简介

从Kubernetes 1.8开始,Kubernetes通过Metrics API提供资源使用指标,例如容器CPU和内存使用率。这些度量可以由用户直接访问(例如,通过使用kubectl top命令),或者由集群中的控制器(例如,Horizontal Pod Autoscaler)使用来进行决策,具体的组件为Metrics-Server,用来替换之前的heapster,heapster从1.11开始逐渐被废弃。

Metrics Server是集群核心资源监控数据的聚合器,您可以在CCE控制台中快速安装本插件。

安装本插件后,可在“弹性伸缩”页面的“工作负载伸缩”页签下,创建HPA策略,具体请参见创建工作负载弹性伸缩(HPA)。

社区官方项目及文档:https://github.com/kubernetes-sigs/metrics-server。

作用

Metrics-Server的主要作用为为kube-scheduler,HorizontalPodAutoscaler等k8s核心组件,以及 kubectl top 命令和 Dashboard 等UI组件提供数据来源。

除此之外,也可以自定义Metrics-Server,添加一些其他的监控指标,比如说比较流行的 k8s-prometheus-adapter。

原理

image.png

如何获取监控数据?

Metrics-Server通过kubelet获取监控数据。

在1.7版本之前,k8s在每个节点都安装了一个叫做cAdvisor的程序,负责获取节点和容器的CPU,内存等数据;而在1.7版本及之后,k8s将cAdvisor精简化内置于kubelet中,因此可直接从kubelet中获取数据。

原始数据过于分散且价值不高,因此需要一个叫做resource estimator的程序将来自kubelet的原始数据转换为估算值(如平均,求和)。该程序以DaemonSet方式运行,不过可能也内置于kubelet中。

如何提供监控数据?

Metrics-Server通过metrics API提供监控数据。

先说下API聚合机制,API聚合机制是k8s 1.7版本引入的特性,能将用户扩展的API注册至API Server上。

API Server在此之前只提供k8s资源对象的API,包括资源对象的增删查改功能。举例来说,yaml配置文件中的apiVersion字段描述的即是API名。

有了API聚合机制之后,用户可以发布自己的API,而Metrics-Server用到的metrics API和custom metrics API均属于API聚合机制的应用。

用户可通过配置APIService资源对象以使用API聚合机制,如下是metrics API的配置文件:

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

如上,APIService提供了一个名为v1beta1.metrics.k8s.io的API,并绑定至一个名为metrics-server的Service资源对象。

可以通过kubectl get apiservices命令查询集群中的APIService。

因此,访问Metrics-Server的方式如下:

            /apis/metrics.k8s.io/v1beta1  --->   metrics-server.kube-system.svc  --->   x.x.x.x

+---------+       +-----------+                   +------------------------+        +-----------------------------+
| 发起请求 +----->+ API Server +----------------->+ Service:metrics-server +-------->+ Pod:metrics-server-xxx-xxx |
+---------+       +-----------+                   +------------------------+        +-----------------------------+

有了访问Metrics-Server的方式,HPA,kubectl top等对象就可以正常工作了。

安装插件

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

修改配置:

