kubernetes云平台管理实战：HPA水平自动伸缩（十一）

一、自动伸缩

1、启动

[root@k8s-master ~]# kubectl autoscale deployment nginx-deployment --max=8 --min=2 --cpu-percent=80
deployment "nginx-deployment" autoscaled

2、查看创建

[root@k8s-master ~]# kubectl get all
NAME                      DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
deploy/nginx-deployment   2         2         2            2           13h
 
NAME                   REFERENCE                     TARGET    CURRENT   MINPODS   MAXPODS   AGE
hpa/nginx-deployment   Deployment/nginx-deployment   80%       0%        2         8         17s
 
NAME             CLUSTER-IP      EXTERNAL-IP   PORT(S)        AGE
svc/kubernetes   10.254.0.1      <none>        443/TCP        2d
svc/nginx        10.254.145.15   <nodes>       80:32000/TCP   1d
 
NAME                             DESIRED   CURRENT   READY     AGE
rs/nginx-deployment-2950479891   0         0         0         13h
rs/nginx-deployment-3113009173   2         2         2         13h
 
NAME                                   READY     STATUS    RESTARTS   AGE
po/nginx-deployment-3113009173-h5plc   1/1       Running   0          17s
po/nginx-deployment-3113009173-vckhg   1/1       Running   1          13h

3、修改副本数为1

[root@k8s-master ~]# kubectl edit deployment nginx-deployment
修改为1
replicas: 1
deployment "nginx-deployment" edited
[root@k8s-master ~]# kubectl get all
NAME                      DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
deploy/nginx-deployment   1         1         1            1           13h
 
NAME             CLUSTER-IP      EXTERNAL-IP   PORT(S)        AGE
svc/kubernetes   10.254.0.1      <none>        443/TCP        2d
svc/nginx        10.254.145.15   <nodes>       80:32000/TCP   1d
 
NAME                             DESIRED   CURRENT   READY     AGE
rs/nginx-deployment-2950479891   0         0         0         13h
rs/nginx-deployment-3113009173   1         1         1         13h
 
NAME                                   READY     STATUS    RESTARTS   AGE
po/nginx-deployment-3113009173-vckhg   1/1       Running   1          13h

二、hpa伸缩

1、编辑horizontalpodautoscaler 文件

[root@k8s-master ~]# kubectl get horizontalpodautoscaler
NAME               REFERENCE                     TARGET    CURRENT   MINPODS   MAXPODS   AGE
nginx-deployment   Deployment/nginx-deployment   80%       0%        2         8         1m
 
# Please edit the object below. Lines beginning with a '#' will be ignored,
# and an empty file will abort the edit. If an error occurs while saving this file will be
# reopened with the relevant failures.
#
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
  creationTimestamp: 2019-01-22T01:00:02Z
  name: nginx-deployment
  namespace: default
  resourceVersion: "41194"
  selfLink: /apis/autoscaling/v1/namespaces/default/horizontalpodautoscalers/nginx-deployment
  uid: 0c897472-1de1-11e9-9773-000c292bd9e1
spec:
  maxReplicas: 8
  minReplicas: 2
  scaleTargetRef:
    apiVersion: extensions/v1beta1
    kind: Deployment
    name: nginx-deployment
  targetCPUUtilizationPercentage: 80
status:
  currentCPUUtilizationPercentage: 0
  currentReplicas: 2
  desiredReplicas: 2
  lastScaleTime: 2019-01-22T01:00:02Z

2、修改副本为1

[root@k8s-master ~]# kubectl edit deployment nginx-deployment
  replicas: 1
deployment "nginx-deployment" edited
[root@k8s-master ~]# kubectl get all
NAME                      DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
deploy/nginx-deployment   2         2         2            2           13h
 
NAME                   REFERENCE                     TARGET    CURRENT   MINPODS   MAXPODS   AGE
hpa/nginx-deployment   Deployment/nginx-deployment   80%       0%        2         8         6m
 
NAME             CLUSTER-IP      EXTERNAL-IP   PORT(S)        AGE
svc/kubernetes   10.254.0.1      <none>        443/TCP        2d
svc/nginx        10.254.145.15   <nodes>       80:32000/TCP   1d
 
NAME                             DESIRED   CURRENT   READY     AGE
rs/nginx-deployment-2950479891   0         0         0         13h
rs/nginx-deployment-3113009173   2         2         2         13h
 
NAME                                   READY     STATUS    RESTARTS   AGE
po/nginx-deployment-3113009173-9hlq1   1/1       Running   0          2s
po/nginx-deployment-3113009173-vckhg   1/1       Running   1          13h

