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EFK收集Kubernetes应用日志

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EFK介绍

  • Logstash(或者Fluentd)负责收集日志
  • Elasticsearch存储日志并提供搜索
  • Kibana负责日志查询和展示

官方地址：https://github.com/kubernetes/kubernetes/tree/master/cluster/addons/fluentd-elasticsearch

通过在每台node上部署一个以DaemonSet方式运行的fluentd来收集每台node上的日志。Fluentd将docker日志目录/var/lib/docker/containers和/var/log目录挂载到Pod中，然后Pod会在node节点的/var/log/pods目录中创建新的目录，可以区别不同的容器日志输出，该目录下有一个日志文件链接到/var/lib/docker/contianers目录下的容器日志输出。

配置efk-rbac.yaml文件

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

[root@node1 opt]# mkdir efk
[root@node1 opt]# cd efk
[root@node1 efk]# vim efk-rbac.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
  name: efk
  namespace: kube-system

---

kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1beta1
metadata:
  name: efk
subjects:
  - kind: ServiceAccount
    name: efk
    namespace: kube-system
roleRef:
  kind: ClusterRole
  name: cluster-admin
  apiGroup: rbac.authorization.k8s.io

配置 es-controller.yaml

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[root@node1 efk]# vim es-controller.yaml
apiVersion: v1
kind: ReplicationController
metadata:
  name: elasticsearch-logging-v1
  namespace: kube-system
  labels:
    k8s-app: elasticsearch-logging
    version: v1
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
spec:
  replicas: 2
  selector:
    k8s-app: elasticsearch-logging
    version: v1
  template:
    metadata:
      labels:
        k8s-app: elasticsearch-logging
        version: v1
        kubernetes.io/cluster-service: "true"
    spec:
      serviceAccountName: efk
      containers:
      - image: index.tenxcloud.com/jimmy/elasticsearch:v2.4.1-2
        name: elasticsearch-logging
        resources:
          # need more cpu upon initialization, therefore burstable class
          limits:
            cpu: 1000m
          requests:
            cpu: 100m
        ports:
        - containerPort: 9200
          name: db
          protocol: TCP
        - containerPort: 9300
          name: transport
          protocol: TCP
        volumeMounts:
        - name: es-persistent-storage
          mountPath: /data
        env:
        - name: "NAMESPACE"
          valueFrom:
            fieldRef:
              fieldPath: metadata.namespace
      volumes:
      - name: es-persistent-storage
        emptyDir: {}

配置 es-service.yaml

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[root@node1 efk]# vim es-service.yaml
apiVersion: v1
kind: Service
metadata:
  name: elasticsearch-logging
  namespace: kube-system
  labels:
    k8s-app: elasticsearch-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/name: "Elasticsearch"
spec:
  ports:
  - port: 9200
    protocol: TCP
    targetPort: db
  selector:
    k8s-app: elasticsearch-logging

配置 fluentd-es-ds.yaml

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apiVersion: extensions/v1beta1
kind: DaemonSet
metadata:
  name: fluentd-es-v1.22
  namespace: kube-system
  labels:
    k8s-app: fluentd-es
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
    version: v1.22
spec:
  template:
    metadata:
      labels:
        k8s-app: fluentd-es
        kubernetes.io/cluster-service: "true"
        version: v1.22
      # This annotation ensures that fluentd does not get evicted if the node
      # supports critical pod annotation based priority scheme.
      # Note that this does not guarantee admission on the nodes (#40573).
      annotations:
        scheduler.alpha.kubernetes.io/critical-pod: ''
    spec:  
      serviceAccountName: efk
      containers:
      - name: fluentd-es
        image: index.tenxcloud.com/jimmy/fluentd-elasticsearch:1.22
        command:
          - '/bin/sh'
          - '-c'
          - '/usr/sbin/td-agent 2>&1 >> /var/log/fluentd.log'
        resources:
          limits:
            memory: 200Mi
          requests:
            cpu: 100m
            memory: 200Mi
        volumeMounts:
        - name: varlog
          mountPath: /var/log
        - name: varlibdockercontainers
          mountPath: /var/lib/docker/containers
          readOnly: true
      nodeSelector:
        beta.kubernetes.io/fluentd-ds-ready: "true"
      tolerations:
      - key : "node.alpha.kubernetes.io/ismaster"
        effect: "NoSchedule"
      terminationGracePeriodSeconds: 30
      volumes:
      - name: varlog
        hostPath:
          path: /var/log
      - name: varlibdockercontainers
        hostPath:
          path: /var/lib/docker/containers

