$ oc edit Clusterlogging instance -n openshift-logging
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.
The cluster logging components allow for adjustments to both the CPU and memory limits.
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. |
You can scale the pod that hosts the log visualizer for redundancy.
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. |