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 Loki components documentation Loki Object Storage documentation 10.2. Installing log storage You can use the OpenShift CLI ( oc ) or the Red Hat OpenShift Service on AWS web console to deploy a log store on your Red Hat OpenShift Service on AWS 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 Red Hat OpenShift Service on AWS 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 Red Hat OpenShift Service on AWS 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 Red Hat OpenShift Service on AWS web console. Procedure In the Red Hat OpenShift Service on AWS 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: In the Red Hat OpenShift Service on AWS web console, click Operators OperatorHub . Choose Red Hat OpenShift Logging from the list of available Operators, and click Install . Ensure that the A specific namespace on the cluster is selected under Installation Mode . Ensure that Operator recommended namespace is openshift-logging under Installed Namespace . 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. Select stable-5.y as the Update Channel . 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. 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: v13 effectiveDate: "<yyyy>-<mm>-<dd>" 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: Switch to the Administration Custom Resource Definitions page. On the Custom Resource Definitions page, click ClusterLogging . On the Custom Resource Definition details page, select View Instances from the Actions menu. On the ClusterLoggings page, click Create ClusterLogging . You might have to refresh the page to load the data. 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 Red Hat OpenShift Service on AWS web console. Prerequisites You have administrator permissions. You have access to the Red Hat OpenShift Service on AWS web console. You installed the Loki Operator. Procedure Go to Workloads Secrets in the Administrator perspective of the Red Hat OpenShift Service on AWS 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 Red Hat OpenShift Service on AWS 4.14 and later Logging 5.9 and later Procedure If you use the Red Hat OpenShift Service on AWS 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 Red Hat OpenShift Service on AWS web console. Prerequisites You have administrator permissions. You have access to the Red Hat OpenShift Service on AWS 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 Red Hat OpenShift Service on AWS cluster, an Operator such as Loki Operator for log storage must be installed first. This can be done from the Red Hat OpenShift Service on AWS 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 Red Hat OpenShift Service on AWS 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: USD 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 Red Hat OpenShift Service on AWS 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: USD 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: USD 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: USD 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 Red Hat OpenShift Service on AWS 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: USD 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: v13 effectiveDate: "<yyyy>-<mm>-<dd>" 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: USD 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: type: ocp-console 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: USD oc apply -f <filename>.yaml Verify the installation by running the following command: USD oc get pods -n openshift-logging Example output USD 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: USD 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: USD 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: USD 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: USD 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: USD 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: USD 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: USD 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: USD 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: USD 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=USD(oc get -n openshift-logging configmap loki-bucket-odf -o jsonpath='{.data.BUCKET_HOST}') BUCKET_NAME=USD(oc get -n openshift-logging configmap loki-bucket-odf -o jsonpath='{.data.BUCKET_NAME}') BUCKET_PORT=USD(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=USD(oc get -n openshift-logging secret loki-bucket-odf -o jsonpath='{.data.AWS_ACCESS_KEY_ID}' | base64 -d) SECRET_ACCESS_KEY=USD(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: USD 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: USD 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: USD 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 Red Hat OpenShift Service on AWS 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 . 10.2.3.1. Storage considerations for Elasticsearch A persistent volume is required for each Elasticsearch deployment configuration. On Red Hat OpenShift Service on AWS 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 Red Hat OpenShift Service on AWS nodes might not be large enough to support the Elasticsearch cluster. You must add additional nodes to the Red Hat OpenShift Service on AWS 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 Red Hat OpenShift Service on AWS 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 Red Hat OpenShift Service on AWS 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, Red Hat OpenShift Service on AWS installs three Elasticsearch nodes with memory requests and limits of 16 GB. This initial set of three Red Hat OpenShift Service on AWS 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 a ROSA 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: USD 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: USD 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 Red Hat OpenShift Service on AWS 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: USD 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: USD 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 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 . 