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Chapter 10. Log storage

10.1. About log storage

You can use an internal Loki or Elasticsearch log store on your cluster for storing logs, or you can use a ClusterLogForwarder custom resource (CR) to forward logs to an external store.

10.1.1. Log storage types

Loki is a horizontally scalable, highly available, multi-tenant log aggregation system offered as a GA log store for logging for Red Hat OpenShift that can be visualized with the OpenShift Observability UI. The Loki configuration provided by OpenShift Logging is a short-term log store designed to enable users to perform fast troubleshooting with the collected logs. For that purpose, the logging for Red Hat OpenShift configuration of Loki has short-term storage, and is optimized for very recent queries. For long-term storage or queries over a long time period, users should look to log stores external to their cluster.

Elasticsearch indexes incoming log records completely during ingestion. Loki indexes only a few fixed labels during ingestion and defers more complex parsing until after the logs have been stored. This means Loki can collect logs more quickly.

10.1.1.1. About the Elasticsearch log store

The logging Elasticsearch instance is optimized and tested for short term storage, approximately seven days. If you want to retain your logs over a longer term, it is recommended you move the data to a third-party storage system.

Elasticsearch organizes the log data from Fluentd into datastores, or indices, then subdivides each index into multiple pieces called shards, which it spreads across a set of Elasticsearch nodes in an Elasticsearch cluster. You can configure Elasticsearch to make copies of the shards, called replicas, which Elasticsearch also spreads across the Elasticsearch nodes. The ClusterLogging custom resource (CR) allows you to specify how the shards are replicated to provide data redundancy and resilience to failure. You can also specify how long the different types of logs are retained using a retention policy in the ClusterLogging CR.

Note

The number of primary shards for the index templates is equal to the number of Elasticsearch data nodes.

The Red Hat OpenShift Logging Operator and companion OpenShift Elasticsearch Operator ensure that each Elasticsearch node is deployed using a unique deployment that includes its own storage volume. You can use a ClusterLogging custom resource (CR) to increase the number of Elasticsearch nodes, as needed. See the Elasticsearch documentation for considerations involved in configuring storage.

Note

A highly-available Elasticsearch environment requires at least three Elasticsearch nodes, each on a different host.

Role-based access control (RBAC) applied on the Elasticsearch indices enables the controlled access of the logs to the developers. Administrators can access all logs and developers can access only the logs in their projects.

10.1.2. Querying log stores

You can query Loki by using the LogQL log query language.

10.1.3. Additional resources

10.2. Installing log storage

You can use the OpenShift CLI (oc) or the OpenShift Dedicated web console to deploy a log store on your OpenShift Dedicated cluster.

Note

The Logging 5.9 release does not contain an updated version of the OpenShift Elasticsearch Operator. If you currently use the OpenShift Elasticsearch Operator released with Logging 5.8, it will continue to work with Logging until the EOL of Logging 5.8. As an alternative to using the OpenShift Elasticsearch Operator to manage the default log storage, you can use the Loki Operator. For more information on the Logging lifecycle dates, see Platform Agnostic Operators.

10.2.1. Deploying a Loki log store

You can use the Loki Operator to deploy an internal Loki log store on your OpenShift Dedicated cluster. After install the Loki Operator, you must configure Loki object storage by creating a secret, and create a LokiStack custom resource (CR).

10.2.1.1. Loki deployment sizing

Sizing for Loki follows the format of 1x.<size> where the value 1x is number of instances and <size> specifies performance capabilities.

Important

It is not possible to change the number 1x for the deployment size.

Table 10.1. Loki sizing
	1x.demo	1x.extra-small	1x.small	1x.medium
Data transfer	Demo use only	100GB/day	500GB/day	2TB/day
Queries per second (QPS)	Demo use only	1-25 QPS at 200ms	25-50 QPS at 200ms	25-75 QPS at 200ms
Replication factor	None	2	2	2
Total CPU requests	None	14 vCPUs	34 vCPUs	54 vCPUs
Total CPU requests if using the ruler	None	16 vCPUs	42 vCPUs	70 vCPUs
Total memory requests	None	31Gi	67Gi	139Gi
Total memory requests if using the ruler	None	35Gi	83Gi	171Gi
Total disk requests	40Gi	430Gi	430Gi	590Gi
Total disk requests if using the ruler	80Gi	750Gi	750Gi	910Gi

10.2.1.2. Installing Logging and the Loki Operator using the web console

To install and configure logging on your OpenShift Dedicated cluster, an Operator such as Loki Operator for log storage must be installed first. This can be done from the OperatorHub within the web console.

Prerequisites

You have access to a supported object store (AWS S3, Google Cloud Storage, Azure, Swift, Minio, OpenShift Data Foundation).
You have administrator permissions.
You have access to the OpenShift Dedicated web console.

Procedure

In the OpenShift Dedicated web console Administrator perspective, go to Operators OperatorHub.
Type Loki Operator in the Filter by keyword field. Click Loki Operator in the list of available Operators, and then click Install.
Important
The Community Loki Operator is not supported by Red Hat.
Select stable or stable-x.y as the Update channel.
Note
The stable channel only provides updates to the most recent release of logging. To continue receiving updates for prior releases, you must change your subscription channel to stable-x.y, where x.y represents the major and minor version of logging you have installed. For example, stable-5.7.
The Loki Operator must be deployed to the global operator group namespace openshift-operators-redhat, so the Installation mode and Installed Namespace are already selected. If this namespace does not already exist, it is created for you.
Select Enable Operator-recommended cluster monitoring on this namespace.
This option sets the openshift.io/cluster-monitoring: "true" label in the Namespace object. You must select this option to ensure that cluster monitoring scrapes the openshift-operators-redhat namespace.
For Update approval select Automatic, then click Install.
If the approval strategy in the subscription is set to Automatic, the update process initiates as soon as a new Operator version is available in the selected channel. If the approval strategy is set to Manual, you must manually approve pending updates.
Install the Red Hat OpenShift Logging Operator:
1. In the OpenShift Dedicated web console, click Operators OperatorHub.
2. Choose Red Hat OpenShift Logging from the list of available Operators, and click Install.
3. Ensure that the A specific namespace on the cluster is selected under Installation Mode.
4. Ensure that Operator recommended namespace is openshift-logging under Installed Namespace.
5. Select Enable Operator recommended cluster monitoring on this namespace.
  This option sets the openshift.io/cluster-monitoring: "true" label in the Namespace object. You must select this option to ensure that cluster monitoring scrapes the openshift-logging namespace.
6. Select stable-5.y as the Update Channel.
7. Select an Approval Strategy.
  - The Automatic strategy allows Operator Lifecycle Manager (OLM) to automatically update the Operator when a new version is available.
  - The Manual strategy requires a user with appropriate credentials to approve the Operator update.
8. Click Install.
Go to the Operators Installed Operators page. Click the All instances tab.
From the Create new drop-down list, select LokiStack.
Select YAML view, and then use the following template to create a LokiStack CR:
Example LokiStack CR
```
apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki 1
  namespace: openshift-logging 2
spec:
  size: 1x.small 3
  storage:
    schemas:
    - version: v12
      effectiveDate: "2022-06-01"
    secret:
      name: logging-loki-s3 4
      type: s3 5
      credentialMode: 6
  storageClassName: <storage_class_name> 7
  tenants:
    mode: openshift-logging 8
```
1
Use the name logging-loki.
2
You must specify the openshift-logging namespace.
3
Specify the deployment size. In the logging 5.8 and later versions, the supported size options for production instances of Loki are 1x.extra-small, 1x.small, or 1x.medium.
4
Specify the name of your log store secret.
5
Specify the corresponding storage type.
6
Optional field, logging 5.9 and later. Supported user configured values are as follows: static is the default authentication mode available for all supported object storage types using credentials stored in a Secret. token for short-lived tokens retrieved from a credential source. In this mode the static configuration does not contain credentials needed for the object storage. Instead, they are generated during runtime using a service, which allows for shorter-lived credentials and much more granular control. This authentication mode is not supported for all object storage types. token-cco is the default value when Loki is running on managed STS mode and using CCO on STS/WIF clusters.
7
Specify the name of a storage class for temporary storage. For best performance, specify a storage class that allocates block storage. Available storage classes for your cluster can be listed by using the oc get storageclasses command.
8
LokiStack defaults to running in multi-tenant mode, which cannot be modified. One tenant is provided for each log type: audit, infrastructure, and application logs. This enables access control for individual users and user groups to different log streams.
Important
It is not possible to change the number 1x for the deployment size.
Click Create.
Create an OpenShift Logging instance:
1. Switch to the Administration Custom Resource Definitions page.
2. On the Custom Resource Definitions page, click ClusterLogging.
3. On the Custom Resource Definition details page, select View Instances from the Actions menu.
4. On the ClusterLoggings page, click Create ClusterLogging.
  You might have to refresh the page to load the data.
5. In the YAML field, replace the code with the following:
```
apiVersion: logging.openshift.io/v1
kind: ClusterLogging
metadata:
  name: instance 1
  namespace: openshift-logging 2
spec:
  collection:
    type: vector
  logStore:
    lokistack:
      name: logging-loki
    retentionPolicy:
      application:
        maxAge: 7d
      audit:
        maxAge: 7d
      infra:
        maxAge: 7d
    type: lokistack
  visualization:
    type: ocp-console
    ocpConsole:
      logsLimit: 15

  managementState: Managed
```
  1
  Name must be instance.
  2
  Namespace must be openshift-logging.

Verification

Go to Operators Installed Operators.
Make sure the openshift-logging project is selected.
In the Status column, verify that you see green checkmarks with InstallSucceeded and the text Up to date.

Note

An Operator might display a Failed status before the installation finishes. If the Operator install completes with an InstallSucceeded message, refresh the page.

10.2.1.3. Creating a secret for Loki object storage by using the web console

To configure Loki object storage, you must create a secret. You can create a secret by using the OpenShift Dedicated web console.

Prerequisites

You have administrator permissions.
You have access to the OpenShift Dedicated web console.
You installed the Loki Operator.

Procedure

Go to Workloads Secrets in the Administrator perspective of the OpenShift Dedicated web console.
From the Create drop-down list, select From YAML.

Create a secret that uses the access_key_id and access_key_secret fields to specify your credentials and the bucketnames, endpoint, and region fields to define the object storage location. AWS is used in the following example:

Example Secret object

apiVersion: v1
kind: Secret
metadata:
  name: logging-loki-s3
  namespace: openshift-logging
stringData:
  access_key_id: AKIAIOSFODNN7EXAMPLE
  access_key_secret: wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
  bucketnames: s3-bucket-name
  endpoint: https://s3.eu-central-1.amazonaws.com
  region: eu-central-1

Additional resources

Loki object storage

10.2.1.4. Workload identity federation

Workload identity federation enables authentication to cloud-based log stores using short-lived tokens.

