K8S的HPA

发布时间：2024年01月23日
horiztal Pod Autoscaling：pod的水平自动伸缩，这是k8s自带的模块，它是根据Pod占用cpu比率到达一定的阀值，会触发伸缩机制

Replication controller ?副本控制器：控制pod的副本数

Deployment controller 节点控制器：部署pod

Hpa：控制副本的数量以及控制部署pod

如何检测

Hpa是基于kube-contrroll-manager服务，周期性的检测pod的cpu使用率，默认是30秒检测一次

如何实现

Hpa和replication controller，deployment controller，都属于k8s的资源对象，通过跟踪分析副本控制器和deployment的pod负载变化，针对性的地调整目标pod的副本数。

阀值：正常情况下，pod的副本数，以及达到阀值之后，pod的扩容最大数量

组件

Metrics-server 部署到集群中，对外提供度量的数据

[root@master01 opt]# cd k8s/
[root@master01 k8s]# ls
a.yaml  components.yaml  metrics-server.tar
[root@master01 k8s]# docker load -i metrics-server.tar
[root@master01 k8s]# vim components.yaml

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: 3
  selector:
    matchLabels:
      k8s-app: metrics-server
  strategy:
    rollingUpdate:
      maxUnavailable: 0
  template:
    metadata:
      labels:
        k8s-app: metrics-server
    spec:
      containers:
      - args:
        - --cert-dir=/tmp
        - --secure-port=4443
        - --kubelet-preferred-address-types=InternalIP,ExternalIP,Hostname
        - --kubelet-use-node-status-port
        - --metric-resolution=15s
        - --kubelet-insecure-tls
        image: bitnami/metrics-server:0.6.2
        imagePullPolicy: IfNotPresent
        livenessProbe:
          failureThreshold: 3
          httpGet:
            path: /livez
            port: https
            scheme: HTTPS
          periodSeconds: 10
        name: metrics-server
        ports:
        - containerPort: 4443
          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
          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

[root@master01 k8s]# kubectl get pod -n kube-system
[root@master01 k8s]# kubectl top pod
[root@master01 k8s]# kubectl top node
[root@master01 k8s]# vim a.yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: centos-test
  labels:
    test: centos1
spec:
  replicas: 1
  selector:
    matchLabels:
      test: centos1
  template:
    metadata:
      labels:
        test: centos1
    spec:
      containers:
        - name: centos
          image: centos:7
          command: ["/bin/bash","-c","yum -y install epel-release;yum -y install stress;sleep 3600"]
          resources:
            limits:
              cpu: "1"
              memory: 512Mi
---
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
  name: hpa-centos7
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: centos-test
  minReplicas: 1
  maxReplicas: 3
  targetCPUUtilizationPercentage: 50


[root@master01 k8s]# kubectl apply -f a.yaml
[root@master01 k8s]# kubectl top node
[root@master01 k8s]# kubectl get pod -o wide
[root@master01 k8s]# kubectl get hpa
[root@master01 k8s]# yum -y install stree
[root@master01 k8s]# kubectl exec -it centos-test-b7cd8766d-g84h9 bash
[root@centos-test-b7cd8766d-g84h9 /]# stress --cpu 2
[root@master01 k8s]# kubectl taint node node01 key=1:NoExecute
node/node01 tainted
[root@master01 k8s]# kubectl taint node node02 key=2:NoExecute
node/node02 tainted
[root@master01 k8s]# kubectl describe nodes node01 | grep -i taints
Taints:             key=1:NoExecute
[root@master01 k8s]# kubectl describe nodes node02 | grep -i taints
Taints:             key=2:NoExecute
[root@master01 k8s]# kubectl get hpa -w

?

