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Kubernetes中高度可访问且可扩展的Elasticsearch

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在上一篇文章中，我们缩放了MongoDB副本集并引入了StatefulSet。 现在，我们将对Elasticsearch高可用性群集（与其他主节点，数据节点和客户端节点）进行编排，并使用ES-HQ和Kibana。


您将需要：


  1. 对Elasticsearch，其节点类型及其角色有基本了解。
  2. 运行中的Kubernetes集群具有至少三个节点（至少四个核心，4 GB）。
  3. 与Kibana合作的能力。

部署架构


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  • Elasticsearch 数据节点作为具有无头服务的StatefulSet部署，因此我们具有稳定的网络标识符 。
  • Elasticsearch主节点被部署为具有无头服务的ReplicaSet 。 这是用于自动发现 。
  • Elasticsearch 客户端节点上的Pod被部署为具有内部服务的ReplicaSet ，以便您可以向数据节点发送读取/写入请求。
  • Kibana和ElasticHQ Pod作为ReplicaSet部署，其服务在Kubernetes集群外部可用，但位于子网内部 （它们不必向外打开）。
  • HPA（水平Pod自动缩放器）已部署到客户端节点 ，并负责高负载时的水平自动缩放。
    “记住为环境配置：
    1. ES_JAVA_OPTS变量。
    2. CLUSTER_NAME变量。
    3. NUMBER_OF_MASTERS变量用于主服务器的部署，以避免出现裂脑情况。 如果我们有3位硕士，请指定2位。
    4. 如果工作节点掉落，则类似炉床的反亲和性规则可确保高可靠性。
      ”
      让我们在GKE集群中部署这些服务。

kind: Namespace metadata: name: elasticsearch --- apiVersion: apps/v1beta1 kind: Deployment metadata: name: es-master namespace: elasticsearch labels: component: elasticsearch role: master spec: replicas: 3 template: metadata: labels: component: elasticsearch role: master spec: affinity: podAntiAffinity: preferredDuringSchedulingIgnoredDuringExecution: - weight: 100 podAffinityTerm: labelSelector: matchExpressions: - key: role operator: In values: - master topologyKey: kubernetes.io/hostname initContainers: - name: init-sysctl image: busybox:1.27.2 command: - sysctl - -w - vm.max_map_count=262144 securityContext: privileged: true containers: - name: es-master image: quay.io/pires/docker-elasticsearch-kubernetes:6.2.4 env: - name: NAMESPACE valueFrom: fieldRef: fieldPath: metadata.namespace - name: NODE_NAME valueFrom: fieldRef: fieldPath: metadata.name - name: CLUSTER_NAME value: my-es - name: NUMBER_OF_MASTERS value: "2" - name: NODE_MASTER value: "true" - name: NODE_INGEST value: "false" - name: NODE_DATA value: "false" - name: HTTP_ENABLE value: "false" - name: ES_JAVA_OPTS value: -Xms256m -Xmx256m - name: PROCESSORS valueFrom: resourceFieldRef: resource: limits.cpu resources: limits: cpu: 2 ports: - containerPort: 9300 name: transport volumeMounts: - name: storage mountPath: /data volumes: - emptyDir: medium: "" name: "storage" --- apiVersion: v1 kind: Service metadata: name: elasticsearch-discovery namespace: elasticsearch labels: component: elasticsearch role: master spec: selector: component: elasticsearch role: master ports: - name: transport port: 9300 protocol: TCP clusterIP: None view rawes-master.yml hosted with love by GitHub

（针对主节点的部署和无头服务）


 root$ kubectl -n elasticsearch get all NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE deploy/es-master 3 3 3 3 32s NAME DESIRED CURRENT READY AGE rs/es-master-594b58b86c 3 3 3 31s NAME READY STATUS RESTARTS AGE po/es-master-594b58b86c-9jkj2 1/1 Running 0 31s po/es-master-594b58b86c-bj7g7 1/1 Running 0 31s po/es-master-594b58b86c-lfpps 1/1 Running 0 31s NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE svc/elasticsearch-discovery ClusterIP None <none> 9300/TCP 31s

