环境准备

我们使用的k8s和ceph环境见:
http://emb.ib911.com/leejia/2495558
http://emb.ib911.com/leejia/2499684

ECK简介

Elastic Cloud on Kubernetes,这是一款基于 Kubernetes Operator 模式的新型编排产品,用户可使用该产品在 Kubernetes 上配置、管理和运行 Elasticsearch 集群。ECK 的愿景是为 Kubernetes 上的 Elastic 产品和解决方案提供 SaaS 般的体验。

ECK使用 Kubernetes Operator模式构建而成,需要安装在Kubernetes集群内,ECK用于部署,且更专注于简化所有后期运行工作:

  • 管理和监测多个集群
  • 轻松升级至新版本
  • 扩大或缩小集群容量
  • 更改集群配置
  • 动态调整本地存储的规模
  • 备份

Kubernetes目前是容器编排领域的领头羊,而Elastic社区发布ECK,使Elasticsearch更容易的跑在云上,也是为云原生技术增砖添瓦,紧跟时代潮流。

部署ECK

部署ECK并查看日志是否正常:

# kubectl apply -f http://www.ib911.com/395/downloads/eck/1.1.2/all-in-one.yaml

# kubectl -n elastic-system logs -f statefulset.apps/elastic-operator

过几分钟查看elastic-operator是否运行正常,ECK中只有一个elastic-operator pod:

# kubectl get pods -n elastic-system
NAME                 READY   STATUS    RESTARTS   AGE
elastic-operator-0   1/1     Running   1          2m55s

使用ECK部署使用ceph持久化存储的elasticsearch集群

我们测试情况使用1台master节点和1台data节点来部署集群,生产环境建议使用3+台master节点。如下的manifest中,对实例的heap大小,容器的可使用内存,容器的虚拟机内存都进行了配置,可以根据集群需要做调整:

# vim es.yaml
apiVersion: elasticsearch.k8s.elastic.co/v1
kind: Elasticsearch
metadata:
  name: quickstart
spec:
  version: 7.7.1
  nodeSets:
  - name: master-nodes
    count: 1
    config:
      node.master: true
      node.data: false
    podTemplate:
      spec:
        initContainers:
        - name: sysctl
          securityContext:
            privileged: true
          command: ['sh', '-c', 'sysctl -w vm.max_map_count=262144']
        containers:
        - name: elasticsearch
          env:
          - name: ES_JAVA_OPTS
            value: -Xms1g -Xmx1g
          resources:
            requests:
              memory: 2Gi
            limits:
              memory: 2Gi
    volumeClaimTemplates:
    - metadata:
        name: elasticsearch-data
      spec:
        accessModes:
        - ReadWriteOnce
        resources:
          requests:
            storage: 5Gi
        storageClassName: rook-ceph-block
  - name: data-nodes
    count: 1
    config:
      node.master: false
      node.data: true
    podTemplate:
      spec:
        initContainers:
        - name: sysctl
          securityContext:
            privileged: true
          command: ['sh', '-c', 'sysctl -w vm.max_map_count=262144']
        containers:
        - name: elasticsearch
          env:
          - name: ES_JAVA_OPTS
            value: -Xms1g -Xmx1g
          resources:
            requests:
              memory: 2Gi
            limits:
              memory: 2Gi
    volumeClaimTemplates:
    - metadata:
        name: elasticsearch-data
      spec:
        accessModes:
        - ReadWriteOnce
        resources:
          requests:
            storage: 10Gi
        storageClassName: rook-ceph-block

# kubectl apply -f es.yaml

过段时间,澳门新赌场:查看elasticsearch集群的状态

# kubectl get pods
quickstart-es-data-nodes-0     1/1     Running   0          54s
quickstart-es-master-nodes-0   1/1     Running   0          54s

# kubectl get elasticsearch
NAME         HEALTH   NODES   VERSION   PHASE   AGE
quickstart   green    2       7.7.1     Ready   73s

查看pv的状态,我们可以看到申请的pv已经创建和绑定成功:

# kubectl get pv
pvc-512cc739-3654-41f4-8339-49a44a093ecf   10Gi       RWO            Retain           Bound      default/elasticsearch-data-quickstart-es-data-nodes-0     rook-ceph-block            9m5s
pvc-eff8e0fd-f669-448a-8b9f-05b2d7e06220   5Gi        RWO            Retain           Bound      default/elasticsearch-data-quickstart-es-master-nodes-0   rook-ceph-block            9m5s

