k8s(1.28.2)下部署ES集群。

1. 安装helm

# 下载
wget https://get.helm.sh/helm-v3.13.0-linux-amd64.tar.gz
# 解压
tar xvf helm-v3.13.0-linux-amd64.tar.gz
# 移动文件目录
sudo mv linux-amd64/helm /usr/local/bin/helm
# 查看版本
helm version

2. 创建动态存储storageclass(全局可用)

2.1 制作镜像，并上传到镜像仓库

#拉取可用的 nfs-subdir-external-provisioner:v4.0.2 镜像
docker pull dyrnq/nfs-subdir-external-provisioner:v4.0.2

# tag 192.168.255.132是自己搭建的镜像库地址
docker tag dyrnq/nfs-subdir-external-provisioner:v4.0.2 192.168.255.132/library/nfs-subdir-external-provisioner:v4.0.2
# push
docker push 192.168.255.132/library/nfs-subdir-external-provisioner:v4.0.2

2.2 执行，先确定是否有nfs服务

# 先手动下载 nfs-subdir-external-provisioner-4.0.2.tgz
https://github.com/kubernetes-sigs/nfs-subdir-external-provisioner/releases/download/nfs-subdir-external-provisioner-4.0.2/nfs-subdir-external-provisioner-4.0.2.tgz
# 运行 helm install
# nfs-provisioner-es 名称 可修改
# namespace es-ns 命名空间
# nfs.server nfs服务地址
# nfs.path nfs共享路径
# storageClass.name 创建的storageClass名称
# image.repository、image.tag为镜像仓库地址和镜像版本
helm install nfs-provisioner-es nfs-subdir-external-provisioner-4.0.2.tgz \
	  --namespace es-ns \
	  --set nfs.server=192.168.255.142 \
	  --set nfs.path=/data/es \
	  --set storageClass.name=nfs-client-es \
	  --set image.repository=192.168.255.132/library/nfs-subdir-external-provisioner \
	  --set image.tag=v4.0.2

2.3 测试

#执行命令
# helm list -n es-ns 可查看到如下信息
NAME              	NAMESPACE	REVISION	UPDATED                                	STATUS  	CHART                                 	APP VERSION
nfs-provisioner-es	es-ns    	1       	2023-12-12 19:32:23.296102681 +0800 CST	deployed	nfs-subdir-external-provisioner-4.0.2 	4.0.0     

# kubectl get storageclasses.storage.k8s.io，有如下显示则表示storageclass创建好了。
NAME                  PROVISIONER                                                              RECLAIMPOLICY   VOLUMEBINDINGMODE   ALLOWVOLUMEEXPANSION   AGE
nfs-client-es         cluster.local/nfs-provisioner-es-nfs-subdir-external-provisioner         Delete          Immediate           true                   3m2s

3.部署ES

3.1 制作带分词器的ES镜像

wget https://github.com/medcl/elasticsearch-analysis-ik/releases/download/v7.12.1/elasticsearch-analysis-ik-7.12.1.zip
unzip xxx.zip ./ik/

# Dockerfile
# 使用官方Elasticsearch基础镜像
FROM elasticsearch:7.12.1
# 将IK分词插件目录复制到容器中
COPY ik /usr/share/elasticsearch/plugins/ik

# 制作镜像并上传到仓库
docker build -f Dockerfile -t es-with-ik:v7.12.1 .
docker tag es-with-ik:v7.12.1 192.168.255.132/library/es-with-ik:v7.12.1
docker push  192.168.255.132/library/es-with-ik:v7.12.1

3.2 编写yaml文件，然后执行

kubectl apply -f es-cluster.yaml
kubectl apply -f es-service.yaml
kubectl apply -f es-ingress.yaml
kubectl apply -f kibana.yaml

