Kubernetes 部署 Metrics Server 获取集群指标数据

系统环境:

  • Kubernetes 版本:1.17.4
  • Metrics Server 版本:0.3.6

示例地址:

一、Metrics Server 简介

介绍 Metrics Server 前首先介绍下 Heapster,该工具是用于 Kubernetes 集群监控和性能分析工具,可以收集节点上的指标数据,例如,节点的 CPU、Memory、Network 和 Disk 的 Metric 数据。不过在 Kubernetes V1.11 版本后将被逐渐废弃。而 Metrics Server 正是 Heapster 的代替者。

Metrics Server 是 Kubernetes 集群核心监控数据的聚合器,可以通过 Metrics API 的形式获取 Metrics 数据,不过仅仅是获取指标的最新值,不对旧值进行存储,且不负责将指标转发到第三方目标。Metrics Server 还可以与 Kubectl 工具结合使用,提供 kubectl top 命令来展示集群中的指标数据,接下来我们开始部署 Metrics Server。

 

二、部署应用权限 RBAC 资源

Kubernetes 部署 Metrics Server 前需要先提前部署 RBAC 相关配置,这样 Metrics Server 才能有足够的权限获取系统组件的信息。

 

创建 Metrics RBAC 文件

metrics-rbac.yaml

## ServiceAccount
apiVersion: v1
kind: ServiceAccount
metadata:
  name: metrics-server
  namespace: kube-system
---
## ClusterRole aggregated-metrics-reader
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: system:aggregated-metrics-reader
  labels:
    rbac.authorization.k8s.io/aggregate-to-view: "true"
    rbac.authorization.k8s.io/aggregate-to-edit: "true"
    rbac.authorization.k8s.io/aggregate-to-admin: "true"
rules:
- apiGroups: ["metrics.k8s.io"]
  resources: ["pods","nodes"]
  verbs: ["get","list","watch"]
---
## ClusterRole metrics-server
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: system:metrics-server
rules:
- apiGroups: [""]
  resources: ["pods","nodes","nodes/stats","namespaces","configmaps"]
  verbs: ["get","list","watch"]
---
## ClusterRoleBinding auth-delegator
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: metrics-server:system:auth-delegator
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: system:auth-delegator
subjects:
- kind: ServiceAccount
  name: metrics-server
  namespace: kube-system
---
## RoleBinding metrics-server-auth-reader
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: metrics-server-auth-reader
  namespace: kube-system
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: Role
  name: extension-apiserver-authentication-reader
subjects:
- kind: ServiceAccount
  name: metrics-server
  namespace: kube-system
---
## ClusterRoleBinding system:metrics-server
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: system:metrics-server
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: system:metrics-server
subjects:
- kind: ServiceAccount
  name: metrics-server
  namespace: kube-system

通过 Kubectl 工具部署 Metrics RBAC

  • -n:指定部署应用的 Namespace 命名空间
$ kubectl apply -f metrics-rbac.yaml -n kube-system

三、部署 APIService 资源

设置扩展 API Service 工作于聚合层,允许使用其 API 扩展 Kubernetes apiserver,而这些 API 并不是核心 Kubernetes API 的一部分。这里部署 APIservice 资源,来提供 Kubernetes Metrics 指标 API 数据。

创建 Metrics APIService 文件

metrics-api-service.yaml

## APIService
apiVersion: apiregistration.k8s.io/v1beta1
kind: APIService
metadata:
  name: v1beta1.metrics.k8s.io
spec:
  service:
    name: metrics-server
    namespace: kube-system
  group: metrics.k8s.io
  version: v1beta1
  insecureSkipTLSVerify: true
  groupPriorityMinimum: 100
  versionPriority: 100

通过 Kubectl 工具部署 Metrics APIService

  • -n:指定部署应用的 Namespace 命名空间
$ kubectl apply -f metrics-api-service.yaml -n kube-system

