【k8s】基于k8s安装高可用HPA扩展

基于k8s安装高可用HPA扩展

最近在部署k8s集群的时候有个需求，需要容器能够弹性扩展，如果资源达到一定程序，能够自动新建容器和销毁容器释放资源，这时候就想到了HPA能够实现这个功能，通过metrics-server来监控容器资源的使用情况，根据实际业务系统是否需要扩展定好规则从而到达自动扩缩容的目的。

安装metrics-server

服务器上新增文件high-availability.yaml,用来直接生成容器，文件命名无所谓，文件内容如下：

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:
  - nodes/metrics
  verbs:
  - get
- apiGroups:
  - ""
  resources:
  - pods
  - nodes
  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:
  replicas: 2
  selector:
    matchLabels:
      k8s-app: metrics-server
  strategy:
    rollingUpdate:
      maxUnavailable: 1
  template:
    metadata:
      labels:
        k8s-app: metrics-server
    spec:
      affinity:
        podAntiAffinity:
          requiredDuringSchedulingIgnoredDuringExecution:
          - labelSelector:
              matchLabels:
                k8s-app: metrics-server
            namespaces:
            - kube-system
            topologyKey: kubernetes.io/hostname
      containers:
      - args:
        - --cert-dir=/tmp
        - --secure-port=10250
        - --kubelet-preferred-address-types=InternalIP,ExternalIP,Hostname
        - --kubelet-use-node-status-port
        - --metric-resolution=15s
        - --kubelet-insecure-tls
        image: registry.k8s.io/metrics-server/metrics-server:v0.7.1
        imagePullPolicy: IfNotPresent
        livenessProbe:
          failureThreshold: 3
          httpGet:
            path: /livez
            port: https
            scheme: HTTPS
          periodSeconds: 10
        name: metrics-server
        ports:
        - containerPort: 10250
          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:
          allowPrivilegeEscalation: false
          capabilities:
            drop:
            - ALL
          readOnlyRootFilesystem: true
          runAsNonRoot: true
          runAsUser: 1000
          seccompProfile:
            type: RuntimeDefault
        volumeMounts:
        - mountPath: /tmp
          name: tmp-dir
      nodeSelector:
        kubernetes.io/os: linux
      priorityClassName: system-cluster-critical
      serviceAccountName: metrics-server
      volumes:
      - emptyDir: {}
        name: tmp-dir
---
apiVersion: policy/v1
kind: PodDisruptionBudget
metadata:
  labels:
    k8s-app: metrics-server
  name: metrics-server
  namespace: kube-system
spec:
  minAvailable: 1
  selector:
    matchLabels:
      k8s-app: metrics-server
---
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

如果下载太慢，可以修改image: registry.k8s.io/metrics-server/metrics-server:v0.7.1这一段，我实际使用是用的自己搭建的私有镜像仓库，文件上传上去之后：

#执行k8s命令安装容器
kubectl apply –f high-availability.yaml

安装过程基本不会出现其他问题，有可能会出现节点污点问题，直接百度解决一下，或者下次有空我再写篇文章。
安装完成后查看集群资源：

kubectl top nodes

输出正常就安装成功了，接下来就是尝试一下弄个demo试试功能

HPA案例

创建容器的时候先设置好系统资源，一般java应用1/2/4核，2048m这些都可以

然后再服务发现这里（我这里是用的rancher做管理平台）创建一个HPA：

选定好目标以及设置阈值，然后就可以了，测试的时候容器资源调下一点，这样才会有作用。
除了这种方式就是还可以直接通过文件的形式创建，比如test.yaml:

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: static-hpa
  namespace: app-dev
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: static-compent
  minReplicas: 1
  maxReplicas: 4
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 50

然后执行：

kubectl apply test.yaml

通过这种方式也可以。