apiVersion: v1
kind: ServiceAccount
metadata:
  labels:
    k8s-app: metrics-server
  name: metrics-server
  namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  labels:
    k8s-app: metrics-server
    rbac.authorization.k8s.io/aggregate-to-admin: "true"
    rbac.authorization.k8s.io/aggregate-to-edit: "true"
    rbac.authorization.k8s.io/aggregate-to-view: "true"
  name: system:aggregated-metrics-reader
rules:
- apiGroups:
  - metrics.k8s.io
  resources:
  - pods
  - nodes
  verbs:
  - get
  - list
  - watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  labels:
    k8s-app: metrics-server
  name: system:metrics-server
rules:
- apiGroups:
  - ""
  resources:
  - pods
  - nodes
  - nodes/stats
  - namespaces
  - configmaps
  verbs:
  - get
  - list
  - watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  labels:
    k8s-app: metrics-server
  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
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  labels:
    k8s-app: metrics-server
  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
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  labels:
    k8s-app: metrics-server
  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
---
apiVersion: v1
kind: Service
metadata:
  labels:
    k8s-app: metrics-server
  name: metrics-server
  namespace: kube-system
spec:
  ports:
  - name: https
    port: 443
    protocol: TCP
    targetPort: https
  selector:
    k8s-app: metrics-server
---
apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    k8s-app: metrics-server
  name: metrics-server
  namespace: kube-system
spec:
  selector:
    matchLabels:
      k8s-app: metrics-server
  strategy:
    rollingUpdate:
      maxUnavailable: 0
  template:
    metadata:
      labels:
        k8s-app: metrics-server
    spec:
      containers:
      - args:
        - --kubelet-insecure-tls  # 取消证书验证,避免 X509 报错
        - --cert-dir=/tmp
        - --secure-port=443
        - --kubelet-preferred-address-types=InternalIP,ExternalIP,Hostname
        - --kubelet-use-node-status-port
        - --metric-resolution=15s
        image: k8s.gcr.io/metrics-server/metrics-server:v0.5.0
        imagePullPolicy: IfNotPresent
        livenessProbe:
          failureThreshold: 3
          httpGet:
            path: /livez
            port: https
            scheme: HTTPS
          periodSeconds: 10
        name: metrics-server
        ports:
        - containerPort: 443
          name: https
          protocol: TCP
        readinessProbe:
          failureThreshold: 3
          httpGet:
            path: /readyz
            port: https
            scheme: HTTPS
          initialDelaySeconds: 20
          periodSeconds: 10
        resources:
          requests:
            cpu: 100m
            memory: 200Mi
        securityContext:
          readOnlyRootFilesystem: true
          runAsNonRoot: true
          runAsUser: 1000
        volumeMounts:
        - mountPath: /tmp
          name: tmp-dir
      nodeSelector:
        kubernetes.io/os: linux
      priorityClassName: system-cluster-critical
      serviceAccountName: metrics-server
      volumes:
      - emptyDir: {}
        name: tmp-dir
---
apiVersion: apiregistration.k8s.io/v1
kind: APIService
metadata:
  labels:
    k8s-app: metrics-server
  name: v1beta1.metrics.k8s.io
spec:
  group: metrics.k8s.io
  groupPriorityMinimum: 100
  insecureSkipTLSVerify: true
  service:
    name: metrics-server
    namespace: kube-system
  version: v1beta1
  versionPriority: 100
kubectl apply -f components.yaml

配置

--kubelet-preferred-address-types - The priority of node address types used when determining an address for connecting to a particular node (default [Hostname,InternalDNS,InternalIP,ExternalDNS,ExternalIP])
--kubelet-insecure-tls - Do not verify the CA of serving certificates presented by Kubelets. For testing purposes only.
--requestheader-client-ca-file - Specify a root certificate bundle for verifying client certificates on incoming requests.

Kubectl top

node

kubectl top node
NAME      CPU(cores)   CPU%   MEMORY(bytes)   MEMORY%   
server1   266m         6%     6342Mi          82%       
worker1   60m          3%     1595Mi          43%       
worker2   75m          3%     1224Mi          33%  

pod

kubectl top pod 
NAME                                         CPU(cores)   MEMORY(bytes)   
csi-rbd-demo-pod                             1m           2Mi             
csi-rbdplugin-p7bwg                          1m           62Mi            
csi-rbdplugin-provisioner-7574fbcd7d-pwlr6   5m           224Mi           
csi-rbdplugin-twjbm                          1m           122Mi 

注意

Metrics Server基于 内存 存储, 重启后数据将全部丢失,而且它仅能留存最近收集到的指标数据,因此,如果用户期望访问历史数据,就不得不借助于第三方 的监控系统( 如 Prometheus 等)。