh-4.4# etcdctl endpoint status -w table --cluster

      Example output

      +---------------------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+
      |         ENDPOINT          |        ID        | VERSION | DB SIZE | IS LEADER | IS LEARNER | RAFT TERM | RAFT INDEX | RAFT APPLIED INDEX | ERRORS |
      +---------------------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+
      |  https://10.0.191.37:2379 | 251cd44483d811c3 |   3.5.9 |  104 MB |     false |      false |         7 |      91624 |              91624 |        |
      | https://10.0.159.225:2379 | 264c7c58ecbdabee |   3.5.9 |   41 MB |     false |      false |         7 |      91624 |              91624 |        | 1
      | https://10.0.199.170:2379 | 9ac311f93915cc79 |   3.5.9 |  104 MB |      true |      false |         7 |      91624 |              91624 |        |
      +---------------------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+

      This example shows that the database size for this etcd member is now 41 MB as opposed to the starting size of 104 MB.

    5. Repeat these steps to connect to each of the other etcd members and defragment them. Always defragment the leader last.

      Wait at least one minute between defragmentation actions to allow the etcd pod to recover. Until the etcd pod recovers, the etcd member will not respond.

  3. If any NOSPACE alarms were triggered due to the space quota being exceeded, clear them.

    1. Check if there are any NOSPACE alarms:

      sh-4.4# etcdctl alarm list

      Example output

      memberID:12345678912345678912 alarm:NOSPACE

    2. Clear the alarms:

      sh-4.4# etcdctl alarm disarm

4.12.7. Restoring to a previous cluster state

You can use a saved etcd backup to restore a previous cluster state or restore a cluster that has lost the majority of control plane hosts.

Note

If your cluster uses a control plane machine set, see "Troubleshooting the control plane machine set" for a more simple etcd recovery procedure.

Important

When you restore your cluster, you must use an etcd backup that was taken from the same z-stream release. For example, an OpenShift Container Platform 4.7.2 cluster must use an etcd backup that was taken from 4.7.2.

Prerequisites

  • Access to the cluster as a user with the cluster-admin role through a certificate-based kubeconfig file, like the one that was used during installation.
  • A healthy control plane host to use as the recovery host.
  • SSH access to control plane hosts.
  • A backup directory containing both the etcd snapshot and the resources for the static pods, which were from the same backup. The file names in the directory must be in the following formats: snapshot_<datetimestamp>.db and static_kuberesources_<datetimestamp>.tar.gz.
Important

For non-recovery control plane nodes, it is not required to establish SSH connectivity or to stop the static pods. You can delete and recreate other non-recovery, control plane machines, one by one.

Procedure

  1. Select a control plane host to use as the recovery host. This is the host that you will run the restore operation on.
  2. Establish SSH connectivity to each of the control plane nodes, including the recovery host.

    kube-apiserver becomes inaccessible after the restore process starts, so you cannot access the control plane nodes. For this reason, it is recommended to establish SSH connectivity to each control plane host in a separate terminal.

    Important

    If you do not complete this step, you will not be able to access the control plane hosts to complete the restore procedure, and you will be unable to recover your cluster from this state.

  3. Copy the etcd backup directory to the recovery control plane host.

    This procedure assumes that you copied the backup directory containing the etcd snapshot and the resources for the static pods to the /home/core/ directory of your recovery control plane host.

  4. Stop the static pods on any other control plane nodes.

    Note

    You do not need to stop the static pods on the recovery host.

    1. Access a control plane host that is not the recovery host.
    2. Move the existing etcd pod file out of the kubelet manifest directory by running:

      $ sudo mv -v /etc/kubernetes/manifests/etcd-pod.yaml /tmp
    3. Verify that the etcd pods are stopped by using:

      $ sudo crictl ps | grep etcd | egrep -v "operator|etcd-guard"

      If the output of this command is not empty, wait a few minutes and check again.

    4. Move the existing kube-apiserver file out of the kubelet manifest directory by running:

      $ sudo mv -v /etc/kubernetes/manifests/kube-apiserver-pod.yaml /tmp
    5. Verify that the kube-apiserver containers are stopped by running:

      $ sudo crictl ps | grep kube-apiserver | egrep -v "operator|guard"

      If the output of this command is not empty, wait a few minutes and check again.

    6. Move the existing kube-controller-manager file out of the kubelet manifest directory by using:

      $ sudo mv -v /etc/kubernetes/manifests/kube-controller-manager-pod.yaml /tmp
    7. Verify that the kube-controller-manager containers are stopped by running:

      $ sudo crictl ps | grep kube-controller-manager | egrep -v "operator|guard"

      If the output of this command is not empty, wait a few minutes and check again.

    8. Move the existing kube-scheduler file out of the kubelet manifest directory by using:

      $ sudo mv -v /etc/kubernetes/manifests/kube-scheduler-pod.yaml /tmp
    9. Verify that the kube-scheduler containers are stopped by using:

      $ sudo crictl ps | grep kube-scheduler | egrep -v "operator|guard"

      If the output of this command is not empty, wait a few minutes and check again.

    10. Move the etcd data directory to a different location with the following example:

      $ sudo mv -v /var/lib/etcd/ /tmp
    11. If the /etc/kubernetes/manifests/keepalived.yaml file exists and the node is deleted, follow these steps:

      1. Move the /etc/kubernetes/manifests/keepalived.yaml file out of the kubelet manifest directory:

        $ sudo mv -v /etc/kubernetes/manifests/keepalived.yaml /tmp
      2. Verify that any containers managed by the keepalived daemon are stopped:

        $ sudo crictl ps --name keepalived

        The output of this command should be empty. If it is not empty, wait a few minutes and check again.

      3. Check if the control plane has any Virtual IPs (VIPs) assigned to it:

        $ ip -o address | egrep '<api_vip>|<ingress_vip>'
      4. For each reported VIP, run the following command to remove it:

        $ sudo ip address del <reported_vip> dev <reported_vip_device>
    12. Repeat this step on each of the other control plane hosts that is not the recovery host.
  5. Access the recovery control plane host.
  6. If the keepalived daemon is in use, verify that the recovery control plane node owns the VIP:

    $ ip -o address | grep <api_vip>

    The address of the VIP is highlighted in the output if it exists. This command returns an empty string if the VIP is not set or configured incorrectly.

  7. If the cluster-wide proxy is enabled, be sure that you have exported the NO_PROXY, HTTP_PROXY, and HTTPS_PROXY environment variables.

    Tip

    You can check whether the proxy is enabled by reviewing the output of oc get proxy cluster -o yaml. The proxy is enabled if the httpProxy, httpsProxy, and noProxy fields have values set.

  8. Run the restore script on the recovery control plane host and pass in the path to the etcd backup directory:

    $ sudo -E /usr/local/bin/cluster-restore.sh /home/core/assets/backup

    Example script output

    ...stopping kube-scheduler-pod.yaml
    ...stopping kube-controller-manager-pod.yaml
    ...stopping etcd-pod.yaml
    ...stopping kube-apiserver-pod.yaml
    Waiting for container etcd to stop
    .complete
    Waiting for container etcdctl to stop
    .............................complete
    Waiting for container etcd-metrics to stop
    complete
    Waiting for container kube-controller-manager to stop
    complete
    Waiting for container kube-apiserver to stop
    ..........................................................................................complete
    Waiting for container kube-scheduler to stop
    complete
    Moving etcd data-dir /var/lib/etcd/member to /var/lib/etcd-backup
    starting restore-etcd static pod
    starting kube-apiserver-pod.yaml
    static-pod-resources/kube-apiserver-pod-7/kube-apiserver-pod.yaml
    starting kube-controller-manager-pod.yaml
    static-pod-resources/kube-controller-manager-pod-7/kube-controller-manager-pod.yaml
    starting kube-scheduler-pod.yaml
    static-pod-resources/kube-scheduler-pod-8/kube-scheduler-pod.yaml

    The cluster-restore.sh script must show that etcd, kube-apiserver, kube-controller-manager, and kube-scheduler pods are stopped and then started at the end of the restore process.

    Note

    The restore process can cause nodes to enter the NotReady state if the node certificates were updated after the last etcd backup.

  9. Check the nodes to ensure they are in the Ready state.

    1. Run the following command:

      $ oc get nodes -w

      Sample output

      NAME                STATUS  ROLES          AGE     VERSION
      host-172-25-75-28   Ready   master         3d20h   v1.30.3
      host-172-25-75-38   Ready   infra,worker   3d20h   v1.30.3
      host-172-25-75-40   Ready   master         3d20h   v1.30.3
      host-172-25-75-65   Ready   master         3d20h   v1.30.3
      host-172-25-75-74   Ready   infra,worker   3d20h   v1.30.3
      host-172-25-75-79   Ready   worker         3d20h   v1.30.3
      host-172-25-75-86   Ready   worker         3d20h   v1.30.3
      host-172-25-75-98   Ready   infra,worker   3d20h   v1.30.3

      It can take several minutes for all nodes to report their state.

    2. If any nodes are in the NotReady state, log in to the nodes and remove all of the PEM files from the /var/lib/kubelet/pki directory on each node. You can SSH into the nodes or use the terminal window in the web console.

      $  ssh -i <ssh-key-path> core@<master-hostname>

      Sample pki directory

      sh-4.4# pwd
      /var/lib/kubelet/pki
      sh-4.4# ls
      kubelet-client-2022-04-28-11-24-09.pem  kubelet-server-2022-04-28-11-24-15.pem
      kubelet-client-current.pem              kubelet-server-current.pem

  10. Restart the kubelet service on all control plane hosts.

    1. From the recovery host, run:

      $ sudo systemctl restart kubelet.service
    2. Repeat this step on all other control plane hosts.
  11. Approve the pending Certificate Signing Requests (CSRs):

    Note

    Clusters with no worker nodes, such as single-node clusters or clusters consisting of three schedulable control plane nodes, will not have any pending CSRs to approve. You can skip all the commands listed in this step.

    1. Get the list of current CSRs by running:

      $ oc get csr

      Example output

      NAME        AGE    SIGNERNAME                                    REQUESTOR                                                                   CONDITION
      csr-2s94x   8m3s   kubernetes.io/kubelet-serving                 system:node:<node_name>                                                     Pending 1
      csr-4bd6t   8m3s   kubernetes.io/kubelet-serving                 system:node:<node_name>                                                     Pending 2
      csr-4hl85   13m    kubernetes.io/kube-apiserver-client-kubelet   system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending 3
      csr-zhhhp   3m8s   kubernetes.io/kube-apiserver-client-kubelet   system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending 4
      ...

      1 1 2
      A pending kubelet serving CSR, requested by the node for the kubelet serving endpoint.
      3 4
      A pending kubelet client CSR, requested with the node-bootstrapper node bootstrap credentials.
    2. Review the details of a CSR to verify that it is valid by running:

      $ oc describe csr <csr_name> 1
      1
      <csr_name> is the name of a CSR from the list of current CSRs.
    3. Approve each valid node-bootstrapper CSR by running:

      $ oc adm certificate approve <csr_name>
    4. For user-provisioned installations, approve each valid kubelet service CSR by running:

      $ oc adm certificate approve <csr_name>
  12. Verify that the single member control plane has started successfully.

    1. From the recovery host, verify that the etcd container is running by using:

      $ sudo crictl ps | grep etcd | egrep -v "operator|etcd-guard"

      Example output

      3ad41b7908e32       36f86e2eeaaffe662df0d21041eb22b8198e0e58abeeae8c743c3e6e977e8009                                                         About a minute ago   Running             etcd                                          0                   7c05f8af362f0

    2. From the recovery host, verify that the etcd pod is running by using:

      $ oc -n openshift-etcd get pods -l k8s-app=etcd

      Example output

      NAME                                             READY   STATUS      RESTARTS   AGE
      etcd-ip-10-0-143-125.ec2.internal                1/1     Running     1          2m47s

      If the status is Pending, or the output lists more than one running etcd pod, wait a few minutes and check again.

  13. If you are using the OVNKubernetes network plugin, you must restart ovnkube-controlplane pods.

    1. Delete all of the ovnkube-controlplane pods by running:

      $ oc -n openshift-ovn-kubernetes delete pod -l app=ovnkube-control-plane
    2. Verify that all of the ovnkube-controlplane pods were redeployed by using:

      $ oc -n openshift-ovn-kubernetes get pod -l app=ovnkube-control-plane
  14. If you are using the OVN-Kubernetes network plugin, restart the Open Virtual Network (OVN) Kubernetes pods on all the nodes one by one. Use the following steps to restart OVN-Kubernetes pods on each node:

    Important

    Restart OVN-Kubernetes pods in the following order

    1. The recovery control plane host
    2. The other control plane hosts (if available)
    3. The other nodes
    Note

    Validating and mutating admission webhooks can reject pods. If you add any additional webhooks with the failurePolicy set to Fail, then they can reject pods and the restoration process can fail. You can avoid this by saving and deleting webhooks while restoring the cluster state. After the cluster state is restored successfully, you can enable the webhooks again.

    Alternatively, you can temporarily set the failurePolicy to Ignore while restoring the cluster state. After the cluster state is restored successfully, you can set the failurePolicy to Fail.

    1. Remove the northbound database (nbdb) and southbound database (sbdb). Access the recovery host and the remaining control plane nodes by using Secure Shell (SSH) and run:

      $ sudo rm -f /var/lib/ovn-ic/etc/*.db
    2. Restart the OpenVSwitch services. Access the node by using Secure Shell (SSH) and run the following command:

      $ sudo systemctl restart ovs-vswitchd ovsdb-server
    3. Delete the ovnkube-node pod on the node by running the following command, replacing <node> with the name of the node that you are restarting:

      $ oc -n openshift-ovn-kubernetes delete pod -l app=ovnkube-node --field-selector=spec.nodeName==<node>
    4. Verify that the ovnkube-node pod is running again with:

      $ oc -n openshift-ovn-kubernetes get pod -l app=ovnkube-node --field-selector=spec.nodeName==<node>
      Note

      It might take several minutes for the pods to restart.

  15. Delete and re-create other non-recovery, control plane machines, one by one. After the machines are re-created, a new revision is forced and etcd automatically scales up.

    • If you use a user-provisioned bare metal installation, you can re-create a control plane machine by using the same method that you used to originally create it. For more information, see "Installing a user-provisioned cluster on bare metal".

      Warning

      Do not delete and re-create the machine for the recovery host.

    • If you are running installer-provisioned infrastructure, or you used the Machine API to create your machines, follow these steps:

      Warning

      Do not delete and re-create the machine for the recovery host.

      For bare metal installations on installer-provisioned infrastructure, control plane machines are not re-created. For more information, see "Replacing a bare-metal control plane node".

      1. Obtain the machine for one of the lost control plane hosts.

        In a terminal that has access to the cluster as a cluster-admin user, run the following command:

        $ oc get machines -n openshift-machine-api -o wide

        Example output:

        NAME                                        PHASE     TYPE        REGION      ZONE         AGE     NODE                           PROVIDERID                              STATE
        clustername-8qw5l-master-0                  Running   m4.xlarge   us-east-1   us-east-1a   3h37m   ip-10-0-131-183.ec2.internal   aws:///us-east-1a/i-0ec2782f8287dfb7e   stopped 1
        clustername-8qw5l-master-1                  Running   m4.xlarge   us-east-1   us-east-1b   3h37m   ip-10-0-143-125.ec2.internal   aws:///us-east-1b/i-096c349b700a19631   running
        clustername-8qw5l-master-2                  Running   m4.xlarge   us-east-1   us-east-1c   3h37m   ip-10-0-154-194.ec2.internal    aws:///us-east-1c/i-02626f1dba9ed5bba  running
        clustername-8qw5l-worker-us-east-1a-wbtgd   Running   m4.large    us-east-1   us-east-1a   3h28m   ip-10-0-129-226.ec2.internal   aws:///us-east-1a/i-010ef6279b4662ced   running
        clustername-8qw5l-worker-us-east-1b-lrdxb   Running   m4.large    us-east-1   us-east-1b   3h28m   ip-10-0-144-248.ec2.internal   aws:///us-east-1b/i-0cb45ac45a166173b   running
        clustername-8qw5l-worker-us-east-1c-pkg26   Running   m4.large    us-east-1   us-east-1c   3h28m   ip-10-0-170-181.ec2.internal   aws:///us-east-1c/i-06861c00007751b0a   running
        1
        This is the control plane machine for the lost control plane host, ip-10-0-131-183.ec2.internal.
      2. Delete the machine of the lost control plane host by running:

        $ oc delete machine -n openshift-machine-api clustername-8qw5l-master-0 1
        1
        Specify the name of the control plane machine for the lost control plane host.

        A new machine is automatically provisioned after deleting the machine of the lost control plane host.

      3. Verify that a new machine has been created by running:

        $ oc get machines -n openshift-machine-api -o wide

        Example output:

        NAME                                        PHASE          TYPE        REGION      ZONE         AGE     NODE                           PROVIDERID                              STATE
        clustername-8qw5l-master-1                  Running        m4.xlarge   us-east-1   us-east-1b   3h37m   ip-10-0-143-125.ec2.internal   aws:///us-east-1b/i-096c349b700a19631   running
        clustername-8qw5l-master-2                  Running        m4.xlarge   us-east-1   us-east-1c   3h37m   ip-10-0-154-194.ec2.internal    aws:///us-east-1c/i-02626f1dba9ed5bba  running
        clustername-8qw5l-master-3                  Provisioning   m4.xlarge   us-east-1   us-east-1a   85s     ip-10-0-173-171.ec2.internal    aws:///us-east-1a/i-015b0888fe17bc2c8  running 1
        clustername-8qw5l-worker-us-east-1a-wbtgd   Running        m4.large    us-east-1   us-east-1a   3h28m   ip-10-0-129-226.ec2.internal   aws:///us-east-1a/i-010ef6279b4662ced   running
        clustername-8qw5l-worker-us-east-1b-lrdxb   Running        m4.large    us-east-1   us-east-1b   3h28m   ip-10-0-144-248.ec2.internal   aws:///us-east-1b/i-0cb45ac45a166173b   running
        clustername-8qw5l-worker-us-east-1c-pkg26   Running        m4.large    us-east-1   us-east-1c   3h28m   ip-10-0-170-181.ec2.internal   aws:///us-east-1c/i-06861c00007751b0a   running
        1
        The new machine, clustername-8qw5l-master-3 is being created and is ready after the phase changes from Provisioning to Running.

        It might take a few minutes for the new machine to be created. The etcd cluster Operator will automatically sync when the machine or node returns to a healthy state.

      4. Repeat these steps for each lost control plane host that is not the recovery host.
  16. Turn off the quorum guard by entering:

    $ oc patch etcd/cluster --type=merge -p '{"spec": {"unsupportedConfigOverrides": {"useUnsupportedUnsafeNonHANonProductionUnstableEtcd": true}}}'

    This command ensures that you can successfully re-create secrets and roll out the static pods.

  17. In a separate terminal window within the recovery host, export the recovery kubeconfig file by running:

    $ export KUBECONFIG=/etc/kubernetes/static-pod-resources/kube-apiserver-certs/secrets/node-kubeconfigs/localhost-recovery.kubeconfig
  18. Force etcd redeployment.

    In the same terminal window where you exported the recovery kubeconfig file, run:

    $ oc patch etcd cluster -p='{"spec": {"forceRedeploymentReason": "recovery-'"$( date --rfc-3339=ns )"'"}}' --type=merge 1
    1
    The forceRedeploymentReason value must be unique, which is why a timestamp is appended.

    The etcd redeployment starts.

    When the etcd cluster Operator performs a redeployment, the existing nodes are started with new pods similar to the initial bootstrap scale up.

  19. Turn the quorum guard back on by entering:

    $ oc patch etcd/cluster --type=merge -p '{"spec": {"unsupportedConfigOverrides": null}}'
  20. You can verify that the unsupportedConfigOverrides section is removed from the object by running:

    $ oc get etcd/cluster -oyaml
  21. Verify all nodes are updated to the latest revision.

    In a terminal that has access to the cluster as a cluster-admin user, run:

    $ oc get etcd -o=jsonpath='{range .items[0].status.conditions[?(@.type=="NodeInstallerProgressing")]}{.reason}{"\n"}{.message}{"\n"}'

    Review the NodeInstallerProgressing status condition for etcd to verify that all nodes are at the latest revision. The output shows AllNodesAtLatestRevision upon successful update:

    AllNodesAtLatestRevision
    3 nodes are at revision 7 1
    1
    In this example, the latest revision number is 7.

    If the output includes multiple revision numbers, such as 2 nodes are at revision 6; 1 nodes are at revision 7, this means that the update is still in progress. Wait a few minutes and try again.

  22. After etcd is redeployed, force new rollouts for the control plane. kube-apiserver will reinstall itself on the other nodes because the kubelet is connected to API servers using an internal load balancer.

    In a terminal that has access to the cluster as a cluster-admin user, run:

    1. Force a new rollout for kube-apiserver:

      $ oc patch kubeapiserver cluster -p='{"spec": {"forceRedeploymentReason": "recovery-'"$( date --rfc-3339=ns )"'"}}' --type=merge

      Verify all nodes are updated to the latest revision.

      $ oc get kubeapiserver -o=jsonpath='{range .items[0].status.conditions[?(@.type=="NodeInstallerProgressing")]}{.reason}{"\n"}{.message}{"\n"}'

      Review the NodeInstallerProgressing status condition to verify that all nodes are at the latest revision. The output shows AllNodesAtLatestRevision upon successful update:

      AllNodesAtLatestRevision
      3 nodes are at revision 7 1
      1
      In this example, the latest revision number is 7.

      If the output includes multiple revision numbers, such as 2 nodes are at revision 6; 1 nodes are at revision 7, this means that the update is still in progress. Wait a few minutes and try again.

    2. Force a new rollout for the Kubernetes controller manager by running the following command:

      $ oc patch kubecontrollermanager cluster -p='{"spec": {"forceRedeploymentReason": "recovery-'"$( date --rfc-3339=ns )"'"}}' --type=merge

      Verify all nodes are updated to the latest revision by running:

      $ oc get kubecontrollermanager -o=jsonpath='{range .items[0].status.conditions[?(@.type=="NodeInstallerProgressing")]}{.reason}{"\n"}{.message}{"\n"}'

      Review the NodeInstallerProgressing status condition to verify that all nodes are at the latest revision. The output shows AllNodesAtLatestRevision upon successful update:

      AllNodesAtLatestRevision
      3 nodes are at revision 7 1
      1
      In this example, the latest revision number is 7.

      If the output includes multiple revision numbers, such as 2 nodes are at revision 6; 1 nodes are at revision 7, this means that the update is still in progress. Wait a few minutes and try again.

    3. Force a new rollout for the kube-scheduler by running:

      $ oc patch kubescheduler cluster -p='{"spec": {"forceRedeploymentReason": "recovery-'"$( date --rfc-3339=ns )"'"}}' --type=merge

      Verify all nodes are updated to the latest revision by using:

      $ oc get kubescheduler -o=jsonpath='{range .items[0].status.conditions[?(@.type=="NodeInstallerProgressing")]}{.reason}{"\n"}{.message}{"\n"}'

      Review the NodeInstallerProgressing status condition to verify that all nodes are at the latest revision. The output shows AllNodesAtLatestRevision upon successful update:

      AllNodesAtLatestRevision
      3 nodes are at revision 7 1
      1
      In this example, the latest revision number is 7.

      If the output includes multiple revision numbers, such as 2 nodes are at revision 6; 1 nodes are at revision 7, this means that the update is still in progress. Wait a few minutes and try again.

  23. Monitor the platform Operators by running:

    $ oc adm wait-for-stable-cluster

    This process can take up to 15 minutes.

  24. Verify that all control plane hosts have started and joined the cluster.

    In a terminal that has access to the cluster as a cluster-admin user, run the following command:

    $ oc -n openshift-etcd get pods -l k8s-app=etcd

    Example output

    etcd-ip-10-0-143-125.ec2.internal                2/2     Running     0          9h
    etcd-ip-10-0-154-194.ec2.internal                2/2     Running     0          9h
    etcd-ip-10-0-173-171.ec2.internal                2/2     Running     0          9h

To ensure that all workloads return to normal operation following a recovery procedure, restart all control plane nodes.

Note

On completion of the previous procedural steps, you might need to wait a few minutes for all services to return to their restored state. For example, authentication by using oc login might not immediately work until the OAuth server pods are restarted.

Consider using the system:admin kubeconfig file for immediate authentication. This method basis its authentication on SSL/TLS client certificates as against OAuth tokens. You can authenticate with this file by issuing the following command:

$ export KUBECONFIG=<installation_directory>/auth/kubeconfig

Issue the following command to display your authenticated user name:

$ oc whoami

4.12.8. Issues and workarounds for restoring a persistent storage state

If your OpenShift Container Platform cluster uses persistent storage of any form, a state of the cluster is typically stored outside etcd. It might be an Elasticsearch cluster running in a pod or a database running in a StatefulSet object. When you restore from an etcd backup, the status of the workloads in OpenShift Container Platform is also restored. However, if the etcd snapshot is old, the status might be invalid or outdated.

Important

The contents of persistent volumes (PVs) are never part of the etcd snapshot. When you restore an OpenShift Container Platform cluster from an etcd snapshot, non-critical workloads might gain access to critical data, or vice-versa.

The following are some example scenarios that produce an out-of-date status:

  • MySQL database is running in a pod backed up by a PV object. Restoring OpenShift Container Platform from an etcd snapshot does not bring back the volume on the storage provider, and does not produce a running MySQL pod, despite the pod repeatedly attempting to start. You must manually restore this pod by restoring the volume on the storage provider, and then editing the PV to point to the new volume.
  • Pod P1 is using volume A, which is attached to node X. If the etcd snapshot is taken while another pod uses the same volume on node Y, then when the etcd restore is performed, pod P1 might not be able to start correctly due to the volume still being attached to node Y. OpenShift Container Platform is not aware of the attachment, and does not automatically detach it. When this occurs, the volume must be manually detached from node Y so that the volume can attach on node X, and then pod P1 can start.
  • Cloud provider or storage provider credentials were updated after the etcd snapshot was taken. This causes any CSI drivers or Operators that depend on the those credentials to not work. You might have to manually update the credentials required by those drivers or Operators.
  • A device is removed or renamed from OpenShift Container Platform nodes after the etcd snapshot is taken. The Local Storage Operator creates symlinks for each PV that it manages from /dev/disk/by-id or /dev directories. This situation might cause the local PVs to refer to devices that no longer exist.

    To fix this problem, an administrator must:

    1. Manually remove the PVs with invalid devices.
    2. Remove symlinks from respective nodes.
    3. Delete LocalVolume or LocalVolumeSet objects (see StorageConfiguring persistent storagePersistent storage using local volumesDeleting the Local Storage Operator Resources).

4.13. Pod disruption budgets

Understand and configure pod disruption budgets.

4.13.1. Understanding how to use pod disruption budgets to specify the number of pods that must be up

A pod disruption budget allows the specification of safety constraints on pods during operations, such as draining a node for maintenance.

PodDisruptionBudget is an API object that specifies the minimum number or percentage of replicas that must be up at a time. Setting these in projects can be helpful during node maintenance (such as scaling a cluster down or a cluster upgrade) and is only honored on voluntary evictions (not on node failures).

A PodDisruptionBudget object’s configuration consists of the following key parts:

  • A label selector, which is a label query over a set of pods.
  • An availability level, which specifies the minimum number of pods that must be available simultaneously, either:

    • minAvailable is the number of pods must always be available, even during a disruption.
    • maxUnavailable is the number of pods can be unavailable during a disruption.
Note

Available refers to the number of pods that has condition Ready=True. Ready=True refers to the pod that is able to serve requests and should be added to the load balancing pools of all matching services.

A maxUnavailable of 0% or 0 or a minAvailable of 100% or equal to the number of replicas is permitted but can block nodes from being drained.

Warning

The default setting for maxUnavailable is 1 for all the machine config pools in OpenShift Container Platform. It is recommended to not change this value and update one control plane node at a time. Do not change this value to 3 for the control plane pool.

You can check for pod disruption budgets across all projects with the following:

$ oc get poddisruptionbudget --all-namespaces
Note

The following example contains some values that are specific to OpenShift Container Platform on AWS.

Example output

NAMESPACE                              NAME                                    MIN AVAILABLE   MAX UNAVAILABLE   ALLOWED DISRUPTIONS   AGE
openshift-apiserver                    openshift-apiserver-pdb                 N/A             1                 1                     121m
openshift-cloud-controller-manager     aws-cloud-controller-manager            1               N/A               1                     125m
openshift-cloud-credential-operator    pod-identity-webhook                    1               N/A               1                     117m
openshift-cluster-csi-drivers          aws-ebs-csi-driver-controller-pdb       N/A             1                 1                     121m
openshift-cluster-storage-operator     csi-snapshot-controller-pdb             N/A             1                 1                     122m
openshift-cluster-storage-operator     csi-snapshot-webhook-pdb                N/A             1                 1                     122m
openshift-console                      console                                 N/A             1                 1                     116m
#...

The PodDisruptionBudget is considered healthy when there are at least minAvailable pods running in the system. Every pod above that limit can be evicted.

Note

Depending on your pod priority and preemption settings, lower-priority pods might be removed despite their pod disruption budget requirements.

4.13.2. Specifying the number of pods that must be up with pod disruption budgets

You can use a PodDisruptionBudget object to specify the minimum number or percentage of replicas that must be up at a time.

Procedure

To configure a pod disruption budget:

  1. Create a YAML file with the an object definition similar to the following:

    apiVersion: policy/v1 1
    kind: PodDisruptionBudget
    metadata:
      name: my-pdb
    spec:
      minAvailable: 2  2
      selector:  3
        matchLabels:
          name: my-pod
    1
    PodDisruptionBudget is part of the policy/v1 API group.
    2
    The minimum number of pods that must be available simultaneously. This can be either an integer or a string specifying a percentage, for example, 20%.
    3
    A label query over a set of resources. The result of matchLabels and matchExpressions are logically conjoined. Leave this parameter blank, for example selector {}, to select all pods in the project.

    Or:

    apiVersion: policy/v1 1
    kind: PodDisruptionBudget
    metadata:
      name: my-pdb
    spec:
      maxUnavailable: 25% 2
      selector: 3
        matchLabels:
          name: my-pod
    1
    PodDisruptionBudget is part of the policy/v1 API group.
    2
    The maximum number of pods that can be unavailable simultaneously. This can be either an integer or a string specifying a percentage, for example, 20%.
    3
    A label query over a set of resources. The result of matchLabels and matchExpressions are logically conjoined. Leave this parameter blank, for example selector {}, to select all pods in the project.
  2. Run the following command to add the object to project:

    $ oc create -f </path/to/file> -n <project_name>

4.13.3. Specifying the eviction policy for unhealthy pods

When you use pod disruption budgets (PDBs) to specify how many pods must be available simultaneously, you can also define the criteria for how unhealthy pods are considered for eviction.

You can choose one of the following policies:

IfHealthyBudget
Running pods that are not yet healthy can be evicted only if the guarded application is not disrupted.
AlwaysAllow

Running pods that are not yet healthy can be evicted regardless of whether the criteria in the pod disruption budget is met. This policy can help evict malfunctioning applications, such as ones with pods stuck in the CrashLoopBackOff state or failing to report the Ready status.

Note

It is recommended to set the unhealthyPodEvictionPolicy field to AlwaysAllow in the PodDisruptionBudget object to support the eviction of misbehaving applications during a node drain. The default behavior is to wait for the application pods to become healthy before the drain can proceed.

Procedure

  1. Create a YAML file that defines a PodDisruptionBudget object and specify the unhealthy pod eviction policy:

    Example pod-disruption-budget.yaml file

    apiVersion: policy/v1
    kind: PodDisruptionBudget
    metadata:
      name: my-pdb
    spec:
      minAvailable: 2
      selector:
        matchLabels:
          name: my-pod
      unhealthyPodEvictionPolicy: AlwaysAllow 1

    1
    Choose either IfHealthyBudget or AlwaysAllow as the unhealthy pod eviction policy. The default is IfHealthyBudget when the unhealthyPodEvictionPolicy field is empty.
  2. Create the PodDisruptionBudget object by running the following command:

    $ oc create -f pod-disruption-budget.yaml

With a PDB that has the AlwaysAllow unhealthy pod eviction policy set, you can now drain nodes and evict the pods for a malfunctioning application guarded by this PDB.

Additional resources

Chapter 5. Postinstallation node tasks

After installing OpenShift Container Platform, you can further expand and customize your cluster to your requirements through certain node tasks.

5.1. Adding RHEL compute machines to an OpenShift Container Platform cluster

Understand and work with RHEL compute nodes.

5.1.1. About adding RHEL compute nodes to a cluster

In OpenShift Container Platform 4.17, you have the option of using Red Hat Enterprise Linux (RHEL) machines as compute machines in your cluster if you use a user-provisioned or installer-provisioned infrastructure installation on the x86_64 architecture. You must use Red Hat Enterprise Linux CoreOS (RHCOS) machines for the control plane machines in your cluster.

If you choose to use RHEL compute machines in your cluster, you are responsible for all operating system life cycle management and maintenance. You must perform system updates, apply patches, and complete all other required tasks.

For installer-provisioned infrastructure clusters, you must manually add RHEL compute machines because automatic scaling in installer-provisioned infrastructure clusters adds Red Hat Enterprise Linux CoreOS (RHCOS) compute machines by default.

Important
  • Because removing OpenShift Container Platform from a machine in the cluster requires destroying the operating system, you must use dedicated hardware for any RHEL machines that you add to the cluster.
  • Swap memory is disabled on all RHEL machines that you add to your OpenShift Container Platform cluster. You cannot enable swap memory on these machines.

5.1.2. System requirements for RHEL compute nodes

The Red Hat Enterprise Linux (RHEL) compute machine hosts in your OpenShift Container Platform environment must meet the following minimum hardware specifications and system-level requirements:

  • You must have an active OpenShift Container Platform subscription on your Red Hat account. If you do not, contact your sales representative for more information.
  • Production environments must provide compute machines to support your expected workloads. As a cluster administrator, you must calculate the expected workload and add about 10% for overhead. For production environments, allocate enough resources so that a node host failure does not affect your maximum capacity.
  • Each system must meet the following hardware requirements:

    • Physical or virtual system, or an instance running on a public or private IaaS.
    • Base OS: RHEL 8.6 and later with "Minimal" installation option.

