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Chapter 6. Scheduling NUMA-aware workloads
Learn about NUMA-aware scheduling and how you can use it to deploy high performance workloads in an OpenShift Container Platform cluster.
NUMA-aware scheduling is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.
For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope.
The NUMA Resources Operator allows you to schedule high-performance workloads in the same NUMA zone. It deploys a node resources exporting agent that reports on available cluster node NUMA resources, and a secondary scheduler that manages the workloads.
6.1. About NUMA-aware scheduling
Non-Uniform Memory Access (NUMA) is a compute platform architecture that allows different CPUs to access different regions of memory at different speeds. NUMA resource topology refers to the locations of CPUs, memory, and PCI devices relative to each other in the compute node. Co-located resources are said to be in the same NUMA zone. For high-performance applications, the cluster needs to process pod workloads in a single NUMA zone.
NUMA architecture allows a CPU with multiple memory controllers to use any available memory across CPU complexes, regardless of where the memory is located. This allows for increased flexibility at the expense of performance. A CPU processing a workload using memory that is outside its NUMA zone is slower than a workload processed in a single NUMA zone. Also, for I/O-constrained workloads, the network interface on a distant NUMA zone slows down how quickly information can reach the application. High-performance workloads, such as telecommunications workloads, cannot operate to specification under these conditions. NUMA-aware scheduling aligns the requested cluster compute resources (CPUs, memory, devices) in the same NUMA zone to process latency-sensitive or high-performance workloads efficiently. NUMA-aware scheduling also improves pod density per compute node for greater resource efficiency.
The default OpenShift Container Platform pod scheduler scheduling logic considers the available resources of the entire compute node, not individual NUMA zones. If the most restrictive resource alignment is requested in the kubelet topology manager, error conditions can occur when admitting the pod to a node. Conversely, if the most restrictive resource alignment is not requested, the pod can be admitted to the node without proper resource alignment, leading to worse or unpredictable performance. For example, runaway pod creation with Topology Affinity Error
statuses can occur when the pod scheduler makes suboptimal scheduling decisions for guaranteed pod workloads by not knowing if the pod’s requested resources are available. Scheduling mismatch decisions can cause indefinite pod startup delays. Also, depending on the cluster state and resource allocation, poor pod scheduling decisions can cause extra load on the cluster because of failed startup attempts.
The NUMA Resources Operator deploys a custom NUMA resources secondary scheduler and other resources to mitigate against the shortcomings of the default OpenShift Container Platform pod scheduler. The following diagram provides a high-level overview of NUMA-aware pod scheduling.
Figure 6.1. NUMA-aware scheduling overview
- NodeResourceTopology API
-
The
NodeResourceTopology
API describes the available NUMA zone resources in each compute node. - NUMA-aware scheduler
-
The NUMA-aware secondary scheduler receives information about the available NUMA zones from the
NodeResourceTopology
API and schedules high-performance workloads on a node where it can be optimally processed. - Node topology exporter
-
The node topology exporter exposes the available NUMA zone resources for each compute node to the
NodeResourceTopology
API. The node topology exporter daemon tracks the resource allocation from the kubelet by using thePodResources
API. - PodResources API
-
The
PodResources
API is local to each node and exposes the resource topology and available resources to the kubelet.
Additional resources
- For more information about running secondary pod schedulers in your cluster and how to deploy pods with a secondary pod scheduler, see Scheduling pods using a secondary scheduler.
6.2. Installing the NUMA Resources Operator
NUMA Resources Operator deploys resources that allow you to schedule NUMA-aware workloads and deployments. You can install the NUMA Resources Operator using the OpenShift Container Platform CLI or the web console.
6.2.1. Installing the NUMA Resources Operator using the CLI
As a cluster administrator, you can install the Operator using the CLI.
Prerequisites
-
Install the OpenShift CLI (
oc
). -
Log in as a user with
cluster-admin
privileges.
