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About configuring cluster <strong>logging</strong> - Configuring your cluster <strong>logging</strong> deployment | <strong>logging</strong> | OpenShift Container Platform 4.1
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About configuring cluster logging

After installing cluster logging into your cluster, you can make the following configurations.

You must set cluster logging to Unmanaged state before performing these configurations, unless otherwise noted. For more information, see Changing the cluster logging management state.

About deploying and configuring cluster logging

OpenShift Container Platform cluster logging is designed to be used with the default configuration, which is tuned for small to medium sized OpenShift Container Platform clusters.

The installation instructions that follow include a sample Cluster logging Custom Resource (CR), which you can use to create a cluster logging instance and configure your cluster logging deployment.

If you want to use the default cluster logging install, you can use the sample CR directly.

If you want to customize your deployment, make changes to the sample CR as needed. The following describes the configurations you can make when installing your cluster logging instance or modify after installtion. See the Configuring sections for more information on working with each component, including modifications you can make outside of the Cluster logging Custom Resource.

Configuring and Tuning Cluster logging

You can configure your cluster logging environment by modifying the Cluster logging Custom Resource deployed in the openshift-logging project.

You can modify any of the following components upon install or after install:

Memory and CPU

You can adjust both the CPU and memory limits for each component by modifying the resources block with valid memory and CPU values:

spec:
  logStore:
    elasticsearch:
      resources:
        limits:
          cpu:
          memory:
        requests:
          cpu: 1
          memory: 16Gi
      type: "elasticsearch"
  collection:
    logs:
      fluentd:
        resources:
          limits:
            cpu:
            memory:
          requests:
            cpu:
            memory:
        type: "fluentd"
  visualization:
    kibana:
      resources:
        limits:
          cpu:
          memory:
        requests:
          cpu:
          memory:
     type: kibana
  curation:
    curator:
      resources:
        limits:
          memory: 200Mi
        requests:
          cpu: 200m
          memory: 200Mi
      type: "curator"
Elasticsearch storage

You can configure a persistent storage class and size for the Elasticsearch cluster using the storageClass name and size parameters. The Cluster logging Operator creates a PersistentVolumeClaim for each data node in the Elasticsearch cluster based on these parameters.

  spec:
    logStore:
      type: "elasticsearch"
      elasticsearch:
        storage:
          storageClassName: "gp2"
          size: "200G"

This example specifies each data node in the cluster will be bound to a PersistentVolumeClaim that requests "200G" of "gp2" storage. Each primary shard will be backed by a single replica.

Omitting the storage block results in a deployment that includes ephemeral storage only.

  spec:
    logStore:
      type: "elasticsearch"
      elasticsearch:
        storage: {}
Elasticsearch replication policy

You can set the policy that defines how Elasticsearch shards are replicated across data nodes in the cluster:

  • FullRedundancy. The shards for each index are fully replicated to every data node.

  • MultipleRedundancy. The shards for each index are spread over half of the data nodes.

  • SingleRedundancy. A single copy of each shard. Logs are always available and recoverable as long as at least two data nodes exist.

  • ZeroRedundancy. No copies of any shards. Logs may be unavailable (or lost) in the event a node is down or fails.

Curator schedule

You specify the schedule for Curator in the [cron format](https://en.wikipedia.org/wiki/Cron).

  spec:
    curation:
    type: "curator"
    resources:
    curator:
      schedule: "30 3 * * *"

Sample modified Cluster logging Custom Resource

The following is an example of a Cluster logging Custom Resource modified using the options previously described.

Sample modified Cluster logging Custom Resource
apiVersion: "logging.openshift.io/v1"
kind: "Clusterlogging"
metadata:
  name: "instance"
  namespace: "openshift-logging"
spec:
  managementState: "Managed"
  logStore:
    type: "elasticsearch"
    elasticsearch:
      nodeCount: 2
      resources:
        limits:
          memory: 2Gi
        requests:
          cpu: 200m
          memory: 2Gi
      storage: {}
      redundancyPolicy: "SingleRedundancy"
  visualization:
    type: "kibana"
    kibana:
      resources:
        limits:
          memory: 1Gi
        requests:
          cpu: 500m
          memory: 1Gi
      replicas: 1
  curation:
    type: "curator"
    curator:
      resources:
        limits:
          memory: 200Mi
        requests:
          cpu: 200m
          memory: 200Mi
      schedule: "*/5 * * * *"
  collection:
    logs:
      type: "fluentd"
      fluentd:
        resources:
          limits:
            memory: 1Gi
          requests:
            cpu: 200m
            memory: 1Gi

Moving the cluster logging resources

You can configure the Cluster logging Operator to deploy the pods for any or all of the Cluster logging components, Elasticsearch, Kibana, and Curator to different nodes. You cannot move the Cluster logging Operator pod from its installed location.

For example, you can move the Elasticsearch pods to a separate node because of high CPU, memory, and disk requirements.

You should set your MachineSet to use at least 6 replicas.
Prerequisites

  • Cluster logging and Elasticsearch must be installed. These features are not installed by default.

Procedure

  1. Edit the Cluster logging Custom Resource in the openshift-logging project:

    $ oc edit Clusterlogging instance
    apiVersion: logging.openshift.io/v1
kind: Clusterlogging

....

spec:
  collection:
    logs:
      fluentd:
        resources: null
      rsyslog:
        resources: null
      type: fluentd
  curation:
    curator:
      nodeSelector: (1)
          node-role.kubernetes.io/infra: ''
      resources: null
      schedule: 30 3 * * *
    type: curator
  logStore:
    elasticsearch:
      nodeCount: 3
      nodeSelector: (1)
          node-role.kubernetes.io/infra: ''
      redundancyPolicy: SingleRedundancy
      resources:
        limits:
          cpu: 500m
          memory: 16Gi
        requests:
          cpu: 500m
          memory: 16Gi
      storage: {}
    type: elasticsearch
  managementState: Managed
  visualization:
    kibana:
      nodeSelector: (1)
          node-role.kubernetes.io/infra: '' (1)
      proxy:
        resources: null
      replicas: 1
      resources: null
    type: kibana

....
1 Add a nodeSelector parameter with the appropriate value to the component you want to move. You can use a nodeSelector in the format shown or use <key>: <value> pairs, based on the value specified for the node.
Verification steps

To verify that a component has moved, you can use the oc get pod -o wide command.