配置 kibana-controller.yaml

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apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: kibana-logging
  namespace: kube-system
  labels:
    k8s-app: kibana-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
spec:
  replicas: 1
  selector:
    matchLabels:
      k8s-app: kibana-logging
  template:
    metadata:
      labels:
        k8s-app: kibana-logging
    spec:
      serviceAccountName: efk
      containers:
      - name: kibana-logging
        image: index.tenxcloud.com/jimmy/kibana:v4.6.1-1
        resources:
          # keep request = limit to keep this container in guaranteed class
          limits:
            cpu: 100m
          requests:
            cpu: 100m
        env:
          - name: "ELASTICSEARCH_URL"
            value: "http://elasticsearch-logging:9200"
          - name: "KIBANA_BASE_URL"
            value: "/api/v1/proxy/namespaces/kube-system/services/kibana-logging"
        ports:
        - containerPort: 5601
          name: ui
          protocol: TCP

配置 kibana-service.yaml

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apiVersion: v1
kind: Service
metadata:
  name: kibana-logging
  namespace: kube-system
  labels:
    k8s-app: kibana-logging
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/name: "Kibana"
spec:
  ports:
  - port: 5601
    protocol: TCP
    targetPort: ui
  selector:
    k8s-app: kibana-logging
[root@node1 efk]# ls
efk-rbac.yaml  es-controller.yaml  es-service.yaml  fluentd-es-ds.yaml  kibana-controller.yaml  kibana-service.yaml

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；

[root@node1 efk]# kubectl label nodes 172.16.7.151 beta.kubernetes.io/fluentd-ds-ready=true
node "172.16.7.151" labeled
[root@node1 efk]# kubectl label nodes 172.16.7.152 beta.kubernetes.io/fluentd-ds-ready=true
node "172.16.7.152" labeled
[root@node1 efk]# kubectl label nodes 172.16.7.153 beta.kubernetes.io/fluentd-ds-ready=true
node "172.16.7.153" labeled

执行定义文件

[root@node1 efk]# kubectl create -f .

检查执行结果

[root@node1 efk]# kubectl get deployment -n kube-system|grep kibana
kibana-logging         1         1         1            1           1h

[root@node1 efk]# kubectl get pods -n kube-system|grep -E 'elasticsearch|fluentd|kibana'
elasticsearch-logging-v1-nw3p3          1/1       Running   0          43m
elasticsearch-logging-v1-pp89h          1/1       Running   0          43m
fluentd-es-v1.22-cqd1s                  1/1       Running   0          15m
fluentd-es-v1.22-f5ljr                  0/1       Error     6          15m
fluentd-es-v1.22-x24jx                  1/1       Running   0          15m
kibana-logging-4293390753-kg8kx         1/1       Running   0          1h

[root@node1 efk]# kubectl get service  -n kube-system|grep -E 'elasticsearch|kibana'
elasticsearch-logging   10.254.50.63     <none>        9200/TCP                        1h
kibana-logging          10.254.169.159   <none>        5601/TCP                        1h

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。

[root@node1 efk]# kubectl logs kibana-logging-4293390753-86h5d -n kube-system -f
ELASTICSEARCH_URL=http://elasticsearch-logging:9200
server.basePath: /api/v1/proxy/namespaces/kube-system/services/kibana-logging
{"type":"log","@timestamp":"2017-10-13T00:51:31Z","tags":["info","optimize"],"pid":5,"message":"Optimizing and caching bundles for kibana and statusPage. This may take a few minutes"}
{"type":"log","@timestamp":"2017-10-13T01:13:36Z","tags":["info","optimize"],"pid":5,"message":"Optimization of bundles for kibana and statusPage complete in 1324.64 seconds"}
{"type":"log","@timestamp":"2017-10-13T01:13:37Z","tags":["status","plugin:kibana@1.0.0","info"],"pid":5,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-10-13T01:13:38Z","tags":["status","plugin:elasticsearch@1.0.0","info"],"pid":5,"state":"yellow","message":"Status changed from uninitialized to yellow - Waiting for Elasticsearch","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-10-13T01:13:39Z","tags":["status","plugin:kbn_vislib_vis_types@1.0.0","info"],"pid":5,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-10-13T01:13:39Z","tags":["status","plugin:markdown_vis@1.0.0","info"],"pid":5,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-10-13T01:13:39Z","tags":["status","plugin:metric_vis@1.0.0","info"],"pid":5,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-10-13T01:13:39Z","tags":["status","plugin:spyModes@1.0.0","info"],"pid":5,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-10-13T01:13:40Z","tags":["status","plugin:statusPage@1.0.0","info"],"pid":5,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-10-13T01:13:40Z","tags":["status","plugin:table_vis@1.0.0","info"],"pid":5,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-10-13T01:13:40Z","tags":["listening","info"],"pid":5,"message":"Server running at http://0.0.0.0:5601"}
{"type":"log","@timestamp":"2017-10-13T01:13:45Z","tags":["status","plugin:elasticsearch@1.0.0","info"],"pid":5,"state":"yellow","message":"Status changed from yellow to yellow - No existing Kibana index found","prevState":"yellow","prevMsg":"Waiting for Elasticsearch"}
{"type":"log","@timestamp":"2017-10-13T01:13:49Z","tags":["status","plugin:elasticsearch@1.0.0","info"],"pid":5,"state":"green","message":"Status changed from yellow to green - Kibana index ready","prevState":"yellow","prevMsg":"No existing Kibana index found"}