四、部署 Metrics Server 应用

创建 Metrics 部署文件

metrics-server-deploy.yaml

## Service
apiVersion: v1
kind: Service
metadata:
  name: metrics-server
  namespace: kube-system
  labels:
    kubernetes.io/name: "Metrics-server"
    kubernetes.io/cluster-service: "true"
spec:
  selector:
    k8s-app: metrics-server
  ports:
  - port: 443
    targetPort: 4443
---
## Deployment
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:
      hostNetwork: true
      serviceAccountName: metrics-server
      containers:
      - name: metrics-server
        image: registry.aliyuncs.com/google_containers/metrics-server-amd64:v0.3.6
        imagePullPolicy: IfNotPresent
        args:
          - --cert-dir=/tmp
          - --secure-port=4443
          - --kubelet-insecure-tls
          - --kubelet-preferred-address-types=InternalDNS,InternalIP,ExternalDNS,ExternalIP,Hostname
        ports:
        - name: main-port
          containerPort: 4443
          protocol: TCP
        securityContext:
          readOnlyRootFilesystem: true
          runAsNonRoot: true
          runAsUser: 1000
        resources:
          limits:
            memory: 1Gi
            cpu: 1000m
          requests:
            memory: 1Gi
            cpu: 1000m
        volumeMounts:
        - name: tmp-dir
          mountPath: /tmp
        - name: localtime
          readOnly: true
          mountPath: /etc/localtime
      volumes:
      - name: tmp-dir
        emptyDir: {}
      - name: localtime
        hostPath:
          type: File
          path: /etc/localtime
      nodeSelector:
        kubernetes.io/os: linux
        kubernetes.io/arch: "amd64"

通过 Kubectl 工具部署 Metrics 应用

  • -n:指定部署应用的 Namespace 命名空间
$ kubectl apply -f metrics-server-deploy.yaml -n kube-system

五、进行测试

当部署完 Metrics Server 后,可以通过 kubectl 工具进行测试,默认支持下面命令:

  • kubectl top pod: 获取 Pod 的 CPU、Memory 使用信息。
  • kubectl top node: 获取 Node 的 CPU、Memory 使用信息。

输入上面命令进行测试,如下:

## 获取全部节点指标信息
$ kubectl top node
NAME            CPU(cores)   CPU%   MEMORY(bytes)   MEMORY%   
k8s-master      228m         5%     1204Mi          44%       
k8s-node-2-12   131m         1%     1843Mi          23%       
k8s-node-2-13   73m          0%     576Mi           7%     

## 获取某个 Namespace Pod 的指标信息
$ kubectl top pods -n kube-system
NAME                                         CPU(cores)   MEMORY(bytes)   
coredns-9d85f5447-c82w7                      7m           22Mi            
coredns-9d85f5447-kcmb4                      7m           21Mi            
dashboard-metrics-scraper-65f454dff8-2pts8   1m           22Mi            
etcd-k8s-master                              22m          104Mi           
kube-apiserver-k8s-master                    58m          311Mi           
kube-controller-manager-k8s-master           27m          46Mi

## 获取某个 Namespace 下某个 Pod 的指标信息
$ kubectl top pods coredns-9d85f5447-c82w7 -n kube-system
NAME                      CPU(cores)   MEMORY(bytes)
coredns-9d85f5447-c82w7   7m           21Mi  

## 获取全部 Namespace 下的 Pod 的指标信息
$ kubectl top pods --all-namespaces
NAMESPACE     NAME                                           CPU(cores)   MEMORY(bytes)
kube-system   coredns-9d85f5447-c82w7                        6m           22Mi            
kube-system   coredns-9d85f5447-kcmb4                        6m           21Mi            
kube-system   dashboard-metrics-scraper-65f454dff8-2pts8     1m           22Mi            
kube-system   etcd-k8s-master                                21m          106Mi           
kube-system   kube-apiserver-k8s-master                      62m          311Mi           
kube-system   kube-controller-manager-k8s-master             26m          46Mi            
kube-system   kube-proxy-kpt7c                               2m           36Mi            
kube-system   kube-proxy-zb2l5                               1m           27Mi            
kube-system   kube-scheduler-k8s-master                      5m           21Mi            
kube-system   kubernetes-dashboard-7bf47cd79c-nctx2          1m           55Mi            
kube-system   metrics-server-6d54447849-nnbfk                3m           20Mi    

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