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Logging subsystem for Red Hat OpenShift uses Elasticsearch 6 (ES) to store and organize the 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

Elasticsearch is a memory-intensive application. Each Elasticsearch node needs at least 16G of memory for both memory requests and limits, unless you specify otherwise in the ClusterLogging custom resource. The initial set of OpenShift Container Platform nodes might not be large enough to support the Elasticsearch cluster. You must add additional nodes to the OpenShift Container Platform cluster to run with the recommended or higher memory, up to a maximum of 64G for each Elasticsearch node.

Each Elasticsearch node can operate with a lower memory setting, though this is not recommended for production environments.

Forwarding audit logs to the log store

By default, OpenShift Logging does not store audit logs in the internal OpenShift Container Platform Elasticsearch log store. You can send audit logs to this log store so, for example, you can view them in Kibana.

To send the audit logs to the default internal Elasticsearch log store, for example to view the audit logs in Kibana, you must use the Log Forwarding API.

The internal OpenShift Container Platform Elasticsearch log store does not provide secure storage for audit logs. Verify that the system to which you forward audit logs complies with your organizational and governmental regulations and is properly secured. The logging subsystem for Red Hat OpenShift does not comply with those regulations.

Procedure

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

  1. 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.

      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

Configuring log retention time

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

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

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

  • The index is older than the rollover.maxAge value in the Elasticsearch CR.

  • The index size is greater than 40 GB × the number of primary shards.

  • The index doc count is greater than 40960 KB × the number of primary shards.

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

Prerequisites
  • The logging subsystem for Red Hat OpenShift and the OpenShift Elasticsearch Operator must be installed.

Procedure

To configure the log retention time:

  1. 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.
  2. You can verify the settings in the Elasticsearch custom resource (CR).

    For example, the Red Hat OpenShift Logging Operator updated the following Elasticsearch CR to configure a retention policy that includes settings to roll over active indices for the infrastructure logs every eight hours and the rolled-over indices are deleted seven days after rollover. OpenShift Container Platform checks every 15 minutes to determine if the indices need to be rolled over.

    apiVersion: "logging.openshift.io/v1"
    kind: "Elasticsearch"
    metadata:
      name: "elasticsearch"
    spec:
    ...
      indexManagement:
        policies: (1)
          - name: infra-policy
            phases:
              delete:
                minAge: 7d (2)
              hot:
                actions:
                  rollover:
                    maxAge: 8h (3)
            pollInterval: 15m (4)
    ...
    1 For each log source, the retention policy indicates when to delete and roll over logs for that source.
    2 When OpenShift Container Platform deletes the rolled-over indices. This setting is the maxAge you set in the ClusterLogging CR.
    3 The index age for OpenShift Container Platform to consider when rolling over the indices. This value is determined from the maxAge you set in the ClusterLogging CR.
    4 When OpenShift Container Platform checks if the indices should be rolled over. This setting is the default and cannot be changed.

    Modifying the Elasticsearch CR is not supported. All changes to the retention policies must be made in the ClusterLogging CR.

    The OpenShift Elasticsearch Operator deploys a cron job to roll over indices for each mapping using the defined policy, scheduled using the pollInterval.

    $ oc get cronjob
    Example output
    NAME                     SCHEDULE       SUSPEND   ACTIVE   LAST SCHEDULE   AGE
    elasticsearch-im-app     */15 * * * *   False     0        <none>          4s
    elasticsearch-im-audit   */15 * * * *   False     0        <none>          4s
    elasticsearch-im-infra   */15 * * * *   False     0        <none>          4s

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.

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 logging subsystem for Red Hat OpenShift and Elasticsearch must be installed.

Procedure
  1. Edit the ClusterLogging custom resource (CR) in the openshift-logging project:

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

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

For example:

      resources:
        limits: (1)
          memory: "32Gi"
        requests: (2)
          cpu: "8"
          memory: "32Gi"
1 The maximum amount of the resource.
2 The minimum amount required.