Procedure
Create a namespace for the NUMA Resources Operator:
Save the following YAML in the
nro-namespace.yaml
file:apiVersion: v1 kind: Namespace metadata: name: openshift-numaresources
Create the
Namespace
CR by running the following command:$ oc create -f nro-namespace.yaml
Create the Operator group for the NUMA Resources Operator:
Save the following YAML in the
nro-operatorgroup.yaml
file:apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: numaresources-operator namespace: openshift-numaresources spec: targetNamespaces: - openshift-numaresources
Create the
OperatorGroup
CR by running the following command:$ oc create -f nro-operatorgroup.yaml
Create the subscription for the NUMA Resources Operator:
Save the following YAML in the
nro-sub.yaml
file:apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: numaresources-operator namespace: openshift-numaresources spec: channel: "{product-version}" name: numaresources-operator source: redhat-operators sourceNamespace: openshift-marketplace
Create the
Subscription
CR by running the following command:$ oc create -f nro-sub.yaml
Verification
Verify that the installation succeeded by inspecting the CSV resource in the
openshift-numaresources
namespace. Run the following command:$ oc get csv -n openshift-numaresources
Example output
NAME DISPLAY VERSION REPLACES PHASE numaresources-operator.v4.10.0 NUMA Resources Operator 4.10.0 Succeeded
6.2.2. Installing the NUMA Resources Operator using the web console
As a cluster administrator, you can install the NUMA Resources Operator using the web console.
Procedure
Install the NUMA Resources Operator using the OpenShift Container Platform web console:
-
In the OpenShift Container Platform web console, click Operators
OperatorHub. - Choose NUMA Resources Operator from the list of available Operators, and then click Install.
-
In the OpenShift Container Platform web console, click Operators
Optional: Verify that the NUMA Resources Operator installed successfully:
-
Switch to the Operators
Installed Operators page. Ensure that NUMA Resources Operator is listed in the default project with a Status of InstallSucceeded.
NoteDuring installation an Operator might display a Failed status. If the installation later succeeds with an InstallSucceeded message, you can ignore the Failed message.
If the Operator does not appear as installed, to troubleshoot further:
-
Go to the Operators
Installed Operators page and inspect the Operator Subscriptions and Install Plans tabs for any failure or errors under Status. -
Go to the Workloads
Pods page and check the logs for pods in the default
project.
-
Go to the Operators
-
Switch to the Operators
6.3. Creating the NUMAResourcesOperator custom resource
When you have installed the NUMA Resources Operator, then create the NUMAResourcesOperator
custom resource (CR) that instructs the NUMA Resources Operator to install all the cluster infrastructure needed to support the NUMA-aware scheduler, including daemon sets and APIs.
Prerequisites
-
Install the OpenShift CLI (
oc
). -
Log in as a user with
cluster-admin
privileges. - Install the NUMA Resources Operator.
Procedure
Create the
MachineConfigPool
custom resource that enables custom kubelet configurations for worker nodes:Save the following YAML in the
nro-machineconfig.yaml
file:apiVersion: machineconfiguration.openshift.io/v1 kind: MachineConfigPool metadata: labels: cnf-worker-tuning: enabled machineconfiguration.openshift.io/mco-built-in: "" pools.operator.machineconfiguration.openshift.io/worker: "" name: worker spec: machineConfigSelector: matchLabels: machineconfiguration.openshift.io/role: worker nodeSelector: matchLabels: node-role.kubernetes.io/worker: ""
Create the
MachineConfigPool
CR by running the following command:$ oc create -f nro-machineconfig.yaml
Create the
NUMAResourcesOperator
custom resource:Save the following YAML in the
nrop.yaml
file:apiVersion: nodetopology.openshift.io/v1alpha1 kind: NUMAResourcesOperator metadata: name: numaresourcesoperator spec: nodeGroups: - machineConfigPoolSelector: matchLabels: pools.operator.machineconfiguration.openshift.io/worker: "" 1
- 1
- Should match the label applied to worker nodes in the related
MachineConfigPool
CR.
