prometheus和metrucs-server （k8s监控）



资源指标：metrucs-server
自定义指标：prometheus， k8s-prometheus-adapter（转换prometheus数据的格式）
新一代架构：
核心指标流水线：由kubelet、metrics-server以及由API server提供的api组成；CPU累积使用率、内存实时使用率、
Pod的资源占用率及容器的磁盘占用率；
监控流水线：用于从系统收集各种指标数据并提供终端用户、存储系统以及HPA，它们包含核心指标及许多非核心指
标。非核心指标本身不能被k8s所解析，

metrics-server：API server

#kube-aggregator()

#部署metrucs-server（使用kubectl top）

#1.20.x安装（注意镜像的下载）

kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml


#github
https://github.com/kubernetes-incubator/metrics-server

git clone https://github.com/kubernetes-incubator/metrics-server 
cd metrics-server

#修改配置文件metrics-server-deployment.yaml
vim deploy/1.8+/metrics-server-deployment.yaml

apiVersion: v1
kind: ServiceAccount
metadata:
  name: metrics-server
  namespace: kube-system
---
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: metrics-server
  namespace: kube-system
  labels:
    k8s-app: metrics-server
spec:
  selector:
    matchLabels:
      k8s-app: metrics-server
  template:
    metadata:
      name: metrics-server
      labels:
        k8s-app: metrics-server
    spec:
      serviceAccountName: metrics-server
      volumes:
      # mount in tmp so we can safely use from-scratch images and/or read-only containers
      - name: tmp-dir
        emptyDir: {}
      containers:
      - name: metrics-server
        image: k8s.gcr.io/metrics-server-amd64:v0.3.1
        imagePullPolicy: Always
        command:
        - /metrics-server
        - --kubelet-insecure-tls
        - --kubelet-preferred-address-types=InternalIP
        volumeMounts:
        - name: tmp-dir
          mountPath: /tmp

#导入文件

kubectl create -f deploy/1.8+/
#查看

##查看
kubectl -n kube-system get pods -l k8s-app=metrics-server
kubectl  api-versions
  
#使用kube-proxy打开端口8080监听
kubectl  proxy --port=8080



#过一会使用kubelet top

[root@k8s-m 1.8+]# curl http://localhost:8080/apis/metrics.k8s.io/v1beta1/nodes
{
  "kind": "NodeMetricsList",
  "apiVersion": "metrics.k8s.io/v1beta1",
  "metadata": {
    "selfLink": "/apis/metrics.k8s.io/v1beta1/nodes"
  },
  "items": [
    {
      "metadata": {
        "name": "k8s-m",
        "selfLink": "/apis/metrics.k8s.io/v1beta1/nodes/k8s-m",
        "creationTimestamp": "2019-01-02T08:12:49Z"
      },
      "timestamp": "2019-01-02T08:11:46Z",
      "window": "30s",
      "usage": {
        "cpu": "391134684n",
        "memory": "1245640Ki"
      }
    },
    {
      "metadata": {
        "name": "node",
        "selfLink": "/apis/metrics.k8s.io/v1beta1/nodes/node",
        "creationTimestamp": "2019-01-02T08:12:49Z"
      },
      "timestamp": "2019-01-02T08:11:44Z",
      "window": "30s",
      "usage": {
        "cpu": "63170360n",
        "memory": "962660Ki"
      }
    }
  ]
}

#使用top
[root@k8s-m 1.8+]# kubectl  top nodes
NAME    CPU(cores)   CPU%   MEMORY(bytes)   MEMORY%   
k8s-m   110m         5%     1216Mi          69%       
node    61m          3%     941Mi           54%       
[root@k8s-m 1.8+]# kubectl  top pod
NAME        CPU(cores)   MEMORY(bytes)   
nginx-pod   0m           2Mi

#安装prometheus+Grafana

#下载yaml
git clone https://github.com/zhangbin804/k8s.git
#导入文件
kubectl create -f  node-exporter.yaml 
kubectl  apply -f prometheus/
kubectl  apply -f grafana/
#查看30003端口服务
http://宿主机IP:30003/graph

#访问Grafana

[root@k8s-m k8s]# kubectl get svc -n kube-system|grep grafana
grafana NodePort 10.108.93.180 <none> 3000:32094/TCP 23m

#账号和密码都是admin