研究主节点上的炉床日志，看看现在如何在其中选择主节点，以及以后在添加新的数据节点和客户端节点时如何选择主节点，这很有趣。


 root$ kubectl -n elasticsearch logs -f po/es-master-594b58b86c-9jkj2 | grep ClusterApplierService [2018-10-21T07:41:54,958][INFO ][oecsClusterApplierService] [es-master-594b58b86c-9jkj2] detected_master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300}, added {{es-master-594b58b86c-lfpps}{wZQmXr5fSfWisCpOHBhaMg}{50jGPeKLSpO9RU_HhnVJCA}{10.9.124.81}{10.9.124.81:9300},{es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300},}, reason: apply cluster state (from master [master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300} committed version [3]])

在这里，您可以看到在es-master下，master选择了名称为es-master-594b58b86c-bj7g7的其他两个容器 。


无头Elasticsearch-discovery服务默认情况下作为环境变量安装在Docker映像中，并用于节点中的检测。 如果需要，可以替换此设置。


同样，我们部署数据节点和客户端节点 。 请参阅下面的配置。


部署数据节点：


 kind: Namespace metadata: name: elasticsearch --- apiVersion: storage.k8s.io/v1beta1 kind: StorageClass metadata: name: fast provisioner: kubernetes.io/gce-pd parameters: type: pd-ssd fsType: xfs allowVolumeExpansion: true --- apiVersion: apps/v1beta1 kind: StatefulSet metadata: name: es-data namespace: elasticsearch labels: component: elasticsearch role: data spec: serviceName: elasticsearch-data replicas: 3 template: metadata: labels: component: elasticsearch role: data spec: affinity: podAntiAffinity: preferredDuringSchedulingIgnoredDuringExecution: - weight: 100 podAffinityTerm: labelSelector: matchExpressions: - key: role operator: In values: - data topologyKey: kubernetes.io/hostname initContainers: - name: init-sysctl image: busybox:1.27.2 command: - sysctl - -w - vm.max_map_count=262144 securityContext: privileged: true containers: - name: es-data image: quay.io/pires/docker-elasticsearch-kubernetes:6.2.4 env: - name: NAMESPACE valueFrom: fieldRef: fieldPath: metadata.namespace - name: NODE_NAME valueFrom: fieldRef: fieldPath: metadata.name - name: CLUSTER_NAME value: my-es - name: NODE_MASTER value: "false" - name: NODE_INGEST value: "false" - name: HTTP_ENABLE value: "false" - name: ES_JAVA_OPTS value: -Xms256m -Xmx256m - name: PROCESSORS valueFrom: resourceFieldRef: resource: limits.cpu resources: limits: cpu: 2 ports: - containerPort: 9300 name: transport volumeMounts: - name: storage mountPath: /data volumeClaimTemplates: - metadata: name: storage annotations: volume.beta.kubernetes.io/storage-class: "fast" spec: accessModes: [ "ReadWriteOnce" ] storageClassName: fast resources: requests: storage: 10Gi --- apiVersion: v1 kind: Service metadata: name: elasticsearch-data namespace: elasticsearch labels: component: elasticsearch role: data spec: ports: - port: 9300 name: transport clusterIP: None selector: component: elasticsearch role: data view rawes-data.yml hosted with love by GitHub

（针对数据节点的StatefulSet和无头服务）


数据节点上的无头服务向节点发出稳定的网络标识符 ，并帮助在节点之间传输数据 。


在将永久卷附加到炉膛之前， 格式化永久卷很重要。 创建存储类时只需指定卷的类型。 您还可以设置允许自动卷扩展的参数。 在此处阅读详细信息。


 parameters: type: pd-ssd fsType: xfs allowVolumeExpansion: true ...

