Kubernetes中的Elasticsearch高可用设置 [英] Elasticsearch Highly Available Setup in Kubernetes

问题描述

我们想在Kubernetes中设置Elasticsearch Highly Available Setup.我们想部署以下对象，并希望对其进行独立缩放

We would like to setup Elasticsearch Highly Available Setup in Kubernetes. we would like to deploy the below objects and would like to scale them independently

1. 主豆荚
2. 数据荚
3. 客户吊舱

如果实施了这种设置，请分享您的建议.最好使用开源工具

please share your suggestions if you have implemented this kind of setup. Preferably using open source tools

推荐答案

请参阅以下有关建议体系结构的要点:

See below some points for a proposed architecture:

1. Elasticsearch主节点不需要持久性存储，因此请使用Deployment来管理这些节点.使用服务在主服务器之间进行负载平衡.

使用ConfigMap来管理其设置.像这样:

Use a ConfigMap to manage their settings. Something like this:

apiVersion: v1
  kind: Service
  metadata:
    name: elasticsearch-discovery
    labels:
      component: elasticsearch
      role: master
      version: v6.5.0 // or whatever version you require
  spec:
    selector:
      component: elasticsearch
      role: master
      version: v6.5.0
    ports:
      - name: transport
        port: 9300 // no need to expose port 9200, as master nodes don't need it
        protocol: TCP
    clusterIP: None
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: elasticsearch-master-configmap
data:
  elasticsearch.yml: |
    # these should get you going
    # if you want more fine-grained control, feel free to add other ES settings
    cluster.name: "${CLUSTER_NAME}"
    node.name: "${NODE_NAME}"

    network.host: 0.0.0.0

    # (no_master_eligible_nodes / 2) + 1
    discovery.zen.minimum_master_nodes: 2
    discovery.zen.ping.unicast.hosts: ${DISCOVERY_SERVICE}

    node.master: true
    node.data: false
    node.ingest: false
---
apiVersion: apps/v1beta1
kind: Deployment
metadata:
  name: elasticsearch-master
  labels:
    component: elasticsearch
    role: master
    version: v6.5.0
spec:
  replicas: 3 // 3 is the recommended minimum
  template:
    metadata:
      labels:
        component: elasticsearch
        role: master
        version: v6.5.0
    spec:
      affinity:
        // you can also add node affinity in case you have a specific node pool
        podAntiAffinity:
          // make sure 2 ES processes don't end up on the same machine
          requiredDuringSchedulingIgnoredDuringExecution:
              - labelSelector:
                matchExpressions:
                  - key: component
                    operator: In
                    values:
                      - elasticsearch
                  - key: role
                    operator: In
                    values:
                      - master
                topologyKey: kubernetes.io/hostname
      initContainers:
        # just basic ES environment configuration
        - name: init-sysctl
          image: busybox:1.27.2
          command:
            - sysctl
            - -w
            - vm.max_map_count=262144
          securityContext:
            privileged: true
      containers:
        - name: elasticsearch-master
          image: // your preferred image
          imagePullPolicy: Always
          env:
            - name: NODE_NAME
              valueFrom:
                fieldRef:
                  fieldPath: metadata.name
            - name: CLUSTER_NAME
              value: elasticsearch-cluster
            - name: DISCOVERY_SERVICE
              value: elasticsearch-discovery
            - name: ES_JAVA_OPTS
              value: -Xms256m -Xmx256m // or more, if you want
          ports:
            - name: tcp-transport
              containerPort: 9300
          volumeMounts:
            - name: configmap
              mountPath: /etc/elasticsearch/elasticsearch.yml
              subPath: elasticsearch.yml
            - name: storage
              mountPath: /usr/share/elasticsearch/data
      volumes:
        - name: configmap
          configMap:
            name: elasticsearch-master-configmap
        - emptyDir:
            medium: ""
          name: storage

也可以以非常相似的方式部署客户端节点，因此我将避免为此添加代码.