Create the
NUMAResourcesOperator
CR by running the following command:$ oc create -f nrop.yaml
Verification
Verify that the NUMA Resources Operator deployed successfully by running the following command:
$ oc get numaresourcesoperators.nodetopology.openshift.io
Example output
NAME AGE numaresourcesoperator 10m
6.4. Deploying the NUMA-aware secondary pod scheduler
After you install the NUMA Resources Operator, do the following to deploy the NUMA-aware secondary pod scheduler:
- Configure the pod admittance policy for the required machine profile
- Create the required machine config pool
- Deploy the NUMA-aware secondary scheduler
Prerequisites
-
Install the OpenShift CLI (
oc
). -
Log in as a user with
cluster-admin
privileges. - Install the NUMA Resources Operator.
Procedure
Create the
KubeletConfig
custom resource that configures the pod admittance policy for the machine profile:Save the following YAML in the
nro-kubeletconfig.yaml
file:apiVersion: machineconfiguration.openshift.io/v1 kind: KubeletConfig metadata: name: cnf-worker-tuning spec: machineConfigPoolSelector: matchLabels: cnf-worker-tuning: enabled kubeletConfig: cpuManagerPolicy: "static" 1 cpuManagerReconcilePeriod: "5s" reservedSystemCPUs: "0,1" memoryManagerPolicy: "Static" 2 evictionHard: memory.available: "100Mi" kubeReserved: memory: "512Mi" reservedMemory: - numaNode: 0 limits: memory: "1124Mi" systemReserved: memory: "512Mi" topologyManagerPolicy: "single-numa-node" 3 topologyManagerScope: "pod"
Create the
KubeletConfig
custom resource (CR) by running the following command:$ oc create -f nro-kubeletconfig.yaml
Create the
NUMAResourcesScheduler
custom resource that deploys the NUMA-aware custom pod scheduler:Save the following YAML in the
nro-scheduler.yaml
file:apiVersion: nodetopology.openshift.io/v1alpha1 kind: NUMAResourcesScheduler metadata: name: numaresourcesscheduler spec: imageSpec: "registry.redhat.io/openshift4/noderesourcetopology-scheduler-container-rhel8:v4.10"
Create the
NUMAResourcesScheduler
CR by running the following command:$ oc create -f nro-scheduler.yaml
Verification
Verify that the required resources deployed successfully by running the following command:
$ oc get all -n openshift-numaresources
Example output
NAME READY STATUS RESTARTS AGE pod/numaresources-controller-manager-7575848485-bns4s 1/1 Running 0 13m pod/numaresourcesoperator-worker-dvj4n 2/2 Running 0 16m pod/numaresourcesoperator-worker-lcg4t 2/2 Running 0 16m pod/secondary-scheduler-56994cf6cf-7qf4q 1/1 Running 0 16m NAME DESIRED CURRENT READY UP-TO-DATE AVAILABLE NODE SELECTOR AGE daemonset.apps/numaresourcesoperator-worker 2 2 2 2 2 node-role.kubernetes.io/worker= 16m NAME READY UP-TO-DATE AVAILABLE AGE deployment.apps/numaresources-controller-manager 1/1 1 1 13m deployment.apps/secondary-scheduler 1/1 1 1 16m NAME DESIRED CURRENT READY AGE replicaset.apps/numaresources-controller-manager-7575848485 1 1 1 13m replicaset.apps/secondary-scheduler-56994cf6cf 1 1 1 16m
6.5. Scheduling workloads with the NUMA-aware scheduler
You can schedule workloads with the NUMA-aware scheduler using Deployment
CRs that specify the minimum required resources to process the workload.
The following example deployment uses NUMA-aware scheduling for a sample workload.
Prerequisites
-
Install the OpenShift CLI (
oc
). -
Log in as a user with
cluster-admin
privileges. - Install the NUMA Resources Operator and deploy the NUMA-aware secondary scheduler.
