配置和安装 EFK

官方文件目录：cluster/addons/fluentd-elasticsearch

  1. $ ls *.yaml
  2. es-controller.yaml  es-service.yaml  fluentd-es-ds.yaml  kibana-controller.yaml  kibana-service.yaml efk-rbac.yaml

同样EFK服务也需要一个efk-rbac.yaml文件，配置serviceaccount为efk。

已经修改好的 yaml 文件见：EFK

配置 es-controller.yaml

  1. #  cat es-controller.yaml
  2. apiVersion: v1
  3. kind: ReplicationController
  4. metadata:
  5.   name: elasticsearch-logging-v1
  6.   namespace: kube-system
  7.   labels:
  8.     k8s-app: elasticsearch-logging
  9.     version: v1
  10.     kubernetes.io/cluster-service: "true"
  11.     addonmanager.kubernetes.io/mode: Reconcile
  12. spec:
  13.   replicas: 2
  14.   selector:
  15.     k8s-app: elasticsearch-logging
  16.     version: v1
  17.   template:
  18.     metadata:
  19.       labels:
  20.         k8s-app: elasticsearch-logging
  21.         version: v1
  22.         kubernetes.io/cluster-service: "true"
  23.     spec:
  24.       serviceAccountName: efk
  25.       containers:
  26.       - image:  index.tenxcloud.com/docker_library/elasticsearch:2.2.0
  27.         name: elasticsearch-logging
  28.         resources:
  29.           # need more cpu upon initialization, therefore burstable class
  30.           limits:
  31.             cpu: 1000m
  32.           requests:
  33.             cpu: 100m
  34.         ports:
  35.         - containerPort: 9200
  36.           name: db
  37.           protocol: TCP
  38.         - containerPort: 9300
  39.           name: transport
  40.           protocol: TCP
  41.         volumeMounts:
  42.         - name: es-persistent-storage
  43.           mountPath: /data
  44.         env:
  45.         - name: "NAMESPACE"
  46.           valueFrom:
  47.             fieldRef:
  48.               fieldPath: metadata.namespace
  49.       volumes:
  50.       - name: es-persistent-storage
  51.         emptyDir: {}

配置 es-service.yaml

无需修改

配置 fluentd-es-ds.yaml

  1. # cat fluentd-es-ds.yaml
  2. apiVersion: extensions/v1beta1
  3. kind: DaemonSet
  4. metadata:
  5.   name: fluentd-es-v1.22
  6.   namespace: kube-system
  7.   labels:
  8.     k8s-app: fluentd-es
  9.     kubernetes.io/cluster-service: "true"
  10.     addonmanager.kubernetes.io/mode: Reconcile
  11.     version: v1.22
  12. spec:
  13.   template:
  14.     metadata:
  15.       labels:
  16.         k8s-app: fluentd-es
  17.         kubernetes.io/cluster-service: "true"
  18.         version: v1.22
  19.       # This annotation ensures that fluentd does not get evicted if the node
  20.       # supports critical pod annotation based priority scheme.
  21.       # Note that this does not guarantee admission on the nodes (#40573).
  22.       annotations:
  23.         scheduler.alpha.kubernetes.io/critical-pod: ''
  24.     spec:
  25.       serviceAccountName: fluentd
  26.       containers:
  27.       - name: fluentd-es
  28.         image: index.tenxcloud.com/zhangshun/fluentd-elasticsearch:v1
  29.         command:
  30.           - '/bin/sh'
  31.           - '-c'
  32.           - '/usr/sbin/td-agent 2>&1 >> /var/log/fluentd.log'
  33.         resources:
  34.           limits:
  35.             memory: 200Mi
  36.           requests:
  37.             cpu: 100m
  38.             memory: 200Mi
  39.         volumeMounts:
  40.         - name: varlog
  41.           mountPath: /var/log
  42.         - name: varlibdockercontainers
  43.           mountPath: /var/lib/docker/containers
  44.           readOnly: true
  45.       nodeSelector:
  46.         beta.kubernetes.io/fluentd-ds-ready: "true"
  47.       tolerations:
  48.       - key : "node.alpha.kubernetes.io/ismaster"
  49.         effect: "NoSchedule"
  50.       terminationGracePeriodSeconds: 30
  51.       volumes:
  52.       - name: varlog
  53.         hostPath:
  54.           path: /var/log
  55.       - name: varlibdockercontainers
  56.         hostPath:
  57.           path: /var/lib/docker/containers