默认集群开启了basic认证,用户名为elastic,密码可以通过secret获取。默认集群也开启了自签名证书http访问。我们可以通过service资源来访问elasticsearch:

# kubectl get services
NAME                         TYPE        CLUSTER-IP       EXTERNAL-IP   PORT(S)    AGE
quickstart-es-data-nodes     ClusterIP   None             <none>        <none>     4m10s
quickstart-es-http           ClusterIP   10.107.201.126   <none>        9200/TCP   4m11s
quickstart-es-master-nodes   ClusterIP   None             <none>        <none>     4m10s
quickstart-es-transport      ClusterIP   None             <none>        9300/TCP   4m11s

# kubectl get secret quickstart-es-elastic-user -o=jsonpath='{.data.elastic}' | base64 --decode; echo

# curl http://www.gfb.7667744.com:9200 -u 'elastic:J1fO9bu88j8pYK8rIu91a73o' -k
{
  "name" : "quickstart-es-data-nodes-0",
  "cluster_name" : "quickstart",
  "cluster_uuid" : "AQxFX8NiTNa40mOPapzNXQ",
  "version" : {
    "number" : "7.7.1",
    "build_flavor" : "default",
    "build_type" : "docker",
    "build_hash" : "ad56dce891c901a492bb1ee393f12dfff473a423",
    "build_date" : "2020-05-28T16:30:01.040088Z",
    "build_snapshot" : false,
    "lucene_version" : "8.5.1",
    "minimum_wire_compatibility_version" : "6.8.0",
    "minimum_index_compatibility_version" : "6.0.0-beta1"
  },
  "tagline" : "You Know, for Search"
}

不停服,扩容一台data节点:修改es.yaml中data-nodes中count的value为2,然后apply下es.yaml即可。

# kubectl apply -f es.yaml
# kubectl get pods
quickstart-es-data-nodes-0     1/1     Running   0          24m
quickstart-es-data-nodes-1     1/1     Running   0          8m22s
quickstart-es-master-nodes-0   1/1     Running   0          24m

# kubectl get elasticsearch
NAME         HEALTH   NODES   VERSION   PHASE   AGE
quickstart   green    3       7.7.1     Ready   25m

不停服,缩容一台data节点,会自动进行数据同步:修改es.yaml中data-nodes中count的value为1,然后apply下es.yaml即可。

对接kibana

由于默认kibana也开启了自签名证书的http访问,我们可以选择关闭,我们来使用ECK部署kibana:

# vim kibana.yaml
apiVersion: kibana.k8s.elastic.co/v1
kind: Kibana
metadata:
  name: quickstart
spec:
  version: 7.7.1
  count: 1
  elasticsearchRef:
    name: quickstart
  http:
    tls:
      selfSignedCertificate:
        disabled: true
# kubectl apply -f kibana.yaml

# kubectl get pods
NAME                             READY   STATUS    RESTARTS   AGE
quickstart-es-data-nodes-0       1/1     Running   0          31m
quickstart-es-data-nodes-1       1/1     Running   1          15m
quickstart-es-master-nodes-0     1/1     Running   0          31m
quickstart-kb-6558457759-2rd7l   1/1     Running   1          4m3s

# kubectl get kibana
NAME         HEALTH   NODES   VERSION   AGE
quickstart   green    1       7.7.1     4m27s

为kibana在ingress中添加一个四层代理,提供对外访问服务:

# vim tsp-kibana.yaml
apiVersion: k8s.nginx.org/v1alpha1
kind: GlobalConfiguration
metadata:
  name: nginx-configuration
  namespace: nginx-ingress
spec:
  listeners:
  - name: kibana-tcp
    port: 5601
    protocol: TCP

---

apiVersion: k8s.nginx.org/v1alpha1
kind: TransportServer
metadata:
  name: kibana-tcp
spec:
  listener:
    name: kibana-tcp
    protocol: TCP
  upstreams:
  - name: kibana-app
    service: quickstart-kb-http
    port: 5601
  action:
    pass: kibana-app

