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Kubernetes 监控指标获取方式对比

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1 对比

node-exporter用于采集服务器层面的运行指标,包括机器的loadavg、filesystem、meminfo等基础监控,类似于传统主机监控维度的zabbix-agent。

metric-server/heapster是从api-server中获取cpu、内存使用率这种监控指标,并把他们发送给存储后端,如influxdb或云厂商,他当前的核心作用是:为HPA等组件提供决策指标支持

kube-state-metrics关注于获取k8s各种资源的最新状态,如deployment或者daemonset。

例如:

  • 我调度了多少个 replicas?现在可用的有几个?
  • 多少个 Pod 是 running/stopped/terminated 状态?
  • Pod 重启了多少次?
  • 我有多少 job 在运行中

这些指标都由kube-state-metrics提供。

之所以没有把kube-state-metrics纳入到metric-server的能力中,是因为他们的关注点本质上是不一样的。

  • metric-server仅仅是获取、格式化现有数据,写入特定的存储,实质上是一个监控系统。
  • kube-state-metrics是将k8s的运行状况在内存中做了个快照,并且获取新的指标,但他没有能力导出这些指标。

2 部署metric-server

下载metric-server部署的yaml文件到本地

wget https://github.com/kubernetes-sigs/metrics-server/releases/download/v0.3.7/components.yaml
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拉取metric-server的镜像到本地

# docker pull zhaoqinchang/metrics-server:0.3.7
0.3.7: Pulling from zhaoqinchang/metrics-server
9ff2acc3204b: Pull complete 
9d14b55ff9a0: Pull complete 
Digest: sha256:c0efe772bb9e5c289db6cc4bc2002c268507d0226f2a3815f7213e00261c38e9
Status: Downloaded newer image for zhaoqinchang/metrics-server:0.3.7
docker.io/zhaoqinchang/metrics-server:0.3.7
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修改components.yaml文件为如下内容

# cat components.yaml 
---
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"]
---
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
---
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
---
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
---
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
        image: zhaoqinchang/metrics-server:0.3.7    #修改镜像为刚刚拉取下来的镜像
        imagePullPolicy: IfNotPresent
        args:
          - --cert-dir=/tmp
          - --secure-port=4443
        command:                 #添加以下三行command命令
            - /metrics-server
            - --kubelet-preferred-address-types=InternalIP
            - --kubelet-insecure-tls
        ports:
        - name: main-port
          containerPort: 4443
          protocol: TCP
        securityContext:
          readOnlyRootFilesystem: true
          runAsNonRoot: true
          runAsUser: 1000
        volumeMounts:
        - name: tmp-dir
          mountPath: /tmp
      nodeSelector:
        kubernetes.io/os: linux
---
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
    protocol: TCP
    targetPort: main-port
---
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
---
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
复制代码

部署metric-server

# kubectl apply  -f components.yaml 
clusterrole.rbac.authorization.k8s.io/system:aggregated-metrics-reader created
clusterrolebinding.rbac.authorization.k8s.io/metrics-server:system:auth-delegator created
rolebinding.rbac.authorization.k8s.io/metrics-server-auth-reader created
apiservice.apiregistration.k8s.io/v1beta1.metrics.k8s.io created
serviceaccount/metrics-server created
deployment.apps/metrics-server created
service/metrics-server created
clusterrole.rbac.authorization.k8s.io/system:metrics-server created
clusterrolebinding.rbac.authorization.k8s.io/system:metrics-server created
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查看metric.k8s.io是否出现在Kubernetes集群的API群组列表中

# kubectl api-versions | grep metrics 
metrics.k8s.io/v1beta1
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3 使用

kubectl top命令可显示节点和Pod对象的资源使用信息,它依赖于集群中的资源指标API来收集各项指标数据。它包含有node和pod两个子命令,可分别显示Node对象和Pod对象的相关资源占用率。

列出Node资源占用率命令的语法格式为"kubectl top node [-l label | NAME]",例如下面显示所有节点的资源占用状况的结果中显示了各节点累计CPU资源占用时长及百分比,以及内容空间占用量及占用比例。必要时,也可以在命令直接给出要查看的特定节点的标识,以及使用标签选择器进行节点过滤

[root@master metric]# kubectl top nodes
NAME      CPU(cores)   CPU%   MEMORY(bytes)   MEMORY%   
master    282m         14%    1902Mi          51%       
node-02   70m          3%     1371Mi          37%       
node-03   121m         1%     892Mi           11%  
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而名称空间级别的Pod对象资源占用率的使用方法会略有不同,使用时,一般应该跟定名称空间及使用标签选择器过滤出目标Pod对象。例如,下面显示kube-system名称空间下的Pod资源使用状况:

[root@master metric]# kubectl top pods -n kube-system
NAME                              CPU(cores)   MEMORY(bytes)   
etcd-master                       32m          300Mi           
kube-apiserver-master             86m          342Mi           
kube-controller-manager-master    30m          48Mi            
kube-flannel-ds-l5ghn             5m           10Mi            
kube-flannel-ds-rqlm2             4m           12Mi            
kube-flannel-ds-v92r9             4m           14Mi            
kube-proxy-7vjcv                  18m          15Mi            
kube-proxy-xrz8f                  13m          21Mi            
kube-proxy-zpwn6                  1m           14Mi            
kube-scheduler-master             7m           17Mi            
metrics-server-5549c7694f-7vb66   2m           14Mi    
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kubectl top命令为用户提供简洁、快速获取Node对象及Pod对象系统资源占用状况的接口,是集群运行和维护的常用命令之一。

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