Horizontal Pod Autoscaler(HPA)控制器
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Horizontal Pod Autoscaler（HPA）是Kubernetes中用于自动根据当前的负载情况，自动调整Pod数量的一种控制器。HPA能够根据CPU使用率、内存使用量或其他选择的度量指标来自动扩展Pod的数量，以确保应用的性能。
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HPA可以获取每个Pod利用率，然后和HPA中定义的指标进行对比，同时计算出需要伸缩的具体值，最后实现Pod的数量的调整。其实HPA与之前Deployment一样，也属于一种Kubernetes资源对象，它通过追踪分析RC控制的所有目标Pod的负载变化情况，来确定是否需要针对性地调整目标Pod的副本数，这是HPA的实现原理。
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HPA的工作原理如下：
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指标收集：Kubernetes会收集Pod的度量指标，如CPU和内存的使用情况。
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比较阈值：HPA会将这些指标与预设的阈值进行比较，这些阈值可以在HPA的配置中定义。
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自动扩缩容：如果当前的负载超出了预设的阈值，HPA会增加Pod的数量以分散负载；如果负载低于阈值，HPA会减少Pod的数量以节省资源。
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持续监控：HPA会持续监控Pod的负载，并根据需要调整Pod的数量。
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安装Metrics Server
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Metrics Server 是 Kubernetes 集群中的一个关键组件，用于收集和报告集群中资源的使用情况，如 CPU 和内存的使用率。这对于使用 HPA（Horizontal Pod Autoscaler）等自动化工具来管理资源至关重要。
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选择 Metrics Server 版本：您需要选择一个与您的 Kubernetes 版本兼容的 Metrics Server 版本。以下是一些版本的兼容性信息43：
Metrics Server 版本 Metrics API group/version 支持的 Kubernetes 版本 0.6.x metrics.k8s.io/v1beta1 1.19+ 0.5.x metrics.k8s.io/v1beta1 *1.8+ 0.4.x metrics.k8s.io/v1beta1 *1.8+ 0.3.x metrics.k8s.io/v1beta1 1.8-1.21
[root@k8s-master ~]# cat components.yaml
apiVersion: v1
kind: ServiceAccount
metadata:labels:k8s-app: metrics-servername: metrics-servernamespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:labels:k8s-app: metrics-serverrbac.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.ioresources:- pods- nodesverbs:- get- list- watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:labels:k8s-app: metrics-servername: system:metrics-server
rules:
- apiGroups:- ""resources:- nodes/metricsverbs:- get
- apiGroups:- ""resources:- pods- nodesverbs:- get- list- watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:labels:k8s-app: metrics-servername: metrics-server-auth-readernamespace: kube-system
roleRef:apiGroup: rbac.authorization.k8s.iokind: Rolename: extension-apiserver-authentication-reader
subjects:
- kind: ServiceAccountname: metrics-servernamespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:labels:k8s-app: metrics-servername: metrics-server:system:auth-delegator
roleRef:apiGroup: rbac.authorization.k8s.iokind: ClusterRolename: system:auth-delegator
subjects:
- kind: ServiceAccountname: metrics-servernamespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:labels:k8s-app: metrics-servername: system:metrics-server
roleRef:apiGroup: rbac.authorization.k8s.iokind: ClusterRolename: system:metrics-server
subjects:
- kind: ServiceAccountname: metrics-servernamespace: kube-system
---
apiVersion: v1
kind: Service
metadata:labels:k8s-app: metrics-servername: metrics-servernamespace: kube-system