# kubectl apply -f tsp-kibana.yaml

默认kibana访问elasticsearch的用户名为elastic,密码获取方式如下

# kubectl get secret quickstart-es-elastic-user -o=jsonpath='{.data.elastic}' | base64 --decode; echo

通过浏览器访问kibana:

删除ECK相关资源

删除elasticsearch和kibana以及ECK

# kubectl get namespaces --no-headers -o custom-columns=:metadata.name \
  | xargs -n1 kubectl delete elastic --all -n

# kubectl delete -f http://www.ib911.com/248/downloads/eck/1.1.2/all-in-one.yaml

对接cerebro

先安装Kubernetes应用的包管理工具helm。Helm是用来封装 Kubernetes原生应用程序的YAML文件,可以在你部署应用的时候自定义应用程序的一些metadata,helm依赖chart实现了应用程序的在k8s上的分发。helm和chart主要实现了如下功能:

  • 应用程序封装
  • 版本管理
  • 依赖检查
  • 应用程序分发
    # wget http://emb.ib911.com/helm-v3.2.3-linux-amd64.tar.gz
    # tar -zxvf helm-v3.0.0-linux-amd64.tar.gz
    # mv linux-amd64/helm /usr/local/bin/helm
    # helm repo add stable http://www.ncn.ib765.com

    通过helm安装cerebro:

    # helm install stable/cerebro --version 1.1.4  --generate-name

    查看cerebro的状态:

    # kubectl get pods|grep cerebro
    cerebro-1591777586-7fd87f7d48-hmlp7   1/1     Running   0          11m

    由于默认ECK部署的elasticsearch开启了自签名证书的http服务,故可以在cerebro配置忽略http证书认证(也可以在cerebro中添加自签名证书的ca证书来识别自签名证书),并重启cerebro:
    1,导出cerebro的configmap:

    # kubectl get configmap cerebro-1591777586 -o yaml > cerebro.yaml

    2,替换configmap中cerebro的hosts相关配置为如下(其中quickstart-es-http为elasticsarch的service资源名字):

    play.ws.ssl.loose.acceptAnyCertificate = true
    hosts = [
      {
        host = "http://www.xif.ib877.com:9200"
        name = "k8s elasticsearch"
      }
    ]

    3,应用cerebro的configmap并重启cerebro pod:

# kubectl apply -f cerebro.yaml

# kubectl get pods|grep cerebro
cerebro-1591777586-7fd87f7d48-hmlp7   1/1     Running   0          11m
# kubectl get pod cerebro-1591777586-7fd87f7d48-hmlp7 -o yaml | kubectl replace --force -f -

先确认cerebro的service资源,然后配置ingress为cerebro添加7层代理:

# kubectl get services
NAME                         TYPE        CLUSTER-IP       EXTERNAL-IP   PORT(S)    AGE
cerebro-1591777586           ClusterIP   10.111.107.171   <none>        80/TCP     19m

# vim cerebro-ingress.yaml
apiVersion: networking.k8s.io/v1beta1
kind: Ingress
metadata:
  name: cerebro-ingress
spec:
  rules:
  - host: cerebro.myk8s.com
    http:
      paths:
      - path: /
        backend:
          serviceName: cerebro-1591777586
          servicePort: 80

# kubectl apply -f cerebro-ingress.yaml

在本地pc的/etc/hosts文件添加host绑定"172.18.2.175 cerebro.myk8s.com",然后通过览器访问:

删除cerebro

# helm list
NAME                NAMESPACE   REVISION    UPDATED                                 STATUS      CHART           APP VERSION
cerebro-1591777586  default     1           2020-06-10 16:26:30.419723417 +0800 CST deployed    cerebro-1.1.4   0.8.4

# heml delete name cerebro-1591777586

参考

http://www.ib911.com/617/guide/en/cloud-on-k8s/current/k8s-deploy-kibana.html
http://www.isx.11w55.com/guide/en/cloud-on-k8s/current/k8s-kibana-http-configuration.html
http://emb.ib911.com/guide/en/cloud-on-k8s/current/k8s-quickstart.html
http://www.hqo.ss348.com/charts/stable/cerebro
http://emb.ib911.com/cn/blog/introducing-elastic-cloud-on-kubernetes-the-elasticsearch-operator-and-beyond
http://www.cao803.com/530/docs/intro/install/