9.3. 使用 OpenShift Serverless 的集群日志记录

您可以通过修改 openshift-logging 项目中部署的集群日志记录自定义资源来配置集群日志记录环境。

您可以在安装时或安装后修改以下任何组件：

spec:
  logStore:
    elasticsearch:
      resources:
        limits:
          cpu:
          memory: 16Gi
        requests:
          cpu: 500m
          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"

  spec:
    logStore:
      type: "elasticsearch"
      elasticsearch:
        nodeCount: 3
        storage:
          storageClassName: "gp2"
          size: "200G"

本例中指定，集群中的每个数据节点将绑定到请求 200G 的 gp2 存储的 PersistentVolumeClaim。每个主分片将由单个副本支持。

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

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

以下是使用前述选项修改的集群日志记录自定义资源的示例。

apiVersion: "logging.openshift.io/v1"
kind: "ClusterLogging"
metadata:
  name: "instance"
  namespace: "openshift-logging"
spec:
  managementState: "Managed"
  logStore:
    type: "elasticsearch"
    elasticsearch:
      nodeCount: 3
      resources:
        limits:
          memory: 32Gi
        requests:
          cpu: 3
          memory: 32Gi
      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