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Horizontal Pod Autoscaling

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

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

自定义metrics

使用方法

  • 控制管理器开启--horizontal-pod-autoscaler-use-rest-clients
  • 控制管理器的--apiserver指向API Server Aggregator
  • 在API Server Aggregator中注册自定义的metrics API

注:可以参考k8s.io/metics开发自定义的metrics API server。

比如HorizontalPodAutoscaler保证每个Pod占用50% CPU、1000pps以及10000请求/s:

HPA示例

apiVersion: autoscaling/v2alpha1
kind: HorizontalPodAutoscaler
metadata:
  name: php-apache
  namespace: default
spec:
  scaleTargetRef:
    apiVersion: apps/v1beta1
    kind: Deployment
    name: php-apache
  minReplicas: 1
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      targetAverageUtilization: 50
  - type: Pods
    pods:
      metricName: packets-per-second
      targetAverageValue: 1k
  - type: Object
    object:
      metricName: requests-per-second
      target:
        apiVersion: extensions/v1beta1
        kind: Ingress
        name: main-route
      targetValue: 10k
status:
  observedGeneration: 1
  lastScaleTime: <some-time>
  currentReplicas: 1
  desiredReplicas: 1
  currentMetrics:
  - type: Resource
    resource:
      name: cpu
      currentAverageUtilization: 0
      currentAverageValue: 0

状态条件

v1.7+可以在客户端中看到Kubernetes为HorizontalPodAutoscaler设置的状态条件status.conditions,用