Procedure
Get the name of the NUMA-aware scheduler that is deployed in the cluster by running the following command:
$ oc get numaresourcesschedulers.nodetopology.openshift.io numaresourcesscheduler -o json | jq '.status.schedulerName'
Example output
topo-aware-scheduler
Create a
Deployment
CR that uses scheduler namedtopo-aware-scheduler
, for example:Save the following YAML in the
nro-deployment.yaml
file:apiVersion: apps/v1 kind: Deployment metadata: name: numa-deployment-1 namespace: openshift-numaresources spec: replicas: 1 selector: matchLabels: app: test template: metadata: labels: app: test spec: schedulerName: topo-aware-scheduler 1 containers: - name: ctnr image: quay.io/openshifttest/hello-openshift:openshift imagePullPolicy: IfNotPresent resources: limits: memory: "100Mi" cpu: "10" requests: memory: "100Mi" cpu: "10" - name: ctnr2 image: registry.access.redhat.com/rhel:latest imagePullPolicy: IfNotPresent command: ["/bin/sh", "-c"] args: [ "while true; do sleep 1h; done;" ] resources: limits: memory: "100Mi" cpu: "8" requests: memory: "100Mi" cpu: "8"
- 1
schedulerName
must match the name of the NUMA-aware scheduler that is deployed in your cluster, for exampletopo-aware-scheduler
.
Create the
Deployment
CR by running the following command:$ oc create -f nro-deployment.yaml
Verification
Verify that the deployment was successful:
$ oc get pods -n openshift-numaresources
Example output
NAME READY STATUS RESTARTS AGE numa-deployment-1-56954b7b46-pfgw8 2/2 Running 0 129m numaresources-controller-manager-7575848485-bns4s 1/1 Running 0 15h numaresourcesoperator-worker-dvj4n 2/2 Running 0 18h numaresourcesoperator-worker-lcg4t 2/2 Running 0 16h secondary-scheduler-56994cf6cf-7qf4q 1/1 Running 0 18h
Verify that the
topo-aware-scheduler
is scheduling the deployed pod by running the following command:$ oc describe pod numa-deployment-1-56954b7b46-pfgw8 -n openshift-numaresources
Example output
Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal Scheduled 130m topo-aware-scheduler Successfully assigned openshift-numaresources/numa-deployment-1-56954b7b46-pfgw8 to compute-0.example.com
NoteDeployments that request more resources than is available for scheduling will fail with a
MinimumReplicasUnavailable
error. The deployment succeeds when the required resources become available. Pods remain in thePending
state until the required resources are available.Verify that the expected allocated resources are listed for the node. Run the following command:
$ oc describe noderesourcetopologies.topology.node.k8s.io
Example output
... Zones: Costs: Name: node-0 Value: 10 Name: node-1 Value: 21 Name: node-0 Resources: Allocatable: 39 Available: 21 1 Capacity: 40 Name: cpu Allocatable: 6442450944 Available: 6442450944 Capacity: 6442450944 Name: hugepages-1Gi Allocatable: 134217728 Available: 134217728 Capacity: 134217728 Name: hugepages-2Mi Allocatable: 262415904768 Available: 262206189568 Capacity: 270146007040 Name: memory Type: Node
- 1
- The
Available
capacity is reduced because of the resources that have been allocated to the guaranteed pod.
Resources consumed by guaranteed pods are subtracted from the available node resources listed under
noderesourcetopologies.topology.node.k8s.io
.Resource allocations for pods with a
Best-effort
orBurstable
quality of service (qosClass
) are not reflected in the NUMA node resources undernoderesourcetopologies.topology.node.k8s.io
. If a pod’s consumed resources are not reflected in the node resource calculation, verify that the pod hasqosClass
ofGuaranteed
by running the following command:$ oc get pod <pod_name> -n <pod_namespace> -o jsonpath="{ .status.qosClass }"
Example output
Guaranteed
6.6. Troubleshooting NUMA-aware scheduling
To troubleshoot common problems with NUMA-aware pod scheduling, perform the following steps.
Prerequisites
-
Install the OpenShift Container Platform CLI (
oc
). - Log in as a user with cluster-admin privileges.
- Install the NUMA Resources Operator and deploy the NUMA-aware secondary scheduler.