spec:ports:- name: httpsport: 443protocol: TCPtargetPort: httpsselector:k8s-app: metrics-server
---
apiVersion: apps/v1
kind: Deployment
metadata:labels:k8s-app: metrics-servername: metrics-servernamespace: kube-system
spec:selector:matchLabels:k8s-app: metrics-serverstrategy:rollingUpdate:maxUnavailable: 0template:metadata:labels:k8s-app: metrics-serverspec: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-tlsimage: registry.cn-hangzhou.aliyuncs.com/google_containers/metrics-server:v0.7.1imagePullPolicy: IfNotPresentlivenessProbe:failureThreshold: 3httpGet:path: /livezport: httpsscheme: HTTPSperiodSeconds: 10name: metrics-serverports:- containerPort: 10250name: httpsprotocol: TCPreadinessProbe:failureThreshold: 3httpGet:path: /readyzport: httpsscheme: HTTPSinitialDelaySeconds: 20periodSeconds: 10resources:requests:cpu: 100mmemory: 200MisecurityContext:allowPrivilegeEscalation: falsecapabilities:drop:- ALLreadOnlyRootFilesystem: truerunAsNonRoot: truerunAsUser: 1000seccompProfile:type: RuntimeDefaultvolumeMounts:- mountPath: /tmpname: tmp-dirnodeSelector:kubernetes.io/os: linuxpriorityClassName: system-cluster-criticalserviceAccountName: metrics-servervolumes:- emptyDir: {}name: tmp-dir
---
apiVersion: apiregistration.k8s.io/v1
kind: APIService
metadata:labels:k8s-app: metrics-servername: v1beta1.metrics.k8s.io
spec:group: metrics.k8s.iogroupPriorityMinimum: 100insecureSkipTLSVerify: trueservice:name: metrics-servernamespace: kube-systemversion: v1beta1versionPriority: 100[root@k8s-master ~]# kubectl apply -f components.yaml
serviceaccount/metrics-server created
clusterrole.rbac.authorization.k8s.io/system:aggregated-metrics-reader created
clusterrole.rbac.authorization.k8s.io/system:metrics-server created
rolebinding.rbac.authorization.k8s.io/metrics-server-auth-reader created
clusterrolebinding.rbac.authorization.k8s.io/metrics-server:system:auth-delegator created
clusterrolebinding.rbac.authorization.k8s.io/system:metrics-server created
service/metrics-server created
deployment.apps/metrics-server created
apiservice.apiregistration.k8s.io/v1beta1.metrics.k8s.io created
[root@k8s-master ~]# kubectl top node
W0119 04:05:38.819138 80109 top_node.go:119] Using json format to get metrics. Next release will switch to protocol-buffers, switch early by passing --use-protocol-buffers flag
Error from server (ServiceUnavailable): the server is currently unable to handle the request (get nodes.metrics.k8s.io)
执行kubectl apply 之后需要等待一段时间等待pod启动
- 查看node的CPU使用率，内存
[root@k8s-master ~]# kubectl top node
W0119 04:08:07.973065 81776 top_node.go:119] Using json format to get metrics. Next release will switch to protocol-buffers, switch early by passing --use-protocol-buffers flag
NAME CPU(cores) CPU% MEMORY(bytes) MEMORY%
k8s-master 351m 17% 1907Mi 51%
k8s-node1 231m 11% 1350Mi 36%
k8s-node2 208m 10% 826Mi 48% -
查看Pod资源占用情况
[root@k8s-master ~]# kubectl get pods -n kube-system
NAME READY STATUS RESTARTS AGE