部署客户端节点：


 kind: Namespace metadata: name: elasticsearch --- apiVersion: apps/v1beta1 kind: Deployment metadata: name: es-client namespace: elasticsearch labels: component: elasticsearch role: client spec: replicas: 2 template: metadata: labels: component: elasticsearch role: client spec: affinity: podAntiAffinity: preferredDuringSchedulingIgnoredDuringExecution: - weight: 100 podAffinityTerm: labelSelector: matchExpressions: - key: role operator: In values: - client topologyKey: kubernetes.io/hostname initContainers: - name: init-sysctl image: busybox:1.27.2 command: - sysctl - -w - vm.max_map_count=262144 securityContext: privileged: true containers: - name: es-client image: quay.io/pires/docker-elasticsearch-kubernetes:6.2.4 env: - name: NAMESPACE valueFrom: fieldRef: fieldPath: metadata.namespace - name: NODE_NAME valueFrom: fieldRef: fieldPath: metadata.name - name: CLUSTER_NAME value: my-es - name: NODE_MASTER value: "false" - name: NODE_DATA value: "false" - name: HTTP_ENABLE value: "true" - name: ES_JAVA_OPTS value: -Xms256m -Xmx256m - name: NETWORK_HOST value: _site_,_lo_ - name: PROCESSORS valueFrom: resourceFieldRef: resource: limits.cpu resources: limits: cpu: 1 ports: - containerPort: 9200 name: http - containerPort: 9300 name: transport volumeMounts: - name: storage mountPath: /data volumes: - emptyDir: medium: "" name: storage --- apiVersion: v1 kind: Service metadata: name: elasticsearch namespace: elasticsearch annotations: cloud.google.com/load-balancer-type: Internal labels: component: elasticsearch role: client spec: selector: component: elasticsearch role: client ports: - name: http port: 9200 type: LoadBalancer view rawes-client.yml hosted with love by GitHub

（为客户端节点部署和外部服务）


此处部署的服务提供对Kubernetes群集外部的ES群集的访问，但仍在子网内部。 注释cloud.google.com/load-balancer-type：内部对此负责。


但是，如果将访问ES集群以进行读写的应用程序部署在集群内部，则可以在http：//elasticsearch.elasticsearch：9200获得对ElasticSearch服务的访问。