Prerequisites

OpenShift Dedicated 4.14 and later
Logging 5.9 and later

Procedure

If you use the OpenShift Dedicated web console to install the Loki Operator, clusters that use short-lived tokens are automatically detected. You are prompted to create roles and supply the data required for the Loki Operator to create a CredentialsRequest object, which populates a secret.
If you use the OpenShift CLI (oc) to install the Loki Operator, you must manually create a subscription object using the appropriate template for your storage provider, as shown in the following examples. This authentication strategy is only supported for the storage providers indicated.

Azure sample subscription

apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: loki-operator
  namespace: openshift-operators-redhat
spec:
  channel: "stable-5.9"
  installPlanApproval: Manual
  name: loki-operator
  source: redhat-operators
  sourceNamespace: openshift-marketplace
  config:
    env:
      - name: CLIENTID
        value: <your_client_id>
      - name: TENANTID
        value: <your_tenant_id>
      - name: SUBSCRIPTIONID
        value: <your_subscription_id>
      - name: REGION
        value: <your_region>

AWS sample subscription

apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: loki-operator
  namespace: openshift-operators-redhat
spec:
  channel: "stable-5.9"
  installPlanApproval: Manual
  name: loki-operator
  source: redhat-operators
  sourceNamespace: openshift-marketplace
  config:
    env:
    - name: ROLEARN
      value: <role_ARN>

10.2.1.5. Creating a LokiStack custom resource by using the web console

You can create a LokiStack custom resource (CR) by using the OpenShift Dedicated web console.

Prerequisites

You have administrator permissions.
You have access to the OpenShift Dedicated web console.
You installed the Loki Operator.

Procedure

Go to the Operators Installed Operators page. Click the All instances tab.
From the Create new drop-down list, select LokiStack.
Select YAML view, and then use the following template to create a LokiStack CR:
```
apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki 1
  namespace: openshift-logging
spec:
  size: 1x.small 2
  storage:
    schemas:
      - effectiveDate: '2023-10-15'
        version: v13
    secret:
      name: logging-loki-s3 3
      type: s3 4
      credentialMode: 5
  storageClassName: <storage_class_name> 6
  tenants:
    mode: openshift-logging
```
1
Use the name logging-loki.
2
Specify the deployment size. In the logging 5.8 and later versions, the supported size options for production instances of Loki are 1x.extra-small, 1x.small, or 1x.medium.
3
Specify the secret used for your log storage.
4
Specify the corresponding storage type.
5
Optional field, logging 5.9 and later. Supported user configured values are as follows: static is the default authentication mode available for all supported object storage types using credentials stored in a Secret. token for short-lived tokens retrieved from a credential source. In this mode the static configuration does not contain credentials needed for the object storage. Instead, they are generated during runtime using a service, which allows for shorter-lived credentials and much more granular control. This authentication mode is not supported for all object storage types. token-cco is the default value when Loki is running on managed STS mode and using CCO on STS/WIF clusters.
6
Enter the name of a storage class for temporary storage. For best performance, specify a storage class that allocates block storage. Available storage classes for your cluster can be listed by using the oc get storageclasses command.

10.2.1.6. Installing Logging and the Loki Operator using the CLI

To install and configure logging on your OpenShift Dedicated cluster, an Operator such as Loki Operator for log storage must be installed first. This can be done from the OpenShift Dedicated CLI.

Prerequisites

You have administrator permissions.
You installed the OpenShift CLI (oc).
You have access to a supported object store. For example: AWS S3, Google Cloud Storage, Azure, Swift, Minio, or OpenShift Data Foundation.

Note

The stable channel only provides updates to the most recent release of logging. To continue receiving updates for prior releases, you must change your subscription channel to stable-x.y, where x.y represents the major and minor version of logging you have installed. For example, stable-5.7.

Create a Namespace object for Loki Operator:
Example Namespace object
```
apiVersion: v1
kind: Namespace
metadata:
  name: openshift-operators-redhat 1
  annotations:
    openshift.io/node-selector: ""
  labels:
    openshift.io/cluster-monitoring: "true" 2
```
1
You must specify the openshift-operators-redhat namespace. To prevent possible conflicts with metrics, you should configure the Prometheus Cluster Monitoring stack to scrape metrics from the openshift-operators-redhat namespace and not the openshift-operators namespace. The openshift-operators namespace might contain community Operators, which are untrusted and could publish a metric with the same name as an OpenShift Dedicated metric, which would cause conflicts.
2
A string value that specifies the label as shown to ensure that cluster monitoring scrapes the openshift-operators-redhat namespace.
Apply the Namespace object by running the following command:
```
$ oc apply -f <filename>.yaml
```
Create a Subscription object for Loki Operator:
Example Subscription object
```
apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: loki-operator
  namespace: openshift-operators-redhat 1
spec:
  channel: stable 2
  name: loki-operator
  source: redhat-operators 3
  sourceNamespace: openshift-marketplace
```
1
You must specify the openshift-operators-redhat namespace.
2
Specify stable, or stable-5.<y> as the channel.
3
Specify redhat-operators. If your OpenShift Dedicated cluster is installed on a restricted network, also known as a disconnected cluster, specify the name of the CatalogSource object you created when you configured the Operator Lifecycle Manager (OLM).
Apply the Subscription object by running the following command:
```
$ oc apply -f <filename>.yaml
```
Create a namespace object for the Red Hat OpenShift Logging Operator:
Example namespace object
```
apiVersion: v1
kind: Namespace
metadata:
  name: openshift-logging 1
annotations:
    openshift.io/node-selector: ""
labels:
    openshift.io/cluster-logging: "true"
    openshift.io/cluster-monitoring: "true" 2
```
1
The Red Hat OpenShift Logging Operator is only deployable to the openshift-logging namespace.
2
A string value that specifies the label as shown to ensure that cluster monitoring scrapes the openshift-operators-redhat namespace.
Apply the namespace object by running the following command:
```
$ oc apply -f <filename>.yaml
```

Create an OperatorGroup object

Example OperatorGroup object

apiVersion: operators.coreos.com/v1
kind: OperatorGroup
metadata:
  name: cluster-logging
  namespace: openshift-logging 1
spec:
  targetNamespaces:
  - openshift-logging

1: You must specify the openshift-logging namespace.

Apply the OperatorGroup object by running the following command:
```
$ oc apply -f <filename>.yaml
```
Create a Subscription object:
```
apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: cluster-logging
  namespace: openshift-logging 1
spec:
  channel: stable 2
  name: cluster-logging
  source: redhat-operators 3
  sourceNamespace: openshift-marketplace
```
1
You must specify the openshift-logging namespace.
2
Specify stable, or stable-5.<y> as the channel.
3
Specify redhat-operators. If your OpenShift Dedicated cluster is installed on a restricted network, also known as a disconnected cluster, specify the name of the CatalogSource object you created when you configured the Operator Lifecycle Manager (OLM).
Apply the Subscription object by running the following command:
```
$ oc apply -f <filename>.yaml
```
Create a LokiStack CR:
Example LokiStack CR
```
apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki 1
  namespace: openshift-logging 2
spec:
  size: 1x.small 3
  storage:
    schemas:
    - version: v12
      effectiveDate: "2022-06-01"
    secret:
      name: logging-loki-s3 4
      type: s3 5
      credentialMode: 6
  storageClassName: <storage_class_name> 7
  tenants:
    mode: openshift-logging 8
```
1
Use the name logging-loki.
2
You must specify the openshift-logging namespace.
3
Specify the deployment size. In the logging 5.8 and later versions, the supported size options for production instances of Loki are 1x.extra-small, 1x.small, or 1x.medium.
4
Specify the name of your log store secret.
5
Specify the corresponding storage type.
6
Optional field, logging 5.9 and later. Supported user configured values are as follows: static is the default authentication mode available for all supported object storage types using credentials stored in a Secret. token for short-lived tokens retrieved from a credential source. In this mode the static configuration does not contain credentials needed for the object storage. Instead, they are generated during runtime using a service, which allows for shorter-lived credentials and much more granular control. This authentication mode is not supported for all object storage types. token-cco is the default value when Loki is running on managed STS mode and using CCO on STS/WIF clusters.
7
Specify the name of a storage class for temporary storage. For best performance, specify a storage class that allocates block storage. Available storage classes for your cluster can be listed by using the oc get storageclasses command.
8
LokiStack defaults to running in multi-tenant mode, which cannot be modified. One tenant is provided for each log type: audit, infrastructure, and application logs. This enables access control for individual users and user groups to different log streams.
Apply the LokiStack CR object by running the following command:
```
$ oc apply -f <filename>.yaml
```

Create a ClusterLogging CR object:

Example ClusterLogging CR object

apiVersion: logging.openshift.io/v1
kind: ClusterLogging
metadata:
  name: instance 1
  namespace: openshift-logging 2
spec:
  collection:
    type: vector
  logStore:
    lokistack:
      name: logging-loki
    retentionPolicy:
      application:
        maxAge: 7d
      audit:
        maxAge: 7d
      infra:
        maxAge: 7d
    type: lokistack
  visualization:
    ocpConsole:
      logsLimit: 15
  managementState: Managed

1: Name must be instance.
2: Namespace must be openshift-logging.

Apply the ClusterLogging CR object by running the following command:
```
$ oc apply -f <filename>.yaml
```

Verify the installation by running the following command:

$ oc get pods -n openshift-logging

Example output

$ oc get pods -n openshift-logging
NAME                                               READY   STATUS    RESTARTS   AGE
cluster-logging-operator-fb7f7cf69-8jsbq           1/1     Running   0          98m
collector-222js                                    2/2     Running   0          18m
collector-g9ddv                                    2/2     Running   0          18m
collector-hfqq8                                    2/2     Running   0          18m
collector-sphwg                                    2/2     Running   0          18m
collector-vv7zn                                    2/2     Running   0          18m
collector-wk5zz                                    2/2     Running   0          18m
logging-view-plugin-6f76fbb78f-n2n4n               1/1     Running   0          18m
lokistack-sample-compactor-0                       1/1     Running   0          42m
lokistack-sample-distributor-7d7688bcb9-dvcj8      1/1     Running   0          42m
lokistack-sample-gateway-5f6c75f879-bl7k9          2/2     Running   0          42m
lokistack-sample-gateway-5f6c75f879-xhq98          2/2     Running   0          42m
lokistack-sample-index-gateway-0                   1/1     Running   0          42m
lokistack-sample-ingester-0                        1/1     Running   0          42m
lokistack-sample-querier-6b7b56bccc-2v9q4          1/1     Running   0          42m
lokistack-sample-query-frontend-84fb57c578-gq2f7   1/1     Running   0          42m

10.2.1.7. Creating a secret for Loki object storage by using the CLI

To configure Loki object storage, you must create a secret. You can do this by using the OpenShift CLI (oc).

Prerequisites

You have administrator permissions.
You installed the Loki Operator.
You installed the OpenShift CLI (oc).

