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Configuring the log visualizer

OKD uses Kibana to display the log data collected by cluster logging.

You can scale Kibana for redundancy and configure the CPU and memory for your Kibana nodes.

Configuring CPU and memory limits

The cluster logging components allow for adjustments to both the CPU and memory limits.

Procedure

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

    $ oc edit ClusterLogging instance -n openshift-logging
    apiVersion: "logging.openshift.io/v1"
kind: "ClusterLogging"
metadata:
  name: "instance"

....

spec:
  managementState: "Managed"
  logStore:
    type: "elasticsearch"
    elasticsearch:
      nodeCount: 2
      resources: (1)
        limits:
          memory: 2Gi
        requests:
          cpu: 200m
          memory: 2Gi
      storage:
        storageClassName: "gp2"
        size: "200G"
      redundancyPolicy: "SingleRedundancy"
  visualization:
    type: "kibana"
    kibana:
      resources: (2)
        limits:
          memory: 1Gi
        requests:
          cpu: 500m
          memory: 1Gi
      proxy:
        resources: (2)
          limits:
            memory: 100Mi
          requests:
            cpu: 100m
            memory: 100Mi
      replicas: 2
  curation:
    type: "curator"
    curator:
      resources: (3)
        limits:
          memory: 200Mi
        requests:
          cpu: 200m
          memory: 200Mi
      schedule: "*/10 * * * *"
  collection:
    logs:
      type: "fluentd"
      fluentd:
        resources: (4)
          limits:
            memory: 736Mi
          requests:
            cpu: 200m
            memory: 736Mi
    1 Specify the CPU and memory limits and requests for the log store as needed. For Elasticsearch, you must adjust both the request value and the limit value.
    2 Specify the CPU and memory limits and requests for the log visualizer as needed.
    3 Specify the CPU and memory limits and requests for the log curator as needed.
    4 Specify the CPU and memory limits and requests for the log collector as needed.

Scaling redundancy for the log visualizer nodes

You can scale the pod that hosts the log visualizer for redundancy.

Procedure

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

    $ oc edit ClusterLogging instance
    $ oc edit ClusterLogging instance

apiVersion: "logging.openshift.io/v1"
kind: "ClusterLogging"
metadata:
  name: "instance"

....

spec:
    visualization:
      type: "kibana"
      kibana:
        replicas: 1 (1)
    1 Specify the number of Kibana nodes.