Procedure
Verify that the
noderesourcetopologies
CRD is deployed in the cluster by running the following command:$ oc get crd | grep noderesourcetopologies
Example output
NAME CREATED AT noderesourcetopologies.topology.node.k8s.io 2022-01-18T08:28:06Z
Check that the NUMA-aware scheduler name matches the name specified in your NUMA-aware workloads by running the following command:
$ oc get numaresourcesschedulers.nodetopology.openshift.io numaresourcesscheduler -o json | jq '.status.schedulerName'
Example output
topo-aware-scheduler
Verify that NUMA-aware scheduable nodes have the
noderesourcetopologies
CR applied to them. Run the following command:$ oc get noderesourcetopologies.topology.node.k8s.io
Example output
NAME AGE compute-0.example.com 17h compute-1.example.com 17h
NoteThe number of nodes should equal the number of worker nodes that are configured by the machine config pool (
mcp
) worker definition.Verify the NUMA zone granularity for all scheduable nodes by running the following command:
$ oc get noderesourcetopologies.topology.node.k8s.io -o yaml
Example output
apiVersion: v1 items: - apiVersion: topology.node.k8s.io/v1alpha1 kind: NodeResourceTopology metadata: annotations: k8stopoawareschedwg/rte-update: periodic creationTimestamp: "2022-06-16T08:55:38Z" generation: 63760 name: worker-0 resourceVersion: "8450223" uid: 8b77be46-08c0-4074-927b-d49361471590 topologyPolicies: - SingleNUMANodeContainerLevel zones: - costs: - name: node-0 value: 10 - name: node-1 value: 21 name: node-0 resources: - allocatable: "38" available: "38" capacity: "40" name: cpu - allocatable: "134217728" available: "134217728" capacity: "134217728" name: hugepages-2Mi - allocatable: "262352048128" available: "262352048128" capacity: "270107316224" name: memory - allocatable: "6442450944" available: "6442450944" capacity: "6442450944" name: hugepages-1Gi type: Node - costs: - name: node-0 value: 21 - name: node-1 value: 10 name: node-1 resources: - allocatable: "268435456" available: "268435456" capacity: "268435456" name: hugepages-2Mi - allocatable: "269231067136" available: "269231067136" capacity: "270573244416" name: memory - allocatable: "40" available: "40" capacity: "40" name: cpu - allocatable: "1073741824" available: "1073741824" capacity: "1073741824" name: hugepages-1Gi type: Node - apiVersion: topology.node.k8s.io/v1alpha1 kind: NodeResourceTopology metadata: annotations: k8stopoawareschedwg/rte-update: periodic creationTimestamp: "2022-06-16T08:55:37Z" generation: 62061 name: worker-1 resourceVersion: "8450129" uid: e8659390-6f8d-4e67-9a51-1ea34bba1cc3 topologyPolicies: - SingleNUMANodeContainerLevel zones: 1 - costs: - name: node-0 value: 10 - name: node-1 value: 21 name: node-0 resources: 2 - allocatable: "38" available: "38" capacity: "40" name: cpu - allocatable: "6442450944" available: "6442450944" capacity: "6442450944" name: hugepages-1Gi - allocatable: "134217728" available: "134217728" capacity: "134217728" name: hugepages-2Mi - allocatable: "262391033856" available: "262391033856" capacity: "270146301952" name: memory type: Node - costs: - name: node-0 value: 21 - name: node-1 value: 10 name: node-1 resources: - allocatable: "40" available: "40" capacity: "40" name: cpu - allocatable: "1073741824" available: "1073741824" capacity: "1073741824" name: hugepages-1Gi - allocatable: "268435456" available: "268435456" capacity: "268435456" name: hugepages-2Mi - allocatable: "269192085504" available: "269192085504" capacity: "270534262784" name: memory type: Node kind: List metadata: resourceVersion: "" selfLink: ""
6.6.1. Checking the NUMA-aware scheduler logs
Troubleshoot problems with the NUMA-aware scheduler by reviewing the logs. If required, you can increase the scheduler log level by modifying the spec.logLevel
field of the NUMAResourcesScheduler
resource. Acceptable values are Normal
, Debug
, and Trace
, with Trace
being the most verbose option.
To change the log level of the secondary scheduler, delete the running scheduler resource and re-deploy it with the changed log level. The scheduler is unavailable for scheduling new workloads during this downtime.
Prerequisites
-
Install the OpenShift CLI (
oc
). -
Log in as a user with
cluster-admin
privileges.