当您展开数据节点和客户端节点时，它们将自动添加到群集中。 （在日志下查找主服务器）


 root$ kubectl -n elasticsearch get pods -l role=data NAME READY STATUS RESTARTS AGE es-data-0 1/1 Running 0 48s es-data-1 1/1 Running 0 28s -------------------------------------------------------------------- root$ kubectl apply -f es-client.yml root$ kubectl -n elasticsearch get pods -l role=client NAME READY STATUS RESTARTS AGE es-client-69b84b46d8-kr7j4 1/1 Running 0 47s es-client-69b84b46d8-v5pj2 1/1 Running 0 47s -------------------------------------------------------------------- root$ kubectl -n elasticsearch get all NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE deploy/es-client 2 2 2 2 1m deploy/es-master 3 3 3 3 9m NAME DESIRED CURRENT READY AGE rs/es-client-69b84b46d8 2 2 2 1m rs/es-master-594b58b86c 3 3 3 9m NAME DESIRED CURRENT AGE statefulsets/es-data 2 2 3m NAME READY STATUS RESTARTS AGE po/es-client-69b84b46d8-kr7j4 1/1 Running 0 1m po/es-client-69b84b46d8-v5pj2 1/1 Running 0 1m po/es-data-0 1/1 Running 0 3m po/es-data-1 1/1 Running 0 3m po/es-master-594b58b86c-9jkj2 1/1 Running 0 9m po/es-master-594b58b86c-bj7g7 1/1 Running 0 9m po/es-master-594b58b86c-lfpps 1/1 Running 0 9m NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE svc/elasticsearch LoadBalancer 10.9.121.160 10.9.120.8 9200:32310/TCP 1m svc/elasticsearch-data ClusterIP None <none> 9300/TCP 3m svc/elasticsearch-discovery ClusterIP None <none> 9300/TCP 9m -------------------------------------------------------------------- #Check logs of es-master leader pod root$ kubectl -n elasticsearch logs po/es-master-594b58b86c-bj7g7 | grep ClusterApplierService [2018-10-21T07:41:53,731][INFO ][oecsClusterApplierService] [es-master-594b58b86c-bj7g7] new_master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300}, added {{es-master-594b58b86c-lfpps}{wZQmXr5fSfWisCpOHBhaMg}{50jGPeKLSpO9RU_HhnVJCA}{10.9.124.81}{10.9.124.81:9300},}, reason: apply cluster state (from master [master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300} committed version [1] source [zen-disco-elected-as-master ([1] nodes joined)[{es-master-594b58b86c-lfpps}{wZQmXr5fSfWisCpOHBhaMg}{50jGPeKLSpO9RU_HhnVJCA}{10.9.124.81}{10.9.124.81:9300}]]]) [2018-10-21T07:41:55,162][INFO ][oecsClusterApplierService] [es-master-594b58b86c-bj7g7] added {{es-master-594b58b86c-9jkj2}{x9Prp1VbTq6_kALQVNwIWg}{7NHUSVpuS0mFDTXzAeKRcg}{10.9.125.81}{10.9.125.81:9300},}, reason: apply cluster state (from master [master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300} committed version [3] source [zen-disco-node-join[{es-master-594b58b86c-9jkj2}{x9Prp1VbTq6_kALQVNwIWg}{7NHUSVpuS0mFDTXzAeKRcg}{10.9.125.81}{10.9.125.81:9300}]]]) [2018-10-21T07:48:02,485][INFO ][oecsClusterApplierService] [es-master-594b58b86c-bj7g7] added {{es-data-0}{SAOhUiLiRkazskZ_TC6EBQ}{qirmfVJBTjSBQtHZnz-QZw}{10.9.126.88}{10.9.126.88:9300},}, reason: apply cluster state (from master [master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300} committed version [4] source [zen-disco-node-join[{es-data-0}{SAOhUiLiRkazskZ_TC6EBQ}{qirmfVJBTjSBQtHZnz-QZw}{10.9.126.88}{10.9.126.88:9300}]]]) [2018-10-21T07:48:21,984][INFO ][oecsClusterApplierService] [es-master-594b58b86c-bj7g7] added {{es-data-1}{fiv5Wh29TRWGPumm5ypJfA}{EXqKGSzIQquRyWRzxIOWhQ}{10.9.125.82}{10.9.125.82:9300},}, reason: apply cluster state (from master [master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300} committed version [5] source [zen-disco-node-join[{es-data-1}{fiv5Wh29TRWGPumm5ypJfA}{EXqKGSzIQquRyWRzxIOWhQ}{10.9.125.82}{10.9.125.82:9300}]]]) [2018-10-21T07:50:51,245][INFO ][oecsClusterApplierService] [es-master-594b58b86c-bj7g7] added {{es-client-69b84b46d8-v5pj2}{MMjA_tlTS7ux-UW44i0osg}{rOE4nB_jSmaIQVDZCjP8Rg}{10.9.125.83}{10.9.125.83:9300},}, reason: apply cluster state (from master [master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300} committed version [6] source [zen-disco-node-join[{es-client-69b84b46d8-v5pj2}{MMjA_tlTS7ux-UW44i0osg}{rOE4nB_jSmaIQVDZCjP8Rg}{10.9.125.83}{10.9.125.83:9300}]]]) [2018-10-21T07:50:58,964][INFO ][oecsClusterApplierService] [es-master-594b58b86c-bj7g7] added {{es-client-69b84b46d8-kr7j4}{gGC7F4diRWy2oM1TLTvNsg}{IgI6g3iZT5Sa0HsFVMpvvw}{10.9.124.82}{10.9.124.82:9300},}, reason: apply cluster state (from master [master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300} committed version [7] source [zen-disco-node-join[{es-client-69b84b46d8-kr7j4}{gGC7F4diRWy2oM1TLTvNsg}{IgI6g3iZT5Sa0HsFVMpvvw}{10.9.124.82}{10.9.124.82:9300}]]]) ] [ES-主594b58b86c-bj7g7]加入{{ES-主594b58b86c-9jkj2} {x9Prp1VbTq6_kALQVNwIWg} {7NHUSVpuS0mFDTXzAeKRcg} {10.9.125.81} {10.9 