calico-kube-controllers-697d846cf4-79hpj 1/1 Running 1 24d
calico-node-58ss2 1/1 Running 1 24d
calico-node-gc547 1/1 Running 1 24d
calico-node-hdhxf 1/1 Running 1 24d
coredns-6f6b8cc4f6-5nbb6 1/1 Running 1 24d
coredns-6f6b8cc4f6-q9rhc 1/1 Running 1 24d
etcd-k8s-master 1/1 Running 1 24d
kube-apiserver-k8s-master 1/1 Running 1 24d
kube-controller-manager-k8s-master 1/1 Running 1 24d
kube-proxy-7hp6l 1/1 Running 1 24d
kube-proxy-ddhnb 1/1 Running 1 24d
kube-proxy-dwcgd 1/1 Running 1 24d
kube-scheduler-k8s-master 1/1 Running 1 24d
metrics-server-84d7958dc4-p7gwp 1/1 Running 0 15m
准备deployment和servie
[root@k8s-master ~]# cat k8s-hpa-deploy-svc.yaml
apiVersion: apps/v1
kind: Deployment
metadata:name: nginx-deploynamespace: dev
spec:selector:matchLabels:app: nginxtemplate:metadata:labels:app: nginxspec:containers:- name: nginximage: nginx:1.17.1ports:- containerPort: 80resources: # 资源限制requests:cpu: "100m" # 100m 表示100 milli cpu，即 0.1 个CPU
---
apiVersion: v1
kind: Service
metadata:name: nginx-svc
spec:selector:app: nginxtype: NodePortports:- port: 80 # svc 的访问端口name: nginxtargetPort: 80 # Pod 的访问端口protocol: TCPnodePort: 30010 # 在机器上开端口，浏览器访问[root@k8s-master ~]# kubectl get svc,deploy,pod -n dev -o wide
NAME READY UP-TO-DATE AVAILABLE AGE CONTAINERS IMAGES SELECTOR
deployment.apps/nginx-deploy 1/1 1 1 6s nginx nginx:1.17.1 app=nginxNAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
pod/nginx 1/1 Running 0 12m 10.244.36.73 k8s-node1 <none> <none>
pod/nginx-deploy-65794dcb96-phscq 1/1 Running 0 6s 10.244.36.75 k8s-node1 <none> <none>
[root@k8s-master ~]# kubectl get svc,deployment,pod -n dev -o wide
NAME READY UP-TO-DATE AVAILABLE AGE CONTAINERS IMAGES SELECTOR
deployment.apps/nginx-deploy 1/1 1 1 47s nginx nginx:1.17.1 app=nginxNAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
pod/nginx 1/1 Running 0 12m 10.244.36.73 k8s-node1 <none> <none>
pod/nginx-deploy-65794dcb96-phscq 1/1 Running 0 47s 10.244.36.75 k8s-node1 <none> <none>
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创建service
[root@k8s-master ~]# kubectl expose deployment nginx-deploy --type=NodePort --port=80 -n dev
service/nginx-deploy exposed
[root@k8s-master ~]# kubectl get svc,deployment,pod -n dev -o wide
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE SELECTOR
service/nginx-deploy NodePort 10.96.115.240 <none> 80:31580/TCP 4s app=nginxNAME READY UP-TO-DATE AVAILABLE AGE CONTAINERS IMAGES SELECTOR
deployment.apps/nginx-deploy 1/1 1 1 2m10s nginx nginx:1.17.1 app=nginxNAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
pod/nginx 1/1 Running 0 14m 10.244.36.73 k8s-node1 <none> <none>
pod/nginx-deploy-65794dcb96-phscq 1/1 Running 0 2m10s 10.244.36.75 k8s-node1 <none> <none>
[root@k8s-master ~]# kubectl get svc,deployment,pod -n dev -o wide
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE SELECTOR
service/nginx-deploy NodePort 10.96.115.240 <none> 80:31580/TCP 15s app=nginxNAME READY UP-TO-DATE AVAILABLE AGE CONTAINERS IMAGES SELECTOR