访问 kibana

通过 kube-apiserver 访问：获取 kibana 服务 URL

[root@node1 efk]# kubectl cluster-info
Kubernetes master is running at https://172.16.7.151:6443
Elasticsearch is running at https://172.16.7.151:6443/api/v1/proxy/namespaces/kube-system/services/elasticsearch-logging
Heapster is running at https://172.16.7.151:6443/api/v1/proxy/namespaces/kube-system/services/heapster
Kibana is running at https://172.16.7.151:6443/api/v1/proxy/namespaces/kube-system/services/kibana-logging
KubeDNS is running at https://172.16.7.151:6443/api/v1/proxy/namespaces/kube-system/services/kube-dns
kubernetes-dashboard is running at https://172.16.7.151:6443/api/v1/proxy/namespaces/kube-system/services/kubernetes-dashboard
monitoring-grafana is running at https://172.16.7.151:6443/api/v1/proxy/namespaces/kube-system/services/monitoring-grafana
monitoring-influxdb is running at https://172.16.7.151:6443/api/v1/proxy/namespaces/kube-system/services/monitoring-influxdb

To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'.

浏览器访问 URL： https://172.16.7.151:6443/api/v1/proxy/namespaces/kube-system/services/kibana-logging/app/kibana

通过 kubectl proxy 访问：创建代理

[root@node1 efk]# kubectl proxy --address='172.16.7.151' --port=8086 --accept-hosts='^*$' &

浏览器访问 URL：http://172.16.7.151:8086/api/v1/proxy/namespaces/kube-system/services/kibana-logging

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-driver需要设置为json-file格式，默认的可能是journald。

查看当前的–log-driver:

[root@node1 ~]# docker version
Client:
 Version:         1.12.6
 API version:     1.24
 Package version: docker-1.12.6-32.git88a4867.el7.centos.x86_64
 Go version:      go1.7.4
 Git commit:      88a4867/1.12.6
 Built:           Mon Jul  3 16:02:02 2017
 OS/Arch:         linux/amd64

Server:
 Version:         1.12.6
 API version:     1.24
 Package version: docker-1.12.6-32.git88a4867.el7.centos.x86_64
 Go version:      go1.7.4
 Git commit:      88a4867/1.12.6
 Built:           Mon Jul  3 16:02:02 2017
 OS/Arch:         linux/amd64   
[root@node1 efk]# docker info |grep 'Logging Driver'
 WARNING: Usage of loopback devices is strongly discouraged for production use. Use `--storage-opt dm.thinpooldev` to specify a custom block storage device.
WARNING: bridge-nf-call-ip6tables is disabled
Logging Driver: journald

修改当前版本docker的–log-driver:

[root@node1 ~]# vim /etc/sysconfig/docker
OPTIONS='--selinux-enabled --log-driver=json-file --signature-verification=false'
[root@node1 efk]# systemctl restart docker

【注意】：本来修改这个参数应该在在/etc/docker/daemon.json文件中添加

{
  "log-driver": "json-file",
}

但是在该版本中，–log-driver是在文件/etc/sysconfig/docker中定义的。
在docker-ce版本中，默认的–log-driver是json-file。

遇到的问题：
由于之前在/etc/docker/daemon.json中配置–log-driver，重启导致docker程序启动失败，等到后来在/etc/sysconfig/docker配置文件中配置好后，启动docker却发现当前node变成NotReady状态，所有的Pod也变为Unknown状态。查看kubelet状态，发现kubelet程序已经挂掉了。

[root@node1 ~]# kubectl get nodes
NAME           STATUS     AGE       VERSION
172.16.7.151   NotReady   28d       v1.6.0
172.16.7.152   Ready      28d       v1.6.0
172.16.7.153   Ready      28d       v1.6.0

启动kubelet：

[root@node1 ~]# systemctl start kubelet
[root@node1 ~]# kubectl get nodes
NAME           STATUS    AGE       VERSION
172.16.7.151   Ready     28d       v1.6.0
172.16.7.152   Ready     28d       v1.6.0
172.16.7.153   Ready     28d       v1.6.0

浏览器再次访问 kibana URL：http://172.16.7.151:8086/api/v1/proxy/namespaces/kube-system/services/kibana-logging
此时就会发现有Create按钮了。

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

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