K8S部署metrics-server

K8S部署metrics-server

• 前言

在新版的K8S中，系统资源的采集均使用Metrics-Server服务，可以通过Metrics-Server服务采集节点和Pod的内存、磁盘、CPU和网络的使用率等信息。

说的具体点：新版K8S资源使用情况的度量（如容器的 CPU 和内存使用）可以通过 Metrics API 获取。

注意：

• Metrics API 只可以查询当前的度量数据，并不保存历史数据
• Metrics API URI 为 /apis/metrics.k8s.io/，在 k8s.io/metrics维护
• 必须部署 metrics-server 才能使用该 API，metrics-server 通过调用 Kubelet Summary API 获取数据

1.下载地址

[root@master0 ~]# wget https://github.com/kubernetes-sigs/metrics-server/archive/v0.3.6.tar.gz
[root@master0 ~]# tar xf metrics-server-0.3.6.tar.gz

2.开始部署

[root@master0 ~]# cd metrics-server-0.3.6/deploy/1.8+/

#文件里面的镜像是无法直接拉去的 可以先搜索一下官方可用的镜像 k8s.gcr.io/metrics-server-amd64:v0.3.6
[root@master0 ~]# docker search metrics-server
[root@master0 ~]# docker pull mirrorgooglecontainers/metrics-server-amd64:v0.3.6

#文件有好几个 只需要更改这个一个metrics-server-deployment文件即可
[root@master0 ~/metrics-server-0.3.6/deploy/1.8+]# vim metrics-server-deployment.yaml 

3. 更改配置文件

[root@master0 ~/metrics-server-0.3.6/deploy/1.8+]# cat metrics-server-deployment.yaml 
---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: metrics-server
  namespace: kube-system
---
apiVersion: apps/v1
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
        # 修改image 和 imagePullPolicy
        # image: k8s.gcr.io/metrics-server-amd64:v0.3.6
        image: mirrorgooglecontainers/metrics-server-amd64:v0.3.6
        imagePullPolicy: IfNotPresent
        # 新增command配置
        command:
        - /metrics-server
        - --kubelet-insecure-tls
        - --kubelet-preferred-address-types=InternalDNS,InternalIP,ExternalDNS,ExternalIP,Hostname
        volumeMounts:
        - name: tmp-dir
          mountPath: /tmp
        # 新增resources配置
        resources:
          limits:
            cpu: 300m
            memory: 200Mi
          requests:
            cpu: 200m
            memory: 100Mi

4. 执行命令

[root@master0 ~/metrics-server-0.3.6/deploy/1.8+]#  kubectl apply -f .
[root@master0 ~]#  kubectl top node
NAME      CPU(cores)   CPU%   MEMORY(bytes)   MEMORY%   
master0   236m         11%    2572Mi          32%       
node01    56m          5%     1019Mi          26%       
node02    56m          5%     1043Mi          27%    

[root@master0 ~]#  kubectl top pods -A
NAMESPACE     NAME                                       CPU(cores)   MEMORY(bytes)   
kube-system   calico-kube-controllers-6dfcd885bf-qz4x8   1m           12Mi            
kube-system   calico-node-5hdsh                          18m          33Mi            
kube-system   calico-node-9lptj                          41m          36Mi            
kube-system   calico-node-zfspg                          20m          35Mi            
kube-system   coredns-6d56c8448f-rdpt6                   3m           14Mi            
kube-system   coredns-6d56c8448f-wr72d                   3m           12Mi            
kube-system   etcd-master0                               19m          54Mi            
kube-system   kube-apiserver-master0                     75m          356Mi           
kube-system   kube-controller-manager-master0            22m          52Mi            
kube-system   kube-proxy-4t924                           3m           16Mi            
kube-system   kube-proxy-cdk27                           1m           18Mi            
kube-system   kube-proxy-tb6nl                           1m           19Mi            
kube-system   kube-scheduler-master0                     4m           23Mi            
kube-system   metrics-server-b7cff9c67-nr5vh             1m           10Mi      

5. 报错

#他要对节点收集状态与部署 一会就可以使用了 不用着急 
[root@master0 ~/metrics-server-0.3.6/deploy/1.8+]# kubectl top node
error: metrics not available yet