      Important

      Adding RHEL 7 compute machines to an OpenShift Container Platform cluster is not supported.

      If you have RHEL 7 compute machines that were previously supported in a past OpenShift Container Platform version, you cannot upgrade them to RHEL 8. You must deploy new RHEL 8 hosts, and the old RHEL 7 hosts should be removed. See the "Deleting nodes" section for more information.

      For the most recent list of major functionality that has been deprecated or removed within OpenShift Container Platform, refer to the Deprecated and removed features section of the OpenShift Container Platform release notes.

    • If you deployed OpenShift Container Platform in FIPS mode, you must enable FIPS on the RHEL machine before you boot it. See Installing a RHEL 8 system with FIPS mode enabled in the RHEL 8 documentation.

      Important

      To enable FIPS mode for your cluster, you must run the installation program from a Red Hat Enterprise Linux (RHEL) computer configured to operate in FIPS mode. For more information about configuring FIPS mode on RHEL, see Switching RHEL to FIPS mode.

      When running Red Hat Enterprise Linux (RHEL) or Red Hat Enterprise Linux CoreOS (RHCOS) booted in FIPS mode, OpenShift Container Platform core components use the RHEL cryptographic libraries that have been submitted to NIST for FIPS 140-2/140-3 Validation on only the x86_64, ppc64le, and s390x architectures.

    • NetworkManager 1.0 or later.
    • 1 vCPU.
    • Minimum 8 GB RAM.
    • Minimum 15 GB hard disk space for the file system containing /var/.
    • Minimum 1 GB hard disk space for the file system containing /usr/local/bin/.
    • Minimum 1 GB hard disk space for the file system containing its temporary directory. The temporary system directory is determined according to the rules defined in the tempfile module in the Python standard library.
  • Each system must meet any additional requirements for your system provider. For example, if you installed your cluster on VMware vSphere, your disks must be configured according to its storage guidelines and the disk.enableUUID=true attribute must be set.
  • Each system must be able to access the cluster’s API endpoints by using DNS-resolvable hostnames. Any network security access control that is in place must allow system access to the cluster’s API service endpoints.
  • For clusters installed on Microsoft Azure:

    • Ensure the system includes the hardware requirement of a Standard_D8s_v3 virtual machine.
    • Enable Accelerated Networking. Accelerated Networking uses single root I/O virtualization (SR-IOV) to provide Microsoft Azure VMs with a more direct path to the switch.
5.1.2.1. Certificate signing requests management

Because your cluster has limited access to automatic machine management when you use infrastructure that you provision, you must provide a mechanism for approving cluster certificate signing requests (CSRs) after installation. The kube-controller-manager only approves the kubelet client CSRs. The machine-approver cannot guarantee the validity of a serving certificate that is requested by using kubelet credentials because it cannot confirm that the correct machine issued the request. You must determine and implement a method of verifying the validity of the kubelet serving certificate requests and approving them.

5.1.3. Preparing the machine to run the playbook

Before you can add compute machines that use Red Hat Enterprise Linux (RHEL) as the operating system to an OpenShift Container Platform 4.17 cluster, you must prepare a RHEL 8 machine to run an Ansible playbook that adds the new node to the cluster. This machine is not part of the cluster but must be able to access it.

Prerequisites

  • Install the OpenShift CLI (oc) on the machine that you run the playbook on.
  • Log in as a user with cluster-admin permission.

Procedure

  1. Ensure that the kubeconfig file for the cluster and the installation program that you used to install the cluster are on the RHEL 8 machine. One way to accomplish this is to use the same machine that you used to install the cluster.
  2. Configure the machine to access all of the RHEL hosts that you plan to use as compute machines. You can use any method that your company allows, including a bastion with an SSH proxy or a VPN.
  3. Configure a user on the machine that you run the playbook on that has SSH access to all of the RHEL hosts.

    Important

    If you use SSH key-based authentication, you must manage the key with an SSH agent.

  4. If you have not already done so, register the machine with RHSM and attach a pool with an OpenShift subscription to it:

    1. Register the machine with RHSM:

      # subscription-manager register --username=<user_name> --password=<password>
    2. Pull the latest subscription data from RHSM:

      # subscription-manager refresh
    3. List the available subscriptions:

      # subscription-manager list --available --matches '*OpenShift*'
    4. In the output for the previous command, find the pool ID for an OpenShift Container Platform subscription and attach it:

      # subscription-manager attach --pool=<pool_id>
  5. Enable the repositories required by OpenShift Container Platform 4.17:

    # subscription-manager repos \
        --enable="rhel-8-for-x86_64-baseos-rpms" \
        --enable="rhel-8-for-x86_64-appstream-rpms" \
        --enable="rhocp-4.17-for-rhel-8-x86_64-rpms"
  6. Install the required packages, including openshift-ansible:

    # yum install openshift-ansible openshift-clients jq

    The openshift-ansible package provides installation program utilities and pulls in other packages that you require to add a RHEL compute node to your cluster, such as Ansible, playbooks, and related configuration files. The openshift-clients provides the oc CLI, and the jq package improves the display of JSON output on your command line.

5.1.4. Preparing a RHEL compute node

Before you add a Red Hat Enterprise Linux (RHEL) machine to your OpenShift Container Platform cluster, you must register each host with Red Hat Subscription Manager (RHSM), attach an active OpenShift Container Platform subscription, and enable the required repositories.

  1. On each host, register with RHSM:

    # subscription-manager register --username=<user_name> --password=<password>
  2. Pull the latest subscription data from RHSM:

    # subscription-manager refresh
  3. List the available subscriptions:

    # subscription-manager list --available --matches '*OpenShift*'
  4. In the output for the previous command, find the pool ID for an OpenShift Container Platform subscription and attach it:

    # subscription-manager attach --pool=<pool_id>
  5. Disable all yum repositories:

    1. Disable all the enabled RHSM repositories:

      # subscription-manager repos --disable="*"
    2. List the remaining yum repositories and note their names under repo id, if any:

      # yum repolist
    3. Use yum-config-manager to disable the remaining yum repositories:

      # yum-config-manager --disable <repo_id>

      Alternatively, disable all repositories:

      # yum-config-manager --disable \*

      Note that this might take a few minutes if you have a large number of available repositories

  6. Enable only the repositories required by OpenShift Container Platform 4.17:

    # subscription-manager repos \
        --enable="rhel-8-for-x86_64-baseos-rpms" \
        --enable="rhel-8-for-x86_64-appstream-rpms" \
        --enable="rhocp-4.17-for-rhel-8-x86_64-rpms" \
        --enable="fast-datapath-for-rhel-8-x86_64-rpms"
  7. Stop and disable firewalld on the host:

    # systemctl disable --now firewalld.service
    Note

    You must not enable firewalld later. If you do, you cannot access OpenShift Container Platform logs on the worker.

5.1.5. Adding a RHEL compute machine to your cluster

You can add compute machines that use Red Hat Enterprise Linux as the operating system to an OpenShift Container Platform 4.17 cluster.

Prerequisites

  • You installed the required packages and performed the necessary configuration on the machine that you run the playbook on.
  • You prepared the RHEL hosts for installation.

Procedure

Perform the following steps on the machine that you prepared to run the playbook:

  1. Create an Ansible inventory file that is named /<path>/inventory/hosts that defines your compute machine hosts and required variables:

    [all:vars]
    ansible_user=root 1
    #ansible_become=True 2
    
    openshift_kubeconfig_path="~/.kube/config" 3
    
    [new_workers] 4
    mycluster-rhel8-0.example.com
    mycluster-rhel8-1.example.com
    1
    Specify the user name that runs the Ansible tasks on the remote compute machines.
    2
    If you do not specify root for the ansible_user, you must set ansible_become to True and assign the user sudo permissions.
    3
    Specify the path and file name of the kubeconfig file for your cluster.
    4
    List each RHEL machine to add to your cluster. You must provide the fully-qualified domain name for each host. This name is the hostname that the cluster uses to access the machine, so set the correct public or private name to access the machine.
  2. Navigate to the Ansible playbook directory:

    $ cd /usr/share/ansible/openshift-ansible
  3. Run the playbook:

    $ ansible-playbook -i /<path>/inventory/hosts playbooks/scaleup.yml 1
    1
    For <path>, specify the path to the Ansible inventory file that you created.

5.1.6. Required parameters for the Ansible hosts file

You must define the following parameters in the Ansible hosts file before you add Red Hat Enterprise Linux (RHEL) compute machines to your cluster.

ParameterDescriptionValues

ansible_user

The SSH user that allows SSH-based authentication without requiring a password. If you use SSH key-based authentication, then you must manage the key with an SSH agent.

A user name on the system. The default value is root.

ansible_become

If the values of ansible_user is not root, you must set ansible_become to True, and the user that you specify as the ansible_user must be configured for passwordless sudo access.

True. If the value is not True, do not specify and define this parameter.

openshift_kubeconfig_path

Specifies a path and file name to a local directory that contains the kubeconfig file for your cluster.

The path and name of the configuration file.

5.1.7. Optional: Removing RHCOS compute machines from a cluster

After you add the Red Hat Enterprise Linux (RHEL) compute machines to your cluster, you can optionally remove the Red Hat Enterprise Linux CoreOS (RHCOS) compute machines to free up resources.

Prerequisites

  • You have added RHEL compute machines to your cluster.

Procedure

  1. View the list of machines and record the node names of the RHCOS compute machines:

    $ oc get nodes -o wide
  2. For each RHCOS compute machine, delete the node:

    1. Mark the node as unschedulable by running the oc adm cordon command:

      $ oc adm cordon <node_name> 1
      1
      Specify the node name of one of the RHCOS compute machines.
    2. Drain all the pods from the node:

      $ oc adm drain <node_name> --force --delete-emptydir-data --ignore-daemonsets 1
      1
      Specify the node name of the RHCOS compute machine that you isolated.
    3. Delete the node:

      $ oc delete nodes <node_name> 1
      1
      Specify the node name of the RHCOS compute machine that you drained.
  3. Review the list of compute machines to ensure that only the RHEL nodes remain:

    $ oc get nodes -o wide
  4. Remove the RHCOS machines from the load balancer for your cluster’s compute machines. You can delete the virtual machines or reimage the physical hardware for the RHCOS compute machines.

5.2. Adding RHCOS compute machines to an OpenShift Container Platform cluster

You can add more Red Hat Enterprise Linux CoreOS (RHCOS) compute machines to your OpenShift Container Platform cluster on bare metal.

Before you add more compute machines to a cluster that you installed on bare metal infrastructure, you must create RHCOS machines for it to use. You can either use an ISO image or network PXE booting to create the machines.

5.2.1. Prerequisites

  • You installed a cluster on bare metal.
  • You have installation media and Red Hat Enterprise Linux CoreOS (RHCOS) images that you used to create your cluster. If you do not have these files, you must obtain them by following the instructions in the installation procedure.

5.2.2. Creating RHCOS machines using an ISO image

You can create more Red Hat Enterprise Linux CoreOS (RHCOS) compute machines for your bare metal cluster by using an ISO image to create the machines.

Prerequisites

  • Obtain the URL of the Ignition config file for the compute machines for your cluster. You uploaded this file to your HTTP server during installation.
  • You must have the OpenShift CLI (oc) installed.

Procedure

  1. Extract the Ignition config file from the cluster by running the following command:

    $ oc extract -n openshift-machine-api secret/worker-user-data-managed --keys=userData --to=- > worker.ign
  2. Upload the worker.ign Ignition config file you exported from your cluster to your HTTP server. Note the URLs of these files.
  3. You can validate that the ignition files are available on the URLs. The following example gets the Ignition config files for the compute node:

    $ curl -k http://<HTTP_server>/worker.ign
  4. You can access the ISO image for booting your new machine by running to following command:

    RHCOS_VHD_ORIGIN_URL=$(oc -n openshift-machine-config-operator get configmap/coreos-bootimages -o jsonpath='{.data.stream}' | jq -r '.architectures.<architecture>.artifacts.metal.formats.iso.disk.location')
  5. Use the ISO file to install RHCOS on more compute machines. Use the same method that you used when you created machines before you installed the cluster:

    • Burn the ISO image to a disk and boot it directly.
    • Use ISO redirection with a LOM interface.
  6. Boot the RHCOS ISO image without specifying any options, or interrupting the live boot sequence. Wait for the installer to boot into a shell prompt in the RHCOS live environment.

    Note

    You can interrupt the RHCOS installation boot process to add kernel arguments. However, for this ISO procedure you must use the coreos-installer command as outlined in the following steps, instead of adding kernel arguments.

  7. Run the coreos-installer command and specify the options that meet your installation requirements. At a minimum, you must specify the URL that points to the Ignition config file for the node type, and the device that you are installing to:

    $ sudo coreos-installer install --ignition-url=http://<HTTP_server>/<node_type>.ign <device> --ignition-hash=sha512-<digest> 12
    1
    You must run the coreos-installer command by using sudo, because the core user does not have the required root privileges to perform the installation.
    2
    The --ignition-hash option is required when the Ignition config file is obtained through an HTTP URL to validate the authenticity of the Ignition config file on the cluster node. <digest> is the Ignition config file SHA512 digest obtained in a preceding step.
    Note

    If you want to provide your Ignition config files through an HTTPS server that uses TLS, you can add the internal certificate authority (CA) to the system trust store before running coreos-installer.

    The following example initializes a bootstrap node installation to the /dev/sda device. The Ignition config file for the bootstrap node is obtained from an HTTP web server with the IP address 192.168.1.2:

    $ sudo coreos-installer install --ignition-url=http://192.168.1.2:80/installation_directory/bootstrap.ign /dev/sda --ignition-hash=sha512-a5a2d43879223273c9b60af66b44202a1d1248fc01cf156c46d4a79f552b6bad47bc8cc78ddf0116e80c59d2ea9e32ba53bc807afbca581aa059311def2c3e3b
  8. Monitor the progress of the RHCOS installation on the console of the machine.

    Important

    Ensure that the installation is successful on each node before commencing with the OpenShift Container Platform installation. Observing the installation process can also help to determine the cause of RHCOS installation issues that might arise.

  9. Continue to create more compute machines for your cluster.

5.2.3. Creating RHCOS machines by PXE or iPXE booting

You can create more Red Hat Enterprise Linux CoreOS (RHCOS) compute machines for your bare metal cluster by using PXE or iPXE booting.

Prerequisites

  • Obtain the URL of the Ignition config file for the compute machines for your cluster. You uploaded this file to your HTTP server during installation.
  • Obtain the URLs of the RHCOS ISO image, compressed metal BIOS, kernel, and initramfs files that you uploaded to your HTTP server during cluster installation.
  • You have access to the PXE booting infrastructure that you used to create the machines for your OpenShift Container Platform cluster during installation. The machines must boot from their local disks after RHCOS is installed on them.
  • If you use UEFI, you have access to the grub.conf file that you modified during OpenShift Container Platform installation.

Procedure

  1. Confirm that your PXE or iPXE installation for the RHCOS images is correct.

    • For PXE:

      DEFAULT pxeboot
      TIMEOUT 20
      PROMPT 0
      LABEL pxeboot
          KERNEL http://<HTTP_server>/rhcos-<version>-live-kernel-<architecture> 1
          APPEND initrd=http://<HTTP_server>/rhcos-<version>-live-initramfs.<architecture>.img coreos.inst.install_dev=/dev/sda coreos.inst.ignition_url=http://<HTTP_server>/worker.ign coreos.live.rootfs_url=http://<HTTP_server>/rhcos-<version>-live-rootfs.<architecture>.img 2
      1
      Specify the location of the live kernel file that you uploaded to your HTTP server.
      2
      Specify locations of the RHCOS files that you uploaded to your HTTP server. The initrd parameter value is the location of the live initramfs file, the coreos.inst.ignition_url parameter value is the location of the worker Ignition config file, and the coreos.live.rootfs_url parameter value is the location of the live rootfs file. The coreos.inst.ignition_url and coreos.live.rootfs_url parameters only support HTTP and HTTPS.
      Note

      This configuration does not enable serial console access on machines with a graphical console. To configure a different console, add one or more console= arguments to the APPEND line. For example, add console=tty0 console=ttyS0 to set the first PC serial port as the primary console and the graphical console as a secondary console. For more information, see How does one set up a serial terminal and/or console in Red Hat Enterprise Linux?.

    • For iPXE (x86_64 + aarch64):

      kernel http://<HTTP_server>/rhcos-<version>-live-kernel-<architecture> initrd=main coreos.live.rootfs_url=http://<HTTP_server>/rhcos-<version>-live-rootfs.<architecture>.img coreos.inst.install_dev=/dev/sda coreos.inst.ignition_url=http://<HTTP_server>/worker.ign 1 2
      initrd --name main http://<HTTP_server>/rhcos-<version>-live-initramfs.<architecture>.img 3
      boot
      1
      Specify the locations of the RHCOS files that you uploaded to your HTTP server. The kernel parameter value is the location of the kernel file, the initrd=main argument is needed for booting on UEFI systems, the coreos.live.rootfs_url parameter value is the location of the rootfs file, and the coreos.inst.ignition_url parameter value is the location of the worker Ignition config file.
      2
      If you use multiple NICs, specify a single interface in the ip option. For example, to use DHCP on a NIC that is named eno1, set ip=eno1:dhcp.
      3
      Specify the location of the initramfs file that you uploaded to your HTTP server.
      Note

      This configuration does not enable serial console access on machines with a graphical console To configure a different console, add one or more console= arguments to the kernel line. For example, add console=tty0 console=ttyS0 to set the first PC serial port as the primary console and the graphical console as a secondary console. For more information, see How does one set up a serial terminal and/or console in Red Hat Enterprise Linux? and "Enabling the serial console for PXE and ISO installation" in the "Advanced RHCOS installation configuration" section.

      Note

      To network boot the CoreOS kernel on aarch64 architecture, you need to use a version of iPXE build with the IMAGE_GZIP option enabled. See IMAGE_GZIP option in iPXE.

    • For PXE (with UEFI and GRUB as second stage) on aarch64:

      menuentry 'Install CoreOS' {
          linux rhcos-<version>-live-kernel-<architecture>  coreos.live.rootfs_url=http://<HTTP_server>/rhcos-<version>-live-rootfs.<architecture>.img coreos.inst.install_dev=/dev/sda coreos.inst.ignition_url=http://<HTTP_server>/worker.ign 1 2
          initrd rhcos-<version>-live-initramfs.<architecture>.img 3
      }
      1
      Specify the locations of the RHCOS files that you uploaded to your HTTP/TFTP server. The kernel parameter value is the location of the kernel file on your TFTP server. The coreos.live.rootfs_url parameter value is the location of the rootfs file, and the coreos.inst.ignition_url parameter value is the location of the worker Ignition config file on your HTTP Server.
      2
      If you use multiple NICs, specify a single interface in the ip option. For example, to use DHCP on a NIC that is named eno1, set ip=eno1:dhcp.
      3
      Specify the location of the initramfs file that you uploaded to your TFTP server.
  2. Use the PXE or iPXE infrastructure to create the required compute machines for your cluster.

5.2.4. Approving the certificate signing requests for your machines

When you add machines to a cluster, two pending certificate signing requests (CSRs) are generated for each machine that you added. You must confirm that these CSRs are approved or, if necessary, approve them yourself. The client requests must be approved first, followed by the server requests.

Prerequisites

  • You added machines to your cluster.

Procedure

  1. Confirm that the cluster recognizes the machines:

    $ oc get nodes

    Example output

    NAME      STATUS    ROLES   AGE  VERSION
    master-0  Ready     master  63m  v1.30.3
    master-1  Ready     master  63m  v1.30.3
    master-2  Ready     master  64m  v1.30.3

    The output lists all of the machines that you created.

    Note

    The preceding output might not include the compute nodes, also known as worker nodes, until some CSRs are approved.

  2. Review the pending CSRs and ensure that you see the client requests with the Pending or Approved status for each machine that you added to the cluster:

    $ oc get csr

    Example output

    NAME        AGE     REQUESTOR                                                                   CONDITION
    csr-8b2br   15m     system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending
    csr-8vnps   15m     system:serviceaccount:openshift-machine-config-operator:node-bootstrapper   Pending
    ...

    In this example, two machines are joining the cluster. You might see more approved CSRs in the list.

  3. If the CSRs were not approved, after all of the pending CSRs for the machines you added are in Pending status, approve the CSRs for your cluster machines:

    Note

    Because the CSRs rotate automatically, approve your CSRs within an hour of adding the machines to the cluster. If you do not approve them within an hour, the certificates will rotate, and more than two certificates will be present for each node. You must approve all of these certificates. After the client CSR is approved, the Kubelet creates a secondary CSR for the serving certificate, which requires manual approval. Then, subsequent serving certificate renewal requests are automatically approved by the machine-approver if the Kubelet requests a new certificate with identical parameters.

    Note

    For clusters running on platforms that are not machine API enabled, such as bare metal and other user-provisioned infrastructure, you must implement a method of automatically approving the kubelet serving certificate requests (CSRs). If a request is not approved, then the oc exec, oc rsh, and oc logs commands cannot succeed, because a serving certificate is required when the API server connects to the kubelet. Any operation that contacts the Kubelet endpoint requires this certificate approval to be in place. The method must watch for new CSRs, confirm that the CSR was submitted by the node-bootstrapper service account in the system:node or system:admin groups, and confirm the identity of the node.

    • To approve them individually, run the following command for each valid CSR:

      $ oc adm certificate approve <csr_name> 1
      1
      <csr_name> is the name of a CSR from the list of current CSRs.
    • To approve all pending CSRs, run the following command:

      $ oc get csr -o go-template='{{range .items}}{{if not .status}}{{.metadata.name}}{{"\n"}}{{end}}{{end}}' | xargs --no-run-if-empty oc adm certificate approve
      Note

      Some Operators might not become available until some CSRs are approved.

  4. Now that your client requests are approved, you must review the server requests for each machine that you added to the cluster:

    $ oc get csr

    Example output

    NAME        AGE     REQUESTOR                                                                   CONDITION
    csr-bfd72   5m26s   system:node:ip-10-0-50-126.us-east-2.compute.internal                       Pending
    csr-c57lv   5m26s   system:node:ip-10-0-95-157.us-east-2.compute.internal                       Pending
    ...

  5. If the remaining CSRs are not approved, and are in the Pending status, approve the CSRs for your cluster machines:

    • To approve them individually, run the following command for each valid CSR:

      $ oc adm certificate approve <csr_name> 1
      1
      <csr_name> is the name of a CSR from the list of current CSRs.
    • To approve all pending CSRs, run the following command:

      $ oc get csr -o go-template='{{range .items}}{{if not .status}}{{.metadata.name}}{{"\n"}}{{end}}{{end}}' | xargs oc adm certificate approve
  6. After all client and server CSRs have been approved, the machines have the Ready status. Verify this by running the following command:

    $ oc get nodes

    Example output

    NAME      STATUS    ROLES   AGE  VERSION
    master-0  Ready     master  73m  v1.30.3
    master-1  Ready     master  73m  v1.30.3
    master-2  Ready     master  74m  v1.30.3
    worker-0  Ready     worker  11m  v1.30.3
    worker-1  Ready     worker  11m  v1.30.3

    Note

    It can take a few minutes after approval of the server CSRs for the machines to transition to the Ready status.

Additional information

5.2.5. Adding a new RHCOS worker node with a custom /var partition in AWS

OpenShift Container Platform supports partitioning devices during installation by using machine configs that are processed during the bootstrap. However, if you use /var partitioning, the device name must be determined at installation and cannot be changed. You cannot add different instance types as nodes if they have a different device naming schema. For example, if you configured the /var partition with the default AWS device name for m4.large instances, dev/xvdb, you cannot directly add an AWS m5.large instance, as m5.large instances use a /dev/nvme1n1 device by default. The device might fail to partition due to the different naming schema.

The procedure in this section shows how to add a new Red Hat Enterprise Linux CoreOS (RHCOS) compute node with an instance that uses a different device name from what was configured at installation. You create a custom user data secret and configure a new compute machine set. These steps are specific to an AWS cluster. The principles apply to other cloud deployments also. However, the device naming schema is different for other deployments and should be determined on a per-case basis.

Procedure

  1. On a command line, change to the openshift-machine-api namespace:

    $ oc project openshift-machine-api
  2. Create a new secret from the worker-user-data secret:

    1. Export the userData section of the secret to a text file:

      $ oc get secret worker-user-data --template='{{index .data.userData | base64decode}}' | jq > userData.txt
    2. Edit the text file to add the storage, filesystems, and systemd stanzas for the partitions you want to use for the new node. You can specify any Ignition configuration parameters as needed.

      Note

      Do not change the values in the ignition stanza.

      {
        "ignition": {
          "config": {
            "merge": [
              {
                "source": "https:...."
              }
            ]
          },
          "security": {
            "tls": {
              "certificateAuthorities": [
                {
                  "source": "data:text/plain;charset=utf-8;base64,.....=="
                }
              ]
            }
          },
          "version": "3.2.0"
        },
        "storage": {
          "disks": [
            {
              "device": "/dev/nvme1n1", 1
              "partitions": [
                {
                  "label": "var",
                  "sizeMiB": 50000, 2
                  "startMiB": 0 3
                }
              ]
            }
          ],
          "filesystems": [
            {
              "device": "/dev/disk/by-partlabel/var", 4
              "format": "xfs", 5
              "path": "/var" 6
            }
          ]
        },
        "systemd": {
          "units": [ 7
            {
              "contents": "[Unit]\nBefore=local-fs.target\n[Mount]\nWhere=/var\nWhat=/dev/disk/by-partlabel/var\nOptions=defaults,pquota\n[Install]\nWantedBy=local-fs.target\n",
              "enabled": true,
              "name": "var.mount"
            }
          ]
        }
      }
      1
      Specifies an absolute path to the AWS block device.
      2
      Specifies the size of the data partition in Mebibytes.
      3
      Specifies the start of the partition in Mebibytes. When adding a data partition to the boot disk, a minimum value of 25000 MB (Mebibytes) is recommended. The root file system is automatically resized to fill all available space up to the specified offset. If no value is specified, or if the specified value is smaller than the recommended minimum, the resulting root file system will be too small, and future reinstalls of RHCOS might overwrite the beginning of the data partition.
      4
      Specifies an absolute path to the /var partition.
      5
      Specifies the filesystem format.
      6
      Specifies the mount-point of the filesystem while Ignition is running relative to where the root filesystem will be mounted. This is not necessarily the same as where it should be mounted in the real root, but it is encouraged to make it the same.
      7
      Defines a systemd mount unit that mounts the /dev/disk/by-partlabel/var device to the /var partition.
    3. Extract the disableTemplating section from the work-user-data secret to a text file:

      $ oc get secret worker-user-data --template='{{index .data.disableTemplating | base64decode}}' | jq > disableTemplating.txt
    4. Create the new user data secret file from the two text files. This user data secret passes the additional node partition information in the userData.txt file to the newly created node.

      $ oc create secret generic worker-user-data-x5 --from-file=userData=userData.txt --from-file=disableTemplating=disableTemplating.txt
  3. Create a new compute machine set for the new node:

    1. Create a new compute machine set YAML file, similar to the following, which is configured for AWS. Add the required partitions and the newly-created user data secret:

      Tip

      Use an existing compute machine set as a template and change the parameters as needed for the new node.

      apiVersion: machine.openshift.io/v1beta1
      kind: MachineSet
      metadata:
        labels:
          machine.openshift.io/cluster-api-cluster: auto-52-92tf4
        name: worker-us-east-2-nvme1n1 1
        namespace: openshift-machine-api
      spec:
        replicas: 1
        selector:
          matchLabels:
            machine.openshift.io/cluster-api-cluster: auto-52-92tf4
            machine.openshift.io/cluster-api-machineset: auto-52-92tf4-worker-us-east-2b
        template:
          metadata:
            labels:
              machine.openshift.io/cluster-api-cluster: auto-52-92tf4
              machine.openshift.io/cluster-api-machine-role: worker
              machine.openshift.io/cluster-api-machine-type: worker
              machine.openshift.io/cluster-api-machineset: auto-52-92tf4-worker-us-east-2b
          spec:
            metadata: {}
            providerSpec:
              value:
                ami:
                  id: ami-0c2dbd95931a
                apiVersion: awsproviderconfig.openshift.io/v1beta1
                blockDevices:
                - DeviceName: /dev/nvme1n1 2
                  ebs:
                    encrypted: true
                    iops: 0
                    volumeSize: 120
                    volumeType: gp2
                - DeviceName: /dev/nvme1n2 3
                  ebs:
                    encrypted: true
                    iops: 0
                    volumeSize: 50
                    volumeType: gp2
                credentialsSecret:
                  name: aws-cloud-credentials
                deviceIndex: 0
                iamInstanceProfile:
                  id: auto-52-92tf4-worker-profile
                instanceType: m6i.large
                kind: AWSMachineProviderConfig
                metadata:
                  creationTimestamp: null
                placement:
                  availabilityZone: us-east-2b
                  region: us-east-2
                securityGroups:
                - filters:
                  - name: tag:Name
                    values:
                    - auto-52-92tf4-worker-sg
                subnet:
                  id: subnet-07a90e5db1
                tags:
                - name: kubernetes.io/cluster/auto-52-92tf4
                  value: owned
                userDataSecret:
                  name: worker-user-data-x5 4
      1
      Specifies a name for the new node.
      2
      Specifies an absolute path to the AWS block device, here an encrypted EBS volume.
      3
      Optional. Specifies an additional EBS volume.
      4
      Specifies the user data secret file.
    2. Create the compute machine set:

      $ oc create -f <file-name>.yaml

      The machines might take a few moments to become available.

  4. Verify that the new partition and nodes are created:

    1. Verify that the compute machine set is created:

      $ oc get machineset

      Example output

      NAME                                               DESIRED   CURRENT   READY   AVAILABLE   AGE
      ci-ln-2675bt2-76ef8-bdgsc-worker-us-east-1a        1         1         1       1           124m
      ci-ln-2675bt2-76ef8-bdgsc-worker-us-east-1b        2         2         2       2           124m
      worker-us-east-2-nvme1n1                           1         1         1       1           2m35s 1

      1
      This is the new compute machine set.
    2. Verify that the new node is created:

      $ oc get nodes

      Example output

      NAME                           STATUS   ROLES    AGE     VERSION
      ip-10-0-128-78.ec2.internal    Ready    worker   117m    v1.30.3
      ip-10-0-146-113.ec2.internal   Ready    master   127m    v1.30.3
      ip-10-0-153-35.ec2.internal    Ready    worker   118m    v1.30.3
      ip-10-0-176-58.ec2.internal    Ready    master   126m    v1.30.3
      ip-10-0-217-135.ec2.internal   Ready    worker   2m57s   v1.30.3 1
      ip-10-0-225-248.ec2.internal   Ready    master   127m    v1.30.3
      ip-10-0-245-59.ec2.internal    Ready    worker   116m    v1.30.3

      1
      This is new new node.
    3. Verify that the custom /var partition is created on the new node:

      $ oc debug node/<node-name> -- chroot /host lsblk

      For example:

      $ oc debug node/ip-10-0-217-135.ec2.internal -- chroot /host lsblk

      Example output

      NAME        MAJ:MIN  RM  SIZE RO TYPE MOUNTPOINT
      nvme0n1     202:0    0   120G  0 disk
      |-nvme0n1p1 202:1    0     1M  0 part
      |-nvme0n1p2 202:2    0   127M  0 part
      |-nvme0n1p3 202:3    0   384M  0 part /boot
      `-nvme0n1p4 202:4    0 119.5G  0 part /sysroot
      nvme1n1     202:16   0    50G  0 disk
      `-nvme1n1p1 202:17   0  48.8G  0 part /var 1

      1
      The nvme1n1 device is mounted to the /var partition.

Additional resources

  • For more information on how OpenShift Container Platform uses disk partitioning, see Disk partitioning.

5.3. Deploying machine health checks

Understand and deploy machine health checks.

Important

You can use the advanced machine management and scaling capabilities only in clusters where the Machine API is operational. Clusters with user-provisioned infrastructure require additional validation and configuration to use the Machine API.

Clusters with the infrastructure platform type none cannot use the Machine API. This limitation applies even if the compute machines that are attached to the cluster are installed on a platform that supports the feature. This parameter cannot be changed after installation.

To view the platform type for your cluster, run the following command:

$ oc get infrastructure cluster -o jsonpath='{.status.platform}'

5.3.1. About machine health checks

Note

You can only apply a machine health check to machines that are managed by compute machine sets or control plane machine sets.

To monitor machine health, create a resource to define the configuration for a controller. Set a condition to check, such as staying in the NotReady status for five minutes or displaying a permanent condition in the node-problem-detector, and a label for the set of machines to monitor.

The controller that observes a MachineHealthCheck resource checks for the defined condition. If a machine fails the health check, the machine is automatically deleted and one is created to take its place. When a machine is deleted, you see a machine deleted event.

To limit disruptive impact of the machine deletion, the controller drains and deletes only one node at a time. If there are more unhealthy machines than the maxUnhealthy threshold allows for in the targeted pool of machines, remediation stops and therefore enables manual intervention.

Note

Consider the timeouts carefully, accounting for workloads and requirements.

  • Long timeouts can result in long periods of downtime for the workload on the unhealthy machine.
  • Too short timeouts can result in a remediation loop. For example, the timeout for checking the NotReady status must be long enough to allow the machine to complete the startup process.

To stop the check, remove the resource.

5.3.1.1. Limitations when deploying machine health checks

There are limitations to consider before deploying a machine health check:

  • Only machines owned by a machine set are remediated by a machine health check.
  • If the node for a machine is removed from the cluster, a machine health check considers the machine to be unhealthy and remediates it immediately.
  • If the corresponding node for a machine does not join the cluster after the nodeStartupTimeout, the machine is remediated.
  • A machine is remediated immediately if the Machine resource phase is Failed.

