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