文章目录
1、基本概念与控制器特点
在前面的课程中，我们可以通过手工执行kubectl scale命令实现Pod扩容，但是这个显然不符合Kubernetes的定位目标 - 自动化、智能化；因此，Kubernetes期望可以通过检测Pod的使用情况实现Pod数量的自动调整，于是就产生了HPA这种控制器；
HPA可以获取每个Pod的利用率，然后和HAP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数量的调整，HPA与之前的Deployment相同，都属于Kubernetes的资源对象，它通过追踪分析目标Pod的负载变化情况，来确定是否需要针对性的调整Pod数量；
2、安装Metric-Server
metric-server可以用来手机集群汇总的资源使用情况；可以通过GitHub下载最新版本的YAML文件，用来安装metrics-server；GitHub获取安装包
#直接在Linux下载metrics-server相关YAML文件
[root@master ~]# wget https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml
#下载完成后修改此文件如下内容
[root@master ~]# vim components.yaml
~
#切记需要修改的位置是Deployment的template中的spec配置内容（请按照要求修改，否则会产生报错！）
129 spec:
130 hostNetwork: true
131 containers:
132 - args:
133 - --cert-dir=/tmp
134 - --secure-port=4443
135 - --kubelet-insecure-tls
136 - --kubelet-preferred-address-types=InternalIP,Hostname,InternalDNS,ExternalDNS,ExternalIP
137 #- --kubelet-preferred-address-types=InternalIP,ExternalIP,Hostname
138 #- --kubelet-use-node-status-port
139 #- --metric-resolution=15s
140 image: registry.cn-hangzhou.aliyuncs.com/google_containers/metrics-server:v0.5.2
#修改完成后调用YAML文件
[root@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
#查看metrics-server的Pod状态
[root@master ~]# kubectl get pod -n kube-system | grep metrics-server
metrics-server-5dbd4664d9-twm2k 1/1 Running 0 3m41s
#查看Node资源使用情况
[root@master ~]# kubectl top node
NAME CPU(cores) CPU% MEMORY(bytes) MEMORY%
master.k8s 104m 1% 2051Mi 26%
node1.k8s 35m 0% 1098Mi 14%
node2.k8s 33m 0% 994Mi 12%
#查看Pod资源使用情况（需要存在Pod方可查看）
[root@master ~]# kubectl top pod
NAME CPU(cores) MEMORY(bytes)
nginx-7cbb8cd5d8-j4m8l 0m 1Mi
# CPU回显参数说明1核为1000m
2、部署Deployment控制器和Service
#创建Deployment控制器YAML文件
[root@master ~]# vim pc-hpa-deploy.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: pc-deployment
namespace: dev
spec:
replicas: 1 #副本数量
selector:
matchLabels:
app: nginx-pod
template:
metadata:
labels:
app: nginx-pod
spec:
containers:
- name: nginx
image: nginx:1.17.1
resources:
requests:
cpu: "20m"
#调用Deployment控制器YAML文件
[root@master ~]# kubectl apply -f pc-hpa-deploy.yaml
deployment.apps/pc-deployment created
#创建Service
[root@master ~]# kubectl expose deploy pc-deployment --type=NodePort --port=80 -n dev
service/pc-deployment exposed
#查看Deploy、Pod、Service
[root@master ~]# kubectl get deploy,pod,svc -n dev
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/pc-deployment 1/1 1 1 68s
NAME READY STATUS RESTARTS AGE
pod/pc-deployment-7d4dcb85c-fmp7n 1/1 Running 0 68s
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/pc-deployment NodePort 10.108.169.162 <none> 80:30925/TCP 31s
3、部署HPA控制器
#创建HPA控制器YAML文件
[root@master ~]# vim pc-hpa.yaml
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
name: pc-hpa
namespace: dev
spec:
minReplicas: 1 #最小副本数量
maxReplicas: 10 #最大副本数量
targetCPUUtilizationPercentage: 3 #CPU使用率指标
scaleTargetRef: #指定需要控制的Deployment信息
apiVersion: apps/v1
kind: Deployment
name: pc-deployment
#调用HPA控制器YAML文件
[root@master ~]# kubectl apply -f pc-hpa.yaml
horizontalpodautoscaler.autoscaling/pc-hpa created
#查看HPA控制器
[root@master ~]# kubectl get hpa -n dev
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
pc-hpa Deployment/pc-deployment 0%/3% 1 10 1 2m15s
4、测试HPA功能
使用Postman工具检测http服务是否可以正常访问；
4.1 使用软件下发多个http请求
点击[save]，保存请求；
创建保存文件；
命名保存文件；
点击保存；
查看保存http请求是否正确；
点击[Runner]；
选择对应的http请求，并修改请求次数（适量即可，不要把自己系统搞崩了）
查看http请求的下发进度；
4.2 查看HPA、Deployment、Pod监控过程
#监控HPA控制器过程
[root@master ~]# kubectl get hpa -n dev -w
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
pc-hpa Deployment/pc-deployment 0%/3% 1 10 1 35s
pc-hpa Deployment/pc-deployment 10%/3% 1 10 1 2m1s
pc-hpa Deployment/pc-deployment 10%/3% 1 10 4 2m17s