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

Configuring replication policy for the log store

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

Prerequisites
  • The logging subsystem for Red Hat OpenShift and Elasticsearch must be installed.

Procedure
  1. Edit the ClusterLogging custom resource (CR) in the openshift-logging project:

    $ oc edit clusterlogging instance
    apiVersion: "logging.openshift.io/v1"
    kind: "ClusterLogging"
    metadata:
      name: "instance"
    
    ....
    
    spec:
      logStore:
        type: "elasticsearch"
        elasticsearch:
          redundancyPolicy: "SingleRedundancy" (1)
    1 Specify a redundancy policy for the shards. The change is applied upon saving the changes.
    • FullRedundancy. Elasticsearch fully replicates the primary shards for each index to every data node. This provides the highest safety, but at the cost of the highest amount of disk required and the poorest performance.

    • MultipleRedundancy. Elasticsearch fully replicates the primary shards for each index to half of the data nodes. This provides a good tradeoff between safety and performance.

    • SingleRedundancy. Elasticsearch makes one copy of the primary shards for each index. Logs are always available and recoverable as long as at least two data nodes exist. Better performance than MultipleRedundancy, when using 5 or more nodes. You cannot apply this policy on deployments of single Elasticsearch node.

    • ZeroRedundancy. Elasticsearch does not make copies of the primary shards. Logs might be unavailable or lost in the event a node is down or fails. Use this mode when you are more concerned with performance than safety, or have implemented your own disk/PVC backup/restore strategy.

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

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.

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

Configuring persistent storage for the log store

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

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 logging subsystem for Red Hat OpenShift and Elasticsearch must be installed.

Procedure
  1. 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.

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.

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.

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

Prerequisites
  • The logging subsystem for Red Hat OpenShift and Elasticsearch must be installed.

Procedure
  1. Edit the ClusterLogging CR to specify emptyDir:

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

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 logging subsystem for Red Hat OpenShift and Elasticsearch must be installed.

Procedure

To perform a rolling cluster restart:

  1. Change to the openshift-logging project:

    $ oc project openshift-logging
  2. Get the names of the Elasticsearch pods:

    $ oc get pods | grep elasticsearch-
  3. Scale down the Fluentd pods so they stop sending new logs to Elasticsearch:

    $ oc -n openshift-logging patch daemonset/logging-fluentd -p '{"spec":{"template":{"spec":{"nodeSelector":{"logging-infra-fluentd": "false"}}}}}'
  4. Perform a shard synced flush using the OpenShift Container Platform es_util tool to ensure there are no pending operations waiting to be written to disk prior to shutting down:

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

    For example:

    $ oc exec -c elasticsearch-cdm-5ceex6ts-1-dcd6c4c7c-jpw6  -c elasticsearch -- es_util --query="_flush/synced" -XPOST
    Example output
    {"_shards":{"total":4,"successful":4,"failed":0},".security":{"total":2,"successful":2,"failed":0},".kibana_1":{"total":2,"successful":2,"failed":0}}
  5. Prevent shard balancing when purposely bringing down nodes using the OpenShift Container Platform es_util tool:

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

    For example:

    $ oc exec elasticsearch-cdm-5ceex6ts-1-dcd6c4c7c-jpw6 -c elasticsearch -- es_util --query="_cluster/settings" -XPUT -d '{ "persistent": { "cluster.routing.allocation.enable" : "primaries" } }'
    Example output
    {"acknowledged":true,"persistent":{"cluster":{"routing":{"allocation":{"enable":"primaries"}}}},"transient":
  6. After the command is complete, for each deployment you have for an ES cluster:

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

      $ oc rollout resume deployment/<deployment-name>

      For example:

      $ oc rollout resume deployment/elasticsearch-cdm-0-1
      Example output
      deployment.extensions/elasticsearch-cdm-0-1 resumed

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