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k8s 学习笔记之 Pod 控制器——Horizontal Pod Autoscaler（HPA）

发布时间 2023-08-05 14:57:44作者: 三眠

在之前的学习中，我们已经可以实现通过手工执行kubectl scale命令实现 Pod 扩容或缩容，但是这显然不符合 Kubernetes 的定位目标——自动化、智能化。Kubernetes 期望可以实现通过监测 Pod 的使用情况，实现 pod 数量的自动调整，于是就产生了 Horizontal Pod Autoscaler（HPA）这种控制器。

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 与之前的 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。

接下来，我们来做一个实验

1. 安装 metrics-server

metrics-server 可以用来收集集群中的资源使用情况

# 安装git
[root@k8s-master01 ~]# yum install git -y
# 获取 metrics-server, 注意使用的版本
[root@k8s-master01 ~]# git clone -b v0.3.6 https://github.com/kubernetes-incubator/metrics-server
# 修改 deployment, 注意修改的是镜像和初始化参数
[root@k8s-master01 ~]# cd /root/metrics-server/deploy/1.8+/
[root@k8s-master01 1.8+]# vim metrics-server-deployment.yaml
按图中添加下面选项
`spec` 下的选项：
hostNetwork: true

`spec.containers` 下的选项
image: registry.cn-hangzhou.aliyuncs.com/google_containers/metrics-server-amd64:v0.3.6
args:
- --kubelet-insecure-tls
- --kubelet-preferred-address-types=InternalIP,Hostname,InternalDNS,ExternalDNS,ExternalIP


# 安装 metrics-server
[root@k8s-master01 1.8+]# kubectl apply -f ./

# 查看 pod 运行情况
[root@k8s-master01 1.8+]# kubectl get pod -n kube-system
metrics-server-6b976979db-2xwbj   1/1     Running   0          90s

# 使用 kubectl top node 查看资源使用情况（采集数据需要一点时间）
[root@k8s-master01 1.8+]# kubectl top node
NAME           CPU(cores)   CPU%   MEMORY(bytes)   MEMORY%
k8s-master01   289m         14%    1582Mi          54%       
k8s-node01     81m          4%     1195Mi          40%       
k8s-node02     72m          3%     1211Mi          41%  
[root@k8s-master01 1.8+]# kubectl top pod -n kube-system
NAME                              CPU(cores)   MEMORY(bytes)
coredns-6955765f44-7ptsb          3m           9Mi
coredns-6955765f44-vcwr5          3m           8Mi
etcd-master                       14m          145Mi
...
# 至此，metrics-server 安装完成

2. 准备 deployment 和 servie

创建 pc-hpa-pod.yaml 文件，内容如下：

apiVersion: apps/v1
kind: Deployment
metadata:
  name: nginx
  namespace: dev
spec:
  strategy: # 策略
    type: RollingUpdate # 滚动更新策略
  replicas: 1
  selector:
    matchLabels:
      app: nginx-pod
  template:
    metadata:
      labels:
        app: nginx-pod
    spec:
      containers:
      - name: nginx
        image: nginx:1.17.1
        resources: # 资源配额
          limits:  # 限制资源（上限）
            cpu: "1" # CPU 限制，单位是 core 数
          requests: # 请求资源（下限）
            cpu: "100m"  # CPU 限制，单位是 core 数

# 创建 service
[root@k8s-master01 1.8+]# kubectl expose deployment nginx --type=NodePort --port=80 -n dev

# 查看
[root@k8s-master01 1.8+]# kubectl get deployment,pod,svc -n dev
NAME                    READY   UP-TO-DATE   AVAILABLE   AGE
deployment.apps/nginx   1/1     1            1           47s

NAME                         READY   STATUS    RESTARTS   AGE
pod/nginx-7df9756ccc-bh8dr   1/1     Running   0          47s

NAME            TYPE       CLUSTER-IP      EXTERNAL-IP   PORT(S)        AGE
service/nginx   NodePort   10.101.18.29   <none>        80:31830/TCP   35s

3. 部署 HPA

创建 pc-hpa.yaml 文件，内容如下：

apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
  name: pc-hpa
  namespace: dev
spec:
  minReplicas: 1  #最小 pod 数量
  maxReplicas: 10 #最大 pod 数量
  targetCPUUtilizationPercentage: 3 # CPU 使用率指标
  scaleTargetRef:   # 指定要控制的 nginx 信息
    apiVersion: apps/v1
    kind: Deployment
    name: nginx

