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:

    1. $ oc edit ClusterLogging instance -n openshift-logging
    1. apiVersion: "logging.openshift.io/v1"
    2. kind: "ClusterLogging"
    3. metadata:
    4.   name: "instance"
    6. ....
    8. spec:
    9.   managementState: "Managed"
    10.   logStore:
    11.     type: "elasticsearch"
    12.     elasticsearch:
    13.       nodeCount: 2
    14.       resources: (1)
    15.         limits:
    16.           memory: 2Gi
    17.         requests:
    18.           cpu: 200m
    19.           memory: 2Gi
    20.       storage:
    21.         storageClassName: "gp2"
    22.         size: "200G"
    23.       redundancyPolicy: "SingleRedundancy"
    24.   visualization:
    25.     type: "kibana"
    26.     kibana:
    27.       resources: (2)
    28.         limits:
    29.           memory: 1Gi
    30.         requests:
    31.           cpu: 500m
    32.           memory: 1Gi
    33.       proxy:
    34.         resources: (2)
    35.           limits:
    36.             memory: 100Mi
    37.           requests:
    38.             cpu: 100m
    39.             memory: 100Mi
    40.       replicas: 2
    41.   curation:
    42.     type: "curator"
    43.     curator:
    44.       resources: (3)
    45.         limits:
    46.           memory: 200Mi
    47.         requests:
    48.           cpu: 200m
    49.           memory: 200Mi
    50.       schedule: "*/10 * * * *"
    51.   collection:
    52.     logs:
    53.       type: "fluentd"
    54.       fluentd:
    55.         resources: (4)
    56.           limits:
    57.             memory: 736Mi
    58.           requests:
    59.             cpu: 200m
    60.             memory: 736Mi
    1Specify 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.
    2Specify the CPU and memory limits and requests for the log visualizer as needed.
    3Specify the CPU and memory limits and requests for the log curator as needed.
    4Specify 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:

    1. $ oc edit ClusterLogging instance
    1. $ oc edit ClusterLogging instance
    3. apiVersion: "logging.openshift.io/v1"
    4. kind: "ClusterLogging"
    5. metadata:
    6.   name: "instance"
    8. ....
    10. spec:
    11.     visualization:
    12.       type: "kibana"
    13.       kibana:
    14.         replicas: 1 (1)
    1Specify the number of Kibana nodes.