明明修改为1，怎么还有2个？是因为hpa如下配置

spec:
  maxReplicas: 8
  minReplicas: 2

3、修改副本数为5

[root@k8s-master ~]# kubectl edit hpa nginx-deployment
修改：
spec:
  maxReplicas: 8
  minReplicas: 5
horizontalpodautoscaler "nginx-deployment" edited
[root@k8s-master ~]# kubectl get all
NAME                      DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
deploy/nginx-deployment   5         5         5            2           13h
 
NAME                   REFERENCE                     TARGET    CURRENT   MINPODS   MAXPODS   AGE
hpa/nginx-deployment   Deployment/nginx-deployment   80%       0%        5         8         8m
 
NAME             CLUSTER-IP      EXTERNAL-IP   PORT(S)        AGE
svc/kubernetes   10.254.0.1      <none>        443/TCP        2d
svc/nginx        10.254.145.15   <nodes>       80:32000/TCP   1d
 
NAME                             DESIRED   CURRENT   READY     AGE
rs/nginx-deployment-2950479891   0         0         0         13h
rs/nginx-deployment-3113009173   5         5         2         13h
 
NAME                                   READY     STATUS              RESTARTS   AGE
po/nginx-deployment-3113009173-97l9c   0/1       ContainerCreating   0          2s
po/nginx-deployment-3113009173-9hlq1   1/1       Running             0          2m
po/nginx-deployment-3113009173-qq4h8   0/1       ContainerCreating   0          2s
po/nginx-deployment-3113009173-sfp8z   0/1       ContainerCreating   0          2s
po/nginx-deployment-3113009173-vckhg   1/1       Running             1          13h

看到自动伸缩的过程了吧！

三、HAP-deployment-rs-rc-pod调用原理

1、什么是hpa

Horizontal Pod Autoscaling可以根据CPU使用率或应用自定义metrics自动扩展Pod数量（支持replication controller、deployment和replica set）。

控制管理器每隔30s（可以通过–horizontal-pod-autoscaler-sync-period修改）查询metrics的资源使用情况
支持三种metrics类型
- 预定义metrics（比如Pod的CPU）以利用率的方式计算
- 自定义的Pod metrics，以原始值（raw value）的方式计算
- 自定义的object metrics
支持两种metrics查询方式：Heapster和自定义的REST API
支持多metrics

客户端;

通过kubectl创建一个horizontalPodAutoscaler对象，并存储到etcd中

服务端：

api server:负责接受创建hpa对象，然后存入etcd

hpa controler和其他的controler类似，每30s同步一次，将已经创建的hpa进行一次管理（从heapster获取监控数据，查看是否需要scale, controler的store中就保存着从始至终创建出来的hpa，当做一个缓存），watch hpa有变化也会运行。从heapster中获取scale数据，和hpa对比，计算cup利用率等信息，然后重新调整scale。根据hpa.Spec.ScaleTargetRef.Kind（例如Deployment，然后deployment控制器在调整pod数量），调整其值，发送到apiserver存储到etcd，然后更新hpa到etcd.

2、示例

# 创建pod和service
$ kubectl run php-apache --image=gcr.io/google_containers/hpa-example --requests=cpu=200m --expose --port=80
service "php-apache" created
deployment "php-apache" created
 
# 创建autoscaler
$ kubectl autoscale deployment php-apache --cpu-percent=50 --min=1 --max=10
deployment "php-apache" autoscaled
$ kubectl get hpa
NAME         REFERENCE                     TARGET    CURRENT   MINPODS   MAXPODS   AGE
php-apache   Deployment/php-apache/scale   50%       0%        1         10        18s
 
# 增加负载
$ kubectl run -i --tty load-generator --image=busybox /bin/sh
Hit enter for command prompt
$ while true; do wget -q -O- http://php-apache.default.svc.cluster.local; done
 
# 过一会就可以看到负载升高了
$ kubectl get hpa
NAME         REFERENCE                     TARGET    CURRENT   MINPODS   MAXPODS   AGE
php-apache   Deployment/php-apache/scale   50%       305%      1         10        3m
 
# autoscaler将这个deployment扩展为7个pod
$ kubectl get deployment php-apache
NAME         DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
php-apache   7         7         7            7           19m
 
# 删除刚才创建的负载增加pod后会发现负载降低，并且pod数量也自动降回1个
$ kubectl get hpa
NAME         REFERENCE                     TARGET    CURRENT   MINPODS   MAXPODS   AGE
php-apache   Deployment/php-apache/scale   50%       0%        1         10        11m
 
$ kubectl get deployment php-apache
NAME         DESIRED   CURRENT   UP-TO-DATE   AVAILABLE   AGE
php-apache   1         1         1            1           27m

3、关系原理图　

4、小结

1、首先最底层的资源永远都是pod
2、比pod高级一点的资源叫rc副本控制器
3、在pod上面有一个高级的rs
4、那谁来管理rs呢？是deployment
5、HPA自动管理deployment，deployment设置为1，HPA最低设置为3，deployment这就会被自动设计为3个