Procedure

Create a secret in the directory that contains your certificate and key files by running the following command:

$ oc create secret generic -n openshift-logging <your_secret_name> \
 --from-file=tls.key=<your_key_file>
 --from-file=tls.crt=<your_crt_file>
 --from-file=ca-bundle.crt=<your_bundle_file>
 --from-literal=username=<your_username>
 --from-literal=password=<your_password>

Note

Use generic or opaque secrets for best results.

Verification

Verify that a secret was created by running the following command:
```
$ oc get secrets
```

Additional resources

Loki object storage

10.2.1.8. Creating a LokiStack custom resource by using the CLI

You can create a LokiStack custom resource (CR) by using the OpenShift CLI (oc).

Prerequisites

You have administrator permissions.
You installed the Loki Operator.
You installed the OpenShift CLI (oc).

Procedure

Create a LokiStack CR:

Example LokiStack CR

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki 1
  namespace: openshift-logging
spec:
  size: 1x.small 2
  storage:
    schemas:
      - effectiveDate: '2023-10-15'
        version: v13
    secret:
      name: logging-loki-s3 3
      type: s3 4
      credentialMode: 5
  storageClassName: <storage_class_name> 6
  tenants:
    mode: openshift-logging

1

Use the name logging-loki.

2

Specify the deployment size. In the logging 5.8 and later versions, the supported size options for production instances of Loki are 1x.extra-small, 1x.small, or 1x.medium.

3

Specify the secret used for your log storage.

4

Specify the corresponding storage type.

5

Optional field, logging 5.9 and later. Supported user configured values are as follows: static is the default authentication mode available for all supported object storage types using credentials stored in a Secret. token for short-lived tokens retrieved from a credential source. In this mode the static configuration does not contain credentials needed for the object storage. Instead, they are generated during runtime using a service, which allows for shorter-lived credentials and much more granular control. This authentication mode is not supported for all object storage types. token-cco is the default value when Loki is running on managed STS mode and using CCO on STS/WIF clusters.

6

Enter the name of a storage class for temporary storage. For best performance, specify a storage class that allocates block storage. Available storage classes for your cluster can be listed by using the oc get storageclasses command.

Apply the LokiStack CR by running the following command:

Verification

Verify the installation by listing the pods in the openshift-logging project by running the following command and observing the output:

$ oc get pods -n openshift-logging

Confirm that you see several pods for components of the logging, similar to the following list:

Example output

NAME                                           READY   STATUS    RESTARTS   AGE
cluster-logging-operator-78fddc697-mnl82       1/1     Running   0          14m
collector-6cglq                                2/2     Running   0          45s
collector-8r664                                2/2     Running   0          45s
collector-8z7px                                2/2     Running   0          45s
collector-pdxl9                                2/2     Running   0          45s
collector-tc9dx                                2/2     Running   0          45s
collector-xkd76                                2/2     Running   0          45s
logging-loki-compactor-0                       1/1     Running   0          8m2s
logging-loki-distributor-b85b7d9fd-25j9g       1/1     Running   0          8m2s
logging-loki-distributor-b85b7d9fd-xwjs6       1/1     Running   0          8m2s
logging-loki-gateway-7bb86fd855-hjhl4          2/2     Running   0          8m2s
logging-loki-gateway-7bb86fd855-qjtlb          2/2     Running   0          8m2s
logging-loki-index-gateway-0                   1/1     Running   0          8m2s
logging-loki-index-gateway-1                   1/1     Running   0          7m29s
logging-loki-ingester-0                        1/1     Running   0          8m2s
logging-loki-ingester-1                        1/1     Running   0          6m46s
logging-loki-querier-f5cf9cb87-9fdjd           1/1     Running   0          8m2s
logging-loki-querier-f5cf9cb87-fp9v5           1/1     Running   0          8m2s
logging-loki-query-frontend-58c579fcb7-lfvbc   1/1     Running   0          8m2s
logging-loki-query-frontend-58c579fcb7-tjf9k   1/1     Running   0          8m2s
logging-view-plugin-79448d8df6-ckgmx           1/1     Running   0          46s

10.2.2. Loki object storage

The Loki Operator supports AWS S3, as well as other S3 compatible object stores such as Minio and OpenShift Data Foundation. Azure, GCS, and Swift are also supported.

The recommended nomenclature for Loki storage is logging-loki-<your_storage_provider>.

The following table shows the type values within the LokiStack custom resource (CR) for each storage provider. For more information, see the section on your storage provider.

Table 10.2. Secret type quick reference
Storage provider	Secret `type` value
AWS	s3
Azure	azure
Google Cloud	gcs
Minio	s3
OpenShift Data Foundation	s3
Swift	swift

10.2.2.1. AWS storage

Prerequisites

You installed the Loki Operator.
You installed the OpenShift CLI (oc).
You created a bucket on AWS.
You created an AWS IAM Policy and IAM User.

Procedure

Create an object storage secret with the name logging-loki-aws by running the following command:

$ oc create secret generic logging-loki-aws \
  --from-literal=bucketnames="<bucket_name>" \
  --from-literal=endpoint="<aws_bucket_endpoint>" \
  --from-literal=access_key_id="<aws_access_key_id>" \
  --from-literal=access_key_secret="<aws_access_key_secret>" \
  --from-literal=region="<aws_region_of_your_bucket>"

10.2.2.1.1. AWS storage for STS enabled clusters

If your cluster has STS enabled, the Cloud Credential Operator (CCO) supports short-term authentication using AWS tokens.

You can create the Loki object storage secret manually by running the following command:

$ oc -n openshift-logging create secret generic "logging-loki-aws" \
--from-literal=bucketnames="<s3_bucket_name>" \
--from-literal=region="<bucket_region>" \
--from-literal=audience="<oidc_audience>" 1

1: Optional annotation, default value is openshift.

10.2.2.2. Azure storage

Prerequisites

You installed the Loki Operator.
You installed the OpenShift CLI (oc).
You created a bucket on Azure.

Procedure

Create an object storage secret with the name logging-loki-azure by running the following command:

$ oc create secret generic logging-loki-azure \
  --from-literal=container="<azure_container_name>" \
  --from-literal=environment="<azure_environment>" \ 1
  --from-literal=account_name="<azure_account_name>" \
  --from-literal=account_key="<azure_account_key>"

1: Supported environment values are AzureGlobal, AzureChinaCloud, AzureGermanCloud, or AzureUSGovernment.

10.2.2.2.1. Azure storage for Microsoft Entra Workload ID enabled clusters

If your cluster has Microsoft Entra Workload ID enabled, the Cloud Credential Operator (CCO) supports short-term authentication using Workload ID.

You can create the Loki object storage secret manually by running the following command:

$ oc -n openshift-logging create secret generic logging-loki-azure \
--from-literal=environment="<azure_environment>" \
--from-literal=account_name="<storage_account_name>" \
--from-literal=container="<container_name>"

10.2.2.3. Google Cloud Platform storage

Prerequisites

You installed the Loki Operator.
You installed the OpenShift CLI (oc).
You created a project on Google Cloud Platform (GCP).
You created a bucket in the same project.
You created a service account in the same project for GCP authentication.

Procedure

Copy the service account credentials received from GCP into a file called key.json.

Create an object storage secret with the name logging-loki-gcs by running the following command:

$ oc create secret generic logging-loki-gcs \
  --from-literal=bucketname="<bucket_name>" \
  --from-file=key.json="<path/to/key.json>"

10.2.2.4. Minio storage

Prerequisites

You installed the Loki Operator.
You installed the OpenShift CLI (oc).
You have Minio deployed on your cluster.
You created a bucket on Minio.

Procedure

Create an object storage secret with the name logging-loki-minio by running the following command:

$ oc create secret generic logging-loki-minio \
  --from-literal=bucketnames="<bucket_name>" \
  --from-literal=endpoint="<minio_bucket_endpoint>" \
  --from-literal=access_key_id="<minio_access_key_id>" \
  --from-literal=access_key_secret="<minio_access_key_secret>"

10.2.2.5. OpenShift Data Foundation storage

Prerequisites

You installed the Loki Operator.
You installed the OpenShift CLI (oc).
You deployed OpenShift Data Foundation.
You configured your OpenShift Data Foundation cluster for object storage.

Procedure

Create an ObjectBucketClaim custom resource in the openshift-logging namespace:

apiVersion: objectbucket.io/v1alpha1
kind: ObjectBucketClaim
metadata:
  name: loki-bucket-odf
  namespace: openshift-logging
spec:
  generateBucketName: loki-bucket-odf
  storageClassName: openshift-storage.noobaa.io

Get bucket properties from the associated ConfigMap object by running the following command:

BUCKET_HOST=$(oc get -n openshift-logging configmap loki-bucket-odf -o jsonpath='{.data.BUCKET_HOST}')
BUCKET_NAME=$(oc get -n openshift-logging configmap loki-bucket-odf -o jsonpath='{.data.BUCKET_NAME}')
BUCKET_PORT=$(oc get -n openshift-logging configmap loki-bucket-odf -o jsonpath='{.data.BUCKET_PORT}')

Get bucket access key from the associated secret by running the following command:

ACCESS_KEY_ID=$(oc get -n openshift-logging secret loki-bucket-odf -o jsonpath='{.data.AWS_ACCESS_KEY_ID}' | base64 -d)
SECRET_ACCESS_KEY=$(oc get -n openshift-logging secret loki-bucket-odf -o jsonpath='{.data.AWS_SECRET_ACCESS_KEY}' | base64 -d)

Create an object storage secret with the name logging-loki-odf by running the following command:

$ oc create -n openshift-logging secret generic logging-loki-odf \
--from-literal=access_key_id="<access_key_id>" \
--from-literal=access_key_secret="<secret_access_key>" \
--from-literal=bucketnames="<bucket_name>" \
--from-literal=endpoint="https://<bucket_host>:<bucket_port>"

10.2.2.6. Swift storage

Prerequisites

You installed the Loki Operator.
You installed the OpenShift CLI (oc).
You created a bucket on Swift.

Procedure

Create an object storage secret with the name logging-loki-swift by running the following command:

$ oc create secret generic logging-loki-swift \
  --from-literal=auth_url="<swift_auth_url>" \
  --from-literal=username="<swift_usernameclaim>" \
  --from-literal=user_domain_name="<swift_user_domain_name>" \
  --from-literal=user_domain_id="<swift_user_domain_id>" \
  --from-literal=user_id="<swift_user_id>" \
  --from-literal=password="<swift_password>" \
  --from-literal=domain_id="<swift_domain_id>" \
  --from-literal=domain_name="<swift_domain_name>" \
  --from-literal=container_name="<swift_container_name>"

You can optionally provide project-specific data, region, or both by running the following command:

$ oc create secret generic logging-loki-swift \
  --from-literal=auth_url="<swift_auth_url>" \
  --from-literal=username="<swift_usernameclaim>" \
  --from-literal=user_domain_name="<swift_user_domain_name>" \
  --from-literal=user_domain_id="<swift_user_domain_id>" \
  --from-literal=user_id="<swift_user_id>" \
  --from-literal=password="<swift_password>" \
  --from-literal=domain_id="<swift_domain_id>" \
  --from-literal=domain_name="<swift_domain_name>" \
  --from-literal=container_name="<swift_container_name>" \
  --from-literal=project_id="<swift_project_id>" \
  --from-literal=project_name="<swift_project_name>" \
  --from-literal=project_domain_id="<swift_project_domain_id>" \
  --from-literal=project_domain_name="<swift_project_domain_name>" \
  --from-literal=region="<swift_region>"

10.2.3. Deploying an Elasticsearch log store

You can use the OpenShift Elasticsearch Operator to deploy an internal Elasticsearch log store on your OpenShift Dedicated cluster.