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: USD 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 Red Hat OpenShift Service on AWS authentication integration. LokiStack's proxy uses Red Hat OpenShift Service on AWS 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: USD oc adm groups new cluster-admin Enter the following command to add the desired user to the cluster-admin group: USD oc adm groups add-users cluster-admin <username> Enter the following command to add cluster-admin user role to the group: USD 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 Red Hat OpenShift Service on AWS 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 Red Hat OpenShift Service on AWS 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 Red Hat OpenShift Service on AWS, 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 PodAntiAffinity v1 core Kubernetes documentation Assigning Pods to Nodes Kubernetes documentation Placing pods relative to other pods using affinity and anti-affinity rules 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 Red Hat OpenShift Service on AWS 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 Red Hat OpenShift Service on AWS 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 Topology spread constraints Kubernetes documentation Kubernetes storage documentation . 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: USD 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: USD 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 Loki components documentation Loki Query Language (LogQL) documentation Grafana Dashboard documentation Loki Object Storage documentation Loki Operator IngestionLimitSpec documentation Loki Storage Schema documentation 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 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 . 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: USD 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 x the number of primary shards. The index doc count is greater than 40960 KB x 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. Red Hat OpenShift Service on AWS 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 Red Hat OpenShift Service on AWS deletes the rolled-over indices. This setting is the maxAge you set in the ClusterLogging CR. 3 The index age for Red Hat OpenShift Service on AWS to consider when rolling over the indices. This value is determined from the maxAge you set in the ClusterLogging CR. 4 When Red Hat OpenShift Service on AWS 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 . USD 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: USD 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: USD oc -n openshift-logging 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: Get the names of the Elasticsearch pods: Scale down the collector pods so they stop sending new logs to Elasticsearch: USD oc -n openshift-logging patch daemonset/collector -p '{"spec":{"template":{"spec":{"nodeSelector":{"logging-infra-collector": "false"}}}}}' Perform a shard synced flush using the Red Hat OpenShift Service on AWS es_util tool to ensure there are no pending operations waiting to be written to disk prior to shutting down: USD oc exec <any_es_pod_in_the_cluster> -c elasticsearch -- es_util --query="_flush/synced" -XPOST For example: Example output Prevent shard balancing when purposely bringing down nodes using the Red Hat OpenShift Service on AWS es_util tool: For example: 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 Red Hat OpenShift Service on AWS Elasticsearch cluster blocks rollouts to their nodes. Use the following command to allow rollouts and allow the pod to pick up the changes: For example: Example output A new pod is deployed. After the pod has a ready container, you can move on to the deployment. 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: For example: Example output Check that the Elasticsearch cluster is in a green or yellow state: Note If you performed a rollout on the Elasticsearch pod you used in the commands, the pod no longer exists and you need a new pod name here. For example: 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: For example: Example output { "acknowledged" : true, "persistent" : { }, "transient" : { "cluster" : { "routing" : { "allocation" : { "enable" : "all" } } } } } Scale up the collector pods so they send new logs to Elasticsearch. USD 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 Red Hat OpenShift Service on AWS 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 USD{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: USD oc get service elasticsearch -o jsonpath={.spec.clusterIP} -n openshift-logging Example output 172.30.183.229 USD 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: USD oc exec elasticsearch-cdm-oplnhinv-1-5746475887-fj2f8 -n openshift-logging -- curl -tlsv1.2 --insecure -H "Authorization: Bearer USD{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: USD oc project openshift-logging Extract the CA certificate from the log store and write to the admin-ca file: USD oc extract secret/elasticsearch --to=. --keys=admin-ca Example output admin-ca Create the route for the log store service as a YAML file: 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 step. You do not have to set the spec.tls.key , spec.tls.certificate , and spec.tls.caCertificate parameters required by some reencrypt routes. Run the following command to add the log store CA certificate to the route YAML you created in the step: USD cat ./admin-ca | sed -e "s/^/ /" >> <file-name>.yaml Create the route: USD 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: USD token=USD(oc whoami -t) Set the elasticsearch route you created as an environment variable. USD 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 USD{token}" "https://USD{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: USD 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: USD oc get pods -l component=collector -n openshift-logging

