k8s部署kube-state-metrics組件

一、部署kube-state-metrics組件

1.1、kube-state-metrics是什么

kube-state-metrics通過監聽API Server生成有關資源對象的狀態指標，比如Deployment、Node、Pod，需要注意的是kube-state-metrics只是簡單的提供一個metrics數據，並不會存儲這些指標數據，所以我們可以使用Prometheus來抓取這些數據然后存儲，主要關注的是業務相關的一些元數據，比如Deployment、Pod、副本狀態等；調度了多少個replicas？現在可用的有幾個？多少個Pod是running/stopped/terminated狀態？Pod重啟了多少次？我有多少job在運行中。

1.2、安裝kube-state-metrics組件

1）創建sa，並對sa授權

[root@k8s-master1 prometheus]# cat kube-state-metrics-rbac.yaml 
---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: kube-state-metrics
  namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: kube-state-metrics
rules:
- apiGroups: [""]
  resources: ["nodes", "pods", "services", "resourcequotas", "replicationcontrollers", "limitranges", "persistentvolumeclaims", "persistentvolumes", "namespaces", "endpoints"]
  verbs: ["list", "watch"]
- apiGroups: ["extensions"]
  resources: ["daemonsets", "deployments", "replicasets"]
  verbs: ["list", "watch"]
- apiGroups: ["apps"]
  resources: ["statefulsets"]
  verbs: ["list", "watch"]
- apiGroups: ["batch"]
  resources: ["cronjobs", "jobs"]
  verbs: ["list", "watch"]
- apiGroups: ["autoscaling"]
  resources: ["horizontalpodautoscalers"]
  verbs: ["list", "watch"]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: kube-state-metrics
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: kube-state-metrics
subjects:
- kind: ServiceAccount
  name: kube-state-metrics
  namespace: kube-system
  
[root@k8s-master1 prometheus]# kubectl apply -f kube-state-metrics-rbac.yaml
serviceaccount/kube-state-metrics created
clusterrole.rbac.authorization.k8s.io/kube-state-metrics created
clusterrolebinding.rbac.authorization.k8s.io/kube-state-metrics created

2）安裝kube-state-metrics組件

[root@k8s-master1 prometheus]# cat kube-state-metrics-deploy.yaml 
apiVersion: apps/v1
kind: Deployment
metadata:
  name: kube-state-metrics
  namespace: kube-system
spec:
  replicas: 1
  selector:
    matchLabels:
      app: kube-state-metrics
  template:
    metadata:
      labels:
        app: kube-state-metrics
    spec:
      serviceAccountName: kube-state-metrics
      containers:
      - name: kube-state-metrics
        image: quay.io/coreos/kube-state-metrics:v1.9.0
        ports:
        - containerPort: 8080
        
[root@k8s-master1 prometheus]# kubectl apply -f kube-state-metrics-deploy.yaml
deployment.apps/kube-state-metrics created

[root@k8s-master1 prometheus]# kubectl get pods -n kube-system -l app=kube-state-metrics
NAME                                  READY   STATUS    RESTARTS   AGE
kube-state-metrics-58d4957bc5-tcbq5   1/1     Running   0          28s

3）創建service

[root@k8s-master1 prometheus]# cat kube-state-metrics-svc.yaml 
apiVersion: v1
kind: Service
metadata:
  annotations:
    prometheus.io/scrape: 'true'
  name: kube-state-metrics
  namespace: kube-system
  labels:
    app: kube-state-metrics
spec:
  ports:
  - name: kube-state-metrics
    port: 8080
    protocol: TCP
  selector:
    app: kube-state-metrics
    
[root@k8s-master1 prometheus]# kubectl apply -f kube-state-metrics-svc.yaml
service/kube-state-metrics created

[root@k8s-master1 prometheus]# kubectl get svc -n kube-system 
NAME                 TYPE        CLUSTER-IP       EXTERNAL-IP   PORT(S)                  AGE
kube-dns             ClusterIP   10.96.0.10       <none>        53/UDP,53/TCP,9153/TCP   3d12h
kube-state-metrics   ClusterIP   10.110.15.75     <none>        8080/TCP                 12s
monitoring-grafana   NodePort    10.105.174.145   <none>        80:31715/TCP             11h

1.3、Grafana配置

1）導入Kubernetes Cluster (Prometheus)-1577674936972.json

2）導入Kubernetes cluster monitoring (via Prometheus) (k8s 1.16)-1577691996738.json