配置 kibana-controller.yaml

  1. # cat kibana-controller.yaml
  2. apiVersion: extensions/v1beta1
  3. kind: Deployment
  4. metadata:
  5.   name: kibana-logging
  6.   namespace: kube-system
  7.   labels:
  8.     k8s-app: kibana-logging
  9.     kubernetes.io/cluster-service: "true"
  10.     addonmanager.kubernetes.io/mode: Reconcile
  11. spec:
  12.   replicas: 1
  13.   selector:
  14.     matchLabels:
  15.       k8s-app: kibana-logging
  16.   template:
  17.     metadata:
  18.       labels:
  19.         k8s-app: kibana-logging
  20.     spec:
  21.       serviceAccountName: efk
  22.       containers:
  23.       - name: kibana-logging
  24.         image: index.tenxcloud.com/docker_library/kibana:4.5.1
  25.         resources:
  26.           # keep request = limit to keep this container in guaranteed class
  27.           limits:
  28.             cpu: 100m
  29.           requests:
  30.             cpu: 100m
  31.         env:
  32.           - name: "ELASTICSEARCH_URL"
  33.             value: "http://elasticsearch-logging:9200"
  34.           - name: "KIBANA_BASE_URL"
  35.             value: "/api/v1/proxy/namespaces/kube-system/services/kibana-logging"
  36.         ports:
  37.         - containerPort: 5601
  38.           name: ui
  39.           protocol: TCP

给 Node 设置标签

定义 DaemonSet fluentd-es-v1.22 时设置了 nodeSelector beta.kubernetes.io/fluentd-ds-ready=true ，所以需要在期望运行 fluentd 的 Node 上设置该标签；

  1. # kubectl get nodes
  2. NAME            STATUS    AGE       VERSION
  3. 192.168.1.122   Ready     22h       v1.6.2
  4. 192.168.1.123   Ready     22h       v1.6.2
  6. # kubectl label nodes 192.168.1.122 beta.kubernetes.io/fluentd-ds-ready=true
  7. node "172.20.0.112" labeled
  8. # kubectl label nodes 192.168.1.123 beta.kubernetes.io/fluentd-ds-ready=true
  9. node "172.20.0.123" labeled

给其他两台node打上同样的标签。

执行定义文件

  1. $ kubectl create -f .
  2. serviceaccount "efk" created
  3. clusterrolebinding "efk" created
  4. replicationcontroller "elasticsearch-logging-v1" created
  5. service "elasticsearch-logging" created
  6. daemonset "fluentd-es-v1.22" created
  7. deployment "kibana-logging" created
  8. service "kibana-logging" created

检查执行结果

  1. $ kubectl get deployment -n kube-system|grep kibana
  2. kibana-logging         1         1         1            1           2m
  4. $ kubectl get pods -n kube-system|grep -E 'elasticsearch|fluentd|kibana'
  5. elasticsearch-logging-v1-mlstp          1/1       Running   0          1m
  6. elasticsearch-logging-v1-nfbbf          1/1       Running   0          1m
  7. fluentd-es-v1.22-31sm0                  1/1       Running   0          1m
  8. fluentd-es-v1.22-bpgqs                  1/1       Running   0          1m
  9. fluentd-es-v1.22-qmn7h                  1/1       Running   0          1m
  10. kibana-logging-1432287342-0gdng         1/1       Running   0          1m
  12. $ kubectl get service  -n kube-system|grep -E 'elasticsearch|kibana'
  13. elasticsearch-logging   10.254.77.62    <none>        9200/TCP                        2m
  14. kibana-logging          10.254.8.113    <none>        5601/TCP                        2m