root$ kubectl -n elasticsearch get pods -l role=data NAME READY STATUS RESTARTS AGE es-data-0 1/1 Running 0 48s es-data-1 1/1 Running 0 28s -------------------------------------------------------------------- root$ kubectl apply -f es-client.yml root$ kubectl -n elasticsearch get pods -l role=client NAME READY STATUS RESTARTS AGE es-client-69b84b46d8-kr7j4 1/1 Running 0 47s es-client-69b84b46d8-v5pj2 1/1 Running 0 47s -------------------------------------------------------------------- root$ kubectl -n elasticsearch get all NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE deploy/es-client 2 2 2 2 1m deploy/es-master 3 3 3 3 9m NAME DESIRED CURRENT READY AGE rs/es-client-69b84b46d8 2 2 2 1m rs/es-master-594b58b86c 3 3 3 9m NAME DESIRED CURRENT AGE statefulsets/es-data 2 2 3m NAME READY STATUS RESTARTS AGE po/es-client-69b84b46d8-kr7j4 1/1 Running 0 1m po/es-client-69b84b46d8-v5pj2 1/1 Running 0 1m po/es-data-0 1/1 Running 0 3m po/es-data-1 1/1 Running 0 3m po/es-master-594b58b86c-9jkj2 1/1 Running 0 9m po/es-master-594b58b86c-bj7g7 1/1 Running 0 9m po/es-master-594b58b86c-lfpps 1/1 Running 0 9m NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE svc/elasticsearch LoadBalancer 10.9.121.160 10.9.120.8 9200:32310/TCP 1m svc/elasticsearch-data ClusterIP None <none> 9300/TCP 3m svc/elasticsearch-discovery ClusterIP None <none> 9300/TCP 9m -------------------------------------------------------------------- #Check logs of es-master leader pod root$ kubectl -n elasticsearch logs po/es-master-594b58b86c-bj7g7 | grep ClusterApplierService [2018-10-21T07:41:53,731][INFO ][oecsClusterApplierService] [es-master-594b58b86c-bj7g7] new_master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300}, added {{es-master-594b58b86c-lfpps}{wZQmXr5fSfWisCpOHBhaMg}{50jGPeKLSpO9RU_HhnVJCA}{10.9.124.81}{10.9.124.81:9300},}, reason: apply cluster state (from master [master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300} committed version [1] source [zen-disco-elected-as-master ([1] nodes joined)[{es-master-594b58b86c-lfpps}{wZQmXr5fSfWisCpOHBhaMg}{50jGPeKLSpO9RU_HhnVJCA}{10.9.124.81}{10.9.124.81:9300}]]]) [2018-10-21T07:41:55,162][INFO ][oecsClusterApplierService] [es-master-594b58b86c-bj7g7] added {{es-master-594b58b86c-9jkj2}{x9Prp1VbTq6_kALQVNwIWg}{7NHUSVpuS0mFDTXzAeKRcg}{10.9.125.81}{10.9.125.81:9300},}, reason: apply cluster state (from master [master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300} committed version [3] source [zen-disco-node-join[{es-master-594b58b86c-9jkj2}{x9Prp1VbTq6_kALQVNwIWg}{7NHUSVpuS0mFDTXzAeKRcg}{10.9.125.81}{10.9.125.81:9300}]]]) [2018-10-21T07:48:02,485][INFO ][oecsClusterApplierService] [es-master-594b58b86c-bj7g7] added {{es-data-0}{SAOhUiLiRkazskZ_TC6EBQ}{qirmfVJBTjSBQtHZnz-QZw}{10.9.126.88}{10.9.126.88:9300},}, reason: apply cluster state (from master [master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300} committed version [4] source [zen-disco-node-join[{es-data-0}{SAOhUiLiRkazskZ_TC6EBQ}{qirmfVJBTjSBQtHZnz-QZw}{10.9.126.88}{10.9.126.88:9300}]]]) [2018-10-21T07:48:21,984][INFO ][oecsClusterApplierService] [es-master-594b58b86c-bj7g7] added {{es-data-1}{fiv5Wh29TRWGPumm5ypJfA}{EXqKGSzIQquRyWRzxIOWhQ}{10.9.125.82}{10.9.125.82:9300},}, reason: apply cluster state (from master [master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300} committed version [5] source [zen-disco-node-join[{es-data-1}{fiv5Wh29TRWGPumm5ypJfA}{EXqKGSzIQquRyWRzxIOWhQ}{10.9.125.82}{10.9.125.82:9300}]]]) [2018-10-21T07:50:51,245][INFO ][oecsClusterApplierService] [es-master-594b58b86c-bj7g7] added {{es-client-69b84b46d8-v5pj2}{MMjA_tlTS7ux-UW44i0osg}{rOE4nB_jSmaIQVDZCjP8Rg}{10.9.125.83}{10.9.125.83:9300},}, reason: apply cluster state (from master [master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300} committed version [6] source [zen-disco-node-join[{es-client-69b84b46d8-v5pj2}{MMjA_tlTS7ux-UW44i0osg}{rOE4nB_jSmaIQVDZCjP8Rg}{10.9.125.83}{10.9.125.83:9300}]]]) [2018-10-21T07:50:58,964][INFO ][oecsClusterApplierService] [es-master-594b58b86c-bj7g7] added {{es-client-69b84b46d8-kr7j4}{gGC7F4diRWy2oM1TLTvNsg}{IgI6g3iZT5Sa0HsFVMpvvw}{10.9.124.82}{10.9.124.82:9300},}, reason: apply cluster state (from master [master {es-master-594b58b86c-bj7g7}{1aFT97hQQ7yiaBc2CYShBA}{Q3QzlaG3QGazOwtUl7N75Q}{10.9.126.87}{10.9.126.87:9300} committed version [7] source [zen-disco-node-join[{es-client-69b84b46d8-kr7j4}{gGC7F4diRWy2oM1TLTvNsg}{IgI6g3iZT5Sa0HsFVMpvvw}{10.9.124.82}{10.9.124.82:9300}]]])

