# 步骤8 使用HPA对Pod进行自动扩展， 使用CA对集群进行自动扩展

> 本节内容概要
* 配置kube-ops-view 观察pod与node的变化,如果是生产系统service请不要对外开放访问。
* 为集群配置一个HPA，并且部署一个应用进行压力测试，验证Pod 横向扩展能力。
* 为集群配置一个CA，使用CA对集群进行自动扩展。
* 为集群配置一个HPA，并且部署一个应用进行压力测试，验证Pod 横向扩展能力。
* 为集群配置一个CA，使用CA对集群进行自动扩展

 

8.1 配置kube-ops-view, 在8.2,8.3操作中持续观察pod和node的变化

   ```bash
   
   kubectl apply -f kube-ops-view/deploy
   
   kubectl get svc kube-ops-view 
   NAME            TYPE           CLUSTER-IP      EXTERNAL-IP                                                             PORT(S)        AGE
   kube-ops-view   LoadBalancer   10.100.41.212   ae8b0671ef684478e82309532558792d-75589102.us-east-1.elb.amazonaws.com   80:32354/TCP   13m
   ```

   ![image-20200728214630797](/Users/wsuam/Library/Application Support/typora-user-images/image-20200728214630797.png)



8.2 使用HPA对Pod进行自动扩展

8.2.1 Install Metrics Server

```bash
# 安装Metrics Server
cd hpa
kubectl apply -f metrics-server-v0.3.6/deploy/1.8+/

# 验证 Metrics Server installation
kubectl get deployment metrics-server -n kube-system
kubectl get apiservice v1beta1.metrics.k8s.io -o yaml
#输出:all checks passed
 conditions:
  - lastTransitionTime: "2020-07-29T15:04:11Z"
    message: all checks passed
    reason: Passed
    status: "True"
    type: Available
```

8.2.2 安装 HPA sample application php-apache

```bash
kubectl apply -f php-apache.yaml

# Set threshold to CPU30% auto-scaling, and up to 5 pod replicas
kubectl autoscale deployment php-apache --cpu-percent=30 --min=1 --max=5
kubectl get hpa
```

8.2.3 开启 load-generator

```bash
kubectl run --generator=run-pod/v1 -it --rm load-generator --image=busybox /bin/sh

# 提示框输入
while true; do wget -q -O- http://php-apache.default.svc.cluster.local; done
```

8.2.4 Check HPA

```bash
#在cloud9中新开一个终端,观察pod变化
kubectl get hpa --watch
NAME         REFERENCE               TARGETS    MINPODS   MAXPODS   REPLICAS   AGE
php-apache   Deployment/php-apache   250%/30%   1         5         4          3m22s

kubectl get deployment php-apache
NAME         READY   UP-TO-DATE   AVAILABLE   AGE
php-apache   5/5     5            5           6m2s

```

8.3 使用CA对集群进行自动扩展

适用于AWS的Cluster Autoscaler提供与Auto Scaling Group 集成。 它使用户可以从四个不同的部署选项中进行选择：
1. 一个Auto Scaling Group - 本节使用的方式
2. 多个Auto Scaling组
3. 自动发现 Auto-Discovery
4. 主节点设置

8.3.1 修改默认ASG弹性组最大容量Max

修改Capacity为
Min: 2
Max: 6

![image-20200729231230494](media/image-20200729231230494.png)

8.3.3 配置Cluster Autoscaler (CA)

```bash
cd cluster-autoscaler

#查看ASG组
aws autoscaling describe-auto-scaling-groups --query "AutoScalingGroups[0].AutoScalingGroupName" --output text



#使用vi编辑cluster_autoscaler.yml替换为你的ASG组，比如eks-deb9cd6d-75ff-2124-ff17-b6f3c4b5a4ef
--nodes=2:6:<AUTOSCALING GROUP NAME>



# Apply IAM Policy
STACK_NAME=$(eksctl get nodegroup --cluster ${CLUSTER_NAME} --region=${AWS_REGION} -o json | jq -r '.[].StackName')
echo $STACK_NAME
ROLE_NAME=$(aws cloudformation describe-stack-resources --stack-name $STACK_NAME --region=${AWS_DEFAULT_REGION} | jq -r '.StackResources[] | select(.ResourceType=="AWS::IAM::Role") | .PhysicalResourceId')
echo $ROLE_NAME



aws iam put-role-policy --role-name $ROLE_NAME --policy-name ASG-Policy-For-Worker --policy-document file://./k8s-asg-policy.json --region ${AWS_DEFAULT_REGION}

aws iam get-role-policy --role-name $ROLE_NAME --policy-name ASG-Policy-For-Worker --region ${AWS_DEFAULT_REGION}

# 部署 CA
kubectl apply -f cluster_autoscaler.yml
kubectl get pod -n kube-system -o wide \
    $(kubectl get po -n kube-system | egrep -o cluster-autoscaler[a-zA-Z0-9-]+)
#查看日志
#kubectl logs -f deployment/cluster-autoscaler -n kube-system


```

8.3.4 水平扩展集群

```bash
#部署测试应用
kubectl apply -f nginx-to-scaleout.yaml
kubectl get deployment/nginx-to-scaleout

# Scale out the ReplicaSet
kubectl scale --replicas=20 deployment/nginx-to-scaleout

kubectl get pods --watch
NAME                                 READY   STATUS    RESTARTS   AGE
busybox                              1/1     Running   0          22h
nginx-to-scaleout-84f9cdbd84-2tklw   1/1     Running   0          17m
nginx-to-scaleout-84f9cdbd84-4rs5d   1/1     Running   0          17m
nginx-to-scaleout-84f9cdbd84-72sb7   1/1     Running   0          17m
nginx-to-scaleout-84f9cdbd84-7rdjb   1/1     Running   0          17m
nginx-to-scaleout-84f9cdbd84-9kpt6   1/1     Running   0          17m
nginx-to-scaleout-84f9cdbd84-h4fd7   1/1     Running   0          17m
nginx-to-scaleout-84f9cdbd84-hxxq7   1/1     Running   0          17m
nginx-to-scaleout-84f9cdbd84-pxhc5   1/1     Running   0          19m
nginx-to-scaleout-84f9cdbd84-snbc7   1/1     Running   0          17m
nginx-to-scaleout-84f9cdbd84-snd56   1/1     Running   0          17m

kubectl logs -f deployment/cluster-autoscaler -n kube-system

#Check the AWS Management Console to confirm that the Auto Scaling groups are scaling up to meet demand. 
aws ec2 describe-instances --filters "Name=tag:eks:cluster-name,Values=${CLUSTER_NAME}" --query "Reservations[].Instances[].[InstanceId,State.Name]" --region ${AWS_REGION}

[
    [
        "i-00a58166f01483577",
        "running"
    ],
    [
        "i-028933f3a55edae59",
        "running"
    ],
    [
        "i-01adcd8b6e3c7ce8c",
        "running"
    ],
    [
        "i-02e545c32952d9879",
        "running"
    ]
]

```

8.3.5 clean up

```bash
kubectl delete -f cluster-autoscaler/nginx-to-scaleout.yaml
kubectl delete -f cluster-autoscaler/cluster_autoscaler.yml
```