Procedure
Delete the currently running
NUMAResourcesScheduler
resource:Get the active
NUMAResourcesScheduler
by running the following command:$ oc get NUMAResourcesScheduler
Example output
NAME AGE numaresourcesscheduler 90m
Delete the secondary scheduler resource by running the following command:
$ oc delete NUMAResourcesScheduler numaresourcesscheduler
Example output
numaresourcesscheduler.nodetopology.openshift.io "numaresourcesscheduler" deleted
Save the following YAML in the file
nro-scheduler-debug.yaml
. This example changes the log level toDebug
:apiVersion: nodetopology.openshift.io/v1alpha1 kind: NUMAResourcesScheduler metadata: name: numaresourcesscheduler spec: imageSpec: "registry.redhat.io/openshift4/noderesourcetopology-scheduler-container-rhel8:v4.10" logLevel: Debug
Create the updated
Debug
loggingNUMAResourcesScheduler
resource by running the following command:$ oc create -f nro-scheduler-debug.yaml
Example output
numaresourcesscheduler.nodetopology.openshift.io/numaresourcesscheduler created
Verification steps
Check that the NUMA-aware scheduler was successfully deployed:
Run the following command to check that the CRD is created succesfully:
$ oc get crd | grep numaresourcesschedulers
Example output
NAME CREATED AT numaresourcesschedulers.nodetopology.openshift.io 2022-02-25T11:57:03Z
Check that the new custom scheduler is available by running the following command:
$ oc get numaresourcesschedulers.nodetopology.openshift.io
Example output
NAME AGE numaresourcesscheduler 3h26m
Check that the logs for the scheduler shows the increased log level:
Get the list of pods running in the
openshift-numaresources
namespace by running the following command:$ oc get pods -n openshift-numaresources
Example output
NAME READY STATUS RESTARTS AGE numaresources-controller-manager-d87d79587-76mrm 1/1 Running 0 46h numaresourcesoperator-worker-5wm2k 2/2 Running 0 45h numaresourcesoperator-worker-pb75c 2/2 Running 0 45h secondary-scheduler-7976c4d466-qm4sc 1/1 Running 0 21m
Get the logs for the secondary scheduler pod by running the following command:
$ oc logs secondary-scheduler-7976c4d466-qm4sc -n openshift-numaresources
Example output
... I0223 11:04:55.614788 1 reflector.go:535] k8s.io/client-go/informers/factory.go:134: Watch close - *v1.Namespace total 11 items received I0223 11:04:56.609114 1 reflector.go:535] k8s.io/client-go/informers/factory.go:134: Watch close - *v1.ReplicationController total 10 items received I0223 11:05:22.626818 1 reflector.go:535] k8s.io/client-go/informers/factory.go:134: Watch close - *v1.StorageClass total 7 items received I0223 11:05:31.610356 1 reflector.go:535] k8s.io/client-go/informers/factory.go:134: Watch close - *v1.PodDisruptionBudget total 7 items received I0223 11:05:31.713032 1 eventhandlers.go:186] "Add event for scheduled pod" pod="openshift-marketplace/certified-operators-thtvq" I0223 11:05:53.461016 1 eventhandlers.go:244] "Delete event for scheduled pod" pod="openshift-marketplace/certified-operators-thtvq"
6.6.2. Troubleshooting the resource topology exporter
Troubleshoot noderesourcetopologies
objects where unexpected results are occurring by inspecting the corresponding resource-topology-exporter
logs.
It is recommended that NUMA resource topology exporter instances in the cluster are named for nodes they refer to. For example, a worker node with the name worker
should have a corresponding noderesourcetopologies
object called worker
.
Prerequisites
-
Install the OpenShift CLI (
oc
). -
Log in as a user with
cluster-admin
privileges.