Additional resources

5.3.2. Sample MachineHealthCheck resource

The MachineHealthCheck resource for all cloud-based installation types, and other than bare metal, resembles the following YAML file:

apiVersion: machine.openshift.io/v1beta1
kind: MachineHealthCheck
metadata:
  name: example 1
  namespace: openshift-machine-api
spec:
  selector:
    matchLabels:
      machine.openshift.io/cluster-api-machine-role: <role> 2
      machine.openshift.io/cluster-api-machine-type: <role> 3
      machine.openshift.io/cluster-api-machineset: <cluster_name>-<label>-<zone> 4
  unhealthyConditions:
  - type:    "Ready"
    timeout: "300s" 5
    status: "False"
  - type:    "Ready"
    timeout: "300s" 6
    status: "Unknown"
  maxUnhealthy: "40%" 7
  nodeStartupTimeout: "10m" 8
1
Specify the name of the machine health check to deploy.
2 3
Specify a label for the machine pool that you want to check.
4
Specify the machine set to track in <cluster_name>-<label>-<zone> format. For example, prod-node-us-east-1a.
5 6
Specify the timeout duration for a node condition. If a condition is met for the duration of the timeout, the machine will be remediated. Long timeouts can result in long periods of downtime for a workload on an unhealthy machine.
7
Specify the amount of machines allowed to be concurrently remediated in the targeted pool. This can be set as a percentage or an integer. If the number of unhealthy machines exceeds the limit set by maxUnhealthy, remediation is not performed.
8
Specify the timeout duration that a machine health check must wait for a node to join the cluster before a machine is determined to be unhealthy.
Note

The matchLabels are examples only; you must map your machine groups based on your specific needs.

5.3.2.1. Short-circuiting machine health check remediation

Short-circuiting ensures that machine health checks remediate machines only when the cluster is healthy. Short-circuiting is configured through the maxUnhealthy field in the MachineHealthCheck resource.

If the user defines a value for the maxUnhealthy field, before remediating any machines, the MachineHealthCheck compares the value of maxUnhealthy with the number of machines within its target pool that it has determined to be unhealthy. Remediation is not performed if the number of unhealthy machines exceeds the maxUnhealthy limit.

Important

If maxUnhealthy is not set, the value defaults to 100% and the machines are remediated regardless of the state of the cluster.

The appropriate maxUnhealthy value depends on the scale of the cluster you deploy and how many machines the MachineHealthCheck covers. For example, you can use the maxUnhealthy value to cover multiple compute machine sets across multiple availability zones so that if you lose an entire zone, your maxUnhealthy setting prevents further remediation within the cluster. In global Azure regions that do not have multiple availability zones, you can use availability sets to ensure high availability.

Important

If you configure a MachineHealthCheck resource for the control plane, set the value of maxUnhealthy to 1.

This configuration ensures that the machine health check takes no action when multiple control plane machines appear to be unhealthy. Multiple unhealthy control plane machines can indicate that the etcd cluster is degraded or that a scaling operation to replace a failed machine is in progress.

If the etcd cluster is degraded, manual intervention might be required. If a scaling operation is in progress, the machine health check should allow it to finish.

The maxUnhealthy field can be set as either an integer or percentage. There are different remediation implementations depending on the maxUnhealthy value.

5.3.2.1.1. Setting maxUnhealthy by using an absolute value

If maxUnhealthy is set to 2:

  • Remediation will be performed if 2 or fewer nodes are unhealthy
  • Remediation will not be performed if 3 or more nodes are unhealthy

These values are independent of how many machines are being checked by the machine health check.

5.3.2.1.2. Setting maxUnhealthy by using percentages

If maxUnhealthy is set to 40% and there are 25 machines being checked:

  • Remediation will be performed if 10 or fewer nodes are unhealthy
  • Remediation will not be performed if 11 or more nodes are unhealthy

If maxUnhealthy is set to 40% and there are 6 machines being checked:

  • Remediation will be performed if 2 or fewer nodes are unhealthy
  • Remediation will not be performed if 3 or more nodes are unhealthy
Note

The allowed number of machines is rounded down when the percentage of maxUnhealthy machines that are checked is not a whole number.

5.3.3. Creating a machine health check resource

You can create a MachineHealthCheck resource for machine sets in your cluster.

Note

You can only apply a machine health check to machines that are managed by compute machine sets or control plane machine sets.

Prerequisites

  • Install the oc command line interface.

Procedure

  1. Create a healthcheck.yml file that contains the definition of your machine health check.
  2. Apply the healthcheck.yml file to your cluster:

    $ oc apply -f healthcheck.yml

5.3.4. Scaling a compute machine set manually

To add or remove an instance of a machine in a compute machine set, you can manually scale the compute machine set.

This guidance is relevant to fully automated, installer-provisioned infrastructure installations. Customized, user-provisioned infrastructure installations do not have compute machine sets.

Prerequisites

  • Install an OpenShift Container Platform cluster and the oc command line.
  • Log in to oc as a user with cluster-admin permission.

Procedure

  1. View the compute machine sets that are in the cluster by running the following command:

    $ oc get machinesets.machine.openshift.io -n openshift-machine-api

    The compute machine sets are listed in the form of <clusterid>-worker-<aws-region-az>.

  2. View the compute machines that are in the cluster by running the following command:

    $ oc get machines.machine.openshift.io -n openshift-machine-api
  3. Set the annotation on the compute machine that you want to delete by running the following command:

    $ oc annotate machines.machine.openshift.io/<machine_name> -n openshift-machine-api machine.openshift.io/delete-machine="true"
  4. Scale the compute machine set by running one of the following commands:

    $ oc scale --replicas=2 machinesets.machine.openshift.io <machineset> -n openshift-machine-api

    Or:

    $ oc edit machinesets.machine.openshift.io <machineset> -n openshift-machine-api
    Tip

    You can alternatively apply the following YAML to scale the compute machine set:

    apiVersion: machine.openshift.io/v1beta1
    kind: MachineSet
    metadata:
      name: <machineset>
      namespace: openshift-machine-api
    spec:
      replicas: 2

    You can scale the compute machine set up or down. It takes several minutes for the new machines to be available.

    Important

    By default, the machine controller tries to drain the node that is backed by the machine until it succeeds. In some situations, such as with a misconfigured pod disruption budget, the drain operation might not be able to succeed. If the drain operation fails, the machine controller cannot proceed removing the machine.

    You can skip draining the node by annotating machine.openshift.io/exclude-node-draining in a specific machine.

Verification

  • Verify the deletion of the intended machine by running the following command:

    $ oc get machines.machine.openshift.io

5.3.5. Understanding the difference between compute machine sets and the machine config pool

MachineSet objects describe OpenShift Container Platform nodes with respect to the cloud or machine provider.

The MachineConfigPool object allows MachineConfigController components to define and provide the status of machines in the context of upgrades.

The MachineConfigPool object allows users to configure how upgrades are rolled out to the OpenShift Container Platform nodes in the machine config pool.

The NodeSelector object can be replaced with a reference to the MachineSet object.

5.4. Recommended node host practices

The OpenShift Container Platform node configuration file contains important options. For example, two parameters control the maximum number of pods that can be scheduled to a node: podsPerCore and maxPods.

When both options are in use, the lower of the two values limits the number of pods on a node. Exceeding these values can result in:

  • Increased CPU utilization.
  • Slow pod scheduling.
  • Potential out-of-memory scenarios, depending on the amount of memory in the node.
  • Exhausting the pool of IP addresses.
  • Resource overcommitting, leading to poor user application performance.
Important

In Kubernetes, a pod that is holding a single container actually uses two containers. The second container is used to set up networking prior to the actual container starting. Therefore, a system running 10 pods will actually have 20 containers running.

Note

Disk IOPS throttling from the cloud provider might have an impact on CRI-O and kubelet. They might get overloaded when there are large number of I/O intensive pods running on the nodes. It is recommended that you monitor the disk I/O on the nodes and use volumes with sufficient throughput for the workload.

The podsPerCore parameter sets the number of pods the node can run based on the number of processor cores on the node. For example, if podsPerCore is set to 10 on a node with 4 processor cores, the maximum number of pods allowed on the node will be 40.

kubeletConfig:
  podsPerCore: 10

Setting podsPerCore to 0 disables this limit. The default is 0. The value of the podsPerCore parameter cannot exceed the value of the maxPods parameter.

The maxPods parameter sets the number of pods the node can run to a fixed value, regardless of the properties of the node.

 kubeletConfig:
    maxPods: 250

5.4.1. Creating a KubeletConfig CRD to edit kubelet parameters

The kubelet configuration is currently serialized as an Ignition configuration, so it can be directly edited. However, there is also a new kubelet-config-controller added to the Machine Config Controller (MCC). This lets you use a KubeletConfig custom resource (CR) to edit the kubelet parameters.

Note

As the fields in the kubeletConfig object are passed directly to the kubelet from upstream Kubernetes, the kubelet validates those values directly. Invalid values in the kubeletConfig object might cause cluster nodes to become unavailable. For valid values, see the Kubernetes documentation.

Consider the following guidance:

  • Edit an existing KubeletConfig CR to modify existing settings or add new settings, instead of creating a CR for each change. It is recommended that you create a CR only to modify a different machine config pool, or for changes that are intended to be temporary, so that you can revert the changes.
  • Create one KubeletConfig CR for each machine config pool with all the config changes you want for that pool.
  • As needed, create multiple KubeletConfig CRs with a limit of 10 per cluster. For the first KubeletConfig CR, the Machine Config Operator (MCO) creates a machine config appended with kubelet. With each subsequent CR, the controller creates another kubelet machine config with a numeric suffix. For example, if you have a kubelet machine config with a -2 suffix, the next kubelet machine config is appended with -3.
Note

If you are applying a kubelet or container runtime config to a custom machine config pool, the custom role in the machineConfigSelector must match the name of the custom machine config pool.

For example, because the following custom machine config pool is named infra, the custom role must also be infra:

apiVersion: machineconfiguration.openshift.io/v1
kind: MachineConfigPool
metadata:
  name: infra
spec:
  machineConfigSelector:
    matchExpressions:
      - {key: machineconfiguration.openshift.io/role, operator: In, values: [worker,infra]}
# ...

If you want to delete the machine configs, delete them in reverse order to avoid exceeding the limit. For example, you delete the kubelet-3 machine config before deleting the kubelet-2 machine config.

Note

If you have a machine config with a kubelet-9 suffix, and you create another KubeletConfig CR, a new machine config is not created, even if there are fewer than 10 kubelet machine configs.

Example KubeletConfig CR

$ oc get kubeletconfig

NAME                AGE
set-max-pods        15m

Example showing a KubeletConfig machine config

$ oc get mc | grep kubelet

...
99-worker-generated-kubelet-1                  b5c5119de007945b6fe6fb215db3b8e2ceb12511   3.2.0             26m
...

The following procedure is an example to show how to configure the maximum number of pods per node on the worker nodes.

Prerequisites

  1. Obtain the label associated with the static MachineConfigPool CR for the type of node you want to configure. Perform one of the following steps:

    1. View the machine config pool:

      $ oc describe machineconfigpool <name>

      For example:

      $ oc describe machineconfigpool worker

      Example output

      apiVersion: machineconfiguration.openshift.io/v1
      kind: MachineConfigPool
      metadata:
        creationTimestamp: 2019-02-08T14:52:39Z
        generation: 1
        labels:
          custom-kubelet: set-max-pods 1

      1
      If a label has been added it appears under labels.
    2. If the label is not present, add a key/value pair:

      $ oc label machineconfigpool worker custom-kubelet=set-max-pods

Procedure

  1. View the available machine configuration objects that you can select:

    $ oc get machineconfig

    By default, the two kubelet-related configs are 01-master-kubelet and 01-worker-kubelet.

  2. Check the current value for the maximum pods per node:

    $ oc describe node <node_name>

    For example:

    $ oc describe node ci-ln-5grqprb-f76d1-ncnqq-worker-a-mdv94

    Look for value: pods: <value> in the Allocatable stanza:

    Example output

    Allocatable:
     attachable-volumes-aws-ebs:  25
     cpu:                         3500m
     hugepages-1Gi:               0
     hugepages-2Mi:               0
     memory:                      15341844Ki
     pods:                        250

  3. Set the maximum pods per node on the worker nodes by creating a custom resource file that contains the kubelet configuration:

    Important

    Kubelet configurations that target a specific machine config pool also affect any dependent pools. For example, creating a kubelet configuration for the pool containing worker nodes will also apply to any subset pools, including the pool containing infrastructure nodes. To avoid this, you must create a new machine config pool with a selection expression that only includes worker nodes, and have your kubelet configuration target this new pool.

    apiVersion: machineconfiguration.openshift.io/v1
    kind: KubeletConfig
    metadata:
      name: set-max-pods
    spec:
      machineConfigPoolSelector:
        matchLabels:
          custom-kubelet: set-max-pods 1
      kubeletConfig:
        maxPods: 500 2
    1
    Enter the label from the machine config pool.
    2
    Add the kubelet configuration. In this example, use maxPods to set the maximum pods per node.
    Note

    The rate at which the kubelet talks to the API server depends on queries per second (QPS) and burst values. The default values, 50 for kubeAPIQPS and 100 for kubeAPIBurst, are sufficient if there are limited pods running on each node. It is recommended to update the kubelet QPS and burst rates if there are enough CPU and memory resources on the node.

    apiVersion: machineconfiguration.openshift.io/v1
    kind: KubeletConfig
    metadata:
      name: set-max-pods
    spec:
      machineConfigPoolSelector:
        matchLabels:
          custom-kubelet: set-max-pods
      kubeletConfig:
        maxPods: <pod_count>
        kubeAPIBurst: <burst_rate>
        kubeAPIQPS: <QPS>
    1. Update the machine config pool for workers with the label:

      $ oc label machineconfigpool worker custom-kubelet=set-max-pods
    2. Create the KubeletConfig object:

      $ oc create -f change-maxPods-cr.yaml
    3. Verify that the KubeletConfig object is created:

      $ oc get kubeletconfig

      Example output

      NAME                AGE
      set-max-pods        15m

      Depending on the number of worker nodes in the cluster, wait for the worker nodes to be rebooted one by one. For a cluster with 3 worker nodes, this could take about 10 to 15 minutes.

  4. Verify that the changes are applied to the node:

    1. Check on a worker node that the maxPods value changed:

      $ oc describe node <node_name>
    2. Locate the Allocatable stanza:

       ...
      Allocatable:
        attachable-volumes-gce-pd:  127
        cpu:                        3500m
        ephemeral-storage:          123201474766
        hugepages-1Gi:              0
        hugepages-2Mi:              0
        memory:                     14225400Ki
        pods:                       500 1
       ...
      1
      In this example, the pods parameter should report the value you set in the KubeletConfig object.
  5. Verify the change in the KubeletConfig object:

    $ oc get kubeletconfigs set-max-pods -o yaml

    This should show a status of True and type:Success, as shown in the following example:

    spec:
      kubeletConfig:
        maxPods: 500
      machineConfigPoolSelector:
        matchLabels:
          custom-kubelet: set-max-pods
    status:
      conditions:
      - lastTransitionTime: "2021-06-30T17:04:07Z"
        message: Success
        status: "True"
        type: Success

5.4.2. Modifying the number of unavailable worker nodes

By default, only one machine is allowed to be unavailable when applying the kubelet-related configuration to the available worker nodes. For a large cluster, it can take a long time for the configuration change to be reflected. At any time, you can adjust the number of machines that are updating to speed up the process.

Procedure

  1. Edit the worker machine config pool:

    $ oc edit machineconfigpool worker
  2. Add the maxUnavailable field and set the value:

    spec:
      maxUnavailable: <node_count>
    Important

    When setting the value, consider the number of worker nodes that can be unavailable without affecting the applications running on the cluster.

5.4.3. Control plane node sizing

The control plane node resource requirements depend on the number and type of nodes and objects in the cluster. The following control plane node size recommendations are based on the results of a control plane density focused testing, or Cluster-density. This test creates the following objects across a given number of namespaces:

  • 1 image stream
  • 1 build
  • 5 deployments, with 2 pod replicas in a sleep state, mounting 4 secrets, 4 config maps, and 1 downward API volume each
  • 5 services, each one pointing to the TCP/8080 and TCP/8443 ports of one of the previous deployments
  • 1 route pointing to the first of the previous services
  • 10 secrets containing 2048 random string characters
  • 10 config maps containing 2048 random string characters
Number of worker nodesCluster-density (namespaces)CPU coresMemory (GB)

24

500

4

16

120

1000

8

32

252

4000

16, but 24 if using the OVN-Kubernetes network plug-in

64, but 128 if using the OVN-Kubernetes network plug-in

501, but untested with the OVN-Kubernetes network plug-in

4000

16

96

The data from the table above is based on an OpenShift Container Platform running on top of AWS, using r5.4xlarge instances as control-plane nodes and m5.2xlarge instances as worker nodes.

On a large and dense cluster with three control plane nodes, the CPU and memory usage will spike up when one of the nodes is stopped, rebooted, or fails. The failures can be due to unexpected issues with power, network, underlying infrastructure, or intentional cases where the cluster is restarted after shutting it down to save costs. The remaining two control plane nodes must handle the load in order to be highly available, which leads to increase in the resource usage. This is also expected during upgrades because the control plane nodes are cordoned, drained, and rebooted serially to apply the operating system updates, as well as the control plane Operators update. To avoid cascading failures, keep the overall CPU and memory resource usage on the control plane nodes to at most 60% of all available capacity to handle the resource usage spikes. Increase the CPU and memory on the control plane nodes accordingly to avoid potential downtime due to lack of resources.

Important

The node sizing varies depending on the number of nodes and object counts in the cluster. It also depends on whether the objects are actively being created on the cluster. During object creation, the control plane is more active in terms of resource usage compared to when the objects are in the running phase.

Operator Lifecycle Manager (OLM ) runs on the control plane nodes and its memory footprint depends on the number of namespaces and user installed operators that OLM needs to manage on the cluster. Control plane nodes need to be sized accordingly to avoid OOM kills. Following data points are based on the results from cluster maximums testing.

Number of namespacesOLM memory at idle state (GB)OLM memory with 5 user operators installed (GB)

500

0.823

1.7

1000

1.2

2.5

1500

1.7

3.2

2000

2

4.4

3000

2.7

5.6

4000

3.8

7.6

5000

4.2

9.02

6000

5.8

11.3

7000

6.6

12.9

8000

6.9

14.8

9000

8

17.7

10,000

9.9

21.6

Important

You can modify the control plane node size in a running OpenShift Container Platform 4.17 cluster for the following configurations only:

  • Clusters installed with a user-provisioned installation method.
  • AWS clusters installed with an installer-provisioned infrastructure installation method.
  • Clusters that use a control plane machine set to manage control plane machines.

For all other configurations, you must estimate your total node count and use the suggested control plane node size during installation.

Note

In OpenShift Container Platform 4.17, half of a CPU core (500 millicore) is now reserved by the system by default compared to OpenShift Container Platform 3.11 and previous versions. The sizes are determined taking that into consideration.

5.4.4. Setting up CPU Manager

To configure CPU manager, create a KubeletConfig custom resource (CR) and apply it to the desired set of nodes.

Procedure

  1. Label a node by running the following command:

    # oc label node perf-node.example.com cpumanager=true
  2. To enable CPU Manager for all compute nodes, edit the CR by running the following command:

    # oc edit machineconfigpool worker
  3. Add the custom-kubelet: cpumanager-enabled label to metadata.labels section.

    metadata:
      creationTimestamp: 2020-xx-xxx
      generation: 3
      labels:
        custom-kubelet: cpumanager-enabled
  4. Create a KubeletConfig, cpumanager-kubeletconfig.yaml, custom resource (CR). Refer to the label created in the previous step to have the correct nodes updated with the new kubelet config. See the machineConfigPoolSelector section:

    apiVersion: machineconfiguration.openshift.io/v1
    kind: KubeletConfig
    metadata:
      name: cpumanager-enabled
    spec:
      machineConfigPoolSelector:
        matchLabels:
          custom-kubelet: cpumanager-enabled
      kubeletConfig:
         cpuManagerPolicy: static 1
         cpuManagerReconcilePeriod: 5s 2
    1
    Specify a policy:
    • none. This policy explicitly enables the existing default CPU affinity scheme, providing no affinity beyond what the scheduler does automatically. This is the default policy.
    • static. This policy allows containers in guaranteed pods with integer CPU requests. It also limits access to exclusive CPUs on the node. If static, you must use a lowercase s.
    2
    Optional. Specify the CPU Manager reconcile frequency. The default is 5s.
  5. Create the dynamic kubelet config by running the following command:

    # oc create -f cpumanager-kubeletconfig.yaml

    This adds the CPU Manager feature to the kubelet config and, if needed, the Machine Config Operator (MCO) reboots the node. To enable CPU Manager, a reboot is not needed.

  6. Check for the merged kubelet config by running the following command:

    # oc get machineconfig 99-worker-XXXXXX-XXXXX-XXXX-XXXXX-kubelet -o json | grep ownerReference -A7

    Example output

           "ownerReferences": [
                {
                    "apiVersion": "machineconfiguration.openshift.io/v1",
                    "kind": "KubeletConfig",
                    "name": "cpumanager-enabled",
                    "uid": "7ed5616d-6b72-11e9-aae1-021e1ce18878"
                }
            ]

  7. Check the compute node for the updated kubelet.conf file by running the following command:

    # oc debug node/perf-node.example.com
    sh-4.2# cat /host/etc/kubernetes/kubelet.conf | grep cpuManager

    Example output

    cpuManagerPolicy: static        1
    cpuManagerReconcilePeriod: 5s   2

    1
    cpuManagerPolicy is defined when you create the KubeletConfig CR.
    2
    cpuManagerReconcilePeriod is defined when you create the KubeletConfig CR.
  8. Create a project by running the following command:

    $ oc new-project <project_name>
  9. Create a pod that requests a core or multiple cores. Both limits and requests must have their CPU value set to a whole integer. That is the number of cores that will be dedicated to this pod:

    # cat cpumanager-pod.yaml

    Example output

    apiVersion: v1
    kind: Pod
    metadata:
      generateName: cpumanager-
    spec:
      securityContext:
        runAsNonRoot: true
        seccompProfile:
          type: RuntimeDefault
      containers:
      - name: cpumanager
        image: gcr.io/google_containers/pause:3.2
        resources:
          requests:
            cpu: 1
            memory: "1G"
          limits:
            cpu: 1
            memory: "1G"
        securityContext:
          allowPrivilegeEscalation: false
          capabilities:
            drop: [ALL]
      nodeSelector:
        cpumanager: "true"

  10. Create the pod:

    # oc create -f cpumanager-pod.yaml

Verification

  1. Verify that the pod is scheduled to the node that you labeled by running the following command:

    # oc describe pod cpumanager

    Example output

    Name:               cpumanager-6cqz7
    Namespace:          default
    Priority:           0
    PriorityClassName:  <none>
    Node:  perf-node.example.com/xxx.xx.xx.xxx
    ...
     Limits:
          cpu:     1
          memory:  1G
        Requests:
          cpu:        1
          memory:     1G
    ...
    QoS Class:       Guaranteed
    Node-Selectors:  cpumanager=true

  2. Verify that a CPU has been exclusively assigned to the pod by running the following command:

    # oc describe node --selector='cpumanager=true' | grep -i cpumanager- -B2

    Example output

    NAMESPACE    NAME                CPU Requests  CPU Limits  Memory Requests  Memory Limits  Age
    cpuman       cpumanager-mlrrz    1 (28%)       1 (28%)     1G (13%)         1G (13%)       27m

  3. Verify that the cgroups are set up correctly. Get the process ID (PID) of the pause process by running the following commands:

    # oc debug node/perf-node.example.com
    sh-4.2# systemctl status | grep -B5 pause
    Note

    If the output returns multiple pause process entries, you must identify the correct pause process.

    Example output

    # ├─init.scope
    │ └─1 /usr/lib/systemd/systemd --switched-root --system --deserialize 17
    └─kubepods.slice
      ├─kubepods-pod69c01f8e_6b74_11e9_ac0f_0a2b62178a22.slice
      │ ├─crio-b5437308f1a574c542bdf08563b865c0345c8f8c0b0a655612c.scope
      │ └─32706 /pause

  4. Verify that pods of quality of service (QoS) tier Guaranteed are placed within the kubepods.slice subdirectory by running the following commands:

    # cd /sys/fs/cgroup/kubepods.slice/kubepods-pod69c01f8e_6b74_11e9_ac0f_0a2b62178a22.slice/crio-b5437308f1ad1a7db0574c542bdf08563b865c0345c86e9585f8c0b0a655612c.scope
    # for i in `ls cpuset.cpus cgroup.procs` ; do echo -n "$i "; cat $i ; done
    Note

    Pods of other QoS tiers end up in child cgroups of the parent kubepods.

    Example output

    cpuset.cpus 1
    tasks 32706

  5. Check the allowed CPU list for the task by running the following command:

    # grep ^Cpus_allowed_list /proc/32706/status

    Example output

     Cpus_allowed_list:    1

  6. Verify that another pod on the system cannot run on the core allocated for the Guaranteed pod. For example, to verify the pod in the besteffort QoS tier, run the following commands:

    # cat /sys/fs/cgroup/kubepods.slice/kubepods-besteffort.slice/kubepods-besteffort-podc494a073_6b77_11e9_98c0_06bba5c387ea.slice/crio-c56982f57b75a2420947f0afc6cafe7534c5734efc34157525fa9abbf99e3849.scope/cpuset.cpus
    # oc describe node perf-node.example.com

    Example output

    ...
    Capacity:
     attachable-volumes-aws-ebs:  39
     cpu:                         2
     ephemeral-storage:           124768236Ki
     hugepages-1Gi:               0
     hugepages-2Mi:               0
     memory:                      8162900Ki
     pods:                        250
    Allocatable:
     attachable-volumes-aws-ebs:  39
     cpu:                         1500m
     ephemeral-storage:           124768236Ki
     hugepages-1Gi:               0
     hugepages-2Mi:               0
     memory:                      7548500Ki
     pods:                        250
    -------                               ----                           ------------  ----------  ---------------  -------------  ---
      default                                 cpumanager-6cqz7               1 (66%)       1 (66%)     1G (12%)         1G (12%)       29m
    
    Allocated resources:
      (Total limits may be over 100 percent, i.e., overcommitted.)
      Resource                    Requests          Limits
      --------                    --------          ------
      cpu                         1440m (96%)       1 (66%)

    This VM has two CPU cores. The system-reserved setting reserves 500 millicores, meaning that half of one core is subtracted from the total capacity of the node to arrive at the Node Allocatable amount. You can see that Allocatable CPU is 1500 millicores. This means you can run one of the CPU Manager pods since each will take one whole core. A whole core is equivalent to 1000 millicores. If you try to schedule a second pod, the system will accept the pod, but it will never be scheduled:

    NAME                    READY   STATUS    RESTARTS   AGE
    cpumanager-6cqz7        1/1     Running   0          33m
    cpumanager-7qc2t        0/1     Pending   0          11s

5.5. Huge pages

Understand and configure huge pages.

5.5.1. What huge pages do

Memory is managed in blocks known as pages. On most systems, a page is 4Ki. 1Mi of memory is equal to 256 pages; 1Gi of memory is 256,000 pages, and so on. CPUs have a built-in memory management unit that manages a list of these pages in hardware. The Translation Lookaside Buffer (TLB) is a small hardware cache of virtual-to-physical page mappings. If the virtual address passed in a hardware instruction can be found in the TLB, the mapping can be determined quickly. If not, a TLB miss occurs, and the system falls back to slower, software-based address translation, resulting in performance issues. Since the size of the TLB is fixed, the only way to reduce the chance of a TLB miss is to increase the page size.

A huge page is a memory page that is larger than 4Ki. On x86_64 architectures, there are two common huge page sizes: 2Mi and 1Gi. Sizes vary on other architectures. To use huge pages, code must be written so that applications are aware of them. Transparent Huge Pages (THP) attempt to automate the management of huge pages without application knowledge, but they have limitations. In particular, they are limited to 2Mi page sizes. THP can lead to performance degradation on nodes with high memory utilization or fragmentation due to defragmenting efforts of THP, which can lock memory pages. For this reason, some applications may be designed to (or recommend) usage of pre-allocated huge pages instead of THP.

5.5.2. How huge pages are consumed by apps

Nodes must pre-allocate huge pages in order for the node to report its huge page capacity. A node can only pre-allocate huge pages for a single size.

Huge pages can be consumed through container-level resource requirements using the resource name hugepages-<size>, where size is the most compact binary notation using integer values supported on a particular node. For example, if a node supports 2048KiB page sizes, it exposes a schedulable resource hugepages-2Mi. Unlike CPU or memory, huge pages do not support over-commitment.

apiVersion: v1
kind: Pod
metadata:
  generateName: hugepages-volume-
spec:
  containers:
  - securityContext:
      privileged: true
    image: rhel7:latest
    command:
    - sleep
    - inf
    name: example
    volumeMounts:
    - mountPath: /dev/hugepages
      name: hugepage
    resources:
      limits:
        hugepages-2Mi: 100Mi 1
        memory: "1Gi"
        cpu: "1"
  volumes:
  - name: hugepage
    emptyDir:
      medium: HugePages
1
Specify the amount of memory for hugepages as the exact amount to be allocated. Do not specify this value as the amount of memory for hugepages multiplied by the size of the page. For example, given a huge page size of 2MB, if you want to use 100MB of huge-page-backed RAM for your application, then you would allocate 50 huge pages. OpenShift Container Platform handles the math for you. As in the above example, you can specify 100MB directly.

Allocating huge pages of a specific size

Some platforms support multiple huge page sizes. To allocate huge pages of a specific size, precede the huge pages boot command parameters with a huge page size selection parameter hugepagesz=<size>. The <size> value must be specified in bytes with an optional scale suffix [kKmMgG]. The default huge page size can be defined with the default_hugepagesz=<size> boot parameter.

Huge page requirements

  • Huge page requests must equal the limits. This is the default if limits are specified, but requests are not.
  • Huge pages are isolated at a pod scope. Container isolation is planned in a future iteration.
  • EmptyDir volumes backed by huge pages must not consume more huge page memory than the pod request.
  • Applications that consume huge pages via shmget() with SHM_HUGETLB must run with a supplemental group that matches proc/sys/vm/hugetlb_shm_group.

5.5.3. Configuring huge pages at boot time

Nodes must pre-allocate huge pages used in an OpenShift Container Platform cluster. There are two ways of reserving huge pages: at boot time and at run time. Reserving at boot time increases the possibility of success because the memory has not yet been significantly fragmented. The Node Tuning Operator currently supports boot time allocation of huge pages on specific nodes.

Procedure

To minimize node reboots, the order of the steps below needs to be followed:

  1. Label all nodes that need the same huge pages setting by a label.

    $ oc label node <node_using_hugepages> node-role.kubernetes.io/worker-hp=
  2. Create a file with the following content and name it hugepages-tuned-boottime.yaml:

    apiVersion: tuned.openshift.io/v1
    kind: Tuned
    metadata:
      name: hugepages 1
      namespace: openshift-cluster-node-tuning-operator
    spec:
      profile: 2
      - data: |
          [main]
          summary=Boot time configuration for hugepages
          include=openshift-node
          [bootloader]
          cmdline_openshift_node_hugepages=hugepagesz=2M hugepages=50 3
        name: openshift-node-hugepages
    
      recommend:
      - machineConfigLabels: 4
          machineconfiguration.openshift.io/role: "worker-hp"
        priority: 30
        profile: openshift-node-hugepages
    1
    Set the name of the Tuned resource to hugepages.
    2
    Set the profile section to allocate huge pages.
    3
    Note the order of parameters is important as some platforms support huge pages of various sizes.
    4
    Enable machine config pool based matching.
  3. Create the Tuned hugepages object

    $ oc create -f hugepages-tuned-boottime.yaml
  4. Create a file with the following content and name it hugepages-mcp.yaml:

    apiVersion: machineconfiguration.openshift.io/v1
    kind: MachineConfigPool
    metadata:
      name: worker-hp
      labels:
        worker-hp: ""
    spec:
      machineConfigSelector:
        matchExpressions:
          - {key: machineconfiguration.openshift.io/role, operator: In, values: [worker,worker-hp]}
      nodeSelector:
        matchLabels:
          node-role.kubernetes.io/worker-hp: ""
  5. Create the machine config pool:

    $ oc create -f hugepages-mcp.yaml

Given enough non-fragmented memory, all the nodes in the worker-hp machine config pool should now have 50 2Mi huge pages allocated.

$ oc get node <node_using_hugepages> -o jsonpath="{.status.allocatable.hugepages-2Mi}"
100Mi
Note

The TuneD bootloader plugin only supports Red Hat Enterprise Linux CoreOS (RHCOS) worker nodes.

5.6. Understanding device plugins

The device plugin provides a consistent and portable solution to consume hardware devices across clusters. The device plugin provides support for these devices through an extension mechanism, which makes these devices available to Containers, provides health checks of these devices, and securely shares them.

Important

OpenShift Container Platform supports the device plugin API, but the device plugin Containers are supported by individual vendors.

A device plugin is a gRPC service running on the nodes (external to the kubelet) that is responsible for managing specific hardware resources. Any device plugin must support following remote procedure calls (RPCs):

service DevicePlugin {
      // GetDevicePluginOptions returns options to be communicated with Device
      // Manager
      rpc GetDevicePluginOptions(Empty) returns (DevicePluginOptions) {}

      // ListAndWatch returns a stream of List of Devices
      // Whenever a Device state change or a Device disappears, ListAndWatch
      // returns the new list
      rpc ListAndWatch(Empty) returns (stream ListAndWatchResponse) {}

      // Allocate is called during container creation so that the Device
      // Plug-in can run device specific operations and instruct Kubelet
      // of the steps to make the Device available in the container
      rpc Allocate(AllocateRequest) returns (AllocateResponse) {}

      // PreStartcontainer is called, if indicated by Device Plug-in during
      // registration phase, before each container start. Device plug-in
      // can run device specific operations such as resetting the device
      // before making devices available to the container
      rpc PreStartcontainer(PreStartcontainerRequest) returns (PreStartcontainerResponse) {}
}
Example device plugins
Note

For easy device plugin reference implementation, there is a stub device plugin in the Device Manager code: vendor/k8s.io/kubernetes/pkg/kubelet/cm/deviceplugin/device_plugin_stub.go.