deployment.apps/nginx-deploy 1/1 1 1 2m21s nginx nginx:1.17.1 app=nginxNAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
pod/nginx 1/1 Running 0 14m 10.244.36.73 k8s-node1 <none> <none>
pod/nginx-deploy-65794dcb96-phscq 1/1 Running 0 2m21s 10.244.36.75 k8s-node1 <none> <none>
[root@k8s-master ~]# curl 10.96.115.240:80
<!DOCTYPE html>
<html>
<head>
<title>Welcome to nginx!</title>
<style>body {width: 35em;margin: 0 auto;font-family: Tahoma, Verdana, Arial, sans-serif;}
</style>
</head>
<body>
<h1>Welcome to nginx!</h1>
<p>If you see this page, the nginx web server is successfully installed and
working. Further configuration is required.</p><p>For online documentation and support please refer to
<a href="http://nginx.org/">nginx.org</a>.<br/>
Commercial support is available at
<a href="http://nginx.com/">nginx.com</a>.</p><p><em>Thank you for using nginx.</em></p>
</body>
</html>
提供虚拟机ip加31580访问nginx页面
- 创建 HPA ：
[root@k8s-master ~]# cat k8s-hpa.yaml
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:name: k8s-hpa
spec:minReplicas: 1 # 最小 Pod 数量maxReplicas: 10 # 最大 Pod 数量targetCPUUtilizationPercentage: 3 # CPU 使用率指标，即 CPU 超过 3%（Pod 的 limit 的 cpu ） 就进行扩容scaleTargetRef: # 指定要控制的Nginx的信息apiVersion: apps/v1kind: Deploymentname: nginx-deploy
测试：
kubectl run -i --tty load-generator --rm --image=busybox --restart=Never -- /bin/sh -c "while sleep 0.01; do wget -q -O- http://192.168.65.100:30010; done"通过 kubectl 创建了一个名为 load-generator 的 Pod，它会持续执行 wget 请求，目标地址是 http://192.168.65.100:30010，并且每次请求之间等待 0.01 秒。
- kubectl get deploy -w
[root@k8s-master ~]# kubectl get deploy -w
NAME READY UP-TO-DATE AVAILABLE AGE
nginx-deploy 1/1 1 1 149m
nginx-deploy 1/4 1 1 151m
nginx-deploy 1/4 1 1 151m
nginx-deploy 1/4 1 1 151m
nginx-deploy 1/4 4 1 151m
nginx-deploy 2/4 4 2 151m
nginx-deploy 3/4 4 3 151m
nginx-deploy 4/4 4 4 151m
nginx-deploy 4/8 4 4 151m
nginx-deploy 4/8 4 4 151m
nginx-deploy 4/8 4 4 151m
nginx-deploy 4/8 8 4 151m
nginx-deploy 5/8 8 5 151m
nginx-deploy 6/8 8 6 152m
nginx-deploy 7/8 8 7 152m
nginx-deploy 8/8 8 8 152m
nginx-deploy 8/10 8 8 152m
nginx-deploy 8/10 8 8 152m
nginx-deploy 8/10 8 8 152m
nginx-deploy 8/10 10 8 152m
nginx-deploy 9/10 10 9 152m
nginx-deploy 10/10 10 10 152m
- kubectl get pods -w
[root@k8s-master ~]# kubectl get pods -w
NAME READY STATUS RESTARTS AGE
nginx-deploy-65794dcb96-8c9r8 1/1 Running 0 149m
load-generator 0/1 Pending 0 0s
load-generator 0/1 Pending 0 0s
load-generator 0/1 ContainerCreating 0 0s
load-generator 0/1 ContainerCreating 0 2s
load-generator 0/1 ErrImagePull 0 33s
load-generator 0/1 ImagePullBackOff 0 46s
load-generator 1/1 Running 0 55s
nginx-deploy-65794dcb96-9dp9v 0/1 Pending 0 0s
nginx-deploy-65794dcb96-9dp9v 0/1 Pending 0 0s
nginx-deploy-65794dcb96-drgxc 0/1 Pending 0 0s
nginx-deploy-65794dcb96-6s8ng 0/1 Pending 0 0s
nginx-deploy-65794dcb96-6s8ng 0/1 Pending 0 0s
nginx-deploy-65794dcb96-drgxc 0/1 Pending 0 0s
nginx-deploy-65794dcb96-9dp9v 0/1 ContainerCreating 0 0s
