云原生 | K8S集群部署es集群+kibana

 1.创建命名空间

kubectl create ns elk

2. 创建elasticsearch的svc，sts

vim es-sts.yaml

---
apiVersion: v1
kind: Service
metadata:
  name: elasticsearch-logging
  namespace: elk
  labels:
    k8s-app: elasticsearch-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/name: "Elasticsearch"
spec:
  ports:
  - port: 9200
    protocol: TCP
    targetPort: db
  selector:
    k8s-app: elasticsearch-logging
---
# RBAC authn and authz
apiVersion: v1
kind: ServiceAccount
metadata:
  name: elasticsearch-logging
  namespace: elk
  labels:
    k8s-app: elasticsearch-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
---
kind: ClusterRole
apiVersion: rbac.authorization.k8s.io/v1
metadata:
  name: elasticsearch-logging
  labels:
    k8s-app: elasticsearch-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
rules:
- apiGroups:
  - ""
  resources:
  - "services"
  - "namespaces"
  - "endpoints"
  verbs:
  - "get"
---
kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1
metadata:
  namespace: elk
  name: elasticsearch-logging
  labels:
    k8s-app: elasticsearch-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
subjects:
- kind: ServiceAccount
  name: elasticsearch-logging
  namespace: elk
  apiGroup: ""
roleRef:
  kind: ClusterRole
  name: elasticsearch-logging
  apiGroup: ""
---
# Elasticsearch deployment itself
apiVersion: apps/v1
kind: StatefulSet #使用statefulset创建Pod
metadata:
  name: elasticsearch-logging #pod名称,使用statefulSet创建的Pod是有序号有顺序的
  namespace: elk  #命名空间
  labels:
    k8s-app: elasticsearch-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
    srv: srv-elasticsearch
spec:
  serviceName: elasticsearch-logging #与svc相关联，这可以确保使用以下DNS地址访问Statefulset中的每个pod (es-cluster-[0,1,2].elasticsearch.elk.svc.cluster.local)
  replicas: 1 #副本数量,单节点
  selector:
    matchLabels:
      k8s-app: elasticsearch-logging #和pod template配置的labels相匹配
  template:
    metadata:
      labels:
        k8s-app: elasticsearch-logging
        kubernetes.io/cluster-service: "true"
    spec:
      serviceAccountName: elasticsearch-logging
      containers:
      - image: docker.io/library/elasticsearch:7.9.3
        name: elasticsearch-logging
        resources:
          # need more cpu upon initialization, therefore burstable class
          limits:
            cpu: 1000m
            memory: 2Gi
          requests:
            cpu: 100m
            memory: 500Mi
        ports:
        - containerPort: 9200
          name: db
          protocol: TCP
        - containerPort: 9300
          name: transport
          protocol: TCP
        volumeMounts:
        - name: elasticsearch-logging
          mountPath: /usr/share/elasticsearch/data/   #挂载点
        env:
        - name: "NAMESPACE"
          valueFrom:
            fieldRef:
              fieldPath: metadata.namespace
        - name: "discovery.type"  #定义单节点类型
          value: "single-node"
        - name: ES_JAVA_OPTS #设置Java的内存参数，可以适当进行加大调整
          value: "-Xms512m -Xmx2g" 
      volumes:
      - name: elasticsearch-logging
        hostPath:
          path: /data/es/
      nodeSelector: #如果需要匹配落盘节点可以添加nodeSelect
        es: data
      tolerations:
      - effect: NoSchedule
        operator: Exists
      # Elasticsearch requires vm.max_map_count to be at least 262144.
      # If your OS already sets up this number to a higher value, feel free
      # to remove this init container.
      initContainers: #容器初始化前的操作
      - name: elasticsearch-logging-init
        image: alpine:3.6
        command: ["/sbin/sysctl", "-w", "vm.max_map_count=262144"] #添加mmap计数限制，太低可能造成内存不足的错误
        securityContext:  #仅应用到指定的容器上，并且不会影响Volume
          privileged: true #运行特权容器
      - name: increase-fd-ulimit
        image: busybox
        imagePullPolicy: IfNotPresent
        command: ["sh", "-c", "ulimit -n 65536"] #修改文件描述符最大数量
        securityContext:
          privileged: true
      - name: elasticsearch-volume-init #es数据落盘初始化，加上777权限
        image: alpine:3.6
        command:
          - chmod
          - -R
          - "777"
          - /usr/share/elasticsearch/data/
        volumeMounts:
        - name: elasticsearch-logging
          mountPath: /usr/share/elasticsearch/data/

 生成sts

kubectl apply -f  es-sts.yaml

 查看es是否启动

kubectl get pod -n elk

查看svc 

kubectl get svc -n elk

3.检查es集群

#登录ip+端口
192.168.112.156:32500

查看集群节点：
http://192.168.112.156:32500/_cat/nodes?v

查看集群健康状态：
http://192.168.112.156:32500/_cat/health?v

 4.创建kibana

vim kibana.yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: kibana
  namespace: elk
spec:
  selector:
    matchLabels:
      app: kibana
  replicas: 1
  template:
    metadata:
      labels:
        app: kibana
    spec:
      restartPolicy: Always
      containers:
        - name: kibana
          image: kibana:7.9.1
          imagePullPolicy: Always
          ports:
            - containerPort: 5601
          env:
            - name: ELASTICSEARCH_HOSTS
              value: http://es-cluster-svc:9200
            - name: I18N.LOCALE
              value: zh-CN    #汉化
          resources:
            requests:
              memory: 1024Mi
              cpu: 50m
            limits:
              memory: 1024Mi
              cpu: 1000m
---
apiVersion: v1
kind: Service
metadata:
  name: kibana
  namespace: elk
spec:
  type: NodePort
  ports:
    - name: kibana
      port: 5601
      targetPort: 5601
      nodePort: 32681
  selector:
    app: kibana

kubectl apply -f kibana.yaml

查看pod和svc

kubectl get pod,svc -n elk

5.访问kibana

192.168.112.156:32681