当将每个节点添加到集群时，主主节点pod的日志将清楚显示。 在调试时了解这一点很有用。


我们已经部署了所有组件，现在我们需要检查：


1）使用Ubuntu容器从Kubernetes集群部署Elasticsearch。


 root$ kubectl run my-shell --rm -i --tty --image ubuntu -- bash root@my-shell-68974bb7f7-pj9x6:/# curl http://elasticsearch.elasticsearch:9200/_cluster/health?pretty { "cluster_name" : "my-es", "status" : "green", "timed_out" : false, "number_of_nodes" : 7, "number_of_data_nodes" : 2, "active_primary_shards" : 0, "active_shards" : 0, "relocating_shards" : 0, "initializing_shards" : 0, "unassigned_shards" : 0, "delayed_unassigned_shards" : 0, "number_of_pending_tasks" : 0, "number_of_in_flight_fetch" : 0, "task_max_waiting_in_queue_millis" : 0, "active_shards_percent_as_number" : 100.0 }

2）通过内部平衡器GCP的IP（在我们的示例中为10.9.120.8 ）从集群外部部署Elasticsearch。


 root$ curl http://10.9.120.8:9200/_cluster/health?pretty { "cluster_name" : "my-es", "status" : "green", "timed_out" : false, "number_of_nodes" : 7, "number_of_data_nodes" : 2, "active_primary_shards" : 0, "active_shards" : 0, "relocating_shards" : 0, "initializing_shards" : 0, "unassigned_shards" : 0, "delayed_unassigned_shards" : 0, "number_of_pending_tasks" : 0, "number_of_in_flight_fetch" : 0, "task_max_waiting_in_queue_millis" : 0, "active_shards_percent_as_number" : 100.0 }

3）ES炉床的反关联性规则。


 root$ kubectl -n elasticsearch get pods -o wide NAME READY STATUS RESTARTS AGE IP NODE es-client-69b84b46d8-kr7j4 1/1 Running 0 10m 10.8.14.52 gke-cluster1-pool1-d2ef2b34-t6h9 es-client-69b84b46d8-v5pj2 1/1 Running 0 10m 10.8.15.53 gke-cluster1-pool1-42b4fbc4-cncn es-data-0 1/1 Running 0 12m 10.8.16.58 gke-cluster1-pool1-4cfd808c-kpx1 es-data-1 1/1 Running 0 12m 10.8.15.52 gke-cluster1-pool1-42b4fbc4-cncn es-master-594b58b86c-9jkj2 1/1 Running 0 18m 10.8.15.51 gke-cluster1-pool1-42b4fbc4-cncn es-master-594b58b86c-bj7g7 1/1 Running 0 18m 10.8.16.57 gke-cluster1-pool1-4cfd808c-kpx1 es-master-594b58b86c-lfpps 1/1 Running 0 18m 10.8.14.51 gke-cluster1-pool1-d2ef2b34-t6h9