Note

10.2.3.1. Storage considerations for Elasticsearch

A persistent volume is required for each Elasticsearch deployment configuration. On OpenShift Dedicated this is achieved using persistent volume claims (PVCs).

Note

If you use a local volume for persistent storage, do not use a raw block volume, which is described with volumeMode: block in the LocalVolume object. Elasticsearch cannot use raw block volumes.

The OpenShift Elasticsearch Operator names the PVCs using the Elasticsearch resource name.

Fluentd ships any logs from systemd journal and /var/log/containers/*.log to Elasticsearch.

Elasticsearch requires sufficient memory to perform large merge operations. If it does not have enough memory, it becomes unresponsive. To avoid this problem, evaluate how much application log data you need, and allocate approximately double that amount of free storage capacity.

By default, when storage capacity is 85% full, Elasticsearch stops allocating new data to the node. At 90%, Elasticsearch attempts to relocate existing shards from that node to other nodes if possible. But if no nodes have a free capacity below 85%, Elasticsearch effectively rejects creating new indices and becomes RED.

Note

These low and high watermark values are Elasticsearch defaults in the current release. You can modify these default values. Although the alerts use the same default values, you cannot change these values in the alerts.

10.2.3.2. Installing the OpenShift Elasticsearch Operator by using the web console

The OpenShift Elasticsearch Operator creates and manages the Elasticsearch cluster used by OpenShift Logging.

Prerequisites

Elasticsearch is a memory-intensive application. Each Elasticsearch node needs at least 16GB of memory for both memory requests and limits, unless you specify otherwise in the ClusterLogging custom resource.
The initial set of OpenShift Dedicated nodes might not be large enough to support the Elasticsearch cluster. You must add additional nodes to the OpenShift Dedicated cluster to run with the recommended or higher memory, up to a maximum of 64GB for each Elasticsearch node.
Elasticsearch nodes can operate with a lower memory setting, though this is not recommended for production environments.
Ensure that you have the necessary persistent storage for Elasticsearch. Note that each Elasticsearch node requires its own storage volume.
Note
If you use a local volume for persistent storage, do not use a raw block volume, which is described with volumeMode: block in the LocalVolume object. Elasticsearch cannot use raw block volumes.

Procedure

In the OpenShift Dedicated web console, click Operators OperatorHub.
Click OpenShift Elasticsearch Operator from the list of available Operators, and click Install.
Ensure that the All namespaces on the cluster is selected under Installation mode.
Ensure that openshift-operators-redhat is selected under Installed Namespace.
You must specify the openshift-operators-redhat namespace. The openshift-operators namespace might contain Community Operators, which are untrusted and could publish a metric with the same name as OpenShift Dedicated metric, which would cause conflicts.
Select Enable operator recommended cluster monitoring on this namespace.
This option sets the openshift.io/cluster-monitoring: "true" label in the Namespace object. You must select this option to ensure that cluster monitoring scrapes the openshift-operators-redhat namespace.
Select stable-5.x as the Update channel.
Select an Update approval strategy:
- The Automatic strategy allows Operator Lifecycle Manager (OLM) to automatically update the Operator when a new version is available.
- The Manual strategy requires a user with appropriate credentials to approve the Operator update.
Click Install.

Verification

Verify that the OpenShift Elasticsearch Operator installed by switching to the Operators Installed Operators page.
Ensure that OpenShift Elasticsearch Operator is listed in all projects with a Status of Succeeded.

10.2.3.3. Installing the OpenShift Elasticsearch Operator by using the CLI

You can use the OpenShift CLI (oc) to install the OpenShift Elasticsearch Operator.

Prerequisites

Ensure that you have the necessary persistent storage for Elasticsearch. Note that each Elasticsearch node requires its own storage volume.
Note
If you use a local volume for persistent storage, do not use a raw block volume, which is described with volumeMode: block in the LocalVolume object. Elasticsearch cannot use raw block volumes.
Elasticsearch is a memory-intensive application. By default, OpenShift Dedicated installs three Elasticsearch nodes with memory requests and limits of 16 GB. This initial set of three OpenShift Dedicated nodes might not have enough memory to run Elasticsearch within your cluster. If you experience memory issues that are related to Elasticsearch, add more Elasticsearch nodes to your cluster rather than increasing the memory on existing nodes.
You have administrator permissions.
You have installed the OpenShift CLI (oc).

Procedure

Create a Namespace object as a YAML file:
```
apiVersion: v1
kind: Namespace
metadata:
  name: openshift-operators-redhat 1
  annotations:
    openshift.io/node-selector: ""
  labels:
    openshift.io/cluster-monitoring: "true" 2
```
1
You must specify the openshift-operators-redhat namespace. To prevent possible conflicts with metrics, configure the Prometheus Cluster Monitoring stack to scrape metrics from the openshift-operators-redhat namespace and not the openshift-operators namespace. The openshift-operators namespace might contain community Operators, which are untrusted and could publish a metric with the same name as an OpenShift Dedicated metric, which would cause conflicts.
2
String. You must specify this label as shown to ensure that cluster monitoring scrapes the openshift-operators-redhat namespace.
Apply the Namespace object by running the following command:
```
$ oc apply -f <filename>.yaml
```

Create an OperatorGroup object as a YAML file:

apiVersion: operators.coreos.com/v1
kind: OperatorGroup
metadata:
  name: openshift-operators-redhat
  namespace: openshift-operators-redhat 1
spec: {}

1: You must specify the openshift-operators-redhat namespace.

Apply the OperatorGroup object by running the following command:
```
$ oc apply -f <filename>.yaml
```
Create a Subscription object to subscribe the namespace to the OpenShift Elasticsearch Operator:
Example Subscription
```
apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: elasticsearch-operator
  namespace: openshift-operators-redhat 1
spec:
  channel: stable-x.y 2
  installPlanApproval: Automatic 3
  source: redhat-operators 4
  sourceNamespace: openshift-marketplace
  name: elasticsearch-operator
```
1
You must specify the openshift-operators-redhat namespace.
2
Specify stable, or stable-x.y as the channel. See the following note.
3
Automatic allows the Operator Lifecycle Manager (OLM) to automatically update the Operator when a new version is available. Manual requires a user with appropriate credentials to approve the Operator update.
4
Specify redhat-operators. If your OpenShift Dedicated cluster is installed on a restricted network, also known as a disconnected cluster, specify the name of the CatalogSource object created when you configured the Operator Lifecycle Manager (OLM).
Note
Specifying stable installs the current version of the latest stable release. Using stable with installPlanApproval: "Automatic" automatically upgrades your Operators to the latest stable major and minor release.
Specifying stable-x.y installs the current minor version of a specific major release. Using stable-x.y with installPlanApproval: "Automatic" automatically upgrades your Operators to the latest stable minor release within the major release.
Apply the subscription by running the following command:
```
$ oc apply -f <filename>.yaml
```
The OpenShift Elasticsearch Operator is installed to the openshift-operators-redhat namespace and copied to each project in the cluster.

Verification

Run the following command:
```
$ oc get csv -n --all-namespaces
```

Observe the output and confirm that pods for the OpenShift Elasticsearch Operator exist in each namespace

Example output

NAMESPACE                                          NAME                            DISPLAY                            VERSION          REPLACES                        PHASE
default                                            elasticsearch-operator.v5.8.1   OpenShift Elasticsearch Operator   5.8.1            elasticsearch-operator.v5.8.0   Succeeded
kube-node-lease                                    elasticsearch-operator.v5.8.1   OpenShift Elasticsearch Operator   5.8.1            elasticsearch-operator.v5.8.0   Succeeded
kube-public                                        elasticsearch-operator.v5.8.1   OpenShift Elasticsearch Operator   5.8.1            elasticsearch-operator.v5.8.0   Succeeded
kube-system                                        elasticsearch-operator.v5.8.1   OpenShift Elasticsearch Operator   5.8.1            elasticsearch-operator.v5.8.0   Succeeded
non-destructive-test                               elasticsearch-operator.v5.8.1   OpenShift Elasticsearch Operator   5.8.1            elasticsearch-operator.v5.8.0   Succeeded
openshift-apiserver-operator                       elasticsearch-operator.v5.8.1   OpenShift Elasticsearch Operator   5.8.1            elasticsearch-operator.v5.8.0   Succeeded
openshift-apiserver                                elasticsearch-operator.v5.8.1   OpenShift Elasticsearch Operator   5.8.1            elasticsearch-operator.v5.8.0   Succeeded
...

10.2.4. Configuring log storage

You can configure which log storage type your logging uses by modifying the ClusterLogging custom resource (CR).

Prerequisites

You have administrator permissions.
You have installed the OpenShift CLI (oc).
You have installed the Red Hat OpenShift Logging Operator and an internal log store that is either the LokiStack or Elasticsearch.
You have created a ClusterLogging CR.

Note

Procedure

Modify the ClusterLogging CR logStore spec:

ClusterLogging CR example

apiVersion: logging.openshift.io/v1
kind: ClusterLogging
metadata:
# ...
spec:
# ...
  logStore:
    type: <log_store_type> 1
    elasticsearch: 2
      nodeCount: <integer>
      resources: {}
      storage: {}
      redundancyPolicy: <redundancy_type> 3
    lokistack: 4
      name: {}
# ...

1: Specify the log store type. This can be either lokistack or elasticsearch.
2: Optional configuration options for the Elasticsearch log store.
3: Specify the redundancy type. This value can be ZeroRedundancy, SingleRedundancy, MultipleRedundancy, or FullRedundancy.
4: Optional configuration options for LokiStack.

Example ClusterLogging CR to specify LokiStack as the log store

apiVersion: logging.openshift.io/v1
kind: ClusterLogging
metadata:
  name: instance
  namespace: openshift-logging
spec:
  managementState: Managed
  logStore:
    type: lokistack
    lokistack:
      name: logging-loki
# ...

Apply the ClusterLogging CR by running the following command:
```
$ oc apply -f <filename>.yaml
```

10.3. Configuring the LokiStack log store

In logging documentation, LokiStack refers to the logging supported combination of Loki and web proxy with OpenShift Dedicated authentication integration. LokiStack’s proxy uses OpenShift Dedicated authentication to enforce multi-tenancy. Loki refers to the log store as either the individual component or an external store.