Client nodes can also be deployed in a very similar fashion, so I will avoid adding code for that.

1. 数据节点更加特殊:您需要配置持久性存储，因此必须使用StatefulSets.使用PersistentVolumeClaims为这些Pod创建磁盘.我会做这样的事情:

apiVersion: v1
kind: Service
metadata:
  name: elasticsearch
  labels:
    component: elasticsearch
    role: data
    version: v6.5.0
spec:
  ports:
    - name: http
      port: 9200 # in this example, data nodes are being used as client nodes
    - port: 9300
      name: transport
  selector:
    component: elasticsearch
    role: data
    version: v6.5.0
  type: ClusterIP
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: elasticsearch-data-configmap
data:
  elasticsearch.yml: |
  cluster.name: "${CLUSTER_NAME}"
  node.name: "${NODE_NAME}"

  network.host: 0.0.0.0

  # (no_master_eligible_nodes / 2) + 1
  discovery.zen.minimum_master_nodes: 2
  discovery.zen.ping.unicast.hosts: ${DISCOVERY_SERVICE}

  node.master: false
  node.data: true
  node.ingest: false
---
apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: elasticsearch-data
  labels:
    component: elasticsearch
    role: data
    version: v6.5.0
spec:
  serviceName: elasticsearch
  replicas: 1 # choose the appropriate number
  selector:
    matchLabels:
      component: elasticsearch
      role: data
      version: v6.5.0
  template:
    metadata:
      labels:
        component: elasticsearch
        role: data
        version: v6.5.0
    spec:
      affinity:
        # again, I recommend using nodeAffinity
        podAntiAffinity:
          requiredDuringSchedulingIgnoredDuringExecution:
            - labelSelector:
                matchExpressions:
                  - key: component
                    operator: In
                    values:
                      - elasticsearch
                  - key: role
                    operator: In
                    values:
                      - data
              topologyKey: kubernetes.io/hostname
      terminationGracePeriodSeconds: 180
      initContainers:
        - name: init-sysctl
          image: busybox:1.27.2
          command:
            - sysctl
            - -w
            - vm.max_map_count=262144
          securityContext:
           privileged: true
      containers:
        - name: elasticsearch-production-container
          image: .search the same image that you use for the master node
          imagePullPolicy: Always
          env:
            - name: NODE_NAME
              valueFrom:
                fieldRef:
                  fieldPath: metadata.name
            - name: CLUSTER_NAME
              value: elasticsearch-cluster
            - name: DISCOVERY_SERVICE
              value: elasticsearch-discovery
            - name: ES_JAVA_OPTS
              value: -Xms31g -Xmx31g # do not exceed 32 GB!!!
          ports:
            - name: http
              containerPort: 9200
            - name: tcp-transport
              containerPort: 9300
          volumeMounts:
            - name: configmap
              mountPath: /etc/elasticsearch/elasticsearch.yml
              subPath: elasticsearch.yml
            - name: elasticsearch-node-pvc
              mountPath: /usr/share/elasticsearch/data
          readinessProbe:
            httpGet:
              path: /_cluster/health?local=true
              port: 9200
            initialDelaySeconds: 15
          livenessProbe:
            exec:
              command:
                - /usr/bin/pgrep
                - -x
                - "java"
            initialDelaySeconds: 15
          resources:
            requests:
              # adjust these as per your needs
              memory: "32Gi"
              cpu: "11"
      volumes:
        - name: configmap
          configMap:
            name: elasticsearch-data-configmap
  volumeClaimTemplates:
    - metadata:
        name: elasticsearch-node-pvc
      spec:
        accessModes: [ "ReadWriteOnce" ]
        storageClassName: # this is dependent on your K8s environment
        resources:
          requests:
            storage: 350Gi # choose the desired storage size for each ES data node

希望这会有所帮助！

这篇关于Kubernetes中的Elasticsearch高可用设置的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！