kibana Pod 第一次启动时会用较长时间(10-20分钟)来优化和 Cache 状态页面，可以 tailf 该 Pod 的日志观察进度：

  1. $ kubectl logs kibana-logging-1432287342-0gdng -n kube-system -f
  2. ELASTICSEARCH_URL=http://elasticsearch-logging:9200
  3. server.basePath: /api/v1/proxy/namespaces/kube-system/services/kibana-logging
  4. {"type":"log","@timestamp":"2017-07-26T13:08:06Z","tags":["info","optimize"],"pid":7,"message":"Optimizing and caching bundles for kibana and statusPage. This may take a few minutes"}
  5. {"type":"log","@timestamp":"2017-07-26T13:18:17Z","tags":["info","optimize"],"pid":7,"message":"Optimization of bundles for kibana and statusPage complete in 610.40 seconds"}
  6. {"type":"log","@timestamp":"2017-07-26T13:18:17Z","tags":["status","plugin:kibana@1.0.0","info"],"pid":7,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
  7. {"type":"log","@timestamp":"2017-07-26T13:18:18Z","tags":["status","plugin:elasticsearch@1.0.0","info"],"pid":7,"state":"yellow","message":"Status changed from uninitialized to yellow - Waiting for Elasticsearch","prevState":"uninitialized","prevMsg":"uninitialized"}
  8. {"type":"log","@timestamp":"2017-07-26T13:18:19Z","tags":["status","plugin:kbn_vislib_vis_types@1.0.0","info"],"pid":7,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
  9. {"type":"log","@timestamp":"2017-07-26T13:18:19Z","tags":["status","plugin:markdown_vis@1.0.0","info"],"pid":7,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
  10. {"type":"log","@timestamp":"2017-07-26T13:18:19Z","tags":["status","plugin:metric_vis@1.0.0","info"],"pid":7,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
  11. {"type":"log","@timestamp":"2017-07-26T13:18:19Z","tags":["status","plugin:spyModes@1.0.0","info"],"pid":7,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
  12. {"type":"log","@timestamp":"2017-07-26T13:18:19Z","tags":["status","plugin:statusPage@1.0.0","info"],"pid":7,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
  13. {"type":"log","@timestamp":"2017-07-26T13:18:19Z","tags":["status","plugin:table_vis@1.0.0","info"],"pid":7,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
  14. {"type":"log","@timestamp":"2017-07-26T13:18:19Z","tags":["listening","info"],"pid":7,"message":"Server running at http://0.0.0.0:5601"}
  15. {"type":"log","@timestamp":"2017-07-26T13:18:24Z","tags":["status","plugin:elasticsearch@1.0.0","info"],"pid":7,"state":"yellow","message":"Status changed from yellow to yellow - No existing Kibana index found","prevState":"yellow","prevMsg":"Waiting for Elasticsearch"}
  16. {"type":"log","@timestamp":"2017-07-26T13:18:29Z","tags":["status","plugin:elasticsearch@1.0.0","info"],"pid":7,"state":"green","message":"Status changed from yellow to green - Kibana index ready","prevState":"yellow","prevMsg":"No existing Kibana index found"}

访问 kibana

  1. 通过 kube-apiserver 访问：

获取 monitoring-grafana 服务 URL

  1. # kubectl cluster-info
  2. Kubernetes master is running at https://192.168.1.121:6443
  3. Elasticsearch is running at https://192.168.1.121:6443/api/v1/proxy/namespaces/kube-system/services/elasticsearch-logging
  4. Heapster is running at https://192.168.1.121:6443/api/v1/proxy/namespaces/kube-system/services/heapster
  5. Kibana is running at https://192.168.1.121:6443/api/v1/proxy/namespaces/kube-system/services/kibana-logging
  6. KubeDNS is running at https://192.168.1.121:6443/api/v1/proxy/namespaces/kube-system/services/kube-dns
  7. kubernetes-dashboard is running at https://192.168.1.121:6443/api/v1/proxy/namespaces/kube-system/services/kubernetes-dashboard
  8. monitoring-grafana is running at https://192.168.1.121:6443/api/v1/proxy/namespaces/kube-system/services/monitoring-grafana
  9. monitoring-influxdb is running at https://192.168.1.121:6443/api/v1/proxy/namespaces/kube-system/services/monitoring-influxd
  1. 浏览器访问 URL： `https://192.168.1.121:6443/api/v1/proxy/namespaces/kube-system/services/kibana-logging/app/kibana`

  1. 通过 kubectl proxy 访问：

    创建代理

    1. $ kubectl proxy --address='192.168.1.121' --port=8086 --accept-hosts='^*$'
    2. Starting to serve on 192.168.1.121:8086

    浏览器访问 URL：http://192.168.1.121:8086/api/v1/proxy/namespaces/kube-system/services/kibana-logging

在 Settings -> Indices 页面创建一个 index（相当于 mysql 中的一个 database），选中 Index contains time-based events，使用默认的 logstash-* pattern，点击 Create ;

可能遇到的问题

如果你在这里发现Create按钮是灰色的无法点击，且Time-filed name中没有选项，fluentd要读取/var/log/containers/目录下的log日志，这些日志是从/var/lib/docker/containers/${CONTAINER_ID}/${CONTAINER_ID}-json.log链接过来的，查看你的docker配置，—log-dirver需要设置为json-file格式，默认的可能是journald，参考docker logging。

创建Index后，可以在 Discover 下看到 ElasticSearch logging 中汇聚的日志；

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