# 创建 hpa
[root@k8s-master01 1.8+]# kubectl create -f pc-hpa.yaml
horizontalpodautoscaler.autoscaling/pc-hpa created

# 查看 hpa
    [root@k8s-master01 1.8+]# kubectl get hpa -n dev
NAME     REFERENCE          TARGETS   MINPODS   MAXPODS   REPLICAS   AGE
pc-hpa   Deployment/nginx   0%/3%     1         10        1          62s

4. 测试

使用压测工具对 service 地址192.168.x.x:xxxxx进行压测，然后通过控制台查看 hpa 和 pod 的变化

hpa 变化

[root@k8s-master01 ~]# kubectl get hpa -n dev -w
NAME   REFERENCE      TARGETS  MINPODS  MAXPODS  REPLICAS  AGE
pc-hpa  Deployment/nginx  0%/3%   1     10     1      4m11s
pc-hpa  Deployment/nginx  0%/3%   1     10     1      5m19s
pc-hpa  Deployment/nginx  22%/3%   1     10     1      6m50s
pc-hpa  Deployment/nginx  22%/3%   1     10     4      7m5s
pc-hpa  Deployment/nginx  22%/3%   1     10     8      7m21s
pc-hpa  Deployment/nginx  6%/3%   1     10     8      7m51s
pc-hpa  Deployment/nginx  0%/3%   1     10     8      9m6s
pc-hpa  Deployment/nginx  0%/3%   1     10     8      13m
pc-hpa  Deployment/nginx  0%/3%   1     10     1      14m

deployment 变化

[root@k8s-master01 ~]# kubectl get deployment -n dev -w
NAME    READY   UP-TO-DATE   AVAILABLE   AGE
nginx   1/1     1            1           11m
nginx   1/4     1            1           13m
nginx   1/4     1            1           13m
nginx   1/4     1            1           13m
nginx   1/4     4            1           13m
nginx   1/8     4            1           14m
nginx   1/8     4            1           14m
nginx   1/8     4            1           14m
nginx   1/8     8            1           14m
nginx   2/8     8            2           14m
nginx   3/8     8            3           14m
nginx   4/8     8            4           14m
nginx   5/8     8            5           14m
nginx   6/8     8            6           14m
nginx   7/8     8            7           14m
nginx   8/8     8            8           15m
nginx   8/1     8            8           20m
nginx   8/1     8            8           20m
nginx   1/1     1            1           20m

pod 变化

[root@k8s-master01 ~]# kubectl get pods -n dev -w
NAME                     READY   STATUS    RESTARTS   AGE
nginx-7df9756ccc-bh8dr   1/1     Running   0          11m
nginx-7df9756ccc-cpgrv   0/1     Pending   0          0s
nginx-7df9756ccc-8zhwk   0/1     Pending   0          0s
nginx-7df9756ccc-rr9bn   0/1     Pending   0          0s
nginx-7df9756ccc-cpgrv   0/1     ContainerCreating   0          0s
nginx-7df9756ccc-8zhwk   0/1     ContainerCreating   0          0s
nginx-7df9756ccc-rr9bn   0/1     ContainerCreating   0          0s
nginx-7df9756ccc-m9gsj   0/1     Pending             0          0s
nginx-7df9756ccc-g56qb   0/1     Pending             0          0s
nginx-7df9756ccc-sl9c6   0/1     Pending             0          0s
nginx-7df9756ccc-fgst7   0/1     Pending             0          0s
nginx-7df9756ccc-g56qb   0/1     ContainerCreating   0          0s
nginx-7df9756ccc-m9gsj   0/1     ContainerCreating   0          0s
nginx-7df9756ccc-sl9c6   0/1     ContainerCreating   0          0s
nginx-7df9756ccc-fgst7   0/1     ContainerCreating   0          0s
nginx-7df9756ccc-8zhwk   1/1     Running             0          19s
nginx-7df9756ccc-rr9bn   1/1     Running             0          30s
nginx-7df9756ccc-m9gsj   1/1     Running             0          21s
nginx-7df9756ccc-cpgrv   1/1     Running             0          47s
nginx-7df9756ccc-sl9c6   1/1     Running             0          33s
nginx-7df9756ccc-g56qb   1/1     Running             0          48s
nginx-7df9756ccc-fgst7   1/1     Running             0          66s
nginx-7df9756ccc-fgst7   1/1     Terminating         0          6m50s
nginx-7df9756ccc-8zhwk   1/1     Terminating         0          7m5s
nginx-7df9756ccc-cpgrv   1/1     Terminating         0          7m5s
nginx-7df9756ccc-g56qb   1/1     Terminating         0          6m50s
nginx-7df9756ccc-rr9bn   1/1     Terminating         0          7m5s
nginx-7df9756ccc-m9gsj   1/1     Terminating         0          6m50s
nginx-7df9756ccc-sl9c6   1/1     Terminating         0          6m50s