Commands:
apiVersion: loki.grafana.com/v1 kind: LokiStack metadata: name: logging-loki 1 namespace: openshift-logging 2 spec: size: 1x.small 3 storage: schemas: - version: v13 effectiveDate: "<yyyy>-<mm>-<dd>" secret: name: logging-loki-s3 4 type: s3 5 credentialMode: 6 storageClassName: <storage_class_name> 7 tenants: mode: openshift-logging 8
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
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
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>
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>
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
apiVersion: v1 kind: Namespace metadata: name: openshift-operators-redhat 1 annotations: openshift.io/node-selector: "" labels: openshift.io/cluster-monitoring: "true" 2
oc apply -f <filename>.yaml
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
oc apply -f <filename>.yaml
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
oc apply -f <filename>.yaml
apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: cluster-logging namespace: openshift-logging 1 spec: targetNamespaces: - openshift-logging
oc apply -f <filename>.yaml
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
oc apply -f <filename>.yaml
apiVersion: loki.grafana.com/v1 kind: LokiStack metadata: name: logging-loki 1 namespace: openshift-logging 2 spec: size: 1x.small 3 storage: schemas: - version: v13 effectiveDate: "<yyyy>-<mm>-<dd>" secret: name: logging-loki-s3 4 type: s3 5 credentialMode: 6 storageClassName: <storage_class_name> 7 tenants: mode: openshift-logging 8
oc apply -f <filename>.yaml
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
oc apply -f <filename>.yaml
oc get pods -n openshift-logging
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
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>
oc get secrets
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
oc get pods -n openshift-logging
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
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>"
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
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>"
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>"
oc create secret generic logging-loki-gcs --from-literal=bucketname="<bucket_name>" --from-file=key.json="<path/to/key.json>"
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>"
apiVersion: objectbucket.io/v1alpha1 kind: ObjectBucketClaim metadata: name: loki-bucket-odf namespace: openshift-logging spec: generateBucketName: loki-bucket-odf storageClassName: openshift-storage.noobaa.io
BUCKET_HOST=USD(oc get -n openshift-logging configmap loki-bucket-odf -o jsonpath='{.data.BUCKET_HOST}') BUCKET_NAME=USD(oc get -n openshift-logging configmap loki-bucket-odf -o jsonpath='{.data.BUCKET_NAME}') BUCKET_PORT=USD(oc get -n openshift-logging configmap loki-bucket-odf -o jsonpath='{.data.BUCKET_PORT}')
ACCESS_KEY_ID=USD(oc get -n openshift-logging secret loki-bucket-odf -o jsonpath='{.data.AWS_ACCESS_KEY_ID}' | base64 -d) SECRET_ACCESS_KEY=USD(oc get -n openshift-logging secret loki-bucket-odf -o jsonpath='{.data.AWS_SECRET_ACCESS_KEY}' | base64 -d)
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>"
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>"
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>"
apiVersion: v1 kind: Namespace metadata: name: openshift-operators-redhat 1 annotations: openshift.io/node-selector: "" labels: openshift.io/cluster-monitoring: "true" 2
oc apply -f <filename>.yaml
apiVersion: operators.coreos.com/v1 kind: OperatorGroup metadata: name: openshift-operators-redhat namespace: openshift-operators-redhat 1 spec: {}
oc apply -f <filename>.yaml
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
oc apply -f <filename>.yaml
oc get csv -n --all-namespaces
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
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: {}
apiVersion: logging.openshift.io/v1 kind: ClusterLogging metadata: name: instance namespace: openshift-logging spec: managementState: Managed logStore: type: lokistack lokistack: name: logging-loki
oc apply -f <filename>.yaml
oc adm groups new cluster-admin
oc adm groups add-users cluster-admin <username>
oc adm policy add-cluster-role-to-group cluster-admin cluster-admin
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
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
get pods --field-selector status.phase==Pending -n openshift-logging
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
get pvc -o=json -n openshift-logging | jq '.items[] | select(.status.phase == "Pending") | .metadata.name' -r
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 pvc __<pvc_name>__ -n openshift-logging
delete pod __<pod_name>__ -n openshift-logging
patch pvc __<pvc_name>__ -p '{"metadata":{"finalizers":null}}' -n openshift-logging
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
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