10.3.1. Creating a new group for the cluster-admin user role

Important

Querying application logs for multiple namespaces as a cluster-admin user, where the sum total of characters of all of the namespaces in the cluster is greater than 5120, results in the error Parse error: input size too long (XXXX > 5120). For better control over access to logs in LokiStack, make the cluster-admin user a member of the cluster-admin group. If the cluster-admin group does not exist, create it and add the desired users to it.

Use the following procedure to create a new group for users with cluster-admin permissions.

Procedure

Enter the following command to create a new group:
```
$ oc adm groups new cluster-admin
```
Enter the following command to add the desired user to the cluster-admin group:
```
$ oc adm groups add-users cluster-admin <username>
```
Enter the following command to add cluster-admin user role to the group:
```
$ oc adm policy add-cluster-role-to-group cluster-admin cluster-admin
```

10.3.2. LokiStack behavior during cluster restarts

In logging version 5.8 and newer versions, when an OpenShift Dedicated cluster is restarted, LokiStack ingestion and the query path continue to operate within the available CPU and memory resources available for the node. This means that there is no downtime for the LokiStack during OpenShift Dedicated cluster updates. This behavior is achieved by using PodDisruptionBudget resources. The Loki Operator provisions PodDisruptionBudget resources for Loki, which determine the minimum number of pods that must be available per component to ensure normal operations under certain conditions.

Additional resources

Pod disruption budgets Kubernetes documentation

10.3.3. Configuring Loki to tolerate node failure

In the logging 5.8 and later versions, the Loki Operator supports setting pod anti-affinity rules to request that pods of the same component are scheduled on different available nodes in the cluster.

Affinity is a property of pods that controls the nodes on which they prefer to be scheduled. Anti-affinity is a property of pods that prevents a pod from being scheduled on a node.

In OpenShift Dedicated, pod affinity and pod anti-affinity allow you to constrain which nodes your pod is eligible to be scheduled on based on the key-value labels on other pods.

The Operator sets default, preferred podAntiAffinity rules for all Loki components, which includes the compactor, distributor, gateway, indexGateway, ingester, querier, queryFrontend, and ruler components.

You can override the preferred podAntiAffinity settings for Loki components by configuring required settings in the requiredDuringSchedulingIgnoredDuringExecution field:

Example user settings for the ingester component

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
# ...
  template:
    ingester:
      podAntiAffinity:
      # ...
        requiredDuringSchedulingIgnoredDuringExecution: 1
        - labelSelector:
            matchLabels: 2
              app.kubernetes.io/component: ingester
          topologyKey: kubernetes.io/hostname
# ...

1: The stanza to define a required rule.
2: The key-value pair (label) that must be matched to apply the rule.

Additional resources

10.3.4. Zone aware data replication

In the logging 5.8 and later versions, the Loki Operator offers support for zone-aware data replication through pod topology spread constraints. Enabling this feature enhances reliability and safeguards against log loss in the event of a single zone failure. When configuring the deployment size as 1x.extra.small, 1x.small, or 1x.medium, the replication.factor field is automatically set to 2.

To ensure proper replication, you need to have at least as many availability zones as the replication factor specifies. While it is possible to have more availability zones than the replication factor, having fewer zones can lead to write failures. Each zone should host an equal number of instances for optimal operation.

Example LokiStack CR with zone replication enabled

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
 name: logging-loki
 namespace: openshift-logging
spec:
 replicationFactor: 2 1
 replication:
   factor: 2 2
   zones:
   -  maxSkew: 1 3
      topologyKey: topology.kubernetes.io/zone 4

1: Deprecated field, values entered are overwritten by replication.factor.
2: This value is automatically set when deployment size is selected at setup.
3: The maximum difference in number of pods between any two topology domains. The default is 1, and you cannot specify a value of 0.
4: Defines zones in the form of a topology key that corresponds to a node label.

10.3.4.1. Recovering Loki pods from failed zones

In OpenShift Dedicated a zone failure happens when specific availability zone resources become inaccessible. Availability zones are isolated areas within a cloud provider’s data center, aimed at enhancing redundancy and fault tolerance. If your OpenShift Dedicated cluster is not configured to handle this, a zone failure can lead to service or data loss.

Loki pods are part of a StatefulSet, and they come with Persistent Volume Claims (PVCs) provisioned by a StorageClass object. Each Loki pod and its PVCs reside in the same zone. When a zone failure occurs in a cluster, the StatefulSet controller automatically attempts to recover the affected pods in the failed zone.

Warning

The following procedure will delete the PVCs in the failed zone, and all data contained therein. To avoid complete data loss the replication factor field of the LokiStack CR should always be set to a value greater than 1 to ensure that Loki is replicating.

Prerequisites

Logging version 5.8 or later.
Verify your LokiStack CR has a replication factor greater than 1.
Zone failure detected by the control plane, and nodes in the failed zone are marked by cloud provider integration.

The StatefulSet controller automatically attempts to reschedule pods in a failed zone. Because the associated PVCs are also in the failed zone, automatic rescheduling to a different zone does not work. You must manually delete the PVCs in the failed zone to allow successful re-creation of the stateful Loki Pod and its provisioned PVC in the new zone.

Procedure

List the pods in Pending status by running the following command:

oc get pods --field-selector status.phase==Pending -n openshift-logging

Example oc get pods output

NAME                           READY   STATUS    RESTARTS   AGE 1
logging-loki-index-gateway-1   0/1     Pending   0          17m
logging-loki-ingester-1        0/1     Pending   0          16m
logging-loki-ruler-1           0/1     Pending   0          16m

1: These pods are in Pending status because their corresponding PVCs are in the failed zone.

List the PVCs in Pending status by running the following command:

oc get pvc -o=json -n openshift-logging | jq '.items[] | select(.status.phase == "Pending") | .metadata.name' -r

Example oc get pvc output

storage-logging-loki-index-gateway-1
storage-logging-loki-ingester-1
wal-logging-loki-ingester-1
storage-logging-loki-ruler-1
wal-logging-loki-ruler-1

Delete the PVC(s) for a pod by running the following command:
```
oc delete pvc __<pvc_name>__  -n openshift-logging
```
Then delete the pod(s) by running the following command:
```
oc delete pod __<pod_name>__  -n openshift-logging
```

Once these objects have been successfully deleted, they should automatically be rescheduled in an available zone.

10.3.4.1.1. Troubleshooting PVC in a terminating state

The PVCs might hang in the terminating state without being deleted, if PVC metadata finalizers are set to kubernetes.io/pv-protection. Removing the finalizers should allow the PVCs to delete successfully.

Remove the finalizer for each PVC by running the command below, then retry deletion.

oc patch pvc __<pvc_name>__ -p '{"metadata":{"finalizers":null}}' -n openshift-logging

Additional resources

10.3.5. Fine grained access for Loki logs

In logging 5.8 and later, the Red Hat OpenShift Logging Operator does not grant all users access to logs by default. As an administrator, you must configure your users' access unless the Operator was upgraded and prior configurations are in place. Depending on your configuration and need, you can configure fine grain access to logs using the following:

Cluster wide policies
Namespace scoped policies
Creation of custom admin groups

As an administrator, you need to create the role bindings and cluster role bindings appropriate for your deployment. The Red Hat OpenShift Logging Operator provides the following cluster roles:

cluster-logging-application-view grants permission to read application logs.
cluster-logging-infrastructure-view grants permission to read infrastructure logs.
cluster-logging-audit-view grants permission to read audit logs.

If you have upgraded from a prior version, an additional cluster role logging-application-logs-reader and associated cluster role binding logging-all-authenticated-application-logs-reader provide backward compatibility, allowing any authenticated user read access in their namespaces.

Note

Users with access by namespace must provide a namespace when querying application logs.

10.3.5.1. Cluster wide access

Cluster role binding resources reference cluster roles, and set permissions cluster wide.

Example ClusterRoleBinding

kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1
metadata:
  name: logging-all-application-logs-reader
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: cluster-logging-application-view 1
subjects: 2
- kind: Group
  name: system:authenticated
  apiGroup: rbac.authorization.k8s.io

1: Additional ClusterRoles are cluster-logging-infrastructure-view, and cluster-logging-audit-view.
2: Specifies the users or groups this object applies to.

10.3.5.2. Namespaced access

RoleBinding resources can be used with ClusterRole objects to define the namespace a user or group has access to logs for.

Example RoleBinding

kind: RoleBinding
apiVersion: rbac.authorization.k8s.io/v1
metadata:
  name: allow-read-logs
  namespace: log-test-0 1
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: cluster-logging-application-view
subjects:
- kind: User
  apiGroup: rbac.authorization.k8s.io
  name: testuser-0

1: Specifies the namespace this RoleBinding applies to.

10.3.5.3. Custom admin group access

If you have a large deployment with several users who require broader permissions, you can create a custom group using the adminGroup field. Users who are members of any group specified in the adminGroups field of the LokiStack CR are considered administrators.

Administrator users have access to all application logs in all namespaces, if they also get assigned the cluster-logging-application-view role.

Example LokiStack CR

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
  tenants:
    mode: openshift-logging 1
    openshift:
      adminGroups: 2
      - cluster-admin
      - custom-admin-group 3

1: Custom admin groups are only available in this mode.
2: Entering an empty list [] value for this field disables admin groups.
3: Overrides the default groups (system:cluster-admins, cluster-admin, dedicated-admin)

10.3.6. Enabling stream-based retention with Loki

Additional resources

With Logging version 5.6 and higher, you can configure retention policies based on log streams. Rules for these may be set globally, per tenant, or both. If you configure both, tenant rules apply before global rules.

Important

If there is no retention period defined on the s3 bucket or in the LokiStack custom resource (CR), then the logs are not pruned and they stay in the s3 bucket forever, which might fill up the s3 storage.

Note

Although logging version 5.9 and higher supports schema v12, v13 is recommended.

To enable stream-based retention, create a LokiStack CR:

Example global stream-based retention for AWS

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
  limits:
   global: 1
      retention: 2
        days: 20
        streams:
        - days: 4
          priority: 1
          selector: '{kubernetes_namespace_name=~"test.+"}' 3
        - days: 1
          priority: 1
          selector: '{log_type="infrastructure"}'
  managementState: Managed
  replicationFactor: 1
  size: 1x.small
  storage:
    schemas:
    - effectiveDate: "2020-10-11"
      version: v11
    secret:
      name: logging-loki-s3
      type: aws
  storageClassName: gp3-csi
  tenants:
    mode: openshift-logging

1: Sets retention policy for all log streams. Note: This field does not impact the retention period for stored logs in object storage.
2: Retention is enabled in the cluster when this block is added to the CR.
3: Contains the LogQL query used to define the log stream.spec: limits:

Example per-tenant stream-based retention for AWS

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
  limits:
    global:
      retention:
        days: 20
    tenants: 1
      application:
        retention:
          days: 1
          streams:
            - days: 4
              selector: '{kubernetes_namespace_name=~"test.+"}' 2
      infrastructure:
        retention:
          days: 5
          streams:
            - days: 1
              selector: '{kubernetes_namespace_name=~"openshift-cluster.+"}'
  managementState: Managed
  replicationFactor: 1
  size: 1x.small
  storage:
    schemas:
    - effectiveDate: "2020-10-11"
      version: v11
    secret:
      name: logging-loki-s3
      type: aws
  storageClassName: gp3-csi
  tenants:
    mode: openshift-logging

1: Sets retention policy by tenant. Valid tenant types are application, audit, and infrastructure.
2: Contains the LogQL query used to define the log stream.