pc-hpa Deployment/pc-deployment 75%/3% 1 10 4 3m4s
pc-hpa Deployment/pc-deployment 75%/3% 1 10 8 3m19s
pc-hpa Deployment/pc-deployment 75%/3% 1 10 10 3m34s
pc-hpa Deployment/pc-deployment 20%/3% 1 10 10 4m5s
pc-hpa Deployment/pc-deployment 0%/3% 1 10 10 5m5s
#监控Deploy控制器过程
[root@master ~]# kubectl get deploy -n dev -w
NAME READY UP-TO-DATE AVAILABLE AGE
pc-deployment 1/1 1 1 4m34s
pc-deployment 1/4 1 1 5m31s
pc-deployment 1/4 1 1 5m31s
pc-deployment 1/4 1 1 5m31s
pc-deployment 1/4 4 1 5m31s
pc-deployment 2/4 4 2 5m51s
pc-deployment 3/4 4 3 6m19s
pc-deployment 4/4 4 4 6m19s
pc-deployment 4/8 4 4 6m34s
pc-deployment 4/8 4 4 6m34s
pc-deployment 4/8 4 4 6m34s
pc-deployment 4/8 8 4 6m35s
pc-deployment 5/8 8 5 6m48s
pc-deployment 6/8 8 6 6m49s
pc-deployment 6/10 8 6 6m49s
pc-deployment 6/10 8 6 6m49s
pc-deployment 6/10 8 6 6m49s
pc-deployment 6/10 10 6 6m49s
pc-deployment 7/10 10 7 6m53s
pc-deployment 8/10 10 8 7m15s
pc-deployment 9/10 10 9 7m15s
pc-deployment 10/10 10 10 7m16s
#Deployment控制器最多创建10个Pod
#监控Pod创建过程
[root@master ~]# kubectl get pod -n dev -w
NAME READY STATUS RESTARTS AGE
pc-deployment-7d4dcb85c-fmp7n 1/1 Running 0 4m15s
pc-deployment-7d4dcb85c-lqlrc 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-blwt2 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-2tpr8 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-lqlrc 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-blwt2 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-2tpr8 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-lqlrc 0/1 ContainerCreating 0 0s
pc-deployment-7d4dcb85c-blwt2 0/1 ContainerCreating 0 0s
pc-deployment-7d4dcb85c-2tpr8 0/1 ContainerCreating 0 0s
pc-deployment-7d4dcb85c-blwt2 0/1 ContainerCreating 0 19s
pc-deployment-7d4dcb85c-blwt2 1/1 Running 0 20s
pc-deployment-7d4dcb85c-2tpr8 0/1 ContainerCreating 0 48s
pc-deployment-7d4dcb85c-lqlrc 0/1 ContainerCreating 0 48s
pc-deployment-7d4dcb85c-lqlrc 1/1 Running 0 48s
pc-deployment-7d4dcb85c-2tpr8 1/1 Running 0 48s
pc-deployment-7d4dcb85c-r2fpw 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-bj7k4 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-lzbfp 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-svgs5 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-bj7k4 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-svgs5 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-r2fpw 0/1 Pending 0 1s
pc-deployment-7d4dcb85c-lzbfp 0/1 Pending 0 1s
pc-deployment-7d4dcb85c-bj7k4 0/1 ContainerCreating 0 1s
pc-deployment-7d4dcb85c-svgs5 0/1 ContainerCreating 0 1s
pc-deployment-7d4dcb85c-r2fpw 0/1 ContainerCreating 0 1s
pc-deployment-7d4dcb85c-lzbfp 0/1 ContainerCreating 0 1s
pc-deployment-7d4dcb85c-svgs5 0/1 ContainerCreating 0 13s
pc-deployment-7d4dcb85c-bj7k4 0/1 ContainerCreating 0 14s
pc-deployment-7d4dcb85c-svgs5 1/1 Running 0 14s
pc-deployment-7d4dcb85c-bj7k4 1/1 Running 0 15s
pc-deployment-7d4dcb85c-n7b6w 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-lb6xm 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-n7b6w 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-lb6xm 0/1 Pending 0 0s
pc-deployment-7d4dcb85c-lb6xm 0/1 ContainerCreating 0 0s
pc-deployment-7d4dcb85c-n7b6w 0/1 ContainerCreating 0 1s
pc-deployment-7d4dcb85c-lb6xm 0/1 ContainerCreating 0 3s
pc-deployment-7d4dcb85c-lb6xm 1/1 Running 0 4s
pc-deployment-7d4dcb85c-lzbfp 0/1 ContainerCreating 0 40s
pc-deployment-7d4dcb85c-r2fpw 0/1 ContainerCreating 0 40s
pc-deployment-7d4dcb85c-lzbfp 1/1 Running 0 41s
pc-deployment-7d4dcb85c-n7b6w 0/1 ContainerCreating 0 26s
pc-deployment-7d4dcb85c-r2fpw 1/1 Running 0 41s
pc-deployment-7d4dcb85c-n7b6w 1/1 Running 0 27s
~
#由于内容较多，不再展示
