详解k8s一个完整的监控方案(Heapster+Grafana+InfluxDB) - kubernetes

小说:干美团兼职怎么样作者:密伯道更新时间:2018-11-16字数:35849

详解k8s一个完整的监控方案(Heapster+Grafana+InfluxDB) - kubernetes


1、浅析整个监控流程

heapster以k8s内置的cAdvisor作为数据源收集集群信息,并汇总出有价值的性能数据(Metrics):cpu、内存、网络流量等,然后将这些数据输出到外部存储,如InfluxDB,最后就可以通过相应的UI界面显示出来,如grafana。 另外heapster的数据源和外部存储都是可插拔的,所以可以很灵活的组建出很多监控方案,如:Heapster+ElasticSearch+Kibana等等。

2、创建k8s资源对象

使用官方提供的yml文件有一些小问题,请参考以下改动和说明:

2.1、创建InfluxDB资源对象

apiVersion: apps/v1
kind: Deployment
metadata:
  name: monitoring-influxdb
  namespace: kube-system
spec:
  replicas: 1
  selector:
    matchLabels:
      task: monitoring
      k8s-app: influxdb
  template:
    metadata:
      labels:
        task: monitoring
        k8s-app: influxdb
    spec:
      containers:
      - name: influxdb
        image: k8s.gcr.io/heapster-influxdb-amd64:v1.3.3
        volumeMounts:
        - mountPath: /data
          name: influxdb-storage
      volumes:
      - name: influxdb-storage
        emptyDir: {}
---
apiVersion: v1
kind: Service
metadata:
  labels:
    task: monitoring
    kubernetes.io/cluster-service: "true"
    kubernetes.io/name: monitoring-influxdb
  name: monitoring-influxdb
  namespace: kube-system
spec:
  type: NodePort
  ports:
  - nodePort: 31001
    port: 8086
    targetPort: 8086
  selector:
    k8s-app: influxdb

注意:这里我们使用NotePort暴露monitoring-influxdb服务在主机的31001端口上,那么InfluxDB服务端的地址:http://[host-ip]:31001 ,记下这个地址,以便创建heapster和为grafana配置数据源时,可以直接使用。

2.1、创建Grafana资源对象

apiVersion: apps/v1
kind: Deployment
metadata:
  name: monitoring-grafana
  namespace: kube-system
spec:
  replicas: 1
  selector:
    matchLabels:
      task: monitoring
      k8s-app: grafana
  template:
    metadata:
      labels:
        task: monitoring
        k8s-app: grafana
    spec:
      containers:
      - name: grafana
        image: k8s.gcr.io/heapster-grafana-amd64:v4.4.3
        ports:
        - containerPort: 3000
          protocol: TCP
        volumeMounts:
        - mountPath: /etc/ssl/certs
          name: ca-certificates
          readOnly: true
        - mountPath: /var
          name: grafana-storage
        env:
        - name: INFLUXDB_HOST
          value: monitoring-influxdb
        - name: GF_SERVER_HTTP_PORT
          value: "3000"
          # The following env variables are required to make Grafana accessible via
          # the kubernetes api-server proxy. On production clusters, we recommend
          # removing these env variables, setup auth for grafana, and expose the grafana
          # service using a LoadBalancer or a public IP.
        - name: GF_AUTH_BASIC_ENABLED
          value: "false"
        - name: GF_AUTH_ANONYMOUS_ENABLED
          value: "true"
        - name: GF_AUTH_ANONYMOUS_ORG_ROLE
          value: Admin
        - name: GF_SERVER_ROOT_URL
          # If you"re only using the API Server proxy, set this value instead:
          # value: /api/v1/namespaces/kube-system/services/monitoring-grafana/proxy
          value: /
      volumes:
      - name: ca-certificates
        hostPath:
          path: /etc/ssl/certs
      - name: grafana-storage
        emptyDir: {}
---
apiVersion: v1
kind: Service
metadata:
  labels:
    # For use as a Cluster add-on (https://github.com/kubernetes/kubernetes/tree/master/cluster/addons)
    # If you are NOT using this as an addon, you should comment out this line.
    kubernetes.io/cluster-service: "true"
    kubernetes.io/name: monitoring-grafana
  name: monitoring-grafana
  namespace: kube-system
spec:
  # In a production setup, we recommend accessing Grafana through an external Loadbalancer
  # or through a public IP.
  # type: LoadBalancer
  # You could also use NodePort to expose the service at a randomly-generated port
  type: NodePort
  ports:
  - nodePort: 30108
    port: 80
    targetPort: 3000
  selector:
    k8s-app: grafana

注意:这里我们使用NotePort暴露monitoring-grafana服务在主机的30108上,那么Grafana服务端的地址:http://registry.wuling.com:30108 ,通过浏览器访问,为Grafana修改数据源,如下:

标红的地方,为上一步记录下的InfluxDB服务端的地址。

2.2、创建Heapster资源对象

apiVersion: v1
kind: ServiceAccount
metadata:
  name: heapster
  namespace: kube-system
---
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: heapster
  namespace: kube-system
spec:
  replicas: 1
  selector:
    matchLabels:
      task: monitoring
      k8s-app: heapster
  template:
    metadata:
      labels:
        task: monitoring
        k8s-app: heapster
    spec:
      serviceAccountName: heapster
      containers:
      - name: heapster
        image: k8s.gcr.io/heapster-amd64:v1.4.2
        imagePullPolicy: IfNotPresent
        command:
        - /heapster
        - --source=kubernetes:https://kubernetes.default 
        - --sink=influxdb:http://150.109.39.33:31001  # 这里填写刚刚记录下的InfluxDB服务端的地址。
---
apiVersion: v1
kind: Service
metadata:
  labels:
    task: monitoring
    # For use as a Cluster add-on (https://github.com/kubernetes/kubernetes/tree/master/cluster/addons)
    # If you are NOT using this as an addon, you should comment out this line.
    kubernetes.io/cluster-service: "true"
    kubernetes.io/name: Heapster
  name: heapster
  namespace: kube-system
spec:
  ports:
  - port: 80
    targetPort: 8082
  selector:
    k8s-app: heapster

--source 为heapster指定获取集群信息的数据源。参考:https://github.com/kubernetes/heapster/blob/master/docs/source-configuration.md
--sink 为heaster指定后端存储,这里我们使用InfluxDB,其他的,请参考:https://github.com/kubernetes/heapster/blob/master/docs/sink-owners.md
这里heapster留下了一个的坑,请继续往下看,当我部署完heapster,通过查看Heapster容器组的镜像发现:

很多人都以为是https或者k8s配置的问题,于是去就慌忙的去配置InSecure http方式,导致坑越来越深,透明度越来越低,更是无从下手,我也是这样弄了很久,都较上劲了,此处省略一万字。。。,当这些路子都走遍了,再次品读下面的原文:

才发现是权限的问题,heaster默认使用一个令牌(Token)与ApiServer进行认证,通过查看heapster.yml发现 serviceAccountName: heapster ,现在明白了吧,就是heaster没有权限,那么如何授权呢-----给heaster绑定一个有权限的角色就行了,如下:

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

当创建heapster资源的时候,直接把这段代码加上,就行了。

3、查看监控详情

3.1、通过dashboard查看集群概况





整个监控方案部署成功后,从上图可以看到,在不同粒度/维度下,dashboard上可以呈现对象的具体CPU和内存使用率。

3.2、通过Grafana查看集群详情(cpu、memory、filesystem)






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发布时间:2018-11-16 09:13:46

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