2 Apply the LokiStack CR:

$ oc apply -f <filename>.yaml

Note

This is not for managing the retention for stored logs. Global retention periods for stored logs to a supported maximum of 30 days is configured with your object storage.

10.3.7. Troubleshooting Loki rate limit errors

If the Log Forwarder API forwards a large block of messages that exceeds the rate limit to Loki, Loki generates rate limit (429) errors.

These errors can occur during normal operation. For example, when adding the logging to a cluster that already has some logs, rate limit errors might occur while the logging tries to ingest all of the existing log entries. In this case, if the rate of addition of new logs is less than the total rate limit, the historical data is eventually ingested, and the rate limit errors are resolved without requiring user intervention.

In cases where the rate limit errors continue to occur, you can fix the issue by modifying the LokiStack custom resource (CR).

Important

The LokiStack CR is not available on Grafana-hosted Loki. This topic does not apply to Grafana-hosted Loki servers.

Conditions

The Log Forwarder API is configured to forward logs to Loki.

Your system sends a block of messages that is larger than 2 MB to Loki. For example:

"values":[["1630410392689800468","{\"kind\":\"Event\",\"apiVersion\":\
.......
......
......
......
\"received_at\":\"2021-08-31T11:46:32.800278+00:00\",\"version\":\"1.7.4 1.6.0\"}},\"@timestamp\":\"2021-08-31T11:46:32.799692+00:00\",\"viaq_index_name\":\"audit-write\",\"viaq_msg_id\":\"MzFjYjJkZjItNjY0MC00YWU4LWIwMTEtNGNmM2E5ZmViMGU4\",\"log_type\":\"audit\"}"]]}]}

After you enter oc logs -n openshift-logging -l component=collector, the collector logs in your cluster show a line containing one of the following error messages:

429 Too Many Requests Ingestion rate limit exceeded

Example Vector error message

2023-08-25T16:08:49.301780Z  WARN sink{component_kind="sink" component_id=default_loki_infra component_type=loki component_name=default_loki_infra}: vector::sinks::util::retries: Retrying after error. error=Server responded with an error: 429 Too Many Requests internal_log_rate_limit=true

Example Fluentd error message

2023-08-30 14:52:15 +0000 [warn]: [default_loki_infra] failed to flush the buffer. retry_times=2 next_retry_time=2023-08-30 14:52:19 +0000 chunk="604251225bf5378ed1567231a1c03b8b" error_class=Fluent::Plugin::LokiOutput::LogPostError error="429 Too Many Requests Ingestion rate limit exceeded for user infrastructure (limit: 4194304 bytes/sec) while attempting to ingest '4082' lines totaling '7820025' bytes, reduce log volume or contact your Loki administrator to see if the limit can be increased\n"

The error is also visible on the receiving end. For example, in the LokiStack ingester pod:

Example Loki ingester error message

level=warn ts=2023-08-30T14:57:34.155592243Z caller=grpc_logging.go:43 duration=1.434942ms method=/logproto.Pusher/Push err="rpc error: code = Code(429) desc = entry with timestamp 2023-08-30 14:57:32.012778399 +0000 UTC ignored, reason: 'Per stream rate limit exceeded (limit: 3MB/sec) while attempting to ingest for stream

Procedure

Update the ingestionBurstSize and ingestionRate fields in the LokiStack CR:
```
apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
  limits:
    global:
      ingestion:
        ingestionBurstSize: 16 1
        ingestionRate: 8 2
# ...
```
1
The ingestionBurstSize field defines the maximum local rate-limited sample size per distributor replica in MB. This value is a hard limit. Set this value to at least the maximum logs size expected in a single push request. Single requests that are larger than the ingestionBurstSize value are not permitted.
2
The ingestionRate field is a soft limit on the maximum amount of ingested samples per second in MB. Rate limit errors occur if the rate of logs exceeds the limit, but the collector retries sending the logs. As long as the total average is lower than the limit, the system recovers and errors are resolved without user intervention.

10.3.8. Configuring Loki to tolerate memberlist creation failure

In an OpenShift cluster, administrators generally use a non-private IP network range. As a result, the LokiStack memberlist configuration fails because, by default, it only uses private IP networks.

As an administrator, you can select the pod network for the memberlist configuration. You can modify the LokiStack CR to use the podIP in the hashRing spec. To configure the LokiStack CR, use the following command:

$ oc patch LokiStack logging-loki -n openshift-logging  --type=merge -p '{"spec": {"hashRing":{"memberlist":{"instanceAddrType":"podIP","type": "memberlist"}}}}'

Example LokiStack to include podIP

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
# ...
  hashRing:
    type: memberlist
    memberlist:
      instanceAddrType: podIP
# ...

10.3.9. Additional resources

10.4. Configuring the Elasticsearch log store

You can use Elasticsearch 6 to store and organize log data.

You can make modifications to your log store, including:

Storage for your Elasticsearch cluster
Shard replication across data nodes in the cluster, from full replication to no replication
External access to Elasticsearch data

10.4.1. Configuring log storage

You can configure which log storage type your logging uses by modifying the ClusterLogging custom resource (CR).

Prerequisites

You have administrator permissions.
You have installed the OpenShift CLI (oc).
You have installed the Red Hat OpenShift Logging Operator and an internal log store that is either the LokiStack or Elasticsearch.
You have created a ClusterLogging CR.

Note

Procedure

Modify the ClusterLogging CR logStore spec:

ClusterLogging CR example

apiVersion: logging.openshift.io/v1
kind: ClusterLogging
metadata:
# ...
spec:
# ...
  logStore:
    type: <log_store_type> 1
    elasticsearch: 2
      nodeCount: <integer>
      resources: {}
      storage: {}
      redundancyPolicy: <redundancy_type> 3
    lokistack: 4
      name: {}
# ...

1: Specify the log store type. This can be either lokistack or elasticsearch.
2: Optional configuration options for the Elasticsearch log store.
3: Specify the redundancy type. This value can be ZeroRedundancy, SingleRedundancy, MultipleRedundancy, or FullRedundancy.
4: Optional configuration options for LokiStack.

Example ClusterLogging CR to specify LokiStack as the log store

apiVersion: logging.openshift.io/v1
kind: ClusterLogging
metadata:
  name: instance
  namespace: openshift-logging
spec:
  managementState: Managed
  logStore:
    type: lokistack
    lokistack:
      name: logging-loki
# ...

Apply the ClusterLogging CR by running the following command:
```
$ oc apply -f <filename>.yaml
```

10.4.2. Forwarding audit logs to the log store

In a logging deployment, container and infrastructure logs are forwarded to the internal log store defined in the ClusterLogging custom resource (CR) by default.

Audit logs are not forwarded to the internal log store by default because this does not provide secure storage. You are responsible for ensuring that the system to which you forward audit logs is compliant with your organizational and governmental regulations, and is properly secured.

If this default configuration meets your needs, you do not need to configure a ClusterLogForwarder CR. If a ClusterLogForwarder CR exists, logs are not forwarded to the internal log store unless a pipeline is defined that contains the default output.

Procedure

To use the Log Forward API to forward audit logs to the internal Elasticsearch instance:

Create or edit a YAML file that defines the ClusterLogForwarder CR object:

Create a CR to send all log types to the internal Elasticsearch instance. You can use the following example without making any changes:
```
apiVersion: logging.openshift.io/v1
kind: ClusterLogForwarder
metadata:
  name: instance
  namespace: openshift-logging
spec:
  pipelines: 1
  - name: all-to-default
    inputRefs:
    - infrastructure
    - application
    - audit
    outputRefs:
    - default
```
1
A pipeline defines the type of logs to forward using the specified output. The default output forwards logs to the internal Elasticsearch instance.
Note
You must specify all three types of logs in the pipeline: application, infrastructure, and audit. If you do not specify a log type, those logs are not stored and will be lost.

If you have an existing ClusterLogForwarder CR, add a pipeline to the default output for the audit logs. You do not need to define the default output. For example:

apiVersion: "logging.openshift.io/v1"
kind: ClusterLogForwarder
metadata:
  name: instance
  namespace: openshift-logging
spec:
  outputs:
   - name: elasticsearch-insecure
     type: "elasticsearch"
     url: http://elasticsearch-insecure.messaging.svc.cluster.local
     insecure: true
   - name: elasticsearch-secure
     type: "elasticsearch"
     url: https://elasticsearch-secure.messaging.svc.cluster.local
     secret:
       name: es-audit
   - name: secureforward-offcluster
     type: "fluentdForward"
     url: https://secureforward.offcluster.com:24224
     secret:
       name: secureforward
  pipelines:
   - name: container-logs
     inputRefs:
     - application
     outputRefs:
     - secureforward-offcluster
   - name: infra-logs
     inputRefs:
     - infrastructure
     outputRefs:
     - elasticsearch-insecure
   - name: audit-logs
     inputRefs:
     - audit
     outputRefs:
     - elasticsearch-secure
     - default 1

1: This pipeline sends the audit logs to the internal Elasticsearch instance in addition to an external instance.

Additional resources

About log collection and forwarding

10.4.3. Configuring log retention time

You can configure a retention policy that specifies how long the default Elasticsearch log store keeps indices for each of the three log sources: infrastructure logs, application logs, and audit logs.

To configure the retention policy, you set a maxAge parameter for each log source in the ClusterLogging custom resource (CR). The CR applies these values to the Elasticsearch rollover schedule, which determines when Elasticsearch deletes the rolled-over indices.

Elasticsearch rolls over an index, moving the current index and creating a new index, when an index matches any of the following conditions:

The index is older than the rollover.maxAge value in the Elasticsearch CR.
The index size is greater than 40 GB × the number of primary shards.
The index doc count is greater than 40960 KB × the number of primary shards.

Elasticsearch deletes the rolled-over indices based on the retention policy you configure. If you do not create a retention policy for any log sources, logs are deleted after seven days by default.

Prerequisites

The Red Hat OpenShift Logging Operator and the OpenShift Elasticsearch Operator must be installed.