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
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
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
oc apply -f <filename>.yaml
"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\"}"]]}]}
429 Too Many Requests Ingestion rate limit exceeded
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
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"
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
apiVersion: loki.grafana.com/v1 kind: LokiStack metadata: name: logging-loki namespace: openshift-logging spec: limits: global: ingestion: ingestionBurstSize: 16 1 ingestionRate: 8 2
oc patch LokiStack logging-loki -n openshift-logging --type=merge -p '{"spec": {"hashRing":{"memberlist":{"instanceAddrType":"podIP","type": "memberlist"}}}}'
apiVersion: loki.grafana.com/v1 kind: LokiStack metadata: name: logging-loki namespace: openshift-logging spec: hashRing: type: memberlist memberlist: instanceAddrType: podIP
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: {}
apiVersion: logging.openshift.io/v1 kind: ClusterLogging metadata: name: instance namespace: openshift-logging spec: managementState: Managed logStore: type: lokistack lokistack: name: logging-loki
oc apply -f <filename>.yaml
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
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
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
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
oc get cronjob
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
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
resources: limits: 1 memory: "32Gi" requests: 2 cpu: "8" memory: "32Gi"
oc -n openshift-logging edit ClusterLogging instance
apiVersion: "logging.openshift.io/v1" kind: "ClusterLogging" metadata: name: "instance" . spec: logStore: type: "elasticsearch" elasticsearch: redundancyPolicy: "SingleRedundancy" 1
apiVersion: "logging.openshift.io/v1" kind: "ClusterLogging" metadata: name: "instance" spec: logStore: type: "elasticsearch" elasticsearch: nodeCount: 3 storage: storageClassName: "gp2" size: "200G"
spec: logStore: type: "elasticsearch" elasticsearch: nodeCount: 3 storage: {}
oc project openshift-logging
oc get pods -l component=elasticsearch
oc -n openshift-logging patch daemonset/collector -p '{"spec":{"template":{"spec":{"nodeSelector":{"logging-infra-collector": "false"}}}}}'
oc exec <any_es_pod_in_the_cluster> -c elasticsearch -- es_util --query="_flush/synced" -XPOST
oc exec -c elasticsearch-cdm-5ceex6ts-1-dcd6c4c7c-jpw6 -c elasticsearch -- es_util --query="_flush/synced" -XPOST
{"_shards":{"total":4,"successful":4,"failed":0},".security":{"total":2,"successful":2,"failed":0},".kibana_1":{"total":2,"successful":2,"failed":0}}
oc exec <any_es_pod_in_the_cluster> -c elasticsearch -- es_util --query="_cluster/settings" -XPUT -d '{ "persistent": { "cluster.routing.allocation.enable" : "primaries" } }'
oc exec elasticsearch-cdm-5ceex6ts-1-dcd6c4c7c-jpw6 -c elasticsearch -- es_util --query="_cluster/settings" -XPUT -d '{ "persistent": { "cluster.routing.allocation.enable" : "primaries" } }'
{"acknowledged":true,"persistent":{"cluster":{"routing":{"allocation":{"enable":"primaries"}}}},"transient":
oc rollout resume deployment/<deployment-name>
oc rollout resume deployment/elasticsearch-cdm-0-1
deployment.extensions/elasticsearch-cdm-0-1 resumed
oc get pods -l component=elasticsearch-
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
oc rollout pause deployment/<deployment-name>
oc rollout pause deployment/elasticsearch-cdm-0-1
deployment.extensions/elasticsearch-cdm-0-1 paused
oc exec <any_es_pod_in_the_cluster> -c elasticsearch -- es_util --query=_cluster/health?pretty=true
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 }
oc exec <any_es_pod_in_the_cluster> -c elasticsearch -- es_util --query="_cluster/settings" -XPUT -d '{ "persistent": { "cluster.routing.allocation.enable" : "all" } }'
oc exec elasticsearch-cdm-5ceex6ts-1-dcd6c4c7c-jpw6 -c elasticsearch -- es_util --query="_cluster/settings" -XPUT -d '{ "persistent": { "cluster.routing.allocation.enable" : "all" } }'
{ "acknowledged" : true, "persistent" : { }, "transient" : { "cluster" : { "routing" : { "allocation" : { "enable" : "all" } } } } }
oc -n openshift-logging patch daemonset/collector -p '{"spec":{"template":{"spec":{"nodeSelector":{"logging-infra-collector": "true"}}}}}'
oc get service elasticsearch -o jsonpath={.spec.clusterIP} -n openshift-logging
172.30.183.229
oc get service elasticsearch -n openshift-logging
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE elasticsearch ClusterIP 172.30.183.229 <none> 9200/TCP 22h
oc exec elasticsearch-cdm-oplnhinv-1-5746475887-fj2f8 -n openshift-logging -- curl -tlsv1.2 --insecure -H "Authorization: Bearer USD{token}" "https://172.30.183.229:9200/_cat/health"
% Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 29 100 29 0 0 108 0 --:--:-- --:--:-- --:--:-- 108
oc project openshift-logging
oc extract secret/elasticsearch --to=. --keys=admin-ca
admin-ca
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
cat ./admin-ca | sed -e "s/^/ /" >> <file-name>.yaml
oc create -f <file-name>.yaml
route.route.openshift.io/elasticsearch created
token=USD(oc whoami -t)
routeES=`oc get route elasticsearch -o jsonpath={.spec.host}`
curl -tlsv1.2 --insecure -H "Authorization: Bearer USD{token}" "https://USD{routeES}"
{ "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>" }
outputRefs: - default
oc edit ClusterLogging instance
apiVersion: "logging.openshift.io/v1" kind: "ClusterLogging" metadata: name: "instance" namespace: "openshift-logging" spec: managementState: "Managed" collection: type: "fluentd" fluentd: {}
oc get pods -l component=collector -n openshift-logging