5.6.1. Methods for deploying a device plugin

  • Daemon sets are the recommended approach for device plugin deployments.
  • Upon start, the device plugin will try to create a UNIX domain socket at /var/lib/kubelet/device-plugin/ on the node to serve RPCs from Device Manager.
  • Since device plugins must manage hardware resources, access to the host file system, as well as socket creation, they must be run in a privileged security context.
  • More specific details regarding deployment steps can be found with each device plugin implementation.

5.6.2. Understanding the Device Manager

Device Manager provides a mechanism for advertising specialized node hardware resources with the help of plugins known as device plugins.

You can advertise specialized hardware without requiring any upstream code changes.

Important

OpenShift Container Platform supports the device plugin API, but the device plugin Containers are supported by individual vendors.

Device Manager advertises devices as Extended Resources. User pods can consume devices, advertised by Device Manager, using the same Limit/Request mechanism, which is used for requesting any other Extended Resource.

Upon start, the device plugin registers itself with Device Manager invoking Register on the /var/lib/kubelet/device-plugins/kubelet.sock and starts a gRPC service at /var/lib/kubelet/device-plugins/<plugin>.sock for serving Device Manager requests.

Device Manager, while processing a new registration request, invokes ListAndWatch remote procedure call (RPC) at the device plugin service. In response, Device Manager gets a list of Device objects from the plugin over a gRPC stream. Device Manager will keep watching on the stream for new updates from the plugin. On the plugin side, the plugin will also keep the stream open and whenever there is a change in the state of any of the devices, a new device list is sent to the Device Manager over the same streaming connection.

While handling a new pod admission request, Kubelet passes requested Extended Resources to the Device Manager for device allocation. Device Manager checks in its database to verify if a corresponding plugin exists or not. If the plugin exists and there are free allocatable devices as well as per local cache, Allocate RPC is invoked at that particular device plugin.

Additionally, device plugins can also perform several other device-specific operations, such as driver installation, device initialization, and device resets. These functionalities vary from implementation to implementation.

5.6.3. Enabling Device Manager

Enable Device Manager to implement a device plugin to advertise specialized hardware without any upstream code changes.

Device Manager provides a mechanism for advertising specialized node hardware resources with the help of plugins known as device plugins.

  1. Obtain the label associated with the static MachineConfigPool CRD for the type of node you want to configure by entering the following command. Perform one of the following steps:

    1. View the machine config:

      # oc describe machineconfig <name>

      For example:

      # oc describe machineconfig 00-worker

      Example output

      Name:         00-worker
      Namespace:
      Labels:       machineconfiguration.openshift.io/role=worker 1

      1
      Label required for the Device Manager.

Procedure

  1. Create a custom resource (CR) for your configuration change.

    Sample configuration for a Device Manager CR

    apiVersion: machineconfiguration.openshift.io/v1
    kind: KubeletConfig
    metadata:
      name: devicemgr 1
    spec:
      machineConfigPoolSelector:
        matchLabels:
           machineconfiguration.openshift.io: devicemgr 2
      kubeletConfig:
        feature-gates:
          - DevicePlugins=true 3

    1
    Assign a name to CR.
    2
    Enter the label from the Machine Config Pool.
    3
    Set DevicePlugins to 'true`.
  2. Create the Device Manager:

    $ oc create -f devicemgr.yaml

    Example output

    kubeletconfig.machineconfiguration.openshift.io/devicemgr created

  3. Ensure that Device Manager was actually enabled by confirming that /var/lib/kubelet/device-plugins/kubelet.sock is created on the node. This is the UNIX domain socket on which the Device Manager gRPC server listens for new plugin registrations. This sock file is created when the Kubelet is started only if Device Manager is enabled.

5.7. Taints and tolerations

Understand and work with taints and tolerations.

5.7.1. Understanding taints and tolerations

A taint allows a node to refuse a pod to be scheduled unless that pod has a matching toleration.

You apply taints to a node through the Node specification (NodeSpec) and apply tolerations to a pod through the Pod specification (PodSpec). When you apply a taint a node, the scheduler cannot place a pod on that node unless the pod can tolerate the taint.

Example taint in a node specification

apiVersion: v1
kind: Node
metadata:
  name: my-node
#...
spec:
  taints:
  - effect: NoExecute
    key: key1
    value: value1
#...

Example toleration in a Pod spec

apiVersion: v1
kind: Pod
metadata:
  name: my-pod
#...
spec:
  tolerations:
  - key: "key1"
    operator: "Equal"
    value: "value1"
    effect: "NoExecute"
    tolerationSeconds: 3600
#...

Taints and tolerations consist of a key, value, and effect.

Table 5.1. Taint and toleration components
ParameterDescription

key

The key is any string, up to 253 characters. The key must begin with a letter or number, and may contain letters, numbers, hyphens, dots, and underscores.

value

The value is any string, up to 63 characters. The value must begin with a letter or number, and may contain letters, numbers, hyphens, dots, and underscores.

effect

The effect is one of the following:

NoSchedule [1]

  • New pods that do not match the taint are not scheduled onto that node.
  • Existing pods on the node remain.

PreferNoSchedule

  • New pods that do not match the taint might be scheduled onto that node, but the scheduler tries not to.
  • Existing pods on the node remain.

NoExecute

  • New pods that do not match the taint cannot be scheduled onto that node.
  • Existing pods on the node that do not have a matching toleration are removed.

operator

Equal

The key/value/effect parameters must match. This is the default.

Exists

The key/effect parameters must match. You must leave a blank value parameter, which matches any.

  1. If you add a NoSchedule taint to a control plane node, the node must have the node-role.kubernetes.io/master=:NoSchedule taint, which is added by default.

    For example:

    apiVersion: v1
    kind: Node
    metadata:
      annotations:
        machine.openshift.io/machine: openshift-machine-api/ci-ln-62s7gtb-f76d1-v8jxv-master-0
        machineconfiguration.openshift.io/currentConfig: rendered-master-cdc1ab7da414629332cc4c3926e6e59c
      name: my-node
    #...
    spec:
      taints:
      - effect: NoSchedule
        key: node-role.kubernetes.io/master
    #...

A toleration matches a taint:

  • If the operator parameter is set to Equal:

    • the key parameters are the same;
    • the value parameters are the same;
    • the effect parameters are the same.
  • If the operator parameter is set to Exists:

    • the key parameters are the same;
    • the effect parameters are the same.

The following taints are built into OpenShift Container Platform:

  • node.kubernetes.io/not-ready: The node is not ready. This corresponds to the node condition Ready=False.
  • node.kubernetes.io/unreachable: The node is unreachable from the node controller. This corresponds to the node condition Ready=Unknown.
  • node.kubernetes.io/memory-pressure: The node has memory pressure issues. This corresponds to the node condition MemoryPressure=True.
  • node.kubernetes.io/disk-pressure: The node has disk pressure issues. This corresponds to the node condition DiskPressure=True.
  • node.kubernetes.io/network-unavailable: The node network is unavailable.
  • node.kubernetes.io/unschedulable: The node is unschedulable.
  • node.cloudprovider.kubernetes.io/uninitialized: When the node controller is started with an external cloud provider, this taint is set on a node to mark it as unusable. After a controller from the cloud-controller-manager initializes this node, the kubelet removes this taint.
  • node.kubernetes.io/pid-pressure: The node has pid pressure. This corresponds to the node condition PIDPressure=True.

    Important

    OpenShift Container Platform does not set a default pid.available evictionHard.

5.7.2. Adding taints and tolerations

You add tolerations to pods and taints to nodes to allow the node to control which pods should or should not be scheduled on them. For existing pods and nodes, you should add the toleration to the pod first, then add the taint to the node to avoid pods being removed from the node before you can add the toleration.

Procedure

  1. Add a toleration to a pod by editing the Pod spec to include a tolerations stanza:

    Sample pod configuration file with an Equal operator

    apiVersion: v1
    kind: Pod
    metadata:
      name: my-pod
    #...
    spec:
      tolerations:
      - key: "key1" 1
        value: "value1"
        operator: "Equal"
        effect: "NoExecute"
        tolerationSeconds: 3600 2
    #...

    1
    The toleration parameters, as described in the Taint and toleration components table.
    2
    The tolerationSeconds parameter specifies how long a pod can remain bound to a node before being evicted.

    For example:

    Sample pod configuration file with an Exists operator

    apiVersion: v1
    kind: Pod
    metadata:
      name: my-pod
    #...
    spec:
       tolerations:
        - key: "key1"
          operator: "Exists" 1
          effect: "NoExecute"
          tolerationSeconds: 3600
    #...

    1
    The Exists operator does not take a value.

    This example places a taint on node1 that has key key1, value value1, and taint effect NoExecute.

  2. Add a taint to a node by using the following command with the parameters described in the Taint and toleration components table:

    $ oc adm taint nodes <node_name> <key>=<value>:<effect>

    For example:

    $ oc adm taint nodes node1 key1=value1:NoExecute

    This command places a taint on node1 that has key key1, value value1, and effect NoExecute.

    Note

    If you add a NoSchedule taint to a control plane node, the node must have the node-role.kubernetes.io/master=:NoSchedule taint, which is added by default.

    For example:

    apiVersion: v1
    kind: Node
    metadata:
      annotations:
        machine.openshift.io/machine: openshift-machine-api/ci-ln-62s7gtb-f76d1-v8jxv-master-0
        machineconfiguration.openshift.io/currentConfig: rendered-master-cdc1ab7da414629332cc4c3926e6e59c
      name: my-node
    #...
    spec:
      taints:
      - effect: NoSchedule
        key: node-role.kubernetes.io/master
    #...

    The tolerations on the pod match the taint on the node. A pod with either toleration can be scheduled onto node1.

5.7.3. Adding taints and tolerations using a compute machine set

You can add taints to nodes using a compute machine set. All nodes associated with the MachineSet object are updated with the taint. Tolerations respond to taints added by a compute machine set in the same manner as taints added directly to the nodes.

Procedure

  1. Add a toleration to a pod by editing the Pod spec to include a tolerations stanza:

    Sample pod configuration file with Equal operator

    apiVersion: v1
    kind: Pod
    metadata:
      name: my-pod
    #...
    spec:
      tolerations:
      - key: "key1" 1
        value: "value1"
        operator: "Equal"
        effect: "NoExecute"
        tolerationSeconds: 3600 2
    #...

    1
    The toleration parameters, as described in the Taint and toleration components table.
    2
    The tolerationSeconds parameter specifies how long a pod is bound to a node before being evicted.

    For example:

    Sample pod configuration file with Exists operator

    apiVersion: v1
    kind: Pod
    metadata:
      name: my-pod
    #...
    spec:
      tolerations:
      - key: "key1"
        operator: "Exists"
        effect: "NoExecute"
        tolerationSeconds: 3600
    #...

  2. Add the taint to the MachineSet object:

    1. Edit the MachineSet YAML for the nodes you want to taint or you can create a new MachineSet object:

      $ oc edit machineset <machineset>
    2. Add the taint to the spec.template.spec section:

      Example taint in a compute machine set specification

      apiVersion: machine.openshift.io/v1beta1
      kind: MachineSet
      metadata:
        name: my-machineset
      #...
      spec:
      #...
        template:
      #...
          spec:
            taints:
            - effect: NoExecute
              key: key1
              value: value1
      #...

      This example places a taint that has the key key1, value value1, and taint effect NoExecute on the nodes.

    3. Scale down the compute machine set to 0:

      $ oc scale --replicas=0 machineset <machineset> -n openshift-machine-api
      Tip

      You can alternatively apply the following YAML to scale the compute machine set:

      apiVersion: machine.openshift.io/v1beta1
      kind: MachineSet
      metadata:
        name: <machineset>
        namespace: openshift-machine-api
      spec:
        replicas: 0

      Wait for the machines to be removed.

    4. Scale up the compute machine set as needed:

      $ oc scale --replicas=2 machineset <machineset> -n openshift-machine-api

      Or:

      $ oc edit machineset <machineset> -n openshift-machine-api

      Wait for the machines to start. The taint is added to the nodes associated with the MachineSet object.

5.7.4. Binding a user to a node using taints and tolerations

If you want to dedicate a set of nodes for exclusive use by a particular set of users, add a toleration to their pods. Then, add a corresponding taint to those nodes. The pods with the tolerations are allowed to use the tainted nodes or any other nodes in the cluster.

If you want ensure the pods are scheduled to only those tainted nodes, also add a label to the same set of nodes and add a node affinity to the pods so that the pods can only be scheduled onto nodes with that label.

Procedure

To configure a node so that users can use only that node:

  1. Add a corresponding taint to those nodes:

    For example:

    $ oc adm taint nodes node1 dedicated=groupName:NoSchedule
    Tip

    You can alternatively apply the following YAML to add the taint:

    kind: Node
    apiVersion: v1
    metadata:
      name: my-node
    #...
    spec:
      taints:
        - key: dedicated
          value: groupName
          effect: NoSchedule
    #...
  2. Add a toleration to the pods by writing a custom admission controller.

5.7.5. Controlling nodes with special hardware using taints and tolerations

In a cluster where a small subset of nodes have specialized hardware, you can use taints and tolerations to keep pods that do not need the specialized hardware off of those nodes, leaving the nodes for pods that do need the specialized hardware. You can also require pods that need specialized hardware to use specific nodes.

You can achieve this by adding a toleration to pods that need the special hardware and tainting the nodes that have the specialized hardware.

Procedure

To ensure nodes with specialized hardware are reserved for specific pods:

  1. Add a toleration to pods that need the special hardware.

    For example:

    apiVersion: v1
    kind: Pod
    metadata:
      name: my-pod
    #...
    spec:
      tolerations:
        - key: "disktype"
          value: "ssd"
          operator: "Equal"
          effect: "NoSchedule"
          tolerationSeconds: 3600
    #...
  2. Taint the nodes that have the specialized hardware using one of the following commands:

    $ oc adm taint nodes <node-name> disktype=ssd:NoSchedule

    Or:

    $ oc adm taint nodes <node-name> disktype=ssd:PreferNoSchedule
    Tip

    You can alternatively apply the following YAML to add the taint:

    kind: Node
    apiVersion: v1
    metadata:
      name: my_node
    #...
    spec:
      taints:
        - key: disktype
          value: ssd
          effect: PreferNoSchedule
    #...

5.7.6. Removing taints and tolerations

You can remove taints from nodes and tolerations from pods as needed. You should add the toleration to the pod first, then add the taint to the node to avoid pods being removed from the node before you can add the toleration.

Procedure

To remove taints and tolerations:

  1. To remove a taint from a node:

    $ oc adm taint nodes <node-name> <key>-

    For example:

    $ oc adm taint nodes ip-10-0-132-248.ec2.internal key1-

    Example output

    node/ip-10-0-132-248.ec2.internal untainted

  2. To remove a toleration from a pod, edit the Pod spec to remove the toleration:

    apiVersion: v1
    kind: Pod
    metadata:
      name: my-pod
    #...
    spec:
      tolerations:
      - key: "key2"
        operator: "Exists"
        effect: "NoExecute"
        tolerationSeconds: 3600
    #...

5.8. Topology Manager

Understand and work with Topology Manager.

5.8.1. Topology Manager policies

Topology Manager aligns Pod resources of all Quality of Service (QoS) classes by collecting topology hints from Hint Providers, such as CPU Manager and Device Manager, and using the collected hints to align the Pod resources.

Topology Manager supports four allocation policies, which you assign in the KubeletConfig custom resource (CR) named cpumanager-enabled:

none policy
This is the default policy and does not perform any topology alignment.
best-effort policy
For each container in a pod with the best-effort topology management policy, kubelet calls each Hint Provider to discover their resource availability. Using this information, the Topology Manager stores the preferred NUMA Node affinity for that container. If the affinity is not preferred, Topology Manager stores this and admits the pod to the node.
restricted policy
For each container in a pod with the restricted topology management policy, kubelet calls each Hint Provider to discover their resource availability. Using this information, the Topology Manager stores the preferred NUMA Node affinity for that container. If the affinity is not preferred, Topology Manager rejects this pod from the node, resulting in a pod in a Terminated state with a pod admission failure.
single-numa-node policy
For each container in a pod with the single-numa-node topology management policy, kubelet calls each Hint Provider to discover their resource availability. Using this information, the Topology Manager determines if a single NUMA Node affinity is possible. If it is, the pod is admitted to the node. If a single NUMA Node affinity is not possible, the Topology Manager rejects the pod from the node. This results in a pod in a Terminated state with a pod admission failure.

5.8.2. Setting up Topology Manager

To use Topology Manager, you must configure an allocation policy in the KubeletConfig custom resource (CR) named cpumanager-enabled. This file might exist if you have set up CPU Manager. If the file does not exist, you can create the file.

Prerequisites

  • Configure the CPU Manager policy to be static.

Procedure

To activate Topology Manager:

  1. Configure the Topology Manager allocation policy in the custom resource.

    $ oc edit KubeletConfig cpumanager-enabled
    apiVersion: machineconfiguration.openshift.io/v1
    kind: KubeletConfig
    metadata:
      name: cpumanager-enabled
    spec:
      machineConfigPoolSelector:
        matchLabels:
          custom-kubelet: cpumanager-enabled
      kubeletConfig:
         cpuManagerPolicy: static 1
         cpuManagerReconcilePeriod: 5s
         topologyManagerPolicy: single-numa-node 2
    1
    This parameter must be static with a lowercase s.
    2
    Specify your selected Topology Manager allocation policy. Here, the policy is single-numa-node. Acceptable values are: default, best-effort, restricted, single-numa-node.

5.8.3. Pod interactions with Topology Manager policies

The example Pod specs below help illustrate pod interactions with Topology Manager.

The following pod runs in the BestEffort QoS class because no resource requests or limits are specified.

spec:
  containers:
  - name: nginx
    image: nginx

The next pod runs in the Burstable QoS class because requests are less than limits.

spec:
  containers:
  - name: nginx
    image: nginx
    resources:
      limits:
        memory: "200Mi"
      requests:
        memory: "100Mi"

If the selected policy is anything other than none, Topology Manager would not consider either of these Pod specifications.

The last example pod below runs in the Guaranteed QoS class because requests are equal to limits.

spec:
  containers:
  - name: nginx
    image: nginx
    resources:
      limits:
        memory: "200Mi"
        cpu: "2"
        example.com/device: "1"
      requests:
        memory: "200Mi"
        cpu: "2"
        example.com/device: "1"

Topology Manager would consider this pod. The Topology Manager would consult the hint providers, which are CPU Manager and Device Manager, to get topology hints for the pod.

Topology Manager will use this information to store the best topology for this container. In the case of this pod, CPU Manager and Device Manager will use this stored information at the resource allocation stage.

5.9. Resource requests and overcommitment

For each compute resource, a container may specify a resource request and limit. Scheduling decisions are made based on the request to ensure that a node has enough capacity available to meet the requested value. If a container specifies limits, but omits requests, the requests are defaulted to the limits. A container is not able to exceed the specified limit on the node.

The enforcement of limits is dependent upon the compute resource type. If a container makes no request or limit, the container is scheduled to a node with no resource guarantees. In practice, the container is able to consume as much of the specified resource as is available with the lowest local priority. In low resource situations, containers that specify no resource requests are given the lowest quality of service.

Scheduling is based on resources requested, while quota and hard limits refer to resource limits, which can be set higher than requested resources. The difference between request and limit determines the level of overcommit; for instance, if a container is given a memory request of 1Gi and a memory limit of 2Gi, it is scheduled based on the 1Gi request being available on the node, but could use up to 2Gi; so it is 200% overcommitted.

5.10. Cluster-level overcommit using the Cluster Resource Override Operator

The Cluster Resource Override Operator is an admission webhook that allows you to control the level of overcommit and manage container density across all the nodes in your cluster. The Operator controls how nodes in specific projects can exceed defined memory and CPU limits.

You must install the Cluster Resource Override Operator using the OpenShift Container Platform console or CLI as shown in the following sections. During the installation, you create a ClusterResourceOverride custom resource (CR), where you set the level of overcommit, as shown in the following example:

apiVersion: operator.autoscaling.openshift.io/v1
kind: ClusterResourceOverride
metadata:
    name: cluster 1
spec:
  podResourceOverride:
    spec:
      memoryRequestToLimitPercent: 50 2
      cpuRequestToLimitPercent: 25 3
      limitCPUToMemoryPercent: 200 4
# ...
1
The name must be cluster.
2
Optional. If a container memory limit has been specified or defaulted, the memory request is overridden to this percentage of the limit, between 1-100. The default is 50.
3
Optional. If a container CPU limit has been specified or defaulted, the CPU request is overridden to this percentage of the limit, between 1-100. The default is 25.
4
Optional. If a container memory limit has been specified or defaulted, the CPU limit is overridden to a percentage of the memory limit, if specified. Scaling 1Gi of RAM at 100 percent is equal to 1 CPU core. This is processed prior to overriding the CPU request (if configured). The default is 200.
Note

The Cluster Resource Override Operator overrides have no effect if limits have not been set on containers. Create a LimitRange object with default limits per individual project or configure limits in Pod specs for the overrides to apply.

When configured, overrides can be enabled per-project by applying the following label to the Namespace object for each project:

apiVersion: v1
kind: Namespace
metadata:

# ...

  labels:
    clusterresourceoverrides.admission.autoscaling.openshift.io/enabled: "true"

# ...

The Operator watches for the ClusterResourceOverride CR and ensures that the ClusterResourceOverride admission webhook is installed into the same namespace as the operator.

5.10.1. Installing the Cluster Resource Override Operator using the web console

You can use the OpenShift Container Platform CLI to install the Cluster Resource Override Operator to help control overcommit in your cluster.

By default, the installation process creates a Cluster Resource Override Operator pod on a worker node in the clusterresourceoverride-operator namespace. You can move this pod to another node, such as an infrastructure node, as needed. Infrastructure nodes are not counted toward the total number of subscriptions that are required to run the environment. For more information, see "Moving the Cluster Resource Override Operator pods".

Prerequisites

  • The Cluster Resource Override Operator has no effect if limits have not been set on containers. You must specify default limits for a project using a LimitRange object or configure limits in Pod specs for the overrides to apply.

Procedure

To install the Cluster Resource Override Operator using the OpenShift Container Platform web console:

  1. In the OpenShift Container Platform web console, navigate to HomeProjects

    1. Click Create Project.
    2. Specify clusterresourceoverride-operator as the name of the project.
    3. Click Create.
  2. Navigate to OperatorsOperatorHub.

    1. Choose ClusterResourceOverride Operator from the list of available Operators and click Install.
    2. On the Install Operator page, make sure A specific Namespace on the cluster is selected for Installation Mode.
    3. Make sure clusterresourceoverride-operator is selected for Installed Namespace.
    4. Select an Update Channel and Approval Strategy.
    5. Click Install.
  3. On the Installed Operators page, click ClusterResourceOverride.

    1. On the ClusterResourceOverride Operator details page, click Create ClusterResourceOverride.
    2. On the Create ClusterResourceOverride page, click YAML view and edit the YAML template to set the overcommit values as needed:

      apiVersion: operator.autoscaling.openshift.io/v1
      kind: ClusterResourceOverride
      metadata:
        name: cluster 1
      spec:
        podResourceOverride:
          spec:
            memoryRequestToLimitPercent: 50 2
            cpuRequestToLimitPercent: 25 3
            limitCPUToMemoryPercent: 200 4
      1
      The name must be cluster.
      2
      Optional: Specify the percentage to override the container memory limit, if used, between 1-100. The default is 50.
      3
      Optional: Specify the percentage to override the container CPU limit, if used, between 1-100. The default is 25.
      4
      Optional: Specify the percentage to override the container memory limit, if used. Scaling 1 Gi of RAM at 100 percent is equal to 1 CPU core. This is processed before overriding the CPU request, if configured. The default is 200.
    3. Click Create.
  4. Check the current state of the admission webhook by checking the status of the cluster custom resource:

    1. On the ClusterResourceOverride Operator page, click cluster.
    2. On the ClusterResourceOverride Details page, click YAML. The mutatingWebhookConfigurationRef section appears when the webhook is called.

      apiVersion: operator.autoscaling.openshift.io/v1
      kind: ClusterResourceOverride
      metadata:
        annotations:
          kubectl.kubernetes.io/last-applied-configuration: |
            {"apiVersion":"operator.autoscaling.openshift.io/v1","kind":"ClusterResourceOverride","metadata":{"annotations":{},"name":"cluster"},"spec":{"podResourceOverride":{"spec":{"cpuRequestToLimitPercent":25,"limitCPUToMemoryPercent":200,"memoryRequestToLimitPercent":50}}}}
        creationTimestamp: "2019-12-18T22:35:02Z"
        generation: 1
        name: cluster
        resourceVersion: "127622"
        selfLink: /apis/operator.autoscaling.openshift.io/v1/clusterresourceoverrides/cluster
        uid: 978fc959-1717-4bd1-97d0-ae00ee111e8d
      spec:
        podResourceOverride:
          spec:
            cpuRequestToLimitPercent: 25
            limitCPUToMemoryPercent: 200
            memoryRequestToLimitPercent: 50
      status:
      
      # ...
      
          mutatingWebhookConfigurationRef: 1
            apiVersion: admissionregistration.k8s.io/v1
            kind: MutatingWebhookConfiguration
            name: clusterresourceoverrides.admission.autoscaling.openshift.io
            resourceVersion: "127621"
            uid: 98b3b8ae-d5ce-462b-8ab5-a729ea8f38f3
      
      # ...
      1
      Reference to the ClusterResourceOverride admission webhook.

5.10.2. Installing the Cluster Resource Override Operator using the CLI

You can use the OpenShift Container Platform CLI to install the Cluster Resource Override Operator to help control overcommit in your cluster.

By default, the installation process creates a Cluster Resource Override Operator pod on a worker node in the clusterresourceoverride-operator namespace. You can move this pod to another node, such as an infrastructure node, as needed. Infrastructure nodes are not counted toward the total number of subscriptions that are required to run the environment. For more information, see "Moving the Cluster Resource Override Operator pods".

Prerequisites

  • The Cluster Resource Override Operator has no effect if limits have not been set on containers. You must specify default limits for a project using a LimitRange object or configure limits in Pod specs for the overrides to apply.

Procedure

To install the Cluster Resource Override Operator using the CLI:

  1. Create a namespace for the Cluster Resource Override Operator:

    1. Create a Namespace object YAML file (for example, cro-namespace.yaml) for the Cluster Resource Override Operator:

      apiVersion: v1
      kind: Namespace
      metadata:
        name: clusterresourceoverride-operator
    2. Create the namespace:

      $ oc create -f <file-name>.yaml

      For example:

      $ oc create -f cro-namespace.yaml
  2. Create an Operator group:

    1. Create an OperatorGroup object YAML file (for example, cro-og.yaml) for the Cluster Resource Override Operator:

      apiVersion: operators.coreos.com/v1
      kind: OperatorGroup
      metadata:
        name: clusterresourceoverride-operator
        namespace: clusterresourceoverride-operator
      spec:
        targetNamespaces:
          - clusterresourceoverride-operator
    2. Create the Operator Group:

      $ oc create -f <file-name>.yaml

      For example:

      $ oc create -f cro-og.yaml
  3. Create a subscription:

    1. Create a Subscription object YAML file (for example, cro-sub.yaml) for the Cluster Resource Override Operator:

      apiVersion: operators.coreos.com/v1alpha1
      kind: Subscription
      metadata:
        name: clusterresourceoverride
        namespace: clusterresourceoverride-operator
      spec:
        channel: "4.17"
        name: clusterresourceoverride
        source: redhat-operators
        sourceNamespace: openshift-marketplace
    2. Create the subscription:

      $ oc create -f <file-name>.yaml

      For example:

      $ oc create -f cro-sub.yaml
  4. Create a ClusterResourceOverride custom resource (CR) object in the clusterresourceoverride-operator namespace:

    1. Change to the clusterresourceoverride-operator namespace.

      $ oc project clusterresourceoverride-operator
    2. Create a ClusterResourceOverride object YAML file (for example, cro-cr.yaml) for the Cluster Resource Override Operator:

      apiVersion: operator.autoscaling.openshift.io/v1
      kind: ClusterResourceOverride
      metadata:
          name: cluster 1
      spec:
        podResourceOverride:
          spec:
            memoryRequestToLimitPercent: 50 2
            cpuRequestToLimitPercent: 25 3
            limitCPUToMemoryPercent: 200 4
      1
      The name must be cluster.
      2
      Optional: Specify the percentage to override the container memory limit, if used, between 1-100. The default is 50.
      3
      Optional: Specify the percentage to override the container CPU limit, if used, between 1-100. The default is 25.
      4
      Optional: Specify the percentage to override the container memory limit, if used. Scaling 1 Gi of RAM at 100 percent is equal to 1 CPU core. This is processed before overriding the CPU request, if configured. The default is 200.
    3. Create the ClusterResourceOverride object:

      $ oc create -f <file-name>.yaml

      For example:

      $ oc create -f cro-cr.yaml
  5. Verify the current state of the admission webhook by checking the status of the cluster custom resource.

    $ oc get clusterresourceoverride cluster -n clusterresourceoverride-operator -o yaml

    The mutatingWebhookConfigurationRef section appears when the webhook is called.

    Example output

    apiVersion: operator.autoscaling.openshift.io/v1
    kind: ClusterResourceOverride
    metadata:
      annotations:
        kubectl.kubernetes.io/last-applied-configuration: |
          {"apiVersion":"operator.autoscaling.openshift.io/v1","kind":"ClusterResourceOverride","metadata":{"annotations":{},"name":"cluster"},"spec":{"podResourceOverride":{"spec":{"cpuRequestToLimitPercent":25,"limitCPUToMemoryPercent":200,"memoryRequestToLimitPercent":50}}}}
      creationTimestamp: "2019-12-18T22:35:02Z"
      generation: 1
      name: cluster
      resourceVersion: "127622"
      selfLink: /apis/operator.autoscaling.openshift.io/v1/clusterresourceoverrides/cluster
      uid: 978fc959-1717-4bd1-97d0-ae00ee111e8d
    spec:
      podResourceOverride:
        spec:
          cpuRequestToLimitPercent: 25
          limitCPUToMemoryPercent: 200
          memoryRequestToLimitPercent: 50
    status:
    
    # ...
    
        mutatingWebhookConfigurationRef: 1
          apiVersion: admissionregistration.k8s.io/v1
          kind: MutatingWebhookConfiguration
          name: clusterresourceoverrides.admission.autoscaling.openshift.io
          resourceVersion: "127621"
          uid: 98b3b8ae-d5ce-462b-8ab5-a729ea8f38f3
    
    # ...

    1
    Reference to the ClusterResourceOverride admission webhook.

5.10.3. Configuring cluster-level overcommit

The Cluster Resource Override Operator requires a ClusterResourceOverride custom resource (CR) and a label for each project where you want the Operator to control overcommit.

By default, the installation process creates two Cluster Resource Override pods on the control plane nodes in the clusterresourceoverride-operator namespace. You can move these pods to other nodes, such as infrastructure nodes, as needed. Infrastructure nodes are not counted toward the total number of subscriptions that are required to run the environment. For more information, see "Moving the Cluster Resource Override Operator pods".

Prerequisites

  • The Cluster Resource Override Operator has no effect if limits have not been set on containers. You must specify default limits for a project using a LimitRange object or configure limits in Pod specs for the overrides to apply.

Procedure

To modify cluster-level overcommit:

  1. Edit the ClusterResourceOverride CR:

    apiVersion: operator.autoscaling.openshift.io/v1
    kind: ClusterResourceOverride
    metadata:
        name: cluster
    spec:
      podResourceOverride:
        spec:
          memoryRequestToLimitPercent: 50 1
          cpuRequestToLimitPercent: 25 2
          limitCPUToMemoryPercent: 200 3
    # ...
    1
    Optional: Specify the percentage to override the container memory limit, if used, between 1-100. The default is 50.
    2
    Optional: Specify the percentage to override the container CPU limit, if used, between 1-100. The default is 25.
    3
    Optional: Specify the percentage to override the container memory limit, if used. Scaling 1Gi of RAM at 100 percent is equal to 1 CPU core. This is processed before overriding the CPU request, if configured. The default is 200.
  2. Ensure the following label has been added to the Namespace object for each project where you want the Cluster Resource Override Operator to control overcommit:

    apiVersion: v1
    kind: Namespace
    metadata:
    
    # ...
    
      labels:
        clusterresourceoverrides.admission.autoscaling.openshift.io/enabled: "true" 1
    
    # ...
    1
    Add this label to each project.

5.11. Node-level overcommit

You can use various ways to control overcommit on specific nodes, such as quality of service (QOS) guarantees, CPU limits, or reserve resources. You can also disable overcommit for specific nodes and specific projects.

5.11.1. Understanding compute resources and containers

The node-enforced behavior for compute resources is specific to the resource type.

5.11.1.1. Understanding container CPU requests

A container is guaranteed the amount of CPU it requests and is additionally able to consume excess CPU available on the node, up to any limit specified by the container. If multiple containers are attempting to use excess CPU, CPU time is distributed based on the amount of CPU requested by each container.

For example, if one container requested 500m of CPU time and another container requested 250m of CPU time, then any extra CPU time available on the node is distributed among the containers in a 2:1 ratio. If a container specified a limit, it will be throttled not to use more CPU than the specified limit. CPU requests are enforced using the CFS shares support in the Linux kernel. By default, CPU limits are enforced using the CFS quota support in the Linux kernel over a 100ms measuring interval, though this can be disabled.

5.11.1.2. Understanding container memory requests

A container is guaranteed the amount of memory it requests. A container can use more memory than requested, but once it exceeds its requested amount, it could be terminated in a low memory situation on the node. If a container uses less memory than requested, it will not be terminated unless system tasks or daemons need more memory than was accounted for in the node’s resource reservation. If a container specifies a limit on memory, it is immediately terminated if it exceeds the limit amount.