For example:

  • You want to move the Kibana pod from the ip-10-0-147-79.us-east-2.compute.internal node:

    $ oc get pod kibana-5b8bdf44f9-ccpq9 -o wide
NAME                      READY   STATUS    RESTARTS   AGE   IP            NODE                                        NOMINATED NODE   READINESS GATES
kibana-5b8bdf44f9-ccpq9   2/2     Running   0          27s   10.129.2.18   ip-10-0-147-79.us-east-2.compute.internal   <none>           <none>

  • You want to move the Kibana Pod to the ip-10-0-139-48.us-east-2.compute.internal node, a dedicated infrastructure node:

    $ oc get nodes
NAME                                         STATUS   ROLES          AGE   VERSION
ip-10-0-133-216.us-east-2.compute.internal   Ready    master         60m   v1.16.2
ip-10-0-139-146.us-east-2.compute.internal   Ready    master         60m   v1.16.2
ip-10-0-139-192.us-east-2.compute.internal   Ready    worker         51m   v1.16.2
ip-10-0-139-241.us-east-2.compute.internal   Ready    worker         51m   v1.16.2
ip-10-0-147-79.us-east-2.compute.internal    Ready    worker         51m   v1.16.2
ip-10-0-152-241.us-east-2.compute.internal   Ready    master         60m   v1.16.2
ip-10-0-139-48.us-east-2.compute.internal    Ready    infra          51m   v1.16.2

    Note that the node has a node-role.kubernetes.io/infra: '' label:

    $ oc get node ip-10-0-139-48.us-east-2.compute.internal -o yaml

kind: Node
apiVersion: v1
metadata:
  name: ip-10-0-139-48.us-east-2.compute.internal
  selfLink: /api/v1/nodes/ip-10-0-139-48.us-east-2.compute.internal
  uid: 62038aa9-661f-41d7-ba93-b5f1b6ef8751
  resourceVersion: '39083'
  creationTimestamp: '2020-04-13T19:07:55Z'
  labels:
    node-role.kubernetes.io/infra: ''
....

  • To move the Kibana Pod, edit the Cluster logging CR to add a node selector:

    apiVersion: logging.openshift.io/v1
kind: Clusterlogging

....

spec:

....

  visualization:
    kibana:
      nodeSelector: (1)
        node-role.kubernetes.io/infra: '' (1)
      proxy:
        resources: null
      replicas: 1
      resources: null
    type: kibana
    1 Add a node selector to match the label in the node specification.

  • After you save the CR, the current Kibana pod is terminated and new pod is deployed:

    $ oc get pods
NAME                                            READY   STATUS        RESTARTS   AGE
cluster-logging-operator-84d98649c4-zb9g7       1/1     Running       0          29m
elasticsearch-cdm-hwv01pf7-1-56588f554f-kpmlg   2/2     Running       0          28m
elasticsearch-cdm-hwv01pf7-2-84c877d75d-75wqj   2/2     Running       0          28m
elasticsearch-cdm-hwv01pf7-3-f5d95b87b-4nx78    2/2     Running       0          28m
fluentd-42dzz                                   1/1     Running       0          28m
fluentd-d74rq                                   1/1     Running       0          28m
fluentd-m5vr9                                   1/1     Running       0          28m
fluentd-nkxl7                                   1/1     Running       0          28m
fluentd-pdvqb                                   1/1     Running       0          28m
fluentd-tflh6                                   1/1     Running       0          28m
kibana-5b8bdf44f9-ccpq9                         2/2     Terminating   0          4m11s
kibana-7d85dcffc8-bfpfp                         2/2     Running       0          33s

  • The new pod is on the ip-10-0-139-48.us-east-2.compute.internal node:

    $ oc get pod kibana-7d85dcffc8-bfpfp -o wide
NAME                      READY   STATUS        RESTARTS   AGE   IP            NODE                                        NOMINATED NODE   READINESS GATES
kibana-7d85dcffc8-bfpfp   2/2     Running       0          43s   10.131.0.22   ip-10-0-139-48.us-east-2.compute.internal   <none>           <none>

  • After a few moments, the original Kibana pod is removed.

    $ oc get pods
NAME                                            READY   STATUS    RESTARTS   AGE
cluster-logging-operator-84d98649c4-zb9g7       1/1     Running   0          30m
elasticsearch-cdm-hwv01pf7-1-56588f554f-kpmlg   2/2     Running   0          29m
elasticsearch-cdm-hwv01pf7-2-84c877d75d-75wqj   2/2     Running   0          29m
elasticsearch-cdm-hwv01pf7-3-f5d95b87b-4nx78    2/2     Running   0          29m
fluentd-42dzz                                   1/1     Running   0          29m
fluentd-d74rq                                   1/1     Running   0          29m
fluentd-m5vr9                                   1/1     Running   0          29m
fluentd-nkxl7                                   1/1     Running   0          29m
fluentd-pdvqb                                   1/1     Running   0          29m
fluentd-tflh6                                   1/1     Running   0          29m
kibana-7d85dcffc8-bfpfp                         2/2     Running   0          62s