Procedure

To configure the log retention time:

Edit the ClusterLogging CR to add or modify the retentionPolicy parameter:
```
apiVersion: "logging.openshift.io/v1"
kind: "ClusterLogging"
...
spec:
  managementState: "Managed"
  logStore:
    type: "elasticsearch"
    retentionPolicy: 1
      application:
        maxAge: 1d
      infra:
        maxAge: 7d
      audit:
        maxAge: 7d
    elasticsearch:
      nodeCount: 3
...
```
1
Specify the time that Elasticsearch should retain each log source. Enter an integer and a time designation: weeks(w), hours(h/H), minutes(m) and seconds(s). For example, 1d for one day. Logs older than the maxAge are deleted. By default, logs are retained for seven days.
You can verify the settings in the Elasticsearch custom resource (CR).
For example, the Red Hat OpenShift Logging Operator updated the following Elasticsearch CR to configure a retention policy that includes settings to roll over active indices for the infrastructure logs every eight hours and the rolled-over indices are deleted seven days after rollover. OpenShift Dedicated checks every 15 minutes to determine if the indices need to be rolled over.
```
apiVersion: "logging.openshift.io/v1"
kind: "Elasticsearch"
metadata:
  name: "elasticsearch"
spec:
...
  indexManagement:
    policies: 1
      - name: infra-policy
        phases:
          delete:
            minAge: 7d 2
          hot:
            actions:
              rollover:
                maxAge: 8h 3
        pollInterval: 15m 4
...
```
1
For each log source, the retention policy indicates when to delete and roll over logs for that source.
2
When OpenShift Dedicated deletes the rolled-over indices. This setting is the maxAge you set in the ClusterLogging CR.
3
The index age for OpenShift Dedicated to consider when rolling over the indices. This value is determined from the maxAge you set in the ClusterLogging CR.
4
When OpenShift Dedicated checks if the indices should be rolled over. This setting is the default and cannot be changed.
Note
Modifying the Elasticsearch CR is not supported. All changes to the retention policies must be made in the ClusterLogging CR.
The OpenShift Elasticsearch Operator deploys a cron job to roll over indices for each mapping using the defined policy, scheduled using the pollInterval.
```
$ oc get cronjob
```
Example output
```
NAME                     SCHEDULE       SUSPEND   ACTIVE   LAST SCHEDULE   AGE
elasticsearch-im-app     */15 * * * *   False     0        <none>          4s
elasticsearch-im-audit   */15 * * * *   False     0        <none>          4s
elasticsearch-im-infra   */15 * * * *   False     0        <none>          4s
```

10.4.4. Configuring CPU and memory requests for the log store

Each component specification allows for adjustments to both the CPU and memory requests. You should not have to manually adjust these values as the OpenShift Elasticsearch Operator sets values sufficient for your environment.

Note

In large-scale clusters, the default memory limit for the Elasticsearch proxy container might not be sufficient, causing the proxy container to be OOMKilled. If you experience this issue, increase the memory requests and limits for the Elasticsearch proxy.

Each Elasticsearch node can operate with a lower memory setting though this is not recommended for production deployments. For production use, you should have no less than the default 16Gi allocated to each pod. Preferably you should allocate as much as possible, up to 64Gi per pod.

Prerequisites

The Red Hat OpenShift Logging and Elasticsearch Operators must be installed.

Procedure

Edit the ClusterLogging custom resource (CR) in the openshift-logging project:
```
$ oc edit ClusterLogging instance
```
```
apiVersion: "logging.openshift.io/v1"
kind: "ClusterLogging"
metadata:
  name: "instance"
....
spec:
    logStore:
      type: "elasticsearch"
      elasticsearch:1
        resources:
          limits: 2
            memory: "32Gi"
          requests: 3
            cpu: "1"
            memory: "16Gi"
        proxy: 4
          resources:
            limits:
              memory: 100Mi
            requests:
              memory: 100Mi
```
1
Specify the CPU and memory requests for Elasticsearch as needed. If you leave these values blank, the OpenShift Elasticsearch Operator sets default values that should be sufficient for most deployments. The default values are 16Gi for the memory request and 1 for the CPU request.
2
The maximum amount of resources a pod can use.
3
The minimum resources required to schedule a pod.
4
Specify the CPU and memory requests for the Elasticsearch proxy as needed. If you leave these values blank, the OpenShift Elasticsearch Operator sets default values that are sufficient for most deployments. The default values are 256Mi for the memory request and 100m for the CPU request.

When adjusting the amount of Elasticsearch memory, the same value should be used for both requests and limits.

For example:

      resources:
        limits: 1
          memory: "32Gi"
        requests: 2
          cpu: "8"
          memory: "32Gi"

1: The maximum amount of the resource.
2: The minimum amount required.

Kubernetes generally adheres the node configuration and does not allow Elasticsearch to use the specified limits. Setting the same value for the requests and limits ensures that Elasticsearch can use the memory you want, assuming the node has the memory available.

10.4.5. Configuring replication policy for the log store

You can define how Elasticsearch shards are replicated across data nodes in the cluster.

Prerequisites

The Red Hat OpenShift Logging and Elasticsearch Operators must be installed.

Procedure

Edit the ClusterLogging custom resource (CR) in the openshift-logging project:
```
$ oc edit clusterlogging instance
```
```
apiVersion: "logging.openshift.io/v1"
kind: "ClusterLogging"
metadata:
  name: "instance"

....

spec:
  logStore:
    type: "elasticsearch"
    elasticsearch:
      redundancyPolicy: "SingleRedundancy" 1
```
1
Specify a redundancy policy for the shards. The change is applied upon saving the changes.
FullRedundancy. Elasticsearch fully replicates the primary shards for each index to every data node. This provides the highest safety, but at the cost of the highest amount of disk required and the poorest performance.
MultipleRedundancy. Elasticsearch fully replicates the primary shards for each index to half of the data nodes. This provides a good tradeoff between safety and performance.
SingleRedundancy. Elasticsearch makes one copy of the primary shards for each index. Logs are always available and recoverable as long as at least two data nodes exist. Better performance than MultipleRedundancy, when using 5 or more nodes. You cannot apply this policy on deployments of single Elasticsearch node.
ZeroRedundancy. Elasticsearch does not make copies of the primary shards. Logs might be unavailable or lost in the event a node is down or fails. Use this mode when you are more concerned with performance than safety, or have implemented your own disk/PVC backup/restore strategy.

Note

The number of primary shards for the index templates is equal to the number of Elasticsearch data nodes.

10.4.6. Scaling down Elasticsearch pods

Reducing the number of Elasticsearch pods in your cluster can result in data loss or Elasticsearch performance degradation.

If you scale down, you should scale down by one pod at a time and allow the cluster to re-balance the shards and replicas. After the Elasticsearch health status returns to green, you can scale down by another pod.

Note

If your Elasticsearch cluster is set to ZeroRedundancy, you should not scale down your Elasticsearch pods.

10.4.7. Configuring persistent storage for the log store

Elasticsearch requires persistent storage. The faster the storage, the faster the Elasticsearch performance.

Warning

Using NFS storage as a volume or a persistent volume (or via NAS such as Gluster) is not supported for Elasticsearch storage, as Lucene relies on file system behavior that NFS does not supply. Data corruption and other problems can occur.

Prerequisites

The Red Hat OpenShift Logging and Elasticsearch Operators must be installed.

Procedure

Edit the ClusterLogging CR to specify that each data node in the cluster is bound to a Persistent Volume Claim.

apiVersion: "logging.openshift.io/v1"
kind: "ClusterLogging"
metadata:
  name: "instance"
# ...
spec:
  logStore:
    type: "elasticsearch"
    elasticsearch:
      nodeCount: 3
      storage:
        storageClassName: "gp2"
        size: "200G"

This example specifies each data node in the cluster is bound to a Persistent Volume Claim that requests "200G" of AWS General Purpose SSD (gp2) storage.

Note

If you use a local volume for persistent storage, do not use a raw block volume, which is described with volumeMode: block in the LocalVolume object. Elasticsearch cannot use raw block volumes.

10.4.8. Configuring the log store for emptyDir storage

You can use emptyDir with your log store, which creates an ephemeral deployment in which all of a pod’s data is lost upon restart.

Note

When using emptyDir, if log storage is restarted or redeployed, you will lose data.

Prerequisites

The Red Hat OpenShift Logging and Elasticsearch Operators must be installed.

Procedure

Edit the ClusterLogging CR to specify emptyDir:

 spec:
    logStore:
      type: "elasticsearch"
      elasticsearch:
        nodeCount: 3
        storage: {}

10.4.9. Performing an Elasticsearch rolling cluster restart

Perform a rolling restart when you change the elasticsearch config map or any of the elasticsearch-* deployment configurations.

Also, a rolling restart is recommended if the nodes on which an Elasticsearch pod runs requires a reboot.

Prerequisites

The Red Hat OpenShift Logging and Elasticsearch Operators must be installed.

Procedure

To perform a rolling cluster restart:

Change to the openshift-logging project:
```
$ oc project openshift-logging
```

Get the names of the Elasticsearch pods:

$ oc get pods -l component=elasticsearch

Scale down the collector pods so they stop sending new logs to Elasticsearch:

$ oc -n openshift-logging patch daemonset/collector -p '{"spec":{"template":{"spec":{"nodeSelector":{"logging-infra-collector": "false"}}}}}'

Perform a shard synced flush using the OpenShift Dedicated es_util tool to ensure there are no pending operations waiting to be written to disk prior to shutting down:

$ oc exec <any_es_pod_in_the_cluster> -c elasticsearch -- es_util --query="_flush/synced" -XPOST

For example:

$ oc exec -c elasticsearch-cdm-5ceex6ts-1-dcd6c4c7c-jpw6  -c elasticsearch -- es_util --query="_flush/synced" -XPOST

Example output

{"_shards":{"total":4,"successful":4,"failed":0},".security":{"total":2,"successful":2,"failed":0},".kibana_1":{"total":2,"successful":2,"failed":0}}

Prevent shard balancing when purposely bringing down nodes using the OpenShift Dedicated es_util tool:

$ oc exec <any_es_pod_in_the_cluster> -c elasticsearch -- es_util --query="_cluster/settings" -XPUT -d '{ "persistent": { "cluster.routing.allocation.enable" : "primaries" } }'

For example:

$ oc exec elasticsearch-cdm-5ceex6ts-1-dcd6c4c7c-jpw6 -c elasticsearch -- es_util --query="_cluster/settings" -XPUT -d '{ "persistent": { "cluster.routing.allocation.enable" : "primaries" } }'

Example output

{"acknowledged":true,"persistent":{"cluster":{"routing":{"allocation":{"enable":"primaries"}}}},"transient":

After the command is complete, for each deployment you have for an ES cluster:

By default, the OpenShift Dedicated Elasticsearch cluster blocks rollouts to their nodes. Use the following command to allow rollouts and allow the pod to pick up the changes:

$ oc rollout resume deployment/<deployment-name>

For example:

$ oc rollout resume deployment/elasticsearch-cdm-0-1

Example output

deployment.extensions/elasticsearch-cdm-0-1 resumed

A new pod is deployed. After the pod has a ready container, you can move on to the next deployment.