5.11.2. Understanding overcomitment and quality of service classes

A node is overcommitted when it has a pod scheduled that makes no request, or when the sum of limits across all pods on that node exceeds available machine capacity.

In an overcommitted environment, it is possible that the pods on the node will attempt to use more compute resource than is available at any given point in time. When this occurs, the node must give priority to one pod over another. The facility used to make this decision is referred to as a Quality of Service (QoS) Class.

A pod is designated as one of three QoS classes with decreasing order of priority:

Table 5.2. Quality of Service Classes
PriorityClass NameDescription

1 (highest)

Guaranteed

If limits and optionally requests are set (not equal to 0) for all resources and they are equal, then the pod is classified as Guaranteed.

2

Burstable

If requests and optionally limits are set (not equal to 0) for all resources, and they are not equal, then the pod is classified as Burstable.

3 (lowest)

BestEffort

If requests and limits are not set for any of the resources, then the pod is classified as BestEffort.

Memory is an incompressible resource, so in low memory situations, containers that have the lowest priority are terminated first:

  • Guaranteed containers are considered top priority, and are guaranteed to only be terminated if they exceed their limits, or if the system is under memory pressure and there are no lower priority containers that can be evicted.
  • Burstable containers under system memory pressure are more likely to be terminated once they exceed their requests and no other BestEffort containers exist.
  • BestEffort containers are treated with the lowest priority. Processes in these containers are first to be terminated if the system runs out of memory.
5.11.2.1. Understanding how to reserve memory across quality of service tiers

You can use the qos-reserved parameter to specify a percentage of memory to be reserved by a pod in a particular QoS level. This feature attempts to reserve requested resources to exclude pods from lower OoS classes from using resources requested by pods in higher QoS classes.

OpenShift Container Platform uses the qos-reserved parameter as follows:

  • A value of qos-reserved=memory=100% will prevent the Burstable and BestEffort QoS classes from consuming memory that was requested by a higher QoS class. This increases the risk of inducing OOM on BestEffort and Burstable workloads in favor of increasing memory resource guarantees for Guaranteed and Burstable workloads.
  • A value of qos-reserved=memory=50% will allow the Burstable and BestEffort QoS classes to consume half of the memory requested by a higher QoS class.
  • A value of qos-reserved=memory=0% will allow a Burstable and BestEffort QoS classes to consume up to the full node allocatable amount if available, but increases the risk that a Guaranteed workload will not have access to requested memory. This condition effectively disables this feature.

5.11.3. Understanding swap memory and QOS

You can disable swap by default on your nodes to preserve quality of service (QOS) guarantees. Otherwise, physical resources on a node can oversubscribe, affecting the resource guarantees the Kubernetes scheduler makes during pod placement.

For example, if two guaranteed pods have reached their memory limit, each container could start using swap memory. Eventually, if there is not enough swap space, processes in the pods can be terminated due to the system being oversubscribed.

Failing to disable swap results in nodes not recognizing that they are experiencing MemoryPressure, resulting in pods not receiving the memory they made in their scheduling request. As a result, additional pods are placed on the node to further increase memory pressure, ultimately increasing your risk of experiencing a system out of memory (OOM) event.

Important

If swap is enabled, any out-of-resource handling eviction thresholds for available memory will not work as expected. Take advantage of out-of-resource handling to allow pods to be evicted from a node when it is under memory pressure, and rescheduled on an alternative node that has no such pressure.

5.11.4. Understanding nodes overcommitment

In an overcommitted environment, it is important to properly configure your node to provide best system behavior.

When the node starts, it ensures that the kernel tunable flags for memory management are set properly. The kernel should never fail memory allocations unless it runs out of physical memory.

To ensure this behavior, OpenShift Container Platform configures the kernel to always overcommit memory by setting the vm.overcommit_memory parameter to 1, overriding the default operating system setting.

OpenShift Container Platform also configures the kernel not to panic when it runs out of memory by setting the vm.panic_on_oom parameter to 0. A setting of 0 instructs the kernel to call oom_killer in an Out of Memory (OOM) condition, which kills processes based on priority.

You can view the current setting by running the following commands on your nodes:

$ sysctl -a |grep commit

Example output

#...
vm.overcommit_memory = 0
#...

$ sysctl -a |grep panic

Example output

#...
vm.panic_on_oom = 0
#...

Note

The above flags should already be set on nodes, and no further action is required.

You can also perform the following configurations for each node:

  • Disable or enforce CPU limits using CPU CFS quotas
  • Reserve resources for system processes
  • Reserve memory across quality of service tiers

5.11.5. Disabling or enforcing CPU limits using CPU CFS quotas

Nodes by default enforce specified CPU limits using the Completely Fair Scheduler (CFS) quota support in the Linux kernel.

If you disable CPU limit enforcement, it is important to understand the impact on your node:

  • If a container has a CPU request, the request continues to be enforced by CFS shares in the Linux kernel.
  • If a container does not have a CPU request, but does have a CPU limit, the CPU request defaults to the specified CPU limit, and is enforced by CFS shares in the Linux kernel.
  • If a container has both a CPU request and limit, the CPU request is enforced by CFS shares in the Linux kernel, and the CPU limit has no impact on the node.

Prerequisites

  • Obtain the label associated with the static MachineConfigPool CRD for the type of node you want to configure by entering the following command:

    $ oc edit machineconfigpool <name>

    For example:

    $ oc edit machineconfigpool worker

    Example output

    apiVersion: machineconfiguration.openshift.io/v1
    kind: MachineConfigPool
    metadata:
      creationTimestamp: "2022-11-16T15:34:25Z"
      generation: 4
      labels:
        pools.operator.machineconfiguration.openshift.io/worker: "" 1
      name: worker

    1
    The label appears under Labels.
    Tip

    If the label is not present, add a key/value pair such as:

    $ oc label machineconfigpool worker custom-kubelet=small-pods

Procedure

  1. Create a custom resource (CR) for your configuration change.

    Sample configuration for a disabling CPU limits

    apiVersion: machineconfiguration.openshift.io/v1
    kind: KubeletConfig
    metadata:
      name: disable-cpu-units 1
    spec:
      machineConfigPoolSelector:
        matchLabels:
          pools.operator.machineconfiguration.openshift.io/worker: "" 2
      kubeletConfig:
        cpuCfsQuota: false 3

    1
    Assign a name to CR.
    2
    Specify the label from the machine config pool.
    3
    Set the cpuCfsQuota parameter to false.
  2. Run the following command to create the CR:

    $ oc create -f <file_name>.yaml

5.11.6. Reserving resources for system processes

To provide more reliable scheduling and minimize node resource overcommitment, each node can reserve a portion of its resources for use by system daemons that are required to run on your node for your cluster to function. In particular, it is recommended that you reserve resources for incompressible resources such as memory.

Procedure

To explicitly reserve resources for non-pod processes, allocate node resources by specifying resources available for scheduling. For more details, see Allocating Resources for Nodes.

5.11.7. Disabling overcommitment for a node

When enabled, overcommitment can be disabled on each node.

Procedure

To disable overcommitment in a node run the following command on that node:

$ sysctl -w vm.overcommit_memory=0

5.12. Project-level limits

To help control overcommit, you can set per-project resource limit ranges, specifying memory and CPU limits and defaults for a project that overcommit cannot exceed.

For information on project-level resource limits, see Additional resources.

Alternatively, you can disable overcommitment for specific projects.

5.12.1. Disabling overcommitment for a project

When enabled, overcommitment can be disabled per-project. For example, you can allow infrastructure components to be configured independently of overcommitment.

Procedure

  1. Create or edit the namespace object file.
  2. Add the following annotation:

    apiVersion: v1
    kind: Namespace
    metadata:
      annotations:
        quota.openshift.io/cluster-resource-override-enabled: "false" <.>
    # ...

    <.> Setting this annotation to false disables overcommit for this namespace.

5.13. Freeing node resources using garbage collection

Understand and use garbage collection.

5.13.1. Understanding how terminated containers are removed through garbage collection

Container garbage collection removes terminated containers by using eviction thresholds.

When eviction thresholds are set for garbage collection, the node tries to keep any container for any pod accessible from the API. If the pod has been deleted, the containers will be as well. Containers are preserved as long the pod is not deleted and the eviction threshold is not reached. If the node is under disk pressure, it will remove containers and their logs will no longer be accessible using oc logs.

  • eviction-soft - A soft eviction threshold pairs an eviction threshold with a required administrator-specified grace period.
  • eviction-hard - A hard eviction threshold has no grace period, and if observed, OpenShift Container Platform takes immediate action.

The following table lists the eviction thresholds:

Table 5.3. Variables for configuring container garbage collection
Node conditionEviction signalDescription

MemoryPressure

memory.available

The available memory on the node.

DiskPressure

  • nodefs.available
  • nodefs.inodesFree
  • imagefs.available
  • imagefs.inodesFree

The available disk space or inodes on the node root file system, nodefs, or image file system, imagefs.

Note

For evictionHard you must specify all of these parameters. If you do not specify all parameters, only the specified parameters are applied and the garbage collection will not function properly.

If a node is oscillating above and below a soft eviction threshold, but not exceeding its associated grace period, the corresponding node would constantly oscillate between true and false. As a consequence, the scheduler could make poor scheduling decisions.

To protect against this oscillation, use the eviction-pressure-transition-period flag to control how long OpenShift Container Platform must wait before transitioning out of a pressure condition. OpenShift Container Platform will not set an eviction threshold as being met for the specified pressure condition for the period specified before toggling the condition back to false.

5.13.2. Understanding how images are removed through garbage collection

Image garbage collection removes images that are not referenced by any running pods.

OpenShift Container Platform determines which images to remove from a node based on the disk usage that is reported by cAdvisor.

The policy for image garbage collection is based on two conditions:

  • The percent of disk usage (expressed as an integer) which triggers image garbage collection. The default is 85.
  • The percent of disk usage (expressed as an integer) to which image garbage collection attempts to free. Default is 80.

For image garbage collection, you can modify any of the following variables using a custom resource.

Table 5.4. Variables for configuring image garbage collection
SettingDescription

imageMinimumGCAge

The minimum age for an unused image before the image is removed by garbage collection. The default is 2m.

imageGCHighThresholdPercent

The percent of disk usage, expressed as an integer, which triggers image garbage collection. The default is 85.

imageGCLowThresholdPercent

The percent of disk usage, expressed as an integer, to which image garbage collection attempts to free. The default is 80.

Two lists of images are retrieved in each garbage collector run:

  1. A list of images currently running in at least one pod.
  2. A list of images available on a host.

As new containers are run, new images appear. All images are marked with a time stamp. If the image is running (the first list above) or is newly detected (the second list above), it is marked with the current time. The remaining images are already marked from the previous spins. All images are then sorted by the time stamp.

Once the collection starts, the oldest images get deleted first until the stopping criterion is met.

5.13.3. Configuring garbage collection for containers and images

As an administrator, you can configure how OpenShift Container Platform performs garbage collection by creating a kubeletConfig object for each machine config pool.

Note

OpenShift Container Platform supports only one kubeletConfig object for each machine config pool.

You can configure any combination of the following:

  • Soft eviction for containers
  • Hard eviction for containers
  • Eviction for images

Container garbage collection removes terminated containers. Image garbage collection removes images that are not referenced by any running pods.

Prerequisites

  1. Obtain the label associated with the static MachineConfigPool CRD for the type of node you want to configure by entering the following command:

    $ oc edit machineconfigpool <name>

    For example:

    $ oc edit machineconfigpool worker

    Example output

    apiVersion: machineconfiguration.openshift.io/v1
    kind: MachineConfigPool
    metadata:
      creationTimestamp: "2022-11-16T15:34:25Z"
      generation: 4
      labels:
        pools.operator.machineconfiguration.openshift.io/worker: "" 1
      name: worker
    #...

    1
    The label appears under Labels.
    Tip

    If the label is not present, add a key/value pair such as:

    $ oc label machineconfigpool worker custom-kubelet=small-pods

Procedure

  1. Create a custom resource (CR) for your configuration change.

    Important

    If there is one file system, or if /var/lib/kubelet and /var/lib/containers/ are in the same file system, the settings with the highest values trigger evictions, as those are met first. The file system triggers the eviction.

    Sample configuration for a container garbage collection CR

    apiVersion: machineconfiguration.openshift.io/v1
    kind: KubeletConfig
    metadata:
      name: worker-kubeconfig 1
    spec:
      machineConfigPoolSelector:
        matchLabels:
          pools.operator.machineconfiguration.openshift.io/worker: "" 2
      kubeletConfig:
        evictionSoft: 3
          memory.available: "500Mi" 4
          nodefs.available: "10%"
          nodefs.inodesFree: "5%"
          imagefs.available: "15%"
          imagefs.inodesFree: "10%"
        evictionSoftGracePeriod:  5
          memory.available: "1m30s"
          nodefs.available: "1m30s"
          nodefs.inodesFree: "1m30s"
          imagefs.available: "1m30s"
          imagefs.inodesFree: "1m30s"
        evictionHard: 6
          memory.available: "200Mi"
          nodefs.available: "5%"
          nodefs.inodesFree: "4%"
          imagefs.available: "10%"
          imagefs.inodesFree: "5%"
        evictionPressureTransitionPeriod: 0s 7
        imageMinimumGCAge: 5m 8
        imageGCHighThresholdPercent: 80 9
        imageGCLowThresholdPercent: 75 10
    #...

    1
    Name for the object.
    2
    Specify the label from the machine config pool.
    3
    For container garbage collection: Type of eviction: evictionSoft or evictionHard.
    4
    For container garbage collection: Eviction thresholds based on a specific eviction trigger signal.
    5
    For container garbage collection: Grace periods for the soft eviction. This parameter does not apply to eviction-hard.
    6
    For container garbage collection: Eviction thresholds based on a specific eviction trigger signal. For evictionHard you must specify all of these parameters. If you do not specify all parameters, only the specified parameters are applied and the garbage collection will not function properly.
    7
    For container garbage collection: The duration to wait before transitioning out of an eviction pressure condition.
    8
    For image garbage collection: The minimum age for an unused image before the image is removed by garbage collection.
    9
    For image garbage collection: The percent of disk usage (expressed as an integer) that triggers image garbage collection.
    10
    For image garbage collection: The percent of disk usage (expressed as an integer) that image garbage collection attempts to free.
  2. Run the following command to create the CR:

    $ oc create -f <file_name>.yaml

    For example:

    $ oc create -f gc-container.yaml

    Example output

    kubeletconfig.machineconfiguration.openshift.io/gc-container created

Verification

  1. Verify that garbage collection is active by entering the following command. The Machine Config Pool you specified in the custom resource appears with UPDATING as 'true` until the change is fully implemented:

    $ oc get machineconfigpool

    Example output

    NAME     CONFIG                                   UPDATED   UPDATING
    master   rendered-master-546383f80705bd5aeaba93   True      False
    worker   rendered-worker-b4c51bb33ccaae6fc4a6a5   False     True

5.14. Using the Node Tuning Operator

Understand and use the Node Tuning Operator.

Purpose

The Node Tuning Operator helps you manage node-level tuning by orchestrating the TuneD daemon and achieves low latency performance by using the Performance Profile controller. The majority of high-performance applications require some level of kernel tuning. The Node Tuning Operator provides a unified management interface to users of node-level sysctls and more flexibility to add custom tuning specified by user needs.

The Operator manages the containerized TuneD daemon for OpenShift Container Platform as a Kubernetes daemon set. It ensures the custom tuning specification is passed to all containerized TuneD daemons running in the cluster in the format that the daemons understand. The daemons run on all nodes in the cluster, one per node.

Node-level settings applied by the containerized TuneD daemon are rolled back on an event that triggers a profile change or when the containerized TuneD daemon is terminated gracefully by receiving and handling a termination signal.

The Node Tuning Operator uses the Performance Profile controller to implement automatic tuning to achieve low latency performance for OpenShift Container Platform applications.

The cluster administrator configures a performance profile to define node-level settings such as the following:

  • Updating the kernel to kernel-rt.
  • Choosing CPUs for housekeeping.
  • Choosing CPUs for running workloads.

The Node Tuning Operator is part of a standard OpenShift Container Platform installation in version 4.1 and later.

Note

In earlier versions of OpenShift Container Platform, the Performance Addon Operator was used to implement automatic tuning to achieve low latency performance for OpenShift applications. In OpenShift Container Platform 4.11 and later, this functionality is part of the Node Tuning Operator.

5.14.1. Accessing an example Node Tuning Operator specification

Use this process to access an example Node Tuning Operator specification.

Procedure

  • Run the following command to access an example Node Tuning Operator specification:

    oc get tuned.tuned.openshift.io/default -o yaml -n openshift-cluster-node-tuning-operator

The default CR is meant for delivering standard node-level tuning for the OpenShift Container Platform platform and it can only be modified to set the Operator Management state. Any other custom changes to the default CR will be overwritten by the Operator. For custom tuning, create your own Tuned CRs. Newly created CRs will be combined with the default CR and custom tuning applied to OpenShift Container Platform nodes based on node or pod labels and profile priorities.

Warning

While in certain situations the support for pod labels can be a convenient way of automatically delivering required tuning, this practice is discouraged and strongly advised against, especially in large-scale clusters. The default Tuned CR ships without pod label matching. If a custom profile is created with pod label matching, then the functionality will be enabled at that time. The pod label functionality will be deprecated in future versions of the Node Tuning Operator.

5.14.2. Custom tuning specification

The custom resource (CR) for the Operator has two major sections. The first section, profile:, is a list of TuneD profiles and their names. The second, recommend:, defines the profile selection logic.

Multiple custom tuning specifications can co-exist as multiple CRs in the Operator’s namespace. The existence of new CRs or the deletion of old CRs is detected by the Operator. All existing custom tuning specifications are merged and appropriate objects for the containerized TuneD daemons are updated.

Management state

The Operator Management state is set by adjusting the default Tuned CR. By default, the Operator is in the Managed state and the spec.managementState field is not present in the default Tuned CR. Valid values for the Operator Management state are as follows:

  • Managed: the Operator will update its operands as configuration resources are updated
  • Unmanaged: the Operator will ignore changes to the configuration resources
  • Removed: the Operator will remove its operands and resources the Operator provisioned

Profile data

The profile: section lists TuneD profiles and their names.

profile:
- name: tuned_profile_1
  data: |
    # TuneD profile specification
    [main]
    summary=Description of tuned_profile_1 profile

    [sysctl]
    net.ipv4.ip_forward=1
    # ... other sysctl's or other TuneD daemon plugins supported by the containerized TuneD

# ...

- name: tuned_profile_n
  data: |
    # TuneD profile specification
    [main]
    summary=Description of tuned_profile_n profile

    # tuned_profile_n profile settings

Recommended profiles

The profile: selection logic is defined by the recommend: section of the CR. The recommend: section is a list of items to recommend the profiles based on a selection criteria.

recommend:
<recommend-item-1>
# ...
<recommend-item-n>

The individual items of the list:

- machineConfigLabels: 1
    <mcLabels> 2
  match: 3
    <match> 4
  priority: <priority> 5
  profile: <tuned_profile_name> 6
  operand: 7
    debug: <bool> 8
    tunedConfig:
      reapply_sysctl: <bool> 9
1
Optional.
2
A dictionary of key/value MachineConfig labels. The keys must be unique.
3
If omitted, profile match is assumed unless a profile with a higher priority matches first or machineConfigLabels is set.
4
An optional list.
5
Profile ordering priority. Lower numbers mean higher priority (0 is the highest priority).
6
A TuneD profile to apply on a match. For example tuned_profile_1.
7
Optional operand configuration.
8
Turn debugging on or off for the TuneD daemon. Options are true for on or false for off. The default is false.
9
Turn reapply_sysctl functionality on or off for the TuneD daemon. Options are true for on and false for off.

<match> is an optional list recursively defined as follows:

- label: <label_name> 1
  value: <label_value> 2
  type: <label_type> 3
    <match> 4
1
Node or pod label name.
2
Optional node or pod label value. If omitted, the presence of <label_name> is enough to match.
3
Optional object type (node or pod). If omitted, node is assumed.
4
An optional <match> list.

If <match> is not omitted, all nested <match> sections must also evaluate to true. Otherwise, false is assumed and the profile with the respective <match> section will not be applied or recommended. Therefore, the nesting (child <match> sections) works as logical AND operator. Conversely, if any item of the <match> list matches, the entire <match> list evaluates to true. Therefore, the list acts as logical OR operator.

If machineConfigLabels is defined, machine config pool based matching is turned on for the given recommend: list item. <mcLabels> specifies the labels for a machine config. The machine config is created automatically to apply host settings, such as kernel boot parameters, for the profile <tuned_profile_name>. This involves finding all machine config pools with machine config selector matching <mcLabels> and setting the profile <tuned_profile_name> on all nodes that are assigned the found machine config pools. To target nodes that have both master and worker roles, you must use the master role.

The list items match and machineConfigLabels are connected by the logical OR operator. The match item is evaluated first in a short-circuit manner. Therefore, if it evaluates to true, the machineConfigLabels item is not considered.

Important

When using machine config pool based matching, it is advised to group nodes with the same hardware configuration into the same machine config pool. Not following this practice might result in TuneD operands calculating conflicting kernel parameters for two or more nodes sharing the same machine config pool.

Example: Node or pod label based matching

- match:
  - label: tuned.openshift.io/elasticsearch
    match:
    - label: node-role.kubernetes.io/master
    - label: node-role.kubernetes.io/infra
    type: pod
  priority: 10
  profile: openshift-control-plane-es
- match:
  - label: node-role.kubernetes.io/master
  - label: node-role.kubernetes.io/infra
  priority: 20
  profile: openshift-control-plane
- priority: 30
  profile: openshift-node

The CR above is translated for the containerized TuneD daemon into its recommend.conf file based on the profile priorities. The profile with the highest priority (10) is openshift-control-plane-es and, therefore, it is considered first. The containerized TuneD daemon running on a given node looks to see if there is a pod running on the same node with the tuned.openshift.io/elasticsearch label set. If not, the entire <match> section evaluates as false. If there is such a pod with the label, in order for the <match> section to evaluate to true, the node label also needs to be node-role.kubernetes.io/master or node-role.kubernetes.io/infra.

If the labels for the profile with priority 10 matched, openshift-control-plane-es profile is applied and no other profile is considered. If the node/pod label combination did not match, the second highest priority profile (openshift-control-plane) is considered. This profile is applied if the containerized TuneD pod runs on a node with labels node-role.kubernetes.io/master or node-role.kubernetes.io/infra.

Finally, the profile openshift-node has the lowest priority of 30. It lacks the <match> section and, therefore, will always match. It acts as a profile catch-all to set openshift-node profile, if no other profile with higher priority matches on a given node.

Decision workflow

Example: Machine config pool based matching

apiVersion: tuned.openshift.io/v1
kind: Tuned
metadata:
  name: openshift-node-custom
  namespace: openshift-cluster-node-tuning-operator
spec:
  profile:
  - data: |
      [main]
      summary=Custom OpenShift node profile with an additional kernel parameter
      include=openshift-node
      [bootloader]
      cmdline_openshift_node_custom=+skew_tick=1
    name: openshift-node-custom

  recommend:
  - machineConfigLabels:
      machineconfiguration.openshift.io/role: "worker-custom"
    priority: 20
    profile: openshift-node-custom

To minimize node reboots, label the target nodes with a label the machine config pool’s node selector will match, then create the Tuned CR above and finally create the custom machine config pool itself.

Cloud provider-specific TuneD profiles

With this functionality, all Cloud provider-specific nodes can conveniently be assigned a TuneD profile specifically tailored to a given Cloud provider on a OpenShift Container Platform cluster. This can be accomplished without adding additional node labels or grouping nodes into machine config pools.

This functionality takes advantage of spec.providerID node object values in the form of <cloud-provider>://<cloud-provider-specific-id> and writes the file /var/lib/ocp-tuned/provider with the value <cloud-provider> in NTO operand containers. The content of this file is then used by TuneD to load provider-<cloud-provider> profile if such profile exists.

The openshift profile that both openshift-control-plane and openshift-node profiles inherit settings from is now updated to use this functionality through the use of conditional profile loading. Neither NTO nor TuneD currently include any Cloud provider-specific profiles. However, it is possible to create a custom profile provider-<cloud-provider> that will be applied to all Cloud provider-specific cluster nodes.

Example GCE Cloud provider profile

apiVersion: tuned.openshift.io/v1
kind: Tuned
metadata:
  name: provider-gce
  namespace: openshift-cluster-node-tuning-operator
spec:
  profile:
  - data: |
      [main]
      summary=GCE Cloud provider-specific profile
      # Your tuning for GCE Cloud provider goes here.
    name: provider-gce

Note

Due to profile inheritance, any setting specified in the provider-<cloud-provider> profile will be overwritten by the openshift profile and its child profiles.

5.14.3. Default profiles set on a cluster

The following are the default profiles set on a cluster.

apiVersion: tuned.openshift.io/v1
kind: Tuned
metadata:
  name: default
  namespace: openshift-cluster-node-tuning-operator
spec:
  profile:
  - data: |
      [main]
      summary=Optimize systems running OpenShift (provider specific parent profile)
      include=-provider-${f:exec:cat:/var/lib/ocp-tuned/provider},openshift
    name: openshift
  recommend:
  - profile: openshift-control-plane
    priority: 30
    match:
    - label: node-role.kubernetes.io/master
    - label: node-role.kubernetes.io/infra
  - profile: openshift-node
    priority: 40

Starting with OpenShift Container Platform 4.9, all OpenShift TuneD profiles are shipped with the TuneD package. You can use the oc exec command to view the contents of these profiles:

$ oc exec $tuned_pod -n openshift-cluster-node-tuning-operator -- find /usr/lib/tuned/openshift{,-control-plane,-node} -name tuned.conf -exec grep -H ^ {} \;

5.14.4. Supported TuneD daemon plugins

Excluding the [main] section, the following TuneD plugins are supported when using custom profiles defined in the profile: section of the Tuned CR:

  • audio
  • cpu
  • disk
  • eeepc_she
  • modules
  • mounts
  • net
  • scheduler
  • scsi_host
  • selinux
  • sysctl
  • sysfs
  • usb
  • video
  • vm
  • bootloader

There is some dynamic tuning functionality provided by some of these plugins that is not supported. The following TuneD plugins are currently not supported:

  • script
  • systemd
Note

The TuneD bootloader plugin only supports Red Hat Enterprise Linux CoreOS (RHCOS) worker nodes.

5.15. Configuring the maximum number of pods per node

Two parameters control the maximum number of pods that can be scheduled to a node: podsPerCore and maxPods. If you use both options, the lower of the two limits the number of pods on a node.

For example, if podsPerCore is set to 10 on a node with 4 processor cores, the maximum number of pods allowed on the node will be 40.

Prerequisites

  1. Obtain the label associated with the static MachineConfigPool CRD for the type of node you want to configure by entering the following command:

    $ oc edit machineconfigpool <name>

    For example:

    $ oc edit machineconfigpool worker

    Example output

    apiVersion: machineconfiguration.openshift.io/v1
    kind: MachineConfigPool
    metadata:
      creationTimestamp: "2022-11-16T15:34:25Z"
      generation: 4
      labels:
        pools.operator.machineconfiguration.openshift.io/worker: "" 1
      name: worker
    #...

    1
    The label appears under Labels.
    Tip

    If the label is not present, add a key/value pair such as:

    $ oc label machineconfigpool worker custom-kubelet=small-pods

Procedure

  1. Create a custom resource (CR) for your configuration change.

    Sample configuration for a max-pods CR

    apiVersion: machineconfiguration.openshift.io/v1
    kind: KubeletConfig
    metadata:
      name: set-max-pods 1
    spec:
      machineConfigPoolSelector:
        matchLabels:
          pools.operator.machineconfiguration.openshift.io/worker: "" 2
      kubeletConfig:
        podsPerCore: 10 3
        maxPods: 250 4
    #...

    1
    Assign a name to CR.
    2
    Specify the label from the machine config pool.
    3
    Specify the number of pods the node can run based on the number of processor cores on the node.
    4
    Specify the number of pods the node can run to a fixed value, regardless of the properties of the node.
    Note

    Setting podsPerCore to 0 disables this limit.

    In the above example, the default value for podsPerCore is 10 and the default value for maxPods is 250. This means that unless the node has 25 cores or more, by default, podsPerCore will be the limiting factor.

  2. Run the following command to create the CR:

    $ oc create -f <file_name>.yaml

Verification

  1. List the MachineConfigPool CRDs to see if the change is applied. The UPDATING column reports True if the change is picked up by the Machine Config Controller:

    $ oc get machineconfigpools

    Example output

    NAME     CONFIG                        UPDATED   UPDATING   DEGRADED
    master   master-9cc2c72f205e103bb534   False     False      False
    worker   worker-8cecd1236b33ee3f8a5e   False     True       False

    Once the change is complete, the UPDATED column reports True.

    $ oc get machineconfigpools

    Example output

    NAME     CONFIG                        UPDATED   UPDATING   DEGRADED
    master   master-9cc2c72f205e103bb534   False     True       False
    worker   worker-8cecd1236b33ee3f8a5e   True      False      False

5.16. Machine scaling with static IP addresses

After you deployed your cluster to run nodes with static IP addresses, you can scale an instance of a machine or a machine set to use one of these static IP addresses.

5.16.1. Scaling machines to use static IP addresses

You can scale additional machine sets to use pre-defined static IP addresses on your cluster. For this configuration, you need to create a machine resource YAML file and then define static IP addresses in this file.

Prerequisites

  • You deployed a cluster that runs at least one node with a configured static IP address.

Procedure

  1. Create a machine resource YAML file and define static IP address network information in the network parameter.

    Example of a machine resource YAML file with static IP address information defined in the network parameter.

    apiVersion: machine.openshift.io/v1beta1
    kind: Machine
    metadata:
      creationTimestamp: null
      labels:
        machine.openshift.io/cluster-api-cluster: <infrastructure_id>
        machine.openshift.io/cluster-api-machine-role: <role>
        machine.openshift.io/cluster-api-machine-type: <role>
        machine.openshift.io/cluster-api-machineset: <infrastructure_id>-<role>
      name: <infrastructure_id>-<role>
      namespace: openshift-machine-api
    spec:
      lifecycleHooks: {}
      metadata: {}
      providerSpec:
        value:
          apiVersion: machine.openshift.io/v1beta1
          credentialsSecret:
            name: vsphere-cloud-credentials
          diskGiB: 120
          kind: VSphereMachineProviderSpec
          memoryMiB: 8192
          metadata:
            creationTimestamp: null
          network:
            devices:
            - gateway: 192.168.204.1 1
              ipAddrs:
              - 192.168.204.8/24 2
              nameservers: 3
              - 192.168.204.1
              networkName: qe-segment-204
          numCPUs: 4
          numCoresPerSocket: 2
          snapshot: ""
          template: <vm_template_name>
          userDataSecret:
            name: worker-user-data
          workspace:
            datacenter: <vcenter_data_center_name>
            datastore: <vcenter_datastore_name>
            folder: <vcenter_vm_folder_path>
            resourcepool: <vsphere_resource_pool>
            server: <vcenter_server_ip>
    status: {}

    1
    The IP address for the default gateway for the network interface.
    2
    Lists IPv4, IPv6, or both IP addresses that installation program passes to the network interface. Both IP families must use the same network interface for the default network.
    3
    Lists a DNS nameserver. You can define up to 3 DNS nameservers. Consider defining more than one DNS nameserver to take advantage of DNS resolution if that one DNS nameserver becomes unreachable.
    • Create a machine custom resource (CR) by entering the following command in your terminal:

      $ oc create -f <file_name>.yaml

5.16.2. Machine set scaling of machines with configured static IP addresses

You can use a machine set to scale machines with configured static IP addresses.

After you configure a machine set to request a static IP address for a machine, the machine controller creates an IPAddressClaim resource in the openshift-machine-api namespace. The external controller then creates an IPAddress resource and binds any static IP addresses to the IPAddressClaim resource.

Important

Your organization might use numerous types of IP address management (IPAM) services. If you want to enable a particular IPAM service on OpenShift Container Platform, you might need to manually create the IPAddressClaim resource in a YAML definition and then bind a static IP address to this resource by entering the following command in your oc CLI:

$ oc create -f <ipaddressclaim_filename>

The following demonstrates an example of an IPAddressClaim resource:

kind: IPAddressClaim
metadata:
  finalizers:
  - machine.openshift.io/ip-claim-protection
  name: cluster-dev-9n5wg-worker-0-m7529-claim-0-0
  namespace: openshift-machine-api
spec:
  poolRef:
    apiGroup: ipamcontroller.example.io
    kind: IPPool
    name: static-ci-pool
status: {}

The machine controller updates the machine with a status of IPAddressClaimed to indicate that a static IP address has successfully bound to the IPAddressClaim resource. The machine controller applies the same status to a machine with multiple IPAddressClaim resources that each contain a bound static IP address.The machine controller then creates a virtual machine and applies static IP addresses to any nodes listed in the providerSpec of a machine’s configuration.

5.16.3. Using a machine set to scale machines with configured static IP addresses

You can use a machine set to scale machines with configured static IP addresses.

The example in the procedure demonstrates the use of controllers for scaling machines in a machine set.

Prerequisites

  • You deployed a cluster that runs at least one node with a configured static IP address.

