一、准备工作

因为pod的metrics信息来源与heapster，所以在开始之前要保证heapster运行正常。heapster的配置可参考前文。我们可以通过运行kubectl top node来验证heapster是否运行正常。

二、针对CPU的HPA演示

1、直接通过kubectl工具来创建hpa

# docker pull siriuszg/hpa-example 
# kubectl get pod,deployment,svc
# kubectl run php-apache --image=siriuszg/hpa-example --requests=cpu=50m --expose --port=80 
# kubectl autoscale deployment php-apache --cpu-percent=10 --min=1 --max=3

# kubectl get deployment,svc,hpa

2、运行一个deployment来制造压力

# kubectl run -i --tty load-generator --image=registry.59iedu.com/busybox /bin/sh
# nslookup php-apache
# while true; do wget -q -O- http://php-apache; done

从输入的日志上看，可以看到自动扩展的过程中有出现“connection refused”，最后我们将制造压力的deployment删除

# kubectl delete deployment load-generator

3、在整个过程中可以新开一个终端来观察hpa自动扩展和收缩的过程

4、排错

Warning FailedGetResourceMetric 12s (x41 over 20m) horizontal-pod-autoscaler unable to get metrics for resource cpu: unable to fetch metrics from API: the server could not find the requested resource (get pods.metrics.k8s.io)

出现上述错误，需要修改kube-controller-manager的配置文件

# grep 'autoscaler' /usr/lib/systemd/system/kube-controller-manager.service    
  --horizontal-pod-autoscaler-use-rest-clients=false
# systemctl daemon-reload
systemctl restart kube-controller-manager

三、针对内存的HPA演示

1、通过yaml文件创建hpa

# cat hpa-memory.yaml 
apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
metadata:
  name: tomcat-shopxx-hpa
  namespace: default
spec:
  scaleTargetRef:
    apiVersion: apps/v1beta1
    kind: Deployment
    name: tomcat-shopxx
  minReplicas: 1
  maxReplicas: 3
  metrics:
  - type: Resource
    resource:
      name: memory
      targetAverageUtilization: 30

# kubectl create -f hpa-memory.yaml 

2、修改deployment的yaml文件，添加资源的requests和limit限制

如果没有相应的资源限制，则describe查看hpa会有报错信息“missing request for memory on container xxxx”

# cat tomcat.yaml 
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: tomcat-shopxx
  namespace: default
spec:
  replicas: 1
  template:
    metadata:
      labels:
        k8s-app: tomcat-shopxx
    spec:
      containers:
      - image: registry.59iedu.com/filebeat:v5.4.0
        imagePullPolicy: Always
        resources:
          requests:
            cpu: "50m"
            memory: "20Mi"
          limits:
            cpu: "100m"
            memory: "50Mi"
        name: filebeat
        volumeMounts:
        - name: app-logs
          mountPath: /log
        - name: filebeat-config
          mountPath: /etc/filebeat/
      - image: registry.59iedu.com/tomcat_shopxx:v1
        name : tomcat-shopxx
        imagePullPolicy: Always
        resources:
          requests:
            cpu: "50m"
            memory: "200Mi"
          limits:
            cpu: "100m"
            memory: "250Mi"
        env:
        - name: JAVA_OPTS
          value: "-Xmx128m -Xms128m"
        ports:
        - containerPort: 8080
        volumeMounts:
        - name: app-logs
          mountPath: /home/tomcat/logs
      volumes:
      - name: app-logs
        emptyDir: {}
      - name: filebeat-config
        configMap:
          name: filebeat-config

# kubectl apply -f tomcat..yaml 

3、观察hpa过程

#  journalctl -u kube-controller-manager.service -f

# kubectl describe hpa tomcat-shopxx-hpa 

# kubectl get hpa
# kubectl get pod

下文将会介绍基于metric-server的hpa，尽请关注！ 
参考：
https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/
https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/
https://github.com/kubernetes/kubernetes/issues/57673