$ oc get pods -l component=elasticsearch-

Example output

NAME                                            READY   STATUS    RESTARTS   AGE
elasticsearch-cdm-5ceex6ts-1-dcd6c4c7c-jpw6k    2/2     Running   0          22h
elasticsearch-cdm-5ceex6ts-2-f799564cb-l9mj7    2/2     Running   0          22h
elasticsearch-cdm-5ceex6ts-3-585968dc68-k7kjr   2/2     Running   0          22h

After the deployments are complete, reset the pod to disallow rollouts:

$ oc rollout pause deployment/<deployment-name>

For example:

$ oc rollout pause deployment/elasticsearch-cdm-0-1

Example output

deployment.extensions/elasticsearch-cdm-0-1 paused

Check that the Elasticsearch cluster is in a green or yellow state:

$ oc exec <any_es_pod_in_the_cluster> -c elasticsearch -- es_util --query=_cluster/health?pretty=true

Note

If you performed a rollout on the Elasticsearch pod you used in the previous commands, the pod no longer exists and you need a new pod name here.

For example:

$ oc exec elasticsearch-cdm-5ceex6ts-1-dcd6c4c7c-jpw6 -c elasticsearch -- es_util --query=_cluster/health?pretty=true

{
  "cluster_name" : "elasticsearch",
  "status" : "yellow", 1
  "timed_out" : false,
  "number_of_nodes" : 3,
  "number_of_data_nodes" : 3,
  "active_primary_shards" : 8,
  "active_shards" : 16,
  "relocating_shards" : 0,
  "initializing_shards" : 0,
  "unassigned_shards" : 1,
  "delayed_unassigned_shards" : 0,
  "number_of_pending_tasks" : 0,
  "number_of_in_flight_fetch" : 0,
  "task_max_waiting_in_queue_millis" : 0,
  "active_shards_percent_as_number" : 100.0
}

1: Make sure this parameter value is green or yellow before proceeding.

If you changed the Elasticsearch configuration map, repeat these steps for each Elasticsearch pod.

After all the deployments for the cluster have been rolled out, re-enable shard balancing:

$ oc exec <any_es_pod_in_the_cluster> -c elasticsearch -- es_util --query="_cluster/settings" -XPUT -d '{ "persistent": { "cluster.routing.allocation.enable" : "all" } }'

For example:

$ oc exec elasticsearch-cdm-5ceex6ts-1-dcd6c4c7c-jpw6 -c elasticsearch -- es_util --query="_cluster/settings" -XPUT -d '{ "persistent": { "cluster.routing.allocation.enable" : "all" } }'

Example output

{
  "acknowledged" : true,
  "persistent" : { },
  "transient" : {
    "cluster" : {
      "routing" : {
        "allocation" : {
          "enable" : "all"
        }
      }
    }
  }
}

Scale up the collector pods so they send new logs to Elasticsearch.

$ oc -n openshift-logging patch daemonset/collector -p '{"spec":{"template":{"spec":{"nodeSelector":{"logging-infra-collector": "true"}}}}}'

10.4.10. Exposing the log store service as a route

By default, the log store that is deployed with logging is not accessible from outside the logging cluster. You can enable a route with re-encryption termination for external access to the log store service for those tools that access its data.

Externally, you can access the log store by creating a reencrypt route, your OpenShift Dedicated token and the installed log store CA certificate. Then, access a node that hosts the log store service with a cURL request that contains:

The Authorization: Bearer ${token}
The Elasticsearch reencrypt route and an Elasticsearch API request.

Internally, you can access the log store service using the log store cluster IP, which you can get by using either of the following commands:

$ oc get service elasticsearch -o jsonpath={.spec.clusterIP} -n openshift-logging

Example output

172.30.183.229

$ oc get service elasticsearch -n openshift-logging

Example output

NAME            TYPE        CLUSTER-IP       EXTERNAL-IP   PORT(S)    AGE
elasticsearch   ClusterIP   172.30.183.229   <none>        9200/TCP   22h

You can check the cluster IP address with a command similar to the following:

$ oc exec elasticsearch-cdm-oplnhinv-1-5746475887-fj2f8 -n openshift-logging -- curl -tlsv1.2 --insecure -H "Authorization: Bearer ${token}" "https://172.30.183.229:9200/_cat/health"

Example output

  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100    29  100    29    0     0    108      0 --:--:-- --:--:-- --:--:--   108

Prerequisites

The Red Hat OpenShift Logging and Elasticsearch Operators must be installed.
You must have access to the project to be able to access to the logs.

Procedure

To expose the log store externally:

Change to the openshift-logging project:
```
$ oc project openshift-logging
```
Extract the CA certificate from the log store and write to the admin-ca file:
```
$ oc extract secret/elasticsearch --to=. --keys=admin-ca
```
Example output
```
admin-ca
```
Create the route for the log store service as a YAML file:
1. Create a YAML file with the following:
```
apiVersion: route.openshift.io/v1
kind: Route
metadata:
  name: elasticsearch
  namespace: openshift-logging
spec:
  host:
  to:
    kind: Service
    name: elasticsearch
  tls:
    termination: reencrypt
    destinationCACertificate: | 1
```
  1
  Add the log store CA certifcate or use the command in the next step. You do not have to set the spec.tls.key, spec.tls.certificate, and spec.tls.caCertificate parameters required by some reencrypt routes.
2. Run the following command to add the log store CA certificate to the route YAML you created in the previous step:
```
$ cat ./admin-ca | sed -e "s/^/      /" >> <file-name>.yaml
```
3. Create the route:
```
$ oc create -f <file-name>.yaml
```
  Example output
```
route.route.openshift.io/elasticsearch created
```

Check that the Elasticsearch service is exposed:

Get the token of this service account to be used in the request:
```
$ token=$(oc whoami -t)
```
Set the elasticsearch route you created as an environment variable.
```
$ routeES=`oc get route elasticsearch -o jsonpath={.spec.host}`
```

To verify the route was successfully created, run the following command that accesses Elasticsearch through the exposed route:

curl -tlsv1.2 --insecure -H "Authorization: Bearer ${token}" "https://${routeES}"

The response appears similar to the following:

Example output

{
  "name" : "elasticsearch-cdm-i40ktba0-1",
  "cluster_name" : "elasticsearch",
  "cluster_uuid" : "0eY-tJzcR3KOdpgeMJo-MQ",
  "version" : {
  "number" : "6.8.1",
  "build_flavor" : "oss",
  "build_type" : "zip",
  "build_hash" : "Unknown",
  "build_date" : "Unknown",
  "build_snapshot" : true,
  "lucene_version" : "7.7.0",
  "minimum_wire_compatibility_version" : "5.6.0",
  "minimum_index_compatibility_version" : "5.0.0"
},
  "<tagline>" : "<for search>"
}

10.4.11. Removing unused components if you do not use the default Elasticsearch log store

As an administrator, in the rare case that you forward logs to a third-party log store and do not use the default Elasticsearch log store, you can remove several unused components from your logging cluster.

In other words, if you do not use the default Elasticsearch log store, you can remove the internal Elasticsearch logStore and Kibana visualization components from the ClusterLogging custom resource (CR). Removing these components is optional but saves resources.

Prerequisites

Verify that your log forwarder does not send log data to the default internal Elasticsearch cluster. Inspect the ClusterLogForwarder CR YAML file that you used to configure log forwarding. Verify that it does not have an outputRefs element that specifies default. For example:
```
outputRefs:
- default
```

Warning

Suppose the ClusterLogForwarder CR forwards log data to the internal Elasticsearch cluster, and you remove the logStore component from the ClusterLogging CR. In that case, the internal Elasticsearch cluster will not be present to store the log data. This absence can cause data loss.

Procedure

Edit the ClusterLogging custom resource (CR) in the openshift-logging project:
```
$ oc edit ClusterLogging instance
```
If they are present, remove the logStore and visualization stanzas from the ClusterLogging CR.

Preserve the collection stanza of the ClusterLogging CR. The result should look similar to the following example:

apiVersion: "logging.openshift.io/v1"
kind: "ClusterLogging"
metadata:
  name: "instance"
  namespace: "openshift-logging"
spec:
  managementState: "Managed"
  collection:
    type: "fluentd"
    fluentd: {}

Verify that the collector pods are redeployed:

$ oc get pods -l component=collector -n openshift-logging

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Chapter 10. Log storage

10.1. About log storage

10.1.1. Log storage types

10.1.1.1. About the Elasticsearch log store

10.1.2. Querying log stores

10.1.3. Additional resources

10.2. Installing log storage

10.2.1. Deploying a Loki log store

10.2.1.1. Loki deployment sizing

10.2.1.2. Installing Logging and the Loki Operator using the web console

10.2.1.3. Creating a secret for Loki object storage by using the web console

10.2.1.4. Workload identity federation

10.2.1.5. Creating a LokiStack custom resource by using the web console

10.2.1.6. Installing Logging and the Loki Operator using the CLI

10.2.1.7. Creating a secret for Loki object storage by using the CLI

10.2.1.8. Creating a LokiStack custom resource by using the CLI

10.2.2. Loki object storage

10.2.2.1. AWS storage

10.2.2.1.1. AWS storage for STS enabled clusters

10.2.2.2. Azure storage

10.2.2.2.1. Azure storage for Microsoft Entra Workload ID enabled clusters

10.2.2.3. Google Cloud Platform storage

10.2.2.4. Minio storage

10.2.2.5. OpenShift Data Foundation storage

10.2.2.6. Swift storage

10.2.3. Deploying an Elasticsearch log store

10.2.3.1. Storage considerations for Elasticsearch

10.2.3.2. Installing the OpenShift Elasticsearch Operator by using the web console

10.2.3.3. Installing the OpenShift Elasticsearch Operator by using the CLI

10.2.4. Configuring log storage

10.3. Configuring the LokiStack log store

10.3.1. Creating a new group for the cluster-admin user role

10.3.2. LokiStack behavior during cluster restarts

10.3.3. Configuring Loki to tolerate node failure

10.3.4. Zone aware data replication

10.3.4.1. Recovering Loki pods from failed zones

10.3.4.1.1. Troubleshooting PVC in a terminating state

10.3.5. Fine grained access for Loki logs

10.3.5.1. Cluster wide access

10.3.5.2. Namespaced access

10.3.5.3. Custom admin group access

10.3.6. Enabling stream-based retention with Loki

10.3.7. Troubleshooting Loki rate limit errors

10.3.8. Configuring Loki to tolerate memberlist creation failure

10.3.9. Additional resources

10.4. Configuring the Elasticsearch log store

10.4.1. Configuring log storage

10.4.2. Forwarding audit logs to the log store

10.4.3. Configuring log retention time

10.4.4. Configuring CPU and memory requests for the log store

10.4.5. Configuring replication policy for the log store

10.4.6. Scaling down Elasticsearch pods

10.4.7. Configuring persistent storage for the log store

10.4.8. Configuring the log store for emptyDir storage

10.4.9. Performing an Elasticsearch rolling cluster restart

10.4.10. Exposing the log store service as a route

10.4.11. Removing unused components if you do not use the default Elasticsearch log store

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