Procedure

  1. Configure a machine set by specifying IP pool information in the network.devices.addressesFromPools schema of the machine set’s YAML file:

    apiVersion: machine.openshift.io/v1beta1
    kind: MachineSet
    metadata:
      annotations:
        machine.openshift.io/memoryMb: "8192"
        machine.openshift.io/vCPU: "4"
      labels:
        machine.openshift.io/cluster-api-cluster: <infrastructure_id>
      name: <infrastructure_id>-<role>
      namespace: openshift-machine-api
    spec:
      replicas: 0
      selector:
        matchLabels:
          machine.openshift.io/cluster-api-cluster: <infrastructure_id>
          machine.openshift.io/cluster-api-machineset: <infrastructure_id>-<role>
      template:
        metadata:
          labels:
            ipam: "true"
            machine.openshift.io/cluster-api-cluster: <infrastructure_id>
            machine.openshift.io/cluster-api-machine-role: worker
            machine.openshift.io/cluster-api-machine-type: worker
            machine.openshift.io/cluster-api-machineset: <infrastructure_id>-<role>
        spec:
          lifecycleHooks: {}
          metadata: {}
          providerSpec:
            value:
              apiVersion: machine.openshift.io/v1beta1
              credentialsSecret:
                name: vsphere-cloud-credentials
              diskGiB: 120
              kind: VSphereMachineProviderSpec
              memoryMiB: 8192
              metadata: {}
              network:
                devices:
                - addressesFromPools: 1
                  - group: ipamcontroller.example.io
                    name: static-ci-pool
                    resource: IPPool
                  nameservers:
                  - "192.168.204.1" 2
                  networkName: qe-segment-204
              numCPUs: 4
              numCoresPerSocket: 2
              snapshot: ""
              template: rvanderp4-dev-9n5wg-rhcos-generated-region-generated-zone
              userDataSecret:
                name: worker-user-data
              workspace:
                datacenter: IBMCdatacenter
                datastore: /IBMCdatacenter/datastore/vsanDatastore
                folder: /IBMCdatacenter/vm/rvanderp4-dev-9n5wg
                resourcePool: /IBMCdatacenter/host/IBMCcluster//Resources
                server: vcenter.ibmc.devcluster.openshift.com
    1
    Specifies an IP pool, which lists a static IP address or a range of static IP addresses. The IP Pool can either be a reference to a custom resource definition (CRD) or a resource supported by the IPAddressClaims resource handler. The machine controller accesses static IP addresses listed in the machine set’s configuration and then allocates each address to each machine.
    2
    Lists a nameserver. You must specify a nameserver for nodes that receive static IP address, because the Dynamic Host Configuration Protocol (DHCP) network configuration does not support static IP addresses.
  2. Scale the machine set by entering the following commands in your oc CLI:

    $ oc scale --replicas=2 machineset <machineset> -n openshift-machine-api

    Or:

    $ oc edit machineset <machineset> -n openshift-machine-api

    After each machine is scaled up, the machine controller creates an IPAddresssClaim resource.

  3. Optional: Check that the IPAddressClaim resource exists in the openshift-machine-api namespace by entering the following command:

    $ oc get ipaddressclaims.ipam.cluster.x-k8s.io -n openshift-machine-api

    Example oc CLI output that lists two IP pools listed in the openshift-machine-api namespace

    NAME                                         POOL NAME        POOL KIND
    cluster-dev-9n5wg-worker-0-m7529-claim-0-0   static-ci-pool   IPPool
    cluster-dev-9n5wg-worker-0-wdqkt-claim-0-0   static-ci-pool   IPPool

  4. Create an IPAddress resource by entering the following command:

    $ oc create -f ipaddress.yaml

    The following example shows an IPAddress resource with defined network configuration information and one defined static IP address:

    apiVersion: ipam.cluster.x-k8s.io/v1alpha1
    kind: IPAddress
    metadata:
      name: cluster-dev-9n5wg-worker-0-m7529-ipaddress-0-0
      namespace: openshift-machine-api
    spec:
      address: 192.168.204.129
      claimRef: 1
        name: cluster-dev-9n5wg-worker-0-m7529-claim-0-0
      gateway: 192.168.204.1
      poolRef: 2
        apiGroup: ipamcontroller.example.io
        kind: IPPool
        name: static-ci-pool
      prefix: 23
    1
    The name of the target IPAddressClaim resource.
    2
    Details information about the static IP address or addresses from your nodes.
    Note

    By default, the external controller automatically scans any resources in the machine set for recognizable address pool types. When the external controller finds kind: IPPool defined in the IPAddress resource, the controller binds any static IP addresses to the IPAddressClaim resource.

  5. Update the IPAddressClaim status with a reference to the IPAddress resource:

    $ oc --type=merge patch IPAddressClaim cluster-dev-9n5wg-worker-0-m7529-claim-0-0 -p='{"status":{"addressRef": {"name": "cluster-dev-9n5wg-worker-0-m7529-ipaddress-0-0"}}}' -n openshift-machine-api --subresource=status

Chapter 6. Postinstallation network configuration

After installing OpenShift Container Platform, you can further expand and customize your network to your requirements.

6.1. Using the Cluster Network Operator

You can use the Cluster Network Operator (CNO) to deploy and manage cluster network components on an OpenShift Container Platform cluster, including the Container Network Interface (CNI) network plugin selected for the cluster during installation. For more information, see Cluster Network Operator in OpenShift Container Platform.

6.2. Network configuration tasks

6.2.1. Creating default network policies for a new project

As a cluster administrator, you can modify the new project template to automatically include NetworkPolicy objects when you create a new project.

6.2.1.1. Modifying the template for new projects

As a cluster administrator, you can modify the default project template so that new projects are created using your custom requirements.

To create your own custom project template:

Prerequisites

  • You have access to an OpenShift Container Platform cluster using an account with cluster-admin permissions.

Procedure

  1. Log in as a user with cluster-admin privileges.
  2. Generate the default project template:

    $ oc adm create-bootstrap-project-template -o yaml > template.yaml
  3. Use a text editor to modify the generated template.yaml file by adding objects or modifying existing objects.
  4. The project template must be created in the openshift-config namespace. Load your modified template:

    $ oc create -f template.yaml -n openshift-config
  5. Edit the project configuration resource using the web console or CLI.

    • Using the web console:

      1. Navigate to the AdministrationCluster Settings page.
      2. Click Configuration to view all configuration resources.
      3. Find the entry for Project and click Edit YAML.
    • Using the CLI:

      1. Edit the project.config.openshift.io/cluster resource:

        $ oc edit project.config.openshift.io/cluster
  6. Update the spec section to include the projectRequestTemplate and name parameters, and set the name of your uploaded project template. The default name is project-request.

    Project configuration resource with custom project template

    apiVersion: config.openshift.io/v1
    kind: Project
    metadata:
    # ...
    spec:
      projectRequestTemplate:
        name: <template_name>
    # ...

  7. After you save your changes, create a new project to verify that your changes were successfully applied.
6.2.1.2. Adding network policies to the new project template

As a cluster administrator, you can add network policies to the default template for new projects. OpenShift Container Platform will automatically create all the NetworkPolicy objects specified in the template in the project.

Prerequisites

  • Your cluster uses a default CNI network plugin that supports NetworkPolicy objects, such as the OVN-Kubernetes.
  • You installed the OpenShift CLI (oc).
  • You must log in to the cluster with a user with cluster-admin privileges.
  • You must have created a custom default project template for new projects.

Procedure

  1. Edit the default template for a new project by running the following command:

    $ oc edit template <project_template> -n openshift-config

    Replace <project_template> with the name of the default template that you configured for your cluster. The default template name is project-request.

  2. In the template, add each NetworkPolicy object as an element to the objects parameter. The objects parameter accepts a collection of one or more objects.

    In the following example, the objects parameter collection includes several NetworkPolicy objects.

    objects:
    - apiVersion: networking.k8s.io/v1
      kind: NetworkPolicy
      metadata:
        name: allow-from-same-namespace
      spec:
        podSelector: {}
        ingress:
        - from:
          - podSelector: {}
    - apiVersion: networking.k8s.io/v1
      kind: NetworkPolicy
      metadata:
        name: allow-from-openshift-ingress
      spec:
        ingress:
        - from:
          - namespaceSelector:
              matchLabels:
                network.openshift.io/policy-group: ingress
        podSelector: {}
        policyTypes:
        - Ingress
    - apiVersion: networking.k8s.io/v1
      kind: NetworkPolicy
      metadata:
        name: allow-from-kube-apiserver-operator
      spec:
        ingress:
        - from:
          - namespaceSelector:
              matchLabels:
                kubernetes.io/metadata.name: openshift-kube-apiserver-operator
            podSelector:
              matchLabels:
                app: kube-apiserver-operator
        policyTypes:
        - Ingress
    ...
  3. Optional: Create a new project to confirm that your network policy objects are created successfully by running the following commands:

    1. Create a new project:

      $ oc new-project <project> 1
      1
      Replace <project> with the name for the project you are creating.
    2. Confirm that the network policy objects in the new project template exist in the new project:

      $ oc get networkpolicy
      NAME                           POD-SELECTOR   AGE
      allow-from-openshift-ingress   <none>         7s
      allow-from-same-namespace      <none>         7s

Chapter 7. Configuring image streams and image registries

You can update the global pull secret for your cluster by either replacing the current pull secret or appending a new pull secret. The procedure is required when users use a separate registry to store images than the registry used during installation. For more information, see Using image pull secrets.

For information about images and configuring image streams or image registries, see the following documentation:

7.1. Configuring image streams for a disconnected cluster

After installing OpenShift Container Platform in a disconnected environment, configure the image streams for the Cluster Samples Operator and the must-gather image stream.

7.1.1. Cluster Samples Operator assistance for mirroring

During installation, OpenShift Container Platform creates a config map named imagestreamtag-to-image in the openshift-cluster-samples-operator namespace. The imagestreamtag-to-image config map contains an entry, the populating image, for each image stream tag.

The format of the key for each entry in the data field in the config map is <image_stream_name>_<image_stream_tag_name>.

During a disconnected installation of OpenShift Container Platform, the status of the Cluster Samples Operator is set to Removed. If you choose to change it to Managed, it installs samples.

Note

The use of samples in a network-restricted or discontinued environment may require access to services external to your network. Some example services include: Github, Maven Central, npm, RubyGems, PyPi and others. There might be additional steps to take that allow the cluster samples operators’s objects to reach the services they require.

You can use this config map as a reference for which images need to be mirrored for your image streams to import.

  • While the Cluster Samples Operator is set to Removed, you can create your mirrored registry, or determine which existing mirrored registry you want to use.
  • Mirror the samples you want to the mirrored registry using the new config map as your guide.
  • Add any of the image streams you did not mirror to the skippedImagestreams list of the Cluster Samples Operator configuration object.
  • Set samplesRegistry of the Cluster Samples Operator configuration object to the mirrored registry.
  • Then set the Cluster Samples Operator to Managed to install the image streams you have mirrored.

7.1.2. Using Cluster Samples Operator image streams with alternate or mirrored registries

Most image streams in the openshift namespace managed by the Cluster Samples Operator point to images located in the Red Hat registry at registry.redhat.io.

Note

The cli, installer, must-gather, and tests image streams, while part of the install payload, are not managed by the Cluster Samples Operator. These are not addressed in this procedure.

Important

The Cluster Samples Operator must be set to Managed in a disconnected environment. To install the image streams, you have a mirrored registry.

Prerequisites

  • Access to the cluster as a user with the cluster-admin role.
  • Create a pull secret for your mirror registry.

Procedure

  1. Access the images of a specific image stream to mirror, for example:

    $ oc get is <imagestream> -n openshift -o json | jq .spec.tags[].from.name | grep registry.redhat.io
  2. Mirror images from registry.redhat.io associated with any image streams you need

    $ oc image mirror registry.redhat.io/rhscl/ruby-25-rhel7:latest ${MIRROR_ADDR}/rhscl/ruby-25-rhel7:latest
  3. Create the cluster’s image configuration object:

    $ oc create configmap registry-config --from-file=${MIRROR_ADDR_HOSTNAME}..5000=$path/ca.crt -n openshift-config
  4. Add the required trusted CAs for the mirror in the cluster’s image configuration object:

    $ oc patch image.config.openshift.io/cluster --patch '{"spec":{"additionalTrustedCA":{"name":"registry-config"}}}' --type=merge
  5. Update the samplesRegistry field in the Cluster Samples Operator configuration object to contain the hostname portion of the mirror location defined in the mirror configuration:

    $ oc edit configs.samples.operator.openshift.io -n openshift-cluster-samples-operator
    Note

    This is required because the image stream import process does not use the mirror or search mechanism at this time.

  6. Add any image streams that are not mirrored into the skippedImagestreams field of the Cluster Samples Operator configuration object. Or if you do not want to support any of the sample image streams, set the Cluster Samples Operator to Removed in the Cluster Samples Operator configuration object.

    Note

    The Cluster Samples Operator issues alerts if image stream imports are failing but the Cluster Samples Operator is either periodically retrying or does not appear to be retrying them.

    Many of the templates in the openshift namespace reference the image streams. So using Removed to purge both the image streams and templates will eliminate the possibility of attempts to use them if they are not functional because of any missing image streams.

7.1.3. Preparing your cluster to gather support data

Clusters using a restricted network must import the default must-gather image to gather debugging data for Red Hat support. The must-gather image is not imported by default, and clusters on a restricted network do not have access to the internet to pull the latest image from a remote repository.

Procedure

  1. If you have not added your mirror registry’s trusted CA to your cluster’s image configuration object as part of the Cluster Samples Operator configuration, perform the following steps:

    1. Create the cluster’s image configuration object:

      $ oc create configmap registry-config --from-file=${MIRROR_ADDR_HOSTNAME}..5000=$path/ca.crt -n openshift-config
    2. Add the required trusted CAs for the mirror in the cluster’s image configuration object:

      $ oc patch image.config.openshift.io/cluster --patch '{"spec":{"additionalTrustedCA":{"name":"registry-config"}}}' --type=merge
  2. Import the default must-gather image from your installation payload:

    $ oc import-image is/must-gather -n openshift

When running the oc adm must-gather command, use the --image flag and point to the payload image, as in the following example:

$ oc adm must-gather --image=$(oc adm release info --image-for must-gather)

7.2. Configuring periodic importing of Cluster Sample Operator image stream tags

You can ensure that you always have access to the latest versions of the Cluster Sample Operator images by periodically importing the image stream tags when new versions become available.

Procedure

  1. Fetch all the imagestreams in the openshift namespace by running the following command:

    oc get imagestreams -nopenshift
  2. Fetch the tags for every imagestream in the openshift namespace by running the following command:

    $ oc get is <image-stream-name> -o jsonpath="{range .spec.tags[*]}{.name}{'\t'}{.from.name}{'\n'}{end}" -nopenshift

    For example:

    $ oc get is ubi8-openjdk-17 -o jsonpath="{range .spec.tags[*]}{.name}{'\t'}{.from.name}{'\n'}{end}" -nopenshift

    Example output

    1.11	registry.access.redhat.com/ubi8/openjdk-17:1.11
    1.12	registry.access.redhat.com/ubi8/openjdk-17:1.12

  3. Schedule periodic importing of images for each tag present in the image stream by running the following command:

    $ oc tag <repository/image> <image-stream-name:tag> --scheduled -nopenshift

    For example:

    $ oc tag registry.access.redhat.com/ubi8/openjdk-17:1.11 ubi8-openjdk-17:1.11 --scheduled -nopenshift
    $ oc tag registry.access.redhat.com/ubi8/openjdk-17:1.12 ubi8-openjdk-17:1.12 --scheduled -nopenshift

    This command causes OpenShift Container Platform to periodically update this particular image stream tag. This period is a cluster-wide setting set to 15 minutes by default.

  4. Verify the scheduling status of the periodic import by running the following command:

    oc get imagestream <image-stream-name> -o jsonpath="{range .spec.tags[*]}Tag: {.name}{'\t'}Scheduled: {.importPolicy.scheduled}{'\n'}{end}" -nopenshift

    For example:

    oc get imagestream ubi8-openjdk-17 -o jsonpath="{range .spec.tags[*]}Tag: {.name}{'\t'}Scheduled: {.importPolicy.scheduled}{'\n'}{end}" -nopenshift

    Example output

    Tag: 1.11	Scheduled: true
    Tag: 1.12	Scheduled: true

Chapter 8. Postinstallation storage configuration

After installing OpenShift Container Platform, you can further expand and customize your cluster to your requirements, including storage configuration.

By default, containers operate by using the ephemeral storage or transient local storage. The ephemeral storage has a lifetime limitation. To store the data for a long time, you must configure persistent storage. You can configure storage by using one of the following methods:

Dynamic provisioning
You can dynamically provision storage on-demand by defining and creating storage classes that control different levels of storage, including storage access.
Static provisioning
You can use Kubernetes persistent volumes to make existing storage available to a cluster. Static provisioning can support various device configurations and mount options.

8.1. Dynamic provisioning

Dynamic Provisioning allows you to create storage volumes on-demand, eliminating the need for cluster administrators to pre-provision storage. See Dynamic provisioning.

8.2. Recommended configurable storage technology

The following table summarizes the recommended and configurable storage technologies for the given OpenShift Container Platform cluster application.

Table 8.1. Recommended and configurable storage technology
Storage typeBlockFileObject

1 ReadOnlyMany

2 ReadWriteMany

3 Prometheus is the underlying technology used for metrics.

4 This does not apply to physical disk, VM physical disk, VMDK, loopback over NFS, AWS EBS, and Azure Disk.

5 For metrics, using file storage with the ReadWriteMany (RWX) access mode is unreliable. If you use file storage, do not configure the RWX access mode on any persistent volume claims (PVCs) that are configured for use with metrics.

6 For logging, review the recommended storage solution in Configuring persistent storage for the log store section. Using NFS storage as a persistent volume or through NAS, such as Gluster, can corrupt the data. Hence, NFS is not supported for Elasticsearch storage and LokiStack log store in OpenShift Container Platform Logging. You must use one persistent volume type per log store.

7 Object storage is not consumed through OpenShift Container Platform’s PVs or PVCs. Apps must integrate with the object storage REST API.

ROX1

Yes4

Yes4

Yes

RWX2

No

Yes

Yes

Registry

Configurable

Configurable

Recommended

Scaled registry

Not configurable

Configurable

Recommended

Metrics3

Recommended

Configurable5

Not configurable

Elasticsearch Logging

Recommended

Configurable6

Not supported6

Loki Logging

Not configurable

Not configurable

Recommended

Apps

Recommended

Recommended

Not configurable7

Note

A scaled registry is an OpenShift image registry where two or more pod replicas are running.

8.2.1. Specific application storage recommendations

Important

Testing shows issues with using the NFS server on Red Hat Enterprise Linux (RHEL) as a storage backend for core services. This includes the OpenShift Container Registry and Quay, Prometheus for monitoring storage, and Elasticsearch for logging storage. Therefore, using RHEL NFS to back PVs used by core services is not recommended.

Other NFS implementations in the marketplace might not have these issues. Contact the individual NFS implementation vendor for more information on any testing that was possibly completed against these OpenShift Container Platform core components.

8.2.1.1. Registry

In a non-scaled/high-availability (HA) OpenShift image registry cluster deployment:

  • The storage technology does not have to support RWX access mode.
  • The storage technology must ensure read-after-write consistency.
  • The preferred storage technology is object storage followed by block storage.
  • File storage is not recommended for OpenShift image registry cluster deployment with production workloads.
8.2.1.2. Scaled registry

In a scaled/HA OpenShift image registry cluster deployment:

  • The storage technology must support RWX access mode.
  • The storage technology must ensure read-after-write consistency.
  • The preferred storage technology is object storage.
  • Red Hat OpenShift Data Foundation (ODF), Amazon Simple Storage Service (Amazon S3), Google Cloud Storage (GCS), Microsoft Azure Blob Storage, and OpenStack Swift are supported.
  • Object storage should be S3 or Swift compliant.
  • For non-cloud platforms, such as vSphere and bare metal installations, the only configurable technology is file storage.
  • Block storage is not configurable.
  • The use of Network File System (NFS) storage with OpenShift Container Platform is supported. However, the use of NFS storage with a scaled registry can cause known issues. For more information, see the Red Hat Knowledgebase solution, Is NFS supported for OpenShift cluster internal components in Production?.
8.2.1.3. Metrics

In an OpenShift Container Platform hosted metrics cluster deployment:

  • The preferred storage technology is block storage.
  • Object storage is not configurable.
Important

It is not recommended to use file storage for a hosted metrics cluster deployment with production workloads.

8.2.1.4. Logging

In an OpenShift Container Platform hosted logging cluster deployment:

  • Loki Operator:

    • The preferred storage technology is S3 compatible Object storage.
    • Block storage is not configurable.
  • OpenShift Elasticsearch Operator:

    • The preferred storage technology is block storage.
    • Object storage is not supported.
Note

As of logging version 5.4.3 the OpenShift Elasticsearch Operator is deprecated and is planned to be removed in a future release. Red Hat will provide bug fixes and support for this feature during the current release lifecycle, but this feature will no longer receive enhancements and will be removed. As an alternative to using the OpenShift Elasticsearch Operator to manage the default log storage, you can use the Loki Operator.

8.2.1.5. Applications

Application use cases vary from application to application, as described in the following examples:

  • Storage technologies that support dynamic PV provisioning have low mount time latencies, and are not tied to nodes to support a healthy cluster.
  • Application developers are responsible for knowing and understanding the storage requirements for their application, and how it works with the provided storage to ensure that issues do not occur when an application scales or interacts with the storage layer.

8.2.2. Other specific application storage recommendations

Important

It is not recommended to use RAID configurations on Write intensive workloads, such as etcd. If you are running etcd with a RAID configuration, you might be at risk of encountering performance issues with your workloads.

  • Red Hat OpenStack Platform (RHOSP) Cinder: RHOSP Cinder tends to be adept in ROX access mode use cases.
  • Databases: Databases (RDBMSs, NoSQL DBs, etc.) tend to perform best with dedicated block storage.
  • The etcd database must have enough storage and adequate performance capacity to enable a large cluster. Information about monitoring and benchmarking tools to establish ample storage and a high-performance environment is described in Recommended etcd practices.

8.3. Deploy Red Hat OpenShift Data Foundation

Red Hat OpenShift Data Foundation is a provider of agnostic persistent storage for OpenShift Container Platform supporting file, block, and object storage, either in-house or in hybrid clouds. As a Red Hat storage solution, Red Hat OpenShift Data Foundation is completely integrated with OpenShift Container Platform for deployment, management, and monitoring. For more information, see the Red Hat OpenShift Data Foundation documentation.

Important

OpenShift Data Foundation on top of Red Hat Hyperconverged Infrastructure (RHHI) for Virtualization, which uses hyperconverged nodes that host virtual machines installed with OpenShift Container Platform, is not a supported configuration. For more information about supported platforms, see the Red Hat OpenShift Data Foundation Supportability and Interoperability Guide.

If you are looking for Red Hat OpenShift Data Foundation information about…​See the following Red Hat OpenShift Data Foundation documentation:

What’s new, known issues, notable bug fixes, and Technology Previews

OpenShift Data Foundation 4.12 Release Notes

Supported workloads, layouts, hardware and software requirements, sizing and scaling recommendations

Planning your OpenShift Data Foundation 4.12 deployment

Instructions on deploying OpenShift Data Foundation to use an external Red Hat Ceph Storage cluster

Deploying OpenShift Data Foundation 4.12 in external mode

Instructions on deploying OpenShift Data Foundation to local storage on bare metal infrastructure

Deploying OpenShift Data Foundation 4.12 using bare metal infrastructure

Instructions on deploying OpenShift Data Foundation on Red Hat OpenShift Container Platform VMware vSphere clusters

Deploying OpenShift Data Foundation 4.12 on VMware vSphere

Instructions on deploying OpenShift Data Foundation using Amazon Web Services for local or cloud storage

Deploying OpenShift Data Foundation 4.12 using Amazon Web Services

Instructions on deploying and managing OpenShift Data Foundation on existing Red Hat OpenShift Container Platform Google Cloud clusters

Deploying and managing OpenShift Data Foundation 4.12 using Google Cloud

Instructions on deploying and managing OpenShift Data Foundation on existing Red Hat OpenShift Container Platform Azure clusters

Deploying and managing OpenShift Data Foundation 4.12 using Microsoft Azure

Instructions on deploying OpenShift Data Foundation to use local storage on IBM Power® infrastructure

Deploying OpenShift Data Foundation on IBM Power®

Instructions on deploying OpenShift Data Foundation to use local storage on IBM Z® infrastructure

Deploying OpenShift Data Foundation on IBM Z® infrastructure

Allocating storage to core services and hosted applications in Red Hat OpenShift Data Foundation, including snapshot and clone

Managing and allocating resources

Managing storage resources across a hybrid cloud or multicloud environment using the Multicloud Object Gateway (NooBaa)

Managing hybrid and multicloud resources

Safely replacing storage devices for Red Hat OpenShift Data Foundation

Replacing devices

Safely replacing a node in a Red Hat OpenShift Data Foundation cluster

Replacing nodes

Scaling operations in Red Hat OpenShift Data Foundation

Scaling storage

Monitoring a Red Hat OpenShift Data Foundation 4.12 cluster

Monitoring Red Hat OpenShift Data Foundation 4.12

Resolve issues encountered during operations

Troubleshooting OpenShift Data Foundation 4.12

Migrating your OpenShift Container Platform cluster from version 3 to version 4

Migration

Chapter 9. Preparing for users

After installing OpenShift Container Platform, you can further expand and customize your cluster to your requirements, including taking steps to prepare for users.

9.1. Understanding identity provider configuration

The OpenShift Container Platform control plane includes a built-in OAuth server. Developers and administrators obtain OAuth access tokens to authenticate themselves to the API.

As an administrator, you can configure OAuth to specify an identity provider after you install your cluster.

9.1.1. About identity providers in OpenShift Container Platform

By default, only a kubeadmin user exists on your cluster. To specify an identity provider, you must create a custom resource (CR) that describes that identity provider and add it to the cluster.

Note

OpenShift Container Platform user names containing /, :, and % are not supported.

9.1.2. Supported identity providers

You can configure the following types of identity providers:

Identity providerDescription

htpasswd

Configure the htpasswd identity provider to validate user names and passwords against a flat file generated using htpasswd.

Keystone

Configure the keystone identity provider to integrate your OpenShift Container Platform cluster with Keystone to enable shared authentication with an OpenStack Keystone v3 server configured to store users in an internal database.

LDAP

Configure the ldap identity provider to validate user names and passwords against an LDAPv3 server, using simple bind authentication.

Basic authentication

Configure a basic-authentication identity provider for users to log in to OpenShift Container Platform with credentials validated against a remote identity provider. Basic authentication is a generic backend integration mechanism.

Request header

Configure a request-header identity provider to identify users from request header values, such as X-Remote-User. It is typically used in combination with an authenticating proxy, which sets the request header value.

GitHub or GitHub Enterprise

Configure a github identity provider to validate user names and passwords against GitHub or GitHub Enterprise’s OAuth authentication server.

GitLab

Configure a gitlab identity provider to use GitLab.com or any other GitLab instance as an identity provider.

Google

Configure a google identity provider using Google’s OpenID Connect integration.

OpenID Connect

Configure an oidc identity provider to integrate with an OpenID Connect identity provider using an Authorization Code Flow.

After you define an identity provider, you can use RBAC to define and apply permissions.

9.1.3. Identity provider parameters

The following parameters are common to all identity providers:

ParameterDescription

name

The provider name is prefixed to provider user names to form an identity name.

mappingMethod

Defines how new identities are mapped to users when they log in. Enter one of the following values:

claim
The default value. Provisions a user with the identity’s preferred user name. Fails if a user with that user name is already mapped to another identity.
lookup
Looks up an existing identity, user identity mapping, and user, but does not automatically provision users or identities. This allows cluster administrators to set up identities and users manually, or using an external process. Using this method requires you to manually provision users.
add
Provisions a user with the identity’s preferred user name. If a user with that user name already exists, the identity is mapped to the existing user, adding to any existing identity mappings for the user. Required when multiple identity providers are configured that identify the same set of users and map to the same user names.
Note

When adding or changing identity providers, you can map identities from the new provider to existing users by setting the mappingMethod parameter to add.

9.1.4. Sample identity provider CR

The following custom resource (CR) shows the parameters and default values that you use to configure an identity provider. This example uses the htpasswd identity provider.

Sample identity provider CR

apiVersion: config.openshift.io/v1
kind: OAuth
metadata:
  name: cluster
spec:
  identityProviders:
  - name: my_identity_provider 1
    mappingMethod: claim 2
    type: HTPasswd
    htpasswd:
      fileData:
        name: htpass-secret 3

1
This provider name is prefixed to provider user names to form an identity name.
2
Controls how mappings are established between this provider’s identities and User objects.
3
An existing secret containing a file generated using htpasswd.

9.2. Using RBAC to define and apply permissions

Understand and apply role-based access control.

9.2.1. RBAC overview

Role-based access control (RBAC) objects determine whether a user is allowed to perform a given action within a project.

Cluster administrators can use the cluster roles and bindings to control who has various access levels to the OpenShift Container Platform platform itself and all projects.

Developers can use local roles and bindings to control who has access to their projects. Note that authorization is a separate step from authentication, which is more about determining the identity of who is taking the action.

Authorization is managed using:

Authorization objectDescription

Rules

Sets of permitted verbs on a set of objects. For example, whether a user or service account can create pods.

Roles

Collections of rules. You can associate, or bind, users and groups to multiple roles.

Bindings

Associations between users and/or groups with a role.

There are two levels of RBAC roles and bindings that control authorization:

RBAC levelDescription

Cluster RBAC

Roles and bindings that are applicable across all projects. Cluster roles exist cluster-wide, and cluster role bindings can reference only cluster roles.

Local RBAC

Roles and bindings that are scoped to a given project. While local roles exist only in a single project, local role bindings can reference both cluster and local roles.

A cluster role binding is a binding that exists at the cluster level. A role binding exists at the project level. The cluster role view must be bound to a user using a local role binding for that user to view the project. Create local roles only if a cluster role does not provide the set of permissions needed for a particular situation.

This two-level hierarchy allows reuse across multiple projects through the cluster roles while allowing customization inside of individual projects through local roles.

During evaluation, both the cluster role bindings and the local role bindings are used. For example:

  1. Cluster-wide "allow" rules are checked.
  2. Locally-bound "allow" rules are checked.
  3. Deny by default.
9.2.1.1. Default cluster roles

OpenShift Container Platform includes a set of default cluster roles that you can bind to users and groups cluster-wide or locally.

Important

It is not recommended to manually modify the default cluster roles. Modifications to these system roles can prevent a cluster from functioning properly.

Default cluster roleDescription

admin

A project manager. If used in a local binding, an admin has rights to view any resource in the project and modify any resource in the project except for quota.

basic-user

A user that can get basic information about projects and users.

cluster-admin

A super-user that can perform any action in any project. When bound to a user with a local binding, they have full control over quota and every action on every resource in the project.

cluster-status

A user that can get basic cluster status information.

cluster-reader

A user that can get or view most of the objects but cannot modify them.

edit

A user that can modify most objects in a project but does not have the power to view or modify roles or bindings.

self-provisioner

A user that can create their own projects.

view

A user who cannot make any modifications, but can see most objects in a project. They cannot view or modify roles or bindings.

Be mindful of the difference between local and cluster bindings. For example, if you bind the cluster-admin role to a user by using a local role binding, it might appear that this user has the privileges of a cluster administrator. This is not the case. Binding the cluster-admin to a user in a project grants super administrator privileges for only that project to the user. That user has the permissions of the cluster role admin, plus a few additional permissions like the ability to edit rate limits, for that project. This binding can be confusing via the web console UI, which does not list cluster role bindings that are bound to true cluster administrators. However, it does list local role bindings that you can use to locally bind cluster-admin.

The relationships between cluster roles, local roles, cluster role bindings, local role bindings, users, groups and service accounts are illustrated below.

OpenShift Container Platform RBAC
Warning

The get pods/exec, get pods/*, and get * rules grant execution privileges when they are applied to a role. Apply the principle of least privilege and assign only the minimal RBAC rights required for users and agents. For more information, see RBAC rules allow execution privileges.

9.2.1.2. Evaluating authorization

OpenShift Container Platform evaluates authorization by using:

Identity
The user name and list of groups that the user belongs to.
Action

The action you perform. In most cases, this consists of:

  • Project: The project you access. A project is a Kubernetes namespace with additional annotations that allows a community of users to organize and manage their content in isolation from other communities.
  • Verb : The action itself: get, list, create, update, delete, deletecollection, or watch.
  • Resource name: The API endpoint that you access.
Bindings
The full list of bindings, the associations between users or groups with a role.

OpenShift Container Platform evaluates authorization by using the following steps:

  1. The identity and the project-scoped action is used to find all bindings that apply to the user or their groups.
  2. Bindings are used to locate all the roles that apply.
  3. Roles are used to find all the rules that apply.
  4. The action is checked against each rule to find a match.
  5. If no matching rule is found, the action is then denied by default.
Tip

Remember that users and groups can be associated with, or bound to, multiple roles at the same time.

Project administrators can use the CLI to view local roles and bindings, including a matrix of the verbs and resources each are associated with.

Important

The cluster role bound to the project administrator is limited in a project through a local binding. It is not bound cluster-wide like the cluster roles granted to the cluster-admin or system:admin.

Cluster roles are roles defined at the cluster level but can be bound either at the cluster level or at the project level.

9.2.1.2.1. Cluster role aggregation

The default admin, edit, view, and cluster-reader cluster roles support cluster role aggregation, where the cluster rules for each role are dynamically updated as new rules are created. This feature is relevant only if you extend the Kubernetes API by creating custom resources.

9.2.2. Projects and namespaces

A Kubernetes namespace provides a mechanism to scope resources in a cluster. The Kubernetes documentation has more information on namespaces.

Namespaces provide a unique scope for:

  • Named resources to avoid basic naming collisions.
  • Delegated management authority to trusted users.
  • The ability to limit community resource consumption.

Most objects in the system are scoped by namespace, but some are excepted and have no namespace, including nodes and users.

A project is a Kubernetes namespace with additional annotations and is the central vehicle by which access to resources for regular users is managed. A project allows a community of users to organize and manage their content in isolation from other communities. Users must be given access to projects by administrators, or if allowed to create projects, automatically have access to their own projects.

Projects can have a separate name, displayName, and description.

  • The mandatory name is a unique identifier for the project and is most visible when using the CLI tools or API. The maximum name length is 63 characters.
  • The optional displayName is how the project is displayed in the web console (defaults to name).
  • The optional description can be a more detailed description of the project and is also visible in the web console.