Procedure
Get the daemonsets managed by the NUMA Resources Operator. Each daemonset has a corresponding
nodeGroup
in theNUMAResourcesOperator
CR. Run the following command:$ oc get numaresourcesoperators.nodetopology.openshift.io numaresourcesoperator -o jsonpath="{.status.daemonsets[0]}"
Example output
{"name":"numaresourcesoperator-worker","namespace":"openshift-numaresources"}
Get the label for the daemonset of interest using the value for
name
from the previous step:$ oc get ds -n openshift-numaresources numaresourcesoperator-worker -o jsonpath="{.spec.selector.matchLabels}"
Example output
{"name":"resource-topology"}
Get the pods using the
resource-topology
label by running the following command:$ oc get pods -n openshift-numaresources -l name=resource-topology -o wide
Example output
NAME READY STATUS RESTARTS AGE IP NODE numaresourcesoperator-worker-5wm2k 2/2 Running 0 2d1h 10.135.0.64 compute-0.example.com numaresourcesoperator-worker-pb75c 2/2 Running 0 2d1h 10.132.2.33 compute-1.example.com
Examine the logs of the
resource-topology-exporter
container running on the worker pod that corresponds to the node you are troubleshooting. Run the following command:$ oc logs -n openshift-numaresources -c resource-topology-exporter numaresourcesoperator-worker-pb75c
Example output
I0221 13:38:18.334140 1 main.go:206] using sysinfo: reservedCpus: 0,1 reservedMemory: "0": 1178599424 I0221 13:38:18.334370 1 main.go:67] === System information === I0221 13:38:18.334381 1 sysinfo.go:231] cpus: reserved "0-1" I0221 13:38:18.334493 1 sysinfo.go:237] cpus: online "0-103" I0221 13:38:18.546750 1 main.go:72] cpus: allocatable "2-103" hugepages-1Gi: numa cell 0 -> 6 numa cell 1 -> 1 hugepages-2Mi: numa cell 0 -> 64 numa cell 1 -> 128 memory: numa cell 0 -> 45758Mi numa cell 1 -> 48372Mi
6.6.3. Correcting a missing resource topology exporter config map
If you install the NUMA Resources Operator in a cluster with misconfigured cluster settings, in some circumstances, the Operator is shown as active but the logs of the resource topology exporter (RTE) daemon set pods show that the configuration for the RTE is missing, for example:
Info: couldn't find configuration in "/etc/resource-topology-exporter/config.yaml"
This log message indicates that the kubeletconfig
with the required configuration was not properly applied in the cluster, resulting in a missing RTE configmap
. For example, the following cluster is missing a numaresourcesoperator-worker
configmap
custom resource (CR):
$ oc get configmap
Example output
NAME DATA AGE 0e2a6bd3.openshift-kni.io 0 6d21h kube-root-ca.crt 1 6d21h openshift-service-ca.crt 1 6d21h topo-aware-scheduler-config 1 6d18h
In a correctly configured cluster, oc get configmap
also returns a numaresourcesoperator-worker
configmap
CR.
Prerequisites
-
Install the OpenShift Container Platform CLI (
oc
). - Log in as a user with cluster-admin privileges.
- Install the NUMA Resources Operator and deploy the NUMA-aware secondary scheduler.
Procedure
Compare the values for
spec.machineConfigPoolSelector.matchLabels
inkubeletconfig
andmetadata.labels
in theMachineConfigPool
(mcp
) worker CR using the following commands:Check the
kubeletconfig
labels by running the following command:$ oc get kubeletconfig -o yaml
Example output
machineConfigPoolSelector: matchLabels: cnf-worker-tuning: enabled
Check the
mcp
labels by running the following command:$ oc get mcp worker -o yaml
Example output
labels: machineconfiguration.openshift.io/mco-built-in: "" pools.operator.machineconfiguration.openshift.io/worker: ""
The
cnf-worker-tuning: enabled
label is not present in theMachineConfigPool
object.
Edit the
MachineConfigPool
CR to include the missing label, for example:$ oc edit mcp worker -o yaml
Example output
labels: machineconfiguration.openshift.io/mco-built-in: "" pools.operator.machineconfiguration.openshift.io/worker: "" cnf-worker-tuning: enabled
- Apply the label changes and wait for the cluster to apply the updated configuration. Run the following command:
Verification
Check that the missing
numaresourcesoperator-worker
configmap
CR is applied:$ oc get configmap
Example output
NAME DATA AGE 0e2a6bd3.openshift-kni.io 0 6d21h kube-root-ca.crt 1 6d21h numaresourcesoperator-worker 1 5m openshift-service-ca.crt 1 6d21h topo-aware-scheduler-config 1 6d18h