3.2.1 es-cluster.yaml文件

volumeClaimTemplates.spec.storageClassName 为创建的storageClass名称

# es-cluster.yaml
apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: es-cluster
  namespace: es-ns
spec:
  serviceName: es-cluster-svc
  replicas: 3
  selector:
    matchLabels:
      app: es-net-data
  template:
    metadata:
      labels: 
        app: es-net-data
    spec:
      # 初始化容器
      initContainers:
        - name: increase-vm-max-map
          image: busybox:1.32
          command: ["sysctl", "-w", "vm.max_map_count=262144"]
          securityContext:
            privileged: true
        - name: increase-fd-ulimit
          image: busybox:1.32
          command: ["sh", "-c", "ulimit -n 65536"]
          securityContext:
            privileged: true
      # 初始化容器结束后，才能继续创建下面的容器
      containers:
        - name: es-container
          image: 192.168.255.132/library/es-with-ik:v7.12.1
          imagePullPolicy: Always
          ports:
            # 容器内端口
            - name: rest
              containerPort: 9200
              protocol: TCP
          # 限制CPU数量
          resources:
            limits:
              cpu: 1000m
            requests:
              cpu: 100m
          # 设置挂载目录
          volumeMounts:
            - name: es-data
              mountPath: /usr/share/elasticsearch/data
          env:
            - name: cluster.name
              value: k8s-es
            - name: node.name
              valueFrom:
                fieldRef:
                  fieldPath: metadata.name
            - name: cluster.initial_master_nodes
              value: "es-cluster-0,es-cluster-1,es-cluster-2"
            - name: discovery.zen.minimum_master_nodes
              value: "2"
            - name: discovery.seed_hosts
              value: "es-cluster-svc"
            # 配置内存
            - name: ES_JAVA_OPTS
              value: "-Xms500m -Xmx500m"
            - name: network.host
              value: "0.0.0.0"
              
  volumeClaimTemplates:
    - metadata:
        # 对应容器中volumeMounts.name
        name: es-data
        labels:
          app: es-volume
      spec:
        # 存储卷可以被单个节点读写
        accessModes: [ "ReadWriteOnce" ]
        # 对应es-nfs-storage-class.yaml中的metadata.name
        storageClassName: nfs-client-es
        resources:
          requests:
            storage: 10Gi

3.2.2 es-service.yaml文件

# es-service.yaml
apiVersion: v1
kind: Service
metadata:
  name: es-cluster-svc
  namespace: es-ns
spec:
  selector:
    app: es-net-data
  clusterIP: None 
  type: ClusterIP
  ports:
    - name: rest
      protocol: TCP
      port: 9200 
      targetPort: 9200

3.2.3 es-ingress.yaml文件

# es-ingress.yaml
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: es-cluster-ingress
  namespace: es-ns
spec:
  ingressClassName: nginx
  rules:
    - host: es.demo.com
      http:
        paths:
          - path: /
            pathType: Prefix
            backend:
              service:
                name: es-cluster-svc
                port:
                  number: 9200 
    - host: kibana.demo.com
      http:
        paths:
          - path: /
            pathType: Prefix
            backend:
              service:
                name: kibana-svc
                port:
                  number: 5601

3.2.4 kibana.yaml文件

# kibana.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: kibana
  namespace: es-ns
spec:
  selector:
    matchLabels:
      app: kibana
  replicas: 1
  template:
    metadata:
      labels:
        app: kibana
    spec:
      restartPolicy: Always
      containers:
        - name: kibana
          image: kibana:7.12.1
          imagePullPolicy: Always
          ports:
            - containerPort: 5601
          env:
            - name: ELASTICSEARCH_HOSTS
              value: http://es-cluster-svc:9200
            - name: I18N.LOCALE
              value: zh-CN
          resources:
            requests:
              memory: 1024Mi
              cpu: 50m
            limits:
              memory: 1024Mi
              cpu: 1000m
---
apiVersion: v1
kind: Service
metadata:
  name: kibana-svc
  namespace: es-ns
spec:
  selector:
    app: kibana
  clusterIP: None 
  type: ClusterIP
  ports:
    - name: rest
      protocol: TCP
      port: 5601  
      targetPort: 5601

3.3 测试

kubectl get ingress -A 

NAMESPACE   NAME                 CLASS   HOSTS                                      ADDRESS           PORTS     AGE
es-ns       es-cluster-ingress   nginx   es.demo.com,kibana.demo.com                192.168.255.143   80, 443   69d
# 将Windows下hosts文件做映射
192.168.255.143 es.demo.com kibana.demo.com
#便可直接在浏览器中访问。
http://kibana.demo.com/
http://es.demo.com/

查看节点情况
http://es.demo.com/_cat/nodes?v

在k8s集群中，可使用内部域名的方式访问ES。
{service}.{namespace}.svc.cluster.local:port
对应当前部署的ES集群，访问地址就是 es-cluster-svc.es-ns.svc.cluster.local:9200

# 浏览器中访问
https://es.demo.com/_cluster/health?pretty
# 在k8s集群中任意pod里执行
curl -X GET "http://es-cluster-svc.es-ns.svc.cluster.local:9200/_cluster/health?pretty"