Each project scopes its own set of:

ObjectDescription

Objects

Pods, services, replication controllers, etc.

Policies

Rules for which users can or cannot perform actions on objects.

Constraints

Quotas for each kind of object that can be limited.

Service accounts

Service accounts act automatically with designated access to objects in the project.

Cluster administrators can create projects and delegate administrative rights for the project to any member of the user community. Cluster administrators can also allow developers to create their own projects.

Developers and administrators can interact with projects by using the CLI or the web console.

9.2.3. Default projects

OpenShift Container Platform comes with a number of default projects, and projects starting with openshift- are the most essential to users. These projects host master components that run as pods and other infrastructure components. The pods created in these namespaces that have a critical pod annotation are considered critical, and the have guaranteed admission by kubelet. Pods created for master components in these namespaces are already marked as critical.

Important

Do not run workloads in or share access to default projects. Default projects are reserved for running core cluster components.

The following default projects are considered highly privileged: default, kube-public, kube-system, openshift, openshift-infra, openshift-node, and other system-created projects that have the openshift.io/run-level label set to 0 or 1. Functionality that relies on admission plugins, such as pod security admission, security context constraints, cluster resource quotas, and image reference resolution, does not work in highly privileged projects.

9.2.4. Viewing cluster roles and bindings

You can use the oc CLI to view cluster roles and bindings by using the oc describe command.

Prerequisites

  • Install the oc CLI.
  • Obtain permission to view the cluster roles and bindings.

Users with the cluster-admin default cluster role bound cluster-wide can perform any action on any resource, including viewing cluster roles and bindings.

Procedure

  1. To view the cluster roles and their associated rule sets:

    $ oc describe clusterrole.rbac

    Example output

    Name:         admin
    Labels:       kubernetes.io/bootstrapping=rbac-defaults
    Annotations:  rbac.authorization.kubernetes.io/autoupdate: true
    PolicyRule:
      Resources                                                  Non-Resource URLs  Resource Names  Verbs
      ---------                                                  -----------------  --------------  -----
      .packages.apps.redhat.com                                  []                 []              [* create update patch delete get list watch]
      imagestreams                                               []                 []              [create delete deletecollection get list patch update watch create get list watch]
      imagestreams.image.openshift.io                            []                 []              [create delete deletecollection get list patch update watch create get list watch]
      secrets                                                    []                 []              [create delete deletecollection get list patch update watch get list watch create delete deletecollection patch update]
      buildconfigs/webhooks                                      []                 []              [create delete deletecollection get list patch update watch get list watch]
      buildconfigs                                               []                 []              [create delete deletecollection get list patch update watch get list watch]
      buildlogs                                                  []                 []              [create delete deletecollection get list patch update watch get list watch]
      deploymentconfigs/scale                                    []                 []              [create delete deletecollection get list patch update watch get list watch]
      deploymentconfigs                                          []                 []              [create delete deletecollection get list patch update watch get list watch]
      imagestreamimages                                          []                 []              [create delete deletecollection get list patch update watch get list watch]
      imagestreammappings                                        []                 []              [create delete deletecollection get list patch update watch get list watch]
      imagestreamtags                                            []                 []              [create delete deletecollection get list patch update watch get list watch]
      processedtemplates                                         []                 []              [create delete deletecollection get list patch update watch get list watch]
      routes                                                     []                 []              [create delete deletecollection get list patch update watch get list watch]
      templateconfigs                                            []                 []              [create delete deletecollection get list patch update watch get list watch]
      templateinstances                                          []                 []              [create delete deletecollection get list patch update watch get list watch]
      templates                                                  []                 []              [create delete deletecollection get list patch update watch get list watch]
      deploymentconfigs.apps.openshift.io/scale                  []                 []              [create delete deletecollection get list patch update watch get list watch]
      deploymentconfigs.apps.openshift.io                        []                 []              [create delete deletecollection get list patch update watch get list watch]
      buildconfigs.build.openshift.io/webhooks                   []                 []              [create delete deletecollection get list patch update watch get list watch]
      buildconfigs.build.openshift.io                            []                 []              [create delete deletecollection get list patch update watch get list watch]
      buildlogs.build.openshift.io                               []                 []              [create delete deletecollection get list patch update watch get list watch]
      imagestreamimages.image.openshift.io                       []                 []              [create delete deletecollection get list patch update watch get list watch]
      imagestreammappings.image.openshift.io                     []                 []              [create delete deletecollection get list patch update watch get list watch]
      imagestreamtags.image.openshift.io                         []                 []              [create delete deletecollection get list patch update watch get list watch]
      routes.route.openshift.io                                  []                 []              [create delete deletecollection get list patch update watch get list watch]
      processedtemplates.template.openshift.io                   []                 []              [create delete deletecollection get list patch update watch get list watch]
      templateconfigs.template.openshift.io                      []                 []              [create delete deletecollection get list patch update watch get list watch]
      templateinstances.template.openshift.io                    []                 []              [create delete deletecollection get list patch update watch get list watch]
      templates.template.openshift.io                            []                 []              [create delete deletecollection get list patch update watch get list watch]
      serviceaccounts                                            []                 []              [create delete deletecollection get list patch update watch impersonate create delete deletecollection patch update get list watch]
      imagestreams/secrets                                       []                 []              [create delete deletecollection get list patch update watch]
      rolebindings                                               []                 []              [create delete deletecollection get list patch update watch]
      roles                                                      []                 []              [create delete deletecollection get list patch update watch]
      rolebindings.authorization.openshift.io                    []                 []              [create delete deletecollection get list patch update watch]
      roles.authorization.openshift.io                           []                 []              [create delete deletecollection get list patch update watch]
      imagestreams.image.openshift.io/secrets                    []                 []              [create delete deletecollection get list patch update watch]
      rolebindings.rbac.authorization.k8s.io                     []                 []              [create delete deletecollection get list patch update watch]
      roles.rbac.authorization.k8s.io                            []                 []              [create delete deletecollection get list patch update watch]
      networkpolicies.extensions                                 []                 []              [create delete deletecollection patch update create delete deletecollection get list patch update watch get list watch]
      networkpolicies.networking.k8s.io                          []                 []              [create delete deletecollection patch update create delete deletecollection get list patch update watch get list watch]
      configmaps                                                 []                 []              [create delete deletecollection patch update get list watch]
      endpoints                                                  []                 []              [create delete deletecollection patch update get list watch]
      persistentvolumeclaims                                     []                 []              [create delete deletecollection patch update get list watch]
      pods                                                       []                 []              [create delete deletecollection patch update get list watch]
      replicationcontrollers/scale                               []                 []              [create delete deletecollection patch update get list watch]
      replicationcontrollers                                     []                 []              [create delete deletecollection patch update get list watch]
      services                                                   []                 []              [create delete deletecollection patch update get list watch]
      daemonsets.apps                                            []                 []              [create delete deletecollection patch update get list watch]
      deployments.apps/scale                                     []                 []              [create delete deletecollection patch update get list watch]
      deployments.apps                                           []                 []              [create delete deletecollection patch update get list watch]
      replicasets.apps/scale                                     []                 []              [create delete deletecollection patch update get list watch]
      replicasets.apps                                           []                 []              [create delete deletecollection patch update get list watch]
      statefulsets.apps/scale                                    []                 []              [create delete deletecollection patch update get list watch]
      statefulsets.apps                                          []                 []              [create delete deletecollection patch update get list watch]
      horizontalpodautoscalers.autoscaling                       []                 []              [create delete deletecollection patch update get list watch]
      cronjobs.batch                                             []                 []              [create delete deletecollection patch update get list watch]
      jobs.batch                                                 []                 []              [create delete deletecollection patch update get list watch]
      daemonsets.extensions                                      []                 []              [create delete deletecollection patch update get list watch]
      deployments.extensions/scale                               []                 []              [create delete deletecollection patch update get list watch]
      deployments.extensions                                     []                 []              [create delete deletecollection patch update get list watch]
      ingresses.extensions                                       []                 []              [create delete deletecollection patch update get list watch]
      replicasets.extensions/scale                               []                 []              [create delete deletecollection patch update get list watch]
      replicasets.extensions                                     []                 []              [create delete deletecollection patch update get list watch]
      replicationcontrollers.extensions/scale                    []                 []              [create delete deletecollection patch update get list watch]
      poddisruptionbudgets.policy                                []                 []              [create delete deletecollection patch update get list watch]
      deployments.apps/rollback                                  []                 []              [create delete deletecollection patch update]
      deployments.extensions/rollback                            []                 []              [create delete deletecollection patch update]
      catalogsources.operators.coreos.com                        []                 []              [create update patch delete get list watch]
      clusterserviceversions.operators.coreos.com                []                 []              [create update patch delete get list watch]
      installplans.operators.coreos.com                          []                 []              [create update patch delete get list watch]
      packagemanifests.operators.coreos.com                      []                 []              [create update patch delete get list watch]
      subscriptions.operators.coreos.com                         []                 []              [create update patch delete get list watch]
      buildconfigs/instantiate                                   []                 []              [create]
      buildconfigs/instantiatebinary                             []                 []              [create]
      builds/clone                                               []                 []              [create]
      deploymentconfigrollbacks                                  []                 []              [create]
      deploymentconfigs/instantiate                              []                 []              [create]
      deploymentconfigs/rollback                                 []                 []              [create]
      imagestreamimports                                         []                 []              [create]
      localresourceaccessreviews                                 []                 []              [create]
      localsubjectaccessreviews                                  []                 []              [create]
      podsecuritypolicyreviews                                   []                 []              [create]
      podsecuritypolicyselfsubjectreviews                        []                 []              [create]
      podsecuritypolicysubjectreviews                            []                 []              [create]
      resourceaccessreviews                                      []                 []              [create]
      routes/custom-host                                         []                 []              [create]
      subjectaccessreviews                                       []                 []              [create]
      subjectrulesreviews                                        []                 []              [create]
      deploymentconfigrollbacks.apps.openshift.io                []                 []              [create]
      deploymentconfigs.apps.openshift.io/instantiate            []                 []              [create]
      deploymentconfigs.apps.openshift.io/rollback               []                 []              [create]
      localsubjectaccessreviews.authorization.k8s.io             []                 []              [create]
      localresourceaccessreviews.authorization.openshift.io      []                 []              [create]
      localsubjectaccessreviews.authorization.openshift.io       []                 []              [create]
      resourceaccessreviews.authorization.openshift.io           []                 []              [create]
      subjectaccessreviews.authorization.openshift.io            []                 []              [create]
      subjectrulesreviews.authorization.openshift.io             []                 []              [create]
      buildconfigs.build.openshift.io/instantiate                []                 []              [create]
      buildconfigs.build.openshift.io/instantiatebinary          []                 []              [create]
      builds.build.openshift.io/clone                            []                 []              [create]
      imagestreamimports.image.openshift.io                      []                 []              [create]
      routes.route.openshift.io/custom-host                      []                 []              [create]
      podsecuritypolicyreviews.security.openshift.io             []                 []              [create]
      podsecuritypolicyselfsubjectreviews.security.openshift.io  []                 []              [create]
      podsecuritypolicysubjectreviews.security.openshift.io      []                 []              [create]
      jenkins.build.openshift.io                                 []                 []              [edit view view admin edit view]
      builds                                                     []                 []              [get create delete deletecollection get list patch update watch get list watch]
      builds.build.openshift.io                                  []                 []              [get create delete deletecollection get list patch update watch get list watch]
      projects                                                   []                 []              [get delete get delete get patch update]
      projects.project.openshift.io                              []                 []              [get delete get delete get patch update]
      namespaces                                                 []                 []              [get get list watch]
      pods/attach                                                []                 []              [get list watch create delete deletecollection patch update]
      pods/exec                                                  []                 []              [get list watch create delete deletecollection patch update]
      pods/portforward                                           []                 []              [get list watch create delete deletecollection patch update]
      pods/proxy                                                 []                 []              [get list watch create delete deletecollection patch update]
      services/proxy                                             []                 []              [get list watch create delete deletecollection patch update]
      routes/status                                              []                 []              [get list watch update]
      routes.route.openshift.io/status                           []                 []              [get list watch update]
      appliedclusterresourcequotas                               []                 []              [get list watch]
      bindings                                                   []                 []              [get list watch]
      builds/log                                                 []                 []              [get list watch]
      deploymentconfigs/log                                      []                 []              [get list watch]
      deploymentconfigs/status                                   []                 []              [get list watch]
      events                                                     []                 []              [get list watch]
      imagestreams/status                                        []                 []              [get list watch]
      limitranges                                                []                 []              [get list watch]
      namespaces/status                                          []                 []              [get list watch]
      pods/log                                                   []                 []              [get list watch]
      pods/status                                                []                 []              [get list watch]
      replicationcontrollers/status                              []                 []              [get list watch]
      resourcequotas/status                                      []                 []              [get list watch]
      resourcequotas                                             []                 []              [get list watch]
      resourcequotausages                                        []                 []              [get list watch]
      rolebindingrestrictions                                    []                 []              [get list watch]
      deploymentconfigs.apps.openshift.io/log                    []                 []              [get list watch]
      deploymentconfigs.apps.openshift.io/status                 []                 []              [get list watch]
      controllerrevisions.apps                                   []                 []              [get list watch]
      rolebindingrestrictions.authorization.openshift.io         []                 []              [get list watch]
      builds.build.openshift.io/log                              []                 []              [get list watch]
      imagestreams.image.openshift.io/status                     []                 []              [get list watch]
      appliedclusterresourcequotas.quota.openshift.io            []                 []              [get list watch]
      imagestreams/layers                                        []                 []              [get update get]
      imagestreams.image.openshift.io/layers                     []                 []              [get update get]
      builds/details                                             []                 []              [update]
      builds.build.openshift.io/details                          []                 []              [update]
    
    
    Name:         basic-user
    Labels:       <none>
    Annotations:  openshift.io/description: A user that can get basic information about projects.
    	              rbac.authorization.kubernetes.io/autoupdate: true
    PolicyRule:
    	Resources                                           Non-Resource URLs  Resource Names  Verbs
    	  ---------                                           -----------------  --------------  -----
    	  selfsubjectrulesreviews                             []                 []              [create]
    	  selfsubjectaccessreviews.authorization.k8s.io       []                 []              [create]
    	  selfsubjectrulesreviews.authorization.openshift.io  []                 []              [create]
    	  clusterroles.rbac.authorization.k8s.io              []                 []              [get list watch]
    	  clusterroles                                        []                 []              [get list]
    	  clusterroles.authorization.openshift.io             []                 []              [get list]
    	  storageclasses.storage.k8s.io                       []                 []              [get list]
    	  users                                               []                 [~]             [get]
    	  users.user.openshift.io                             []                 [~]             [get]
    	  projects                                            []                 []              [list watch]
    	  projects.project.openshift.io                       []                 []              [list watch]
    	  projectrequests                                     []                 []              [list]
    	  projectrequests.project.openshift.io                []                 []              [list]
    
    Name:         cluster-admin
    Labels:       kubernetes.io/bootstrapping=rbac-defaults
    Annotations:  rbac.authorization.kubernetes.io/autoupdate: true
    PolicyRule:
    Resources  Non-Resource URLs  Resource Names  Verbs
    ---------  -----------------  --------------  -----
    *.*        []                 []              [*]
               [*]                []              [*]
    
    ...

  2. To view the current set of cluster role bindings, which shows the users and groups that are bound to various roles:

    $ oc describe clusterrolebinding.rbac

    Example output

    Name:         alertmanager-main
    Labels:       <none>
    Annotations:  <none>
    Role:
      Kind:  ClusterRole
      Name:  alertmanager-main
    Subjects:
      Kind            Name               Namespace
      ----            ----               ---------
      ServiceAccount  alertmanager-main  openshift-monitoring
    
    
    Name:         basic-users
    Labels:       <none>
    Annotations:  rbac.authorization.kubernetes.io/autoupdate: true
    Role:
      Kind:  ClusterRole
      Name:  basic-user
    Subjects:
      Kind   Name                  Namespace
      ----   ----                  ---------
      Group  system:authenticated
    
    
    Name:         cloud-credential-operator-rolebinding
    Labels:       <none>
    Annotations:  <none>
    Role:
      Kind:  ClusterRole
      Name:  cloud-credential-operator-role
    Subjects:
      Kind            Name     Namespace
      ----            ----     ---------
      ServiceAccount  default  openshift-cloud-credential-operator
    
    
    Name:         cluster-admin
    Labels:       kubernetes.io/bootstrapping=rbac-defaults
    Annotations:  rbac.authorization.kubernetes.io/autoupdate: true
    Role:
      Kind:  ClusterRole
      Name:  cluster-admin
    Subjects:
      Kind   Name            Namespace
      ----   ----            ---------
      Group  system:masters
    
    
    Name:         cluster-admins
    Labels:       <none>
    Annotations:  rbac.authorization.kubernetes.io/autoupdate: true
    Role:
      Kind:  ClusterRole
      Name:  cluster-admin
    Subjects:
      Kind   Name                   Namespace
      ----   ----                   ---------
      Group  system:cluster-admins
      User   system:admin
    
    
    Name:         cluster-api-manager-rolebinding
    Labels:       <none>
    Annotations:  <none>
    Role:
      Kind:  ClusterRole
      Name:  cluster-api-manager-role
    Subjects:
      Kind            Name     Namespace
      ----            ----     ---------
      ServiceAccount  default  openshift-machine-api
    
    ...

9.2.5. Viewing local roles and bindings

You can use the oc CLI to view local roles and bindings by using the oc describe command.

Prerequisites

  • Install the oc CLI.
  • Obtain permission to view the local roles and bindings:

    • Users with the cluster-admin default cluster role bound cluster-wide can perform any action on any resource, including viewing local roles and bindings.
    • Users with the admin default cluster role bound locally can view and manage roles and bindings in that project.

Procedure

  1. To view the current set of local role bindings, which show the users and groups that are bound to various roles for the current project:

    $ oc describe rolebinding.rbac
  2. To view the local role bindings for a different project, add the -n flag to the command:

    $ oc describe rolebinding.rbac -n joe-project

    Example output

    Name:         admin
    Labels:       <none>
    Annotations:  <none>
    Role:
      Kind:  ClusterRole
      Name:  admin
    Subjects:
      Kind  Name        Namespace
      ----  ----        ---------
      User  kube:admin
    
    
    Name:         system:deployers
    Labels:       <none>
    Annotations:  openshift.io/description:
                    Allows deploymentconfigs in this namespace to rollout pods in
                    this namespace.  It is auto-managed by a controller; remove
                    subjects to disa...
    Role:
      Kind:  ClusterRole
      Name:  system:deployer
    Subjects:
      Kind            Name      Namespace
      ----            ----      ---------
      ServiceAccount  deployer  joe-project
    
    
    Name:         system:image-builders
    Labels:       <none>
    Annotations:  openshift.io/description:
                    Allows builds in this namespace to push images to this
                    namespace.  It is auto-managed by a controller; remove subjects
                    to disable.
    Role:
      Kind:  ClusterRole
      Name:  system:image-builder
    Subjects:
      Kind            Name     Namespace
      ----            ----     ---------
      ServiceAccount  builder  joe-project
    
    
    Name:         system:image-pullers
    Labels:       <none>
    Annotations:  openshift.io/description:
                    Allows all pods in this namespace to pull images from this
                    namespace.  It is auto-managed by a controller; remove subjects
                    to disable.
    Role:
      Kind:  ClusterRole
      Name:  system:image-puller
    Subjects:
      Kind   Name                                Namespace
      ----   ----                                ---------
      Group  system:serviceaccounts:joe-project

9.2.6. Adding roles to users

You can use the oc adm administrator CLI to manage the roles and bindings.

Binding, or adding, a role to users or groups gives the user or group the access that is granted by the role. You can add and remove roles to and from users and groups using oc adm policy commands.

You can bind any of the default cluster roles to local users or groups in your project.

Procedure

  1. Add a role to a user in a specific project:

    $ oc adm policy add-role-to-user <role> <user> -n <project>

    For example, you can add the admin role to the alice user in joe project by running:

    $ oc adm policy add-role-to-user admin alice -n joe
    Tip

    You can alternatively apply the following YAML to add the role to the user:

    apiVersion: rbac.authorization.k8s.io/v1
    kind: RoleBinding
    metadata:
      name: admin-0
      namespace: joe
    roleRef:
      apiGroup: rbac.authorization.k8s.io
      kind: ClusterRole
      name: admin
    subjects:
    - apiGroup: rbac.authorization.k8s.io
      kind: User
      name: alice
  2. View the local role bindings and verify the addition in the output:

    $ oc describe rolebinding.rbac -n <project>

    For example, to view the local role bindings for the joe project:

    $ oc describe rolebinding.rbac -n joe

    Example output

    Name:         admin
    Labels:       <none>
    Annotations:  <none>
    Role:
      Kind:  ClusterRole
      Name:  admin
    Subjects:
      Kind  Name        Namespace
      ----  ----        ---------
      User  kube:admin
    
    
    Name:         admin-0
    Labels:       <none>
    Annotations:  <none>
    Role:
      Kind:  ClusterRole
      Name:  admin
    Subjects:
      Kind  Name   Namespace
      ----  ----   ---------
      User  alice 1
    
    
    Name:         system:deployers
    Labels:       <none>
    Annotations:  openshift.io/description:
                    Allows deploymentconfigs in this namespace to rollout pods in
                    this namespace.  It is auto-managed by a controller; remove
                    subjects to disa...
    Role:
      Kind:  ClusterRole
      Name:  system:deployer
    Subjects:
      Kind            Name      Namespace
      ----            ----      ---------
      ServiceAccount  deployer  joe
    
    
    Name:         system:image-builders
    Labels:       <none>
    Annotations:  openshift.io/description:
                    Allows builds in this namespace to push images to this
                    namespace.  It is auto-managed by a controller; remove subjects
                    to disable.
    Role:
      Kind:  ClusterRole
      Name:  system:image-builder
    Subjects:
      Kind            Name     Namespace
      ----            ----     ---------
      ServiceAccount  builder  joe
    
    
    Name:         system:image-pullers
    Labels:       <none>
    Annotations:  openshift.io/description:
                    Allows all pods in this namespace to pull images from this
                    namespace.  It is auto-managed by a controller; remove subjects
                    to disable.
    Role:
      Kind:  ClusterRole
      Name:  system:image-puller
    Subjects:
      Kind   Name                                Namespace
      ----   ----                                ---------
      Group  system:serviceaccounts:joe

    1
    The alice user has been added to the admins RoleBinding.

9.2.7. Creating a local role

You can create a local role for a project and then bind it to a user.

Procedure

  1. To create a local role for a project, run the following command:

    $ oc create role <name> --verb=<verb> --resource=<resource> -n <project>

    In this command, specify:

    • <name>, the local role’s name
    • <verb>, a comma-separated list of the verbs to apply to the role
    • <resource>, the resources that the role applies to
    • <project>, the project name

    For example, to create a local role that allows a user to view pods in the blue project, run the following command:

    $ oc create role podview --verb=get --resource=pod -n blue
  2. To bind the new role to a user, run the following command:

    $ oc adm policy add-role-to-user podview user2 --role-namespace=blue -n blue

9.2.8. Creating a cluster role

You can create a cluster role.

Procedure

  1. To create a cluster role, run the following command:

    $ oc create clusterrole <name> --verb=<verb> --resource=<resource>

    In this command, specify:

    • <name>, the local role’s name
    • <verb>, a comma-separated list of the verbs to apply to the role
    • <resource>, the resources that the role applies to

    For example, to create a cluster role that allows a user to view pods, run the following command:

    $ oc create clusterrole podviewonly --verb=get --resource=pod

9.2.9. Local role binding commands

When you manage a user or group’s associated roles for local role bindings using the following operations, a project may be specified with the -n flag. If it is not specified, then the current project is used.

You can use the following commands for local RBAC management.

Table 9.1. Local role binding operations
CommandDescription

$ oc adm policy who-can <verb> <resource>

Indicates which users can perform an action on a resource.

$ oc adm policy add-role-to-user <role> <username>

Binds a specified role to specified users in the current project.

$ oc adm policy remove-role-from-user <role> <username>

Removes a given role from specified users in the current project.

$ oc adm policy remove-user <username>

Removes specified users and all of their roles in the current project.

$ oc adm policy add-role-to-group <role> <groupname>

Binds a given role to specified groups in the current project.

$ oc adm policy remove-role-from-group <role> <groupname>

Removes a given role from specified groups in the current project.

$ oc adm policy remove-group <groupname>

Removes specified groups and all of their roles in the current project.

9.2.10. Cluster role binding commands

You can also manage cluster role bindings using the following operations. The -n flag is not used for these operations because cluster role bindings use non-namespaced resources.

Table 9.2. Cluster role binding operations
CommandDescription

$ oc adm policy add-cluster-role-to-user <role> <username>

Binds a given role to specified users for all projects in the cluster.

$ oc adm policy remove-cluster-role-from-user <role> <username>

Removes a given role from specified users for all projects in the cluster.

$ oc adm policy add-cluster-role-to-group <role> <groupname>

Binds a given role to specified groups for all projects in the cluster.

$ oc adm policy remove-cluster-role-from-group <role> <groupname>

Removes a given role from specified groups for all projects in the cluster.

9.2.11. Creating a cluster admin

The cluster-admin role is required to perform administrator level tasks on the OpenShift Container Platform cluster, such as modifying cluster resources.

Prerequisites

  • You must have created a user to define as the cluster admin.

Procedure

  • Define the user as a cluster admin:

    $ oc adm policy add-cluster-role-to-user cluster-admin <user>

9.2.12. Cluster role bindings for unauthenticated groups

Note

Before OpenShift Container Platform 4.17, unauthenticated groups were allowed access to some cluster roles. Clusters updated from versions before OpenShift Container Platform 4.17 retain this access for unauthenticated groups.

For security reasons OpenShift Container Platform 4.17 does not allow unauthenticated groups to have default access to cluster roles.

There are use cases where it might be necessary to add system:unauthenticated to a cluster role.

Cluster administrators can add unauthenticated users to the following cluster roles:

  • system:scope-impersonation
  • system:webhook
  • system:oauth-token-deleter
  • self-access-reviewer
Important

Always verify compliance with your organization’s security standards when modifying unauthenticated access.

9.2.13. Adding unauthenticated groups to cluster roles

As a cluster administrator, you can add unauthenticated users to the following cluster roles in OpenShift Container Platform by creating a cluster role binding. Unauthenticated users do not have access to non-public cluster roles. This should only be done in specific use cases when necessary.

You can add unauthenticated users to the following cluster roles:

  • system:scope-impersonation
  • system:webhook
  • system:oauth-token-deleter
  • self-access-reviewer
Important

Always verify compliance with your organization’s security standards when modifying unauthenticated access.

Prerequisites

  • You have access to the cluster as a user with the cluster-admin role.
  • You have installed the OpenShift CLI (oc).

Procedure

  1. Create a YAML file named add-<cluster_role>-unauth.yaml and add the following content:

    apiVersion: rbac.authorization.k8s.io/v1
    kind: ClusterRoleBinding
    metadata:
     annotations:
       rbac.authorization.kubernetes.io/autoupdate: "true"
     name: <cluster_role>access-unauthenticated
    roleRef:
     apiGroup: rbac.authorization.k8s.io
     kind: ClusterRole
     name: <cluster_role>
    subjects:
     - apiGroup: rbac.authorization.k8s.io
       kind: Group
       name: system:unauthenticated
  2. Apply the configuration by running the following command:

    $ oc apply -f add-<cluster_role>.yaml

9.3. The kubeadmin user

OpenShift Container Platform creates a cluster administrator, kubeadmin, after the installation process completes.

This user has the cluster-admin role automatically applied and is treated as the root user for the cluster. The password is dynamically generated and unique to your OpenShift Container Platform environment. After installation completes the password is provided in the installation program’s output. For example:

INFO Install complete!
INFO Run 'export KUBECONFIG=<your working directory>/auth/kubeconfig' to manage the cluster with 'oc', the OpenShift CLI.
INFO The cluster is ready when 'oc login -u kubeadmin -p <provided>' succeeds (wait a few minutes).
INFO Access the OpenShift web-console here: https://console-openshift-console.apps.demo1.openshift4-beta-abcorp.com
INFO Login to the console with user: kubeadmin, password: <provided>

9.3.1. Removing the kubeadmin user

After you define an identity provider and create a new cluster-admin user, you can remove the kubeadmin to improve cluster security.

Warning

If you follow this procedure before another user is a cluster-admin, then OpenShift Container Platform must be reinstalled. It is not possible to undo this command.

Prerequisites

  • You must have configured at least one identity provider.
  • You must have added the cluster-admin role to a user.
  • You must be logged in as an administrator.

Procedure

  • Remove the kubeadmin secrets:

    $ oc delete secrets kubeadmin -n kube-system

9.4. Populating OperatorHub from mirrored Operator catalogs

If you mirrored Operator catalogs for use with disconnected clusters, you can populate OperatorHub with the Operators from your mirrored catalogs. You can use the generated manifests from the mirroring process to create the required ImageContentSourcePolicy and CatalogSource objects.

9.4.1. Prerequisites

9.4.1.1. Creating the ImageContentSourcePolicy object

After mirroring Operator catalog content to your mirror registry, create the required ImageContentSourcePolicy (ICSP) object. The ICSP object configures nodes to translate between the image references stored in Operator manifests and the mirrored registry.

Procedure

  • On a host with access to the disconnected cluster, create the ICSP by running the following command to specify the imageContentSourcePolicy.yaml file in your manifests directory:

    $ oc create -f <path/to/manifests/dir>/imageContentSourcePolicy.yaml

    where <path/to/manifests/dir> is the path to the manifests directory for your mirrored content.

    You can now create a CatalogSource object to reference your mirrored index image and Operator content.

9.4.1.2. Adding a catalog source to a cluster

Adding a catalog source to an OpenShift Container Platform cluster enables the discovery and installation of Operators for users. Cluster administrators can create a CatalogSource object that references an index image. OperatorHub uses catalog sources to populate the user interface.

Tip

Alternatively, you can use the web console to manage catalog sources. From the AdministrationCluster SettingsConfigurationOperatorHub page, click the Sources tab, where you can create, update, delete, disable, and enable individual sources.

Prerequisites

  • You built and pushed an index image to a registry.
  • You have access to the cluster as a user with the cluster-admin role.

Procedure

  1. Create a CatalogSource object that references your index image. If you used the oc adm catalog mirror command to mirror your catalog to a target registry, you can use the generated catalogSource.yaml file in your manifests directory as a starting point.

    1. Modify the following to your specifications and save it as a catalogSource.yaml file:

      apiVersion: operators.coreos.com/v1alpha1
      kind: CatalogSource
      metadata:
        name: my-operator-catalog 1
        namespace: openshift-marketplace 2
      spec:
        sourceType: grpc
        grpcPodConfig:
          securityContextConfig: <security_mode> 3
        image: <registry>/<namespace>/redhat-operator-index:v4.17 4
        displayName: My Operator Catalog
        publisher: <publisher_name> 5
        updateStrategy:
          registryPoll: 6
            interval: 30m
      1
      If you mirrored content to local files before uploading to a registry, remove any backslash (/) characters from the metadata.name field to avoid an "invalid resource name" error when you create the object.
      2
      If you want the catalog source to be available globally to users in all namespaces, specify the openshift-marketplace namespace. Otherwise, you can specify a different namespace for the catalog to be scoped and available only for that namespace.
      3
      Specify the value of legacy or restricted. If the field is not set, the default value is legacy. In a future OpenShift Container Platform release, it is planned that the default value will be restricted. If your catalog cannot run with restricted permissions, it is recommended that you manually set this field to legacy.
      4
      Specify your index image. If you specify a tag after the image name, for example :v4.17, the catalog source pod uses an image pull policy of Always, meaning the pod always pulls the image prior to starting the container. If you specify a digest, for example @sha256:<id>, the image pull policy is IfNotPresent, meaning the pod pulls the image only if it does not already exist on the node.
      5
      Specify your name or an organization name publishing the catalog.
      6
      Catalog sources can automatically check for new versions to keep up to date.
    2. Use the file to create the CatalogSource object:

      $ oc apply -f catalogSource.yaml
  2. Verify the following resources are created successfully.

    1. Check the pods:

      $ oc get pods -n openshift-marketplace

      Example output

      NAME                                    READY   STATUS    RESTARTS  AGE
      my-operator-catalog-6njx6               1/1     Running   0         28s
      marketplace-operator-d9f549946-96sgr    1/1     Running   0         26h

    2. Check the catalog source:

      $ oc get catalogsource -n openshift-marketplace

      Example output

      NAME                  DISPLAY               TYPE PUBLISHER  AGE
      my-operator-catalog   My Operator Catalog   grpc            5s

    3. Check the package manifest:

      $ oc get packagemanifest -n openshift-marketplace

      Example output

      NAME                          CATALOG               AGE
      jaeger-product                My Operator Catalog   93s

You can now install the Operators from the OperatorHub page on your OpenShift Container Platform web console.

9.5. About Operator installation with OperatorHub

OperatorHub is a user interface for discovering Operators; it works in conjunction with Operator Lifecycle Manager (OLM), which installs and manages Operators on a cluster.

As a cluster administrator, you can install an Operator from OperatorHub by using the OpenShift Container Platform web console or CLI. Subscribing an Operator to one or more namespaces makes the Operator available to developers on your cluster.

During installation, you must determine the following initial settings for the Operator:

Installation Mode
Choose All namespaces on the cluster (default) to have the Operator installed on all namespaces or choose individual namespaces, if available, to only install the Operator on selected namespaces. This example chooses All namespaces…​ to make the Operator available to all users and projects.
Update Channel
If an Operator is available through multiple channels, you can choose which channel you want to subscribe to. For example, to deploy from the stable channel, if available, select it from the list.
Approval Strategy

You can choose automatic or manual updates.

If you choose automatic updates for an installed Operator, when a new version of that Operator is available in the selected channel, Operator Lifecycle Manager (OLM) automatically upgrades the running instance of your Operator without human intervention.