请注意，我们在同一节点上没有两个相似的炉床，因此在节点发生故障的情况下确保了高可靠性。


缩放比例


我们可以根据CPU限制为客户端节点部署自动扩展服务 。 客户端节点的示例HPA：


 apiVersion: autoscaling/v1 kind: HorizontalPodAutoscaler metadata: name: es-client namespace: elasticsearch spec: maxReplicas: 5 minReplicas: 2 scaleTargetRef: apiVersion: extensions/v1beta1 kind: Deployment name: es-client targetCPUUtilizationPercentage: 80

自动扩展会将客户端节点上的Pod添加到群集中，这可以在主节点上任何Pod的日志中看到。


对于数据节点上的容器，您只需要在Kubernetes控制面板或GKE控制台中增加副本的数量。 创建的数据节点本身将被添加到群集，并将开始从其他节点复制数据。


我不需要在主节点上进行自动扩展 -它们仅存储有关集群状态的数据。 但是，如果要添加数据节点，请确保集群中的主节点数为奇数 ，并且不要忘记为环境更改NUMBER_OF_MASTERS变量。


部署Kibana和ES-HQ


Kibana和ES-HQ


Kibana是用于可视化ES数据的简单工具，ES-HQ帮助管理和监视Elasticsearch集群。 部署Kibana和ES-HQ时，请记住以下几点：


  • 我们将ES群集名称作为环境变量传递给Docker映像。
  • 用于访问Kibana / ES-HQ部署的服务保留在公司内部，即未创建公共IP。 我们使用内部GCP负载平衡器。

部署基巴纳


 kind: Namespace metadata: name: elasticsearch --- apiVersion: apps/v1beta1 kind: Deployment metadata: name: es-kibana namespace: elasticsearch labels: component: elasticsearch role: kibana spec: replicas: 1 template: metadata: labels: component: elasticsearch role: kibana spec: containers: - name: es-kibana image: docker.elastic.co/kibana/kibana-oss:6.2.2 env: - name: CLUSTER_NAME value: my-es - name: ELASTICSEARCH_URL value: http://elasticsearch:9200 resources: limits: cpu: 0.5 ports: - containerPort: 5601 name: http --- apiVersion: v1 kind: Service metadata: name: kibana annotations: cloud.google.com/load-balancer-type: "Internal" namespace: elasticsearch labels: component: elasticsearch role: kibana spec: selector: component: elasticsearch role: kibana ports: - name: http port: 80 targetPort: 5601 protocol: TCP type: LoadBalancer view rawes-kibana.yml hosted with love by GitHub

（部署和Kibana服务）


部署ES-HQ


 kind: Namespace metadata: name: elasticsearch --- apiVersion: apps/v1beta1 kind: Deployment metadata: name: es-hq namespace: elasticsearch labels: component: elasticsearch role: hq spec: replicas: 1 template: metadata: labels: component: elasticsearch role: hq spec: containers: - name: es-hq image: elastichq/elasticsearch-hq:release-v3.4.0 env: - name: HQ_DEFAULT_URL value: http://elasticsearch:9200 resources: limits: cpu: 0.5 ports: - containerPort: 5000 name: http --- apiVersion: v1 kind: Service metadata: name: hq annotations: cloud.google.com/load-balancer-type: "Internal" namespace: elasticsearch labels: component: elasticsearch role: hq spec: selector: component: elasticsearch role: hq ports: - name: http port: 80 targetPort: 5000 protocol: TCP type: LoadBalancer view rawes-hq.yml hosted with love by GitHub

（部署和ES-HQ服务）


我们通过创建的内部平衡器访问这两种服务。


 root$ kubectl -n elasticsearch get svc -l role=kibana NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kibana LoadBalancer 10.9.121.246 10.9.120.10 80:31400/TCP 1m root$ kubectl -n elasticsearch get svc -l role=hq NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE hq LoadBalancer 10.9.121.150 10.9.120.9 80:31499/TCP 1m

http：// <External-Ip-Kibana-Service> / app / kibana＃/ home？_g =（）



（Kibana控制面板）


http：// <External-Ip-ES-Hq-Service> /＃！/ clusters / my-es



（用于监视和管理集群的ElasticHQ控制面板）


ES是最受欢迎的分布式搜索和分析系统之一，在Kubernetes，它解决了扩展和高可用性的关键问题。 此外，Kubernetes中的新ES群集可立即部署。

Source: https://habr.com/ru/post/zh-CN432374/

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