nginx-deploy-65794dcb96-drgxc 0/1 ContainerCreating 0 0s
nginx-deploy-65794dcb96-6s8ng 0/1 ContainerCreating 0 0s
nginx-deploy-65794dcb96-drgxc 0/1 ContainerCreating 0 1s
nginx-deploy-65794dcb96-drgxc 1/1 Running 0 3s
nginx-deploy-65794dcb96-9dp9v 0/1 ContainerCreating 0 4s
nginx-deploy-65794dcb96-6s8ng 0/1 ContainerCreating 0 4s
nginx-deploy-65794dcb96-9dp9v 1/1 Running 0 5s
nginx-deploy-65794dcb96-6s8ng 1/1 Running 0 6s
nginx-deploy-65794dcb96-ctl4k 0/1 Pending 0 0s
nginx-deploy-65794dcb96-ctl4k 0/1 Pending 0 0s
nginx-deploy-65794dcb96-mklzt 0/1 Pending 0 0s
nginx-deploy-65794dcb96-7vj6q 0/1 Pending 0 0s
nginx-deploy-65794dcb96-ctl4k 0/1 ContainerCreating 0 0s
nginx-deploy-65794dcb96-bf2v5 0/1 Pending 0 0s
nginx-deploy-65794dcb96-7vj6q 0/1 Pending 0 0s
nginx-deploy-65794dcb96-mklzt 0/1 Pending 0 0s
nginx-deploy-65794dcb96-bf2v5 0/1 Pending 0 0s
nginx-deploy-65794dcb96-7vj6q 0/1 ContainerCreating 0 0s
nginx-deploy-65794dcb96-mklzt 0/1 ContainerCreating 0 0s
nginx-deploy-65794dcb96-bf2v5 0/1 ContainerCreating 0 0s
nginx-deploy-65794dcb96-ctl4k 0/1 ContainerCreating 0 2s
nginx-deploy-65794dcb96-mklzt 0/1 ContainerCreating 0 3s
nginx-deploy-65794dcb96-7vj6q 0/1 ContainerCreating 0 3s
nginx-deploy-65794dcb96-bf2v5 0/1 ContainerCreating 0 3s
nginx-deploy-65794dcb96-mklzt 1/1 Running 0 3s
nginx-deploy-65794dcb96-ctl4k 1/1 Running 0 4s
nginx-deploy-65794dcb96-7vj6q 1/1 Running 0 4s
nginx-deploy-65794dcb96-bf2v5 1/1 Running 0 5s
nginx-deploy-65794dcb96-drvg4 0/1 Pending 0 0s
nginx-deploy-65794dcb96-drvg4 0/1 Pending 0 0s
nginx-deploy-65794dcb96-6c8lr 0/1 Pending 0 0s
nginx-deploy-65794dcb96-6c8lr 0/1 Pending 0 0s
nginx-deploy-65794dcb96-drvg4 0/1 ContainerCreating 0 0s
nginx-deploy-65794dcb96-6c8lr 0/1 ContainerCreating 0 0s
nginx-deploy-65794dcb96-drvg4 0/1 ContainerCreating 0 3s
nginx-deploy-65794dcb96-6c8lr 0/1 ContainerCreating 0 4s
nginx-deploy-65794dcb96-drvg4 1/1 Running 0 4s
nginx-deploy-65794dcb96-6c8lr 1/1 Running 0 5s
- kubectl get hpa -w
[root@k8s-master ~]# kubectl get hpa -w
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
k8s-hpa Deployment/nginx-deploy <unknown>/3% 1 10 1 2m40s
k8s-hpa Deployment/nginx-deploy 28%/3% 1 10 1 4m32s
k8s-hpa Deployment/nginx-deploy 29%/3% 1 10 4 4m47s
k8s-hpa Deployment/nginx-deploy 9%/3% 1 10 8 5m2s
k8s-hpa Deployment/nginx-deploy 5%/3% 1 10 10 5m17s
k8s-hpa Deployment/nginx-deploy 3%/3% 1 10 10 5m32s
k8s-hpa Deployment/nginx-deploy 2%/3% 1 10 10 6m47s
k8s-hpa Deployment/nginx-deploy 3%/3% 1 10 10 7m2s
k8s-hpa Deployment/nginx-deploy 2%/3% 1 10 10 7m17s
k8s-hpa Deployment/nginx-deploy 3%/3% 1 10 10 7m33s
k8s-hpa Deployment/nginx-deploy 4%/3% 1 10 10 15m
k8s-hpa Deployment/nginx-deploy 3%/3% 1 10 10 16m
k8s-hpa Deployment/nginx-deploy 2%/3% 1 10 10 16m
k8s-hpa Deployment/nginx-deploy 3%/3% 1 10 10 16m
解释：
- 初始时，
nginx-deploy的 HPA 目标 CPU 使用率为 3%。当nginx-deploy的 CPU 使用率达到 28% 时，HPA 会自动增加 Pod 副本数（从 1 增加到 4）。 - 随着负载的变化，Pod 副本数不断调整，最大可扩展到 10 个副本。
- 通过这种机制，Kubernetes 根据实际负载动态调整 Pod 数量，确保服务能够处理增加的流量，并且避免资源浪费。