If you select manual updates, when a newer version of an Operator is available, OLM creates an update request. As a cluster administrator, you must then manually approve that update request to have the Operator updated to the new version.

9.5.1. Installing from OperatorHub by using the web console

You can install and subscribe to an Operator from OperatorHub by using the OpenShift Container Platform web console.

Prerequisites

  • Access to an OpenShift Container Platform cluster using an account with cluster-admin permissions.

Procedure

  1. Navigate in the web console to the Operators → OperatorHub page.
  2. Scroll or type a keyword into the Filter by keyword box to find the Operator you want. For example, type jaeger to find the Jaeger Operator.

    You can also filter options by Infrastructure Features. For example, select Disconnected if you want to see Operators that work in disconnected environments, also known as restricted network environments.

  3. Select the Operator to display additional information.

    Note

    Choosing a Community Operator warns that Red Hat does not certify Community Operators; you must acknowledge the warning before continuing.

  4. Read the information about the Operator and click Install.
  5. On the Install Operator page, configure your Operator installation:

    1. If you want to install a specific version of an Operator, select an Update channel and Version from the lists. You can browse the various versions of an Operator across any channels it might have, view the metadata for that channel and version, and select the exact version you want to install.

      Note

      The version selection defaults to the latest version for the channel selected. If the latest version for the channel is selected, the Automatic approval strategy is enabled by default. Otherwise, Manual approval is required when not installing the latest version for the selected channel.

      Installing an Operator with Manual approval causes all Operators installed within the namespace to function with the Manual approval strategy and all Operators are updated together. If you want to update Operators independently, install Operators into separate namespaces.

    2. Confirm the installation mode for the Operator:

      • All namespaces on the cluster (default) installs the Operator in the default openshift-operators namespace to watch and be made available to all namespaces in the cluster. This option is not always available.
      • A specific namespace on the cluster allows you to choose a specific, single namespace in which to install the Operator. The Operator will only watch and be made available for use in this single namespace.
    3. For clusters on cloud providers with token authentication enabled:

      • If the cluster uses AWS Security Token Service (STS Mode in the web console), enter the Amazon Resource Name (ARN) of the AWS IAM role of your service account in the role ARN field. To create the role’s ARN, follow the procedure described in Preparing AWS account.
      • If the cluster uses Microsoft Entra Workload ID (Workload Identity / Federated Identity Mode in the web console), add the client ID, tenant ID, and subscription ID in the appropriate fields.
      • If the cluster uses Google Cloud Platform Workload Identity (GCP Workload Identity / Federated Identity Mode in the web console), add the project number, pool ID, provider ID, and service account email in the appropriate fields.
    4. For Update approval, select either the Automatic or Manual approval strategy.

      Important

      If the web console shows that the cluster uses AWS STS, Microsoft Entra Workload ID, or GCP Workload Identity, you must set Update approval to Manual.

      Subscriptions with automatic approvals for updates are not recommended because there might be permission changes to make before updating. Subscriptions with manual approvals for updates ensure that administrators have the opportunity to verify the permissions of the later version, take any necessary steps, and then update.

  6. Click Install to make the Operator available to the selected namespaces on this OpenShift Container Platform cluster:

    1. If you selected a Manual approval strategy, the upgrade status of the subscription remains Upgrading until you review and approve the install plan.

      After approving on the Install Plan page, the subscription upgrade status moves to Up to date.

    2. If you selected an Automatic approval strategy, the upgrade status should resolve to Up to date without intervention.

Verification

  • After the upgrade status of the subscription is Up to date, select OperatorsInstalled Operators to verify that the cluster service version (CSV) of the installed Operator eventually shows up. The Status should eventually resolve to Succeeded in the relevant namespace.

    Note

    For the All namespaces…​ installation mode, the status resolves to Succeeded in the openshift-operators namespace, but the status is Copied if you check in other namespaces.

    If it does not:

    • Check the logs in any pods in the openshift-operators project (or other relevant namespace if A specific namespace…​ installation mode was selected) on the WorkloadsPods page that are reporting issues to troubleshoot further.
  • When the Operator is installed, the metadata indicates which channel and version are installed.

    Note

    The Channel and Version dropdown menus are still available for viewing other version metadata in this catalog context.

9.5.2. Installing from OperatorHub by using the CLI

Instead of using the OpenShift Container Platform web console, you can install an Operator from OperatorHub by using the CLI. Use the oc command to create or update a Subscription object.

For SingleNamespace install mode, you must also ensure an appropriate Operator group exists in the related namespace. An Operator group, defined by an OperatorGroup object, selects target namespaces in which to generate required RBAC access for all Operators in the same namespace as the Operator group.

Tip

In most cases, the web console method of this procedure is preferred because it automates tasks in the background, such as handling the creation of OperatorGroup and Subscription objects automatically when choosing SingleNamespace mode.

Prerequisites

  • Access to an OpenShift Container Platform cluster using an account with cluster-admin permissions.
  • You have installed the OpenShift CLI (oc).

Procedure

  1. View the list of Operators available to the cluster from OperatorHub:

    $ oc get packagemanifests -n openshift-marketplace

    Example 9.1. Example output

    NAME                               CATALOG               AGE
    3scale-operator                    Red Hat Operators     91m
    advanced-cluster-management        Red Hat Operators     91m
    amq7-cert-manager                  Red Hat Operators     91m
    # ...
    couchbase-enterprise-certified     Certified Operators   91m
    crunchy-postgres-operator          Certified Operators   91m
    mongodb-enterprise                 Certified Operators   91m
    # ...
    etcd                               Community Operators   91m
    jaeger                             Community Operators   91m
    kubefed                            Community Operators   91m
    # ...

    Note the catalog for your desired Operator.

  2. Inspect your desired Operator to verify its supported install modes and available channels:

    $ oc describe packagemanifests <operator_name> -n openshift-marketplace

    Example 9.2. Example output

    # ...
    Kind:         PackageManifest
    # ...
          Install Modes: 1
            Supported:  true
            Type:       OwnNamespace
            Supported:  true
            Type:       SingleNamespace
            Supported:  false
            Type:       MultiNamespace
            Supported:  true
            Type:       AllNamespaces
    # ...
        Entries:
          Name:       example-operator.v3.7.11
          Version:    3.7.11
          Name:       example-operator.v3.7.10
          Version:    3.7.10
        Name:         stable-3.7 2
    # ...
       Entries:
          Name:         example-operator.v3.8.5
          Version:      3.8.5
          Name:         example-operator.v3.8.4
          Version:      3.8.4
        Name:           stable-3.8 3
      Default Channel:  stable-3.8 4
    1
    Indicates which install modes are supported.
    2 3
    Example channel names.
    4
    The channel selected by default if one is not specified.
    Tip

    You can print an Operator’s version and channel information in YAML format by running the following command:

    $ oc get packagemanifests <operator_name> -n <catalog_namespace> -o yaml
    • If more than one catalog is installed in a namespace, run the following command to look up the available versions and channels of an Operator from a specific catalog:

      $ oc get packagemanifest \
         --selector=catalog=<catalogsource_name> \
         --field-selector metadata.name=<operator_name> \
         -n <catalog_namespace> -o yaml
      Important

      If you do not specify the Operator’s catalog, running the oc get packagemanifest and oc describe packagemanifest commands might return a package from an unexpected catalog if the following conditions are met:

      • Multiple catalogs are installed in the same namespace.
      • The catalogs contain the same Operators or Operators with the same name.
  3. If the Operator you intend to install supports the AllNamespaces install mode, and you choose to use this mode, skip this step, because the openshift-operators namespace already has an appropriate Operator group in place by default, called global-operators.

    If the Operator you intend to install supports the SingleNamespace install mode, and you choose to use this mode, you must ensure an appropriate Operator group exists in the related namespace. If one does not exist, you can create create one by following these steps:

    Important

    You can only have one Operator group per namespace. For more information, see "Operator groups".

    1. Create an OperatorGroup object YAML file, for example operatorgroup.yaml, for SingleNamespace install mode:

      Example OperatorGroup object for SingleNamespace install mode

      apiVersion: operators.coreos.com/v1
      kind: OperatorGroup
      metadata:
        name: <operatorgroup_name>
        namespace: <namespace> 1
      spec:
        targetNamespaces:
        - <namespace> 2

      1 2
      For SingleNamespace install mode, use the same <namespace> value for both the metadata.namespace and spec.targetNamespaces fields.
    2. Create the OperatorGroup object:

      $ oc apply -f operatorgroup.yaml
  4. Create a Subscription object to subscribe a namespace to an Operator:

    1. Create a YAML file for the Subscription object, for example subscription.yaml:

      Note

      If you want to subscribe to a specific version of an Operator, set the startingCSV field to the desired version and set the installPlanApproval field to Manual to prevent the Operator from automatically upgrading if a later version exists in the catalog. For details, see the following "Example Subscription object with a specific starting Operator version".

      Example 9.3. Example Subscription object

      apiVersion: operators.coreos.com/v1alpha1
      kind: Subscription
      metadata:
        name: <subscription_name>
        namespace: <namespace_per_install_mode> 1
      spec:
        channel: <channel_name> 2
        name: <operator_name> 3
        source: <catalog_name> 4
        sourceNamespace: <catalog_source_namespace> 5
        config:
          env: 6
          - name: ARGS
            value: "-v=10"
          envFrom: 7
          - secretRef:
              name: license-secret
          volumes: 8
          - name: <volume_name>
            configMap:
              name: <configmap_name>
          volumeMounts: 9
          - mountPath: <directory_name>
            name: <volume_name>
          tolerations: 10
          - operator: "Exists"
          resources: 11
            requests:
              memory: "64Mi"
              cpu: "250m"
            limits:
              memory: "128Mi"
              cpu: "500m"
          nodeSelector: 12
            foo: bar
      1
      For default AllNamespaces install mode usage, specify the openshift-operators namespace. Alternatively, you can specify a custom global namespace, if you have created one. For SingleNamespace install mode usage, specify the relevant single namespace.
      2
      Name of the channel to subscribe to.
      3
      Name of the Operator to subscribe to.
      4
      Name of the catalog source that provides the Operator.
      5
      Namespace of the catalog source. Use openshift-marketplace for the default OperatorHub catalog sources.
      6
      The env parameter defines a list of environment variables that must exist in all containers in the pod created by OLM.
      7
      The envFrom parameter defines a list of sources to populate environment variables in the container.
      8
      The volumes parameter defines a list of volumes that must exist on the pod created by OLM.
      9
      The volumeMounts parameter defines a list of volume mounts that must exist in all containers in the pod created by OLM. If a volumeMount references a volume that does not exist, OLM fails to deploy the Operator.
      10
      The tolerations parameter defines a list of tolerations for the pod created by OLM.
      11
      The resources parameter defines resource constraints for all the containers in the pod created by OLM.
      12
      The nodeSelector parameter defines a NodeSelector for the pod created by OLM.

      Example 9.4. Example Subscription object with a specific starting Operator version

      apiVersion: operators.coreos.com/v1alpha1
      kind: Subscription
      metadata:
        name: example-operator
        namespace: example-operator
      spec:
        channel: stable-3.7
        installPlanApproval: Manual 1
        name: example-operator
        source: custom-operators
        sourceNamespace: openshift-marketplace
        startingCSV: example-operator.v3.7.10 2
      1
      Set the approval strategy to Manual in case your specified version is superseded by a later version in the catalog. This plan prevents an automatic upgrade to a later version and requires manual approval before the starting CSV can complete the installation.
      2
      Set a specific version of an Operator CSV.
    2. For clusters on cloud providers with token authentication enabled, such as Amazon Web Services (AWS) Security Token Service (STS), Microsoft Entra Workload ID, or Google Cloud Platform Workload Identity, configure your Subscription object by following these steps:

      1. Ensure the Subscription object is set to manual update approvals:

        Example 9.5. Example Subscription object with manual update approvals

        kind: Subscription
        # ...
        spec:
          installPlanApproval: Manual 1
        1
        Subscriptions with automatic approvals for updates are not recommended because there might be permission changes to make before updating. Subscriptions with manual approvals for updates ensure that administrators have the opportunity to verify the permissions of the later version, take any necessary steps, and then update.
      2. Include the relevant cloud provider-specific fields in the Subscription object’s config section:

        • If the cluster is in AWS STS mode, include the following fields:

          Example 9.6. Example Subscription object with AWS STS variables

          kind: Subscription
          # ...
          spec:
            config:
              env:
              - name: ROLEARN
                value: "<role_arn>" 1
          1
          Include the role ARN details.
        • If the cluster is in Workload ID mode, include the following fields:

          Example 9.7. Example Subscription object with Workload ID variables

          kind: Subscription
          # ...
          spec:
           config:
             env:
             - name: CLIENTID
               value: "<client_id>" 1
             - name: TENANTID
               value: "<tenant_id>" 2
             - name: SUBSCRIPTIONID
               value: "<subscription_id>" 3
          1
          Include the client ID.
          2
          Include the tenant ID.
          3
          Include the subscription ID.
        • If the cluster is in GCP Workload Identity mode, include the following fields:

          Example 9.8. Example Subscription object with GCP Workload Identity variables

          kind: Subscription
          # ...
          spec:
           config:
             env:
             - name: AUDIENCE
               value: "<audience_url>" 1
             - name: SERVICE_ACCOUNT_EMAIL
               value: "<service_account_email>" 2

          where:

          <audience>

          Created in GCP by the administrator when they set up GCP Workload Identity, the AUDIENCE value must be a preformatted URL in the following format:

          //iam.googleapis.com/projects/<project_number>/locations/global/workloadIdentityPools/<pool_id>/providers/<provider_id>
          <service_account_email>

          The SERVICE_ACCOUNT_EMAIL value is a GCP service account email that is impersonated during Operator operation, for example:

          <service_account_name>@<project_id>.iam.gserviceaccount.com
    3. Create the Subscription object by running the following command:

      $ oc apply -f subscription.yaml
  5. If you set the installPlanApproval field to Manual, manually approve the pending install plan to complete the Operator installation. For more information, see "Manually approving a pending Operator update".

At this point, OLM is now aware of the selected Operator. A cluster service version (CSV) for the Operator should appear in the target namespace, and APIs provided by the Operator should be available for creation.

Verification

  1. Check the status of the Subscription object for your installed Operator by running the following command:

    $ oc describe subscription <subscription_name> -n <namespace>
  2. If you created an Operator group for SingleNamespace install mode, check the status of the OperatorGroup object by running the following command:

    $ oc describe operatorgroup <operatorgroup_name> -n <namespace>

Additional resources

Chapter 10. Changing the cloud provider credentials configuration

For supported configurations, you can change how OpenShift Container Platform authenticates with your cloud provider.

To determine which cloud credentials strategy your cluster uses, see Determining the Cloud Credential Operator mode.

10.1. Rotating or removing cloud provider credentials

After installing OpenShift Container Platform, some organizations require the rotation or removal of the cloud provider credentials that were used during the initial installation.

To allow the cluster to use the new credentials, you must update the secrets that the Cloud Credential Operator (CCO) uses to manage cloud provider credentials.

10.1.1. Rotating cloud provider credentials with the Cloud Credential Operator utility

The Cloud Credential Operator (CCO) utility ccoctl supports updating secrets for clusters installed on IBM Cloud®.

10.1.1.1. Rotating API keys

You can rotate API keys for your existing service IDs and update the corresponding secrets.

Prerequisites

  • You have configured the ccoctl binary.
  • You have existing service IDs in a live OpenShift Container Platform cluster installed.

Procedure

  • Use the ccoctl utility to rotate your API keys for the service IDs and update the secrets:

    $ ccoctl <provider_name> refresh-keys \ 1
        --kubeconfig <openshift_kubeconfig_file> \ 2
        --credentials-requests-dir <path_to_credential_requests_directory> \ 3
        --name <name> 4
    1 1
    The name of the provider. For example: ibmcloud or powervs.
    2 2
    The kubeconfig file associated with the cluster. For example, <installation_directory>/auth/kubeconfig.
    3
    The directory where the credential requests are stored.
    4
    The name of the OpenShift Container Platform cluster.
    Note

    If your cluster uses Technology Preview features that are enabled by the TechPreviewNoUpgrade feature set, you must include the --enable-tech-preview parameter.

10.1.2. Maintaining cloud provider credentials

If your cloud provider credentials are changed for any reason, you must manually update the secret that the Cloud Credential Operator (CCO) uses to manage cloud provider credentials.

The process for rotating cloud credentials depends on the mode that the CCO is configured to use. After you rotate credentials for a cluster that is using mint mode, you must manually remove the component credentials that were created by the removed credential.

Prerequisites

  • Your cluster is installed on a platform that supports rotating cloud credentials manually with the CCO mode that you are using:

    • For mint mode, Amazon Web Services (AWS) and Google Cloud Platform (GCP) are supported.
    • For passthrough mode, Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), Red Hat OpenStack Platform (RHOSP), and VMware vSphere are supported.
  • You have changed the credentials that are used to interface with your cloud provider.
  • The new credentials have sufficient permissions for the mode CCO is configured to use in your cluster.

Procedure

  1. In the Administrator perspective of the web console, navigate to WorkloadsSecrets.
  2. In the table on the Secrets page, find the root secret for your cloud provider.

    PlatformSecret name

    AWS

    aws-creds

    Azure

    azure-credentials

    GCP

    gcp-credentials

    RHOSP

    openstack-credentials

    VMware vSphere

    vsphere-creds

  3. Click the Options menu kebab in the same row as the secret and select Edit Secret.
  4. Record the contents of the Value field or fields. You can use this information to verify that the value is different after updating the credentials.
  5. Update the text in the Value field or fields with the new authentication information for your cloud provider, and then click Save.
  6. If you are updating the credentials for a vSphere cluster that does not have the vSphere CSI Driver Operator enabled, you must force a rollout of the Kubernetes controller manager to apply the updated credentials.

    Note

    If the vSphere CSI Driver Operator is enabled, this step is not required.

    To apply the updated vSphere credentials, log in to the OpenShift Container Platform CLI as a user with the cluster-admin role and run the following command:

    $ oc patch kubecontrollermanager cluster \
      -p='{"spec": {"forceRedeploymentReason": "recovery-'"$( date )"'"}}' \
      --type=merge

    While the credentials are rolling out, the status of the Kubernetes Controller Manager Operator reports Progressing=true. To view the status, run the following command:

    $ oc get co kube-controller-manager
    1. Log in to the OpenShift Container Platform CLI as a user with the cluster-admin role.
    2. Get the names and namespaces of all referenced component secrets:

      $ oc -n openshift-cloud-credential-operator get CredentialsRequest \
        -o json | jq -r '.items[] | select (.spec.providerSpec.kind=="<provider_spec>") | .spec.secretRef'

      where <provider_spec> is the corresponding value for your cloud provider:

      • AWS: AWSProviderSpec
      • GCP: GCPProviderSpec

      Partial example output for AWS

      {
        "name": "ebs-cloud-credentials",
        "namespace": "openshift-cluster-csi-drivers"
      }
      {
        "name": "cloud-credential-operator-iam-ro-creds",
        "namespace": "openshift-cloud-credential-operator"
      }

    3. Delete each of the referenced component secrets:

      $ oc delete secret <secret_name> \1
        -n <secret_namespace> 2
      1
      Specify the name of a secret.
      2
      Specify the namespace that contains the secret.

      Example deletion of an AWS secret

      $ oc delete secret ebs-cloud-credentials -n openshift-cluster-csi-drivers

      You do not need to manually delete the credentials from your provider console. Deleting the referenced component secrets will cause the CCO to delete the existing credentials from the platform and create new ones.

Verification

To verify that the credentials have changed:

  1. In the Administrator perspective of the web console, navigate to WorkloadsSecrets.
  2. Verify that the contents of the Value field or fields have changed.

Additional resources

10.1.3. Removing cloud provider credentials

After installing an OpenShift Container Platform cluster with the Cloud Credential Operator (CCO) in mint mode, you can remove the administrator-level credential secret from the kube-system namespace in the cluster. The administrator-level credential is required only during changes that require its elevated permissions, such as upgrades.

Note

Prior to a non z-stream upgrade, you must reinstate the credential secret with the administrator-level credential. If the credential is not present, the upgrade might be blocked.

Prerequisites

  • Your cluster is installed on a platform that supports removing cloud credentials from the CCO. Supported platforms are AWS and GCP.

Procedure

  1. In the Administrator perspective of the web console, navigate to WorkloadsSecrets.
  2. In the table on the Secrets page, find the root secret for your cloud provider.

    PlatformSecret name

    AWS

    aws-creds

    GCP

    gcp-credentials

  3. Click the Options menu kebab in the same row as the secret and select Delete Secret.

10.2. Enabling token-based authentication

After installing an Microsoft Azure OpenShift Container Platform cluster, you can enable Microsoft Entra Workload ID to use short-term credentials.

10.2.1. Configuring the Cloud Credential Operator utility

To create and manage cloud credentials from outside of the cluster when the Cloud Credential Operator (CCO) is operating in manual mode, extract and prepare the CCO utility (ccoctl) binary.

Note

The ccoctl utility is a Linux binary that must run in a Linux environment.

Prerequisites

  • You have access to an OpenShift Container Platform account with cluster administrator access.
  • You have installed the OpenShift CLI (oc).

Procedure

  1. Set a variable for the OpenShift Container Platform release image by running the following command:

    $ RELEASE_IMAGE=$(./openshift-install version | awk '/release image/ {print $3}')
  2. Obtain the CCO container image from the OpenShift Container Platform release image by running the following command:

    $ CCO_IMAGE=$(oc adm release info --image-for='cloud-credential-operator' $RELEASE_IMAGE -a ~/.pull-secret)
    Note

    Ensure that the architecture of the $RELEASE_IMAGE matches the architecture of the environment in which you will use the ccoctl tool.

  3. Extract the ccoctl binary from the CCO container image within the OpenShift Container Platform release image by running the following command:

    $ oc image extract $CCO_IMAGE \
      --file="/usr/bin/ccoctl.<rhel_version>" \1
      -a ~/.pull-secret
    1
    For <rhel_version>, specify the value that corresponds to the version of Red Hat Enterprise Linux (RHEL) that the host uses. If no value is specified, ccoctl.rhel8 is used by default. The following values are valid:
    • rhel8: Specify this value for hosts that use RHEL 8.
    • rhel9: Specify this value for hosts that use RHEL 9.
  4. Change the permissions to make ccoctl executable by running the following command:

    $ chmod 775 ccoctl.<rhel_version>

Verification

  • To verify that ccoctl is ready to use, display the help file. Use a relative file name when you run the command, for example:

    $ ./ccoctl.rhel9

    Example output

    OpenShift credentials provisioning tool
    
    Usage:
      ccoctl [command]
    
    Available Commands:
      aws          Manage credentials objects for AWS cloud
      azure        Manage credentials objects for Azure
      gcp          Manage credentials objects for Google cloud
      help         Help about any command
      ibmcloud     Manage credentials objects for {ibm-cloud-title}
      nutanix      Manage credentials objects for Nutanix
    
    Flags:
      -h, --help   help for ccoctl
    
    Use "ccoctl [command] --help" for more information about a command.

10.2.2. Enabling Microsoft Entra Workload ID on an existing cluster

If you did not configure your Microsoft Azure OpenShift Container Platform cluster to use Microsoft Entra Workload ID during installation, you can enable this authentication method on an existing cluster.

Important

The process to enable Workload ID on an existing cluster is disruptive and takes a significant amount of time. Before proceeding, observe the following considerations:

  • Read the following steps and ensure that you understand and accept the time requirement. The exact time requirement varies depending on the individual cluster, but it is likely to require at least one hour.
  • During this process, you must refresh all service accounts and restart all pods on the cluster. These actions are disruptive to workloads. To mitigate this impact, you can temporarily halt these services and then redeploy them when the cluster is ready.
  • After starting this process, do not attempt to update the cluster until it is complete. If an update is triggered, the process to enable Workload ID on an existing cluster fails.

Prerequisites

  • You have installed an OpenShift Container Platform cluster on Microsoft Azure.
  • You have access to the cluster using an account with cluster-admin permissions.
  • You have installed the OpenShift CLI (oc).
  • You have extracted and prepared the Cloud Credential Operator utility (ccoctl) binary.
  • You have access to your Azure account by using the Azure CLI (az).

Procedure

  1. Create an output directory for the manifests that the ccoctl utility generates. This procedure uses ./output_dir as an example.
  2. Extract the service account public signing key for the cluster to the output directory by running the following command:

    $ oc get configmap \
      --namespace openshift-kube-apiserver bound-sa-token-signing-certs \
      --output 'go-template={{index .data "service-account-001.pub"}}' > ./output_dir/serviceaccount-signer.public 1
    1
    This procedure uses a file named serviceaccount-signer.public as an example.
  3. Use the extracted service account public signing key to create an OpenID Connect (OIDC) issuer and Azure blob storage container with OIDC configuration files by running the following command:

    $ ./ccoctl azure create-oidc-issuer \
      --name <azure_infra_name> \1
      --output-dir ./output_dir \
      --region <azure_region> \2
      --subscription-id <azure_subscription_id> \3
      --tenant-id <azure_tenant_id> \
      --public-key-file ./output_dir/serviceaccount-signer.public 4
    1
    The value of the name parameter is used to create an Azure resource group. To use an existing Azure resource group instead of creating a new one, specify the --oidc-resource-group-name argument with the existing group name as its value.
    2
    Specify the region of the existing cluster.
    3
    Specify the subscription ID of the existing cluster.
    4
    Specify the file that contains the service account public signing key for the cluster.
  4. Verify that the configuration file for the Azure pod identity webhook was created by running the following command:

    $ ll ./output_dir/manifests

    Example output

    total 8
    -rw-------. 1 cloud-user cloud-user 193 May 22 02:29 azure-ad-pod-identity-webhook-config.yaml 1
    -rw-------. 1 cloud-user cloud-user 165 May 22 02:29 cluster-authentication-02-config.yaml

    1
    The file azure-ad-pod-identity-webhook-config.yaml contains the Azure pod identity webhook configuration.
  5. Set an OIDC_ISSUER_URL variable with the OIDC issuer URL from the generated manifests in the output directory by running the following command:

    $ OIDC_ISSUER_URL=`awk '/serviceAccountIssuer/ { print $2 }' ./output_dir/manifests/cluster-authentication-02-config.yaml`
  6. Update the spec.serviceAccountIssuer parameter of the cluster authentication configuration by running the following command:

    $ oc patch authentication cluster \
      --type=merge \
      -p "{\"spec\":{\"serviceAccountIssuer\":\"${OIDC_ISSUER_URL}\"}}"
  7. Monitor the configuration update progress by running the following command:

    $ oc adm wait-for-stable-cluster

    This process might take 15 minutes or longer. The following output indicates that the process is complete:

    All clusteroperators are stable
  8. Restart all of the pods in the cluster by running the following command:

    $ oc adm reboot-machine-config-pool mcp/worker mcp/master

    Restarting a pod updates the serviceAccountIssuer field and refreshes the service account public signing key.

  9. Monitor the restart and update process by running the following command:

    $ oc adm wait-for-node-reboot nodes --all

    This process might take 15 minutes or longer. The following output indicates that the process is complete:

    All nodes rebooted
  10. Update the Cloud Credential Operator spec.credentialsMode parameter to Manual by running the following command:

    $ oc patch cloudcredential cluster \
      --type=merge \
      --patch '{"spec":{"credentialsMode":"Manual"}}'
  11. Extract the list of CredentialsRequest objects from the OpenShift Container Platform release image by running the following command:

    $ oc adm release extract \
      --credentials-requests \
      --included \
      --to <path_to_directory_for_credentials_requests> \
      --registry-config ~/.pull-secret
    Note

    This command might take a few moments to run.

  12. Set an AZURE_INSTALL_RG variable with the Azure resource group name by running the following command:

    $ AZURE_INSTALL_RG=`oc get infrastructure cluster -o jsonpath --template '{ .status.platformStatus.azure.resourceGroupName }'`
  13. Use the ccoctl utility to create managed identities for all CredentialsRequest objects by running the following command:

    $ ccoctl azure create-managed-identities \
      --name <azure_infra_name> \
      --output-dir ./output_dir \
      --region <azure_region> \
      --subscription-id <azure_subscription_id> \
      --credentials-requests-dir <path_to_directory_for_credentials_requests> \
      --issuer-url "${OIDC_ISSUER_URL}" \
      --dnszone-resource-group-name <azure_dns_zone_resourcegroup_name> \1
      --installation-resource-group-name "${AZURE_INSTALL_RG}"
    1
    Specify the name of the resource group that contains the DNS zone.
  14. Apply the Azure pod identity webhook configuration for Workload ID by running the following command:

    $ oc apply -f ./output_dir/manifests/azure-ad-pod-identity-webhook-config.yaml
  15. Apply the secrets generated by the ccoctl utility by running the following command:

    $ find ./output_dir/manifests -iname "openshift*yaml" -print0 | xargs -I {} -0 -t oc replace -f {}

    This process might take several minutes.

  16. Restart all of the pods in the cluster by running the following command:

    $ oc adm reboot-machine-config-pool mcp/worker mcp/master

    Restarting a pod updates the serviceAccountIssuer field and refreshes the service account public signing key.

  17. Monitor the restart and update process by running the following command:

    $ oc adm wait-for-node-reboot nodes --all

    This process might take 15 minutes or longer. The following output indicates that the process is complete:

    All nodes rebooted
  18. Monitor the configuration update progress by running the following command:

    $ oc adm wait-for-stable-cluster

    This process might take 15 minutes or longer. The following output indicates that the process is complete:

    All clusteroperators are stable
  19. Optional: Remove the Azure root credentials secret by running the following command:

    $ oc delete secret -n kube-system azure-credentials

10.2.3. Verifying that a cluster uses short-term credentials

You can verify that a cluster uses short-term security credentials for individual components by checking the Cloud Credential Operator (CCO) configuration and other values in the cluster.

Prerequisites

  • You deployed an OpenShift Container Platform cluster using the Cloud Credential Operator utility (ccoctl) to implement short-term credentials.
  • You installed the OpenShift CLI (oc).
  • You are logged in as a user with cluster-admin privileges.

Procedure

  • Verify that the CCO is configured to operate in manual mode by running the following command:

    $ oc get cloudcredentials cluster \
      -o=jsonpath={.spec.credentialsMode}

    The following output confirms that the CCO is operating in manual mode:

    Example output

    Manual

  • Verify that the cluster does not have root credentials by running the following command:

    $ oc get secrets \
      -n kube-system <secret_name>

    where <secret_name> is the name of the root secret for your cloud provider.

    PlatformSecret name

    Amazon Web Services (AWS)

    aws-creds

    Microsoft Azure

    azure-credentials

    Google Cloud Platform (GCP)

    gcp-credentials

    An error confirms that the root secret is not present on the cluster.

    Example output for an AWS cluster

    Error from server (NotFound): secrets "aws-creds" not found

  • Verify that the components are using short-term security credentials for individual components by running the following command:

    $ oc get authentication cluster \
      -o jsonpath \
      --template='{ .spec.serviceAccountIssuer }'

    This command displays the value of the .spec.serviceAccountIssuer parameter in the cluster Authentication object. An output of a URL that is associated with your cloud provider indicates that the cluster is using manual mode with short-term credentials that are created and managed from outside of the cluster.

  • Azure clusters: Verify that the components are assuming the Azure client ID that is specified in the secret manifests by running the following command:

    $ oc get secrets \
      -n openshift-image-registry installer-cloud-credentials \
      -o jsonpath='{.data}'

    An output that contains the azure_client_id and azure_federated_token_file felids confirms that the components are assuming the Azure client ID.

  • Azure clusters: Verify that the pod identity webhook is running by running the following command:

    $ oc get pods \
      -n openshift-cloud-credential-operator

    Example output

    NAME                                         READY   STATUS    RESTARTS   AGE
    cloud-credential-operator-59cf744f78-r8pbq   2/2     Running   2          71m
    pod-identity-webhook-548f977b4c-859lz        1/1     Running   1          70m

10.3. Additional resources

Chapter 11. Configuring alert notifications

In OpenShift Container Platform, an alert is fired when the conditions defined in an alerting rule are true. An alert provides a notification that a set of circumstances are apparent within a cluster. Firing alerts can be viewed in the Alerting UI in the OpenShift Container Platform web console by default. After an installation, you can configure OpenShift Container Platform to send alert notifications to external systems.

11.1. Sending notifications to external systems

In OpenShift Container Platform 4.17, firing alerts can be viewed in the Alerting UI. Alerts are not configured by default to be sent to any notification systems. You can configure OpenShift Container Platform to send alerts to the following receiver types:

  • PagerDuty
  • Webhook
  • Email
  • Slack
  • Microsoft Teams

Routing alerts to receivers enables you to send timely notifications to the appropriate teams when failures occur. For example, critical alerts require immediate attention and are typically paged to an individual or a critical response team. Alerts that provide non-critical warning notifications might instead be routed to a ticketing system for non-immediate review.

Checking that alerting is operational by using the watchdog alert

OpenShift Container Platform monitoring includes a watchdog alert that fires continuously. Alertmanager repeatedly sends watchdog alert notifications to configured notification providers. The provider is usually configured to notify an administrator when it stops receiving the watchdog alert. This mechanism helps you quickly identify any communication issues between Alertmanager and the notification provider.

11.2. Additional resources

Chapter 12. Converting a connected cluster to a disconnected cluster

There might be some scenarios where you need to convert your OpenShift Container Platform cluster from a connected cluster to a disconnected cluster.

A disconnected cluster, also known as a restricted cluster, does not have an active connection to the internet. As such, you must mirror the contents of your registries and installation media. You can create this mirror registry on a host that can access both the internet and your closed network, or copy images to a device that you can move across network boundaries.

For information on how to convert your cluster, see the Converting a connected cluster to a disconnected cluster procedure in the Disconnected environments section.

Legal Notice

Copyright © 2024 Red Hat, Inc.

OpenShift documentation is licensed under the Apache License 2.0 (https://www.apache.org/licenses/LICENSE-2.0).

Modified versions must remove all Red Hat trademarks.

Portions adapted from https://github.com/kubernetes-incubator/service-catalog/ with modifications by Red Hat.

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