kubernetes Metrics-server 安装

一、Metrics-server安装：

由于使用自动扩容，得安装heapster或metrics-server（由于heapster停止更新故用metrics-server）：

1、安装之前需要为kubernetes增加配置项：

1、为/etc/kubernetes/controller-manager增加启动项：
  ***
    --horizontal-pod-autoscaler-use-rest-clients=true
  ***
 systemctl restart kube-controller-manager

2、为/usr/lib/systemd/system/kube-apiserver.service增加启动项（也可以修改/etc/kubernetes/apiserver文件增加）：
  ***
    --requestheader-client-ca-file=/etc/kubernetes/ssl/ca.pem \
    --requestheader-allowed-names=  \
    --requestheader-extra-headers-prefix=X-Remote-Extra- \
    --requestheader-group-headers=X-Remote-Group \
    --requestheader-username-headers=X-Remote-User \
    --proxy-client-cert-file=/etc/kubernetes/ssl/kubelet-client.crt \
    --proxy-client-key-file=/etc/kubernetes/ssl/kubelet-client.key \
    --enable-aggregator-routing=true
  ***
 systemctl daemon-reload
 systemctl restart kube-apiserver

2、在kubenetes上安装Metrics-server：

1、创建：
kubectl create -f metrics-server.yml 

2、删除：
kubectl delete ServiceAccount metrics-server -n kube-system
kubectl delete ClusterRoleBinding metrics-server:system:auth-delegator -n kube-system
kubectl delete RoleBinding metrics-server-auth-reader -n kube-system
kubectl delete ClusterRole system:metrics-server -n kube-system
kubectl delete  ClusterRoleBinding system:metrics-server -n kube-system
kubectl delete  APIService v1beta1.metrics.k8s.io -n kube-system
kubectl delete Service metrics-server -n kube-system
kubectl delete Deployment metrics-server -n kube-system

注：要修改metrics-server的镜

---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: metrics-server
  namespace: kube-system
---
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: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: system:metrics-server
rules:
  - apiGroups:
      - ""
    resources:
      - pods
      - nodes
      - nodes/stats
      - namespaces
    verbs:
      - get
      - list
      - watch
  - apiGroups:
      - "extensions"
    resources:
      - deployments
    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
---
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: Service
metadata:
  name: metrics-server
  namespace: kube-system
  labels:
    kubernetes.io/name: "Metrics-server"
spec:
  selector:
    k8s-app: metrics-server
  ports:
    - port: 443
      protocol: TCP
      targetPort: 443
---
apiVersion: apps/v1beta2
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
      containers:
        - name: metrics-server
#          image: gcr.io/google_containers/metrics-server-amd64:v0.2.1
          image: 144.202.127.156/google_containers/metrics-server-amd64:v0.2.1
          imagePullPolicy: Always
          command:
            - /metrics-server
            - --source=kubernetes.summary_api:''
          resources:
            requests:
              cpu: 20m
              memory: 200Mi
            limits:
              cpu: 100m
              memory: 500Mi

 3、验证：

1、创建测试资源：
kubectl create -f nginx.yml

2、创建自动伸缩规则：
kubectl autoscale deployment nginx --cpu-percent=75 --min=2 --max=10
kubectl get hpa

NAME           REFERENCE                 TARGETS    MINPODS   MAXPODS   REPLICAS   AGE
bill-service   Deployment/bill-service   0% / 80%   5         10        5          2h
注：TARGETS出现 <unknown> / 80% 说明没有成功就得看metrics-server的日志和hpa的describe来查找原因了。

3、测试是否生效（使用脚本测）：
python pressure-web.py
kubectl get hpa

apiVersion: v1
kind: Service
metadata:
  name: nginx
  labels:
    app: nginx
spec:
  ports:
  - port: 80
    name: web
  selector:
    app: nginx
---
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: web
spec:
  selector:
    matchLabels:
      app: nginx 
  replicas: 3 
  template:
    metadata:
      labels:
        app: nginx 
    spec:
      containers:
      - name: nginx
        image: nginx
        resources:
          limits:
            cpu: 100m
            memory: 100Mi
          requests:
            cpu: 50m
            memory: 50Mi
        ports:
        - containerPort: 80
          name: web

import requests,time,threading

url = "https://www.baidu.com"
requests_timeout = 2


def get_response_time(url,count,ring):
    start_time = time.time()
    try:
        req_obj = requests.get(url,timeout=requests_timeout)
    except requests.exceptions.ReadTimeout as e:
        status = False
    else:
        status = True
    end_time = time.time()
    requests_time = end_time-start_time
    if status and (req_obj.status_code == requests.codes.ok) :
        requests_status = "OK"
    else:
        requests_status = "NO"
    print("第%s轮，第%s连接，请求用时（s）：%s，返回状态：%s"%(ring,count,requests_time,requests_status))


if __name__ == "__main__":
    '''在规定超时时间内，11秒内处理不了100个请求，请求就会累积，一直拖垮'''
    ring = 1
    while True:
        for count in range(100):
            t = threading.Thread(target=get_response_time,args=(url,count,ring))
            time.sleep(0.01)
            t.start()
        time.sleep(10)
        ring += 1
        print("第%s轮开始"%ring)