?HPA的规则

1

定义pod的时候必须要有资源限制，否则HPA无法进行监控

2

扩容时即时的，只要超过阀值会立刻扩容，不是立刻扩容到最大副本数，他会在最小值和最大值之间波动，如果扩容数量满足了需求，就不会再扩容

3

缩容是缓慢地，如果业务的峰值较高，回收的策略太积极的话，可能会产生业务的崩溃，所以缩容的速度是缓慢的，周期性的获取数据，缩容的机制问题

?Pod的副本数扩缩容有两种方式

手动方式

手动方式，修改控制器的副本数

Kubectl scale deployment nginx1 --replicas=5

修改yaml文件，apply -f 部署更新

自动扩缩容

Hap的监控的是cpu

资源限制

pod的资源限制：在部署pod的时候加入resources字段，通过limits/request来对pod进行限制。

除了pod的资源限制还有命名空间的资源限制

命名空间资源限制

如果你有一个lucky-cloud项目部署在test1的命名空间。如果lucky-cloud不做限制或者命名空间不做限制，他依然会占满所有集群资源。

k8s集群部署pod的最大数量：1万个

vim ns.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: centos-test2
  namespace: test1
  labels:
    test: centos2
spec:
  replicas: 11
  selector:
    matchLabels:
      test: centos2
  template:
    metadata:
      labels:
        test: centos2
    spec:
      containers:
        - name: centos
          image: centos:7
          command: ["/bin/bash", "-c", "yum -y install epel-release;yum -y install stress;sleep 3600"]
          resources:
            limits:
              cpu: 1000m
              memory: 512Mi
 
---
 
apiVersion: v1
kind: ResourceQuota
metadata:
  name: ns-resource
  namespace: test1
spec:
  hard:
#硬限制
    pods: "10"
#表示在这个命名空间内只能部署10个pod
    requests.cpu: "2"
#最多只能占用多个个cpu
    requests.memory: 1Gi
#最多只能占用多少内存
    limits.cpu: "4"
#最大需要多少cpu
    limits.memory: 2Gi
#最大需要多少内容
    configmaps: "10"
#当前命名空间内能创建最大的configmap的数量 10个
    persistentvolumeclaims: "4"
#当前命名空间只能使用4个pvc
    secrets: "9"
#创建加密的secrets。只能9个
    services: "5"
#创建service只能5个
    services.nodeports: "2"
#nodeport类型的svc只能2个
[root@master01 k8s]# kubectl describe ns test1
#查看命名空间的限制

?

?通过命名空间的方式对容器进行限制

vim ns2.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: centos-test
  namespace: test2
  labels:
    test: centos2
spec:
  replicas: 1
  selector:
    matchLabels:
      test: centos1
  template:
    metadata:
      labels:
        test: centos1
    spec:
      containers:
        - name: centos
          image: centos:7
          command: ["/bin/bash", "-c", "yum -y install epel-release;yum -y install stress;sleep 3600"]
 
---
 
apiVersion: v1
kind: LimitRange
#表示使用limitrange来进行资源控制的类型
metadata:
  name: test2-limit
  namespace: test2
spec:
  limits:
  - default:
      memory: 512Mi
      cpu: "1"
    defaultRequest:
      memory: 256Mi
      cpu: "0.5"
    type: Container
#对所有部署在这个命名空间内的容器统一进行资源限制
#default: limit
#defaultRequest: request
#type: Container、Pod、Pvc都可以

总结

HPA自动扩缩容

命名空间

第一种

ResourceQuota

可以对命名空间进行资源限制

第二种

LimitRange

直接声明在命名空间当中创建pod。容器的资源限制，这是一种统一限制，所有的pod都受这个条件的制约

Pod的资源限制：一般是我们创建的时候声明号的，必加选项

直接使用resources：

??????????limit:

命名空间资源限制：对命名空间使用cpu和内存一定会做限制，上面和这个两个都必须要做

ResourceQuota

核心： 防止整个集群的资源被一个服务或者一个命名空间占满

命名空间统一资源限制

文章来源:https://blog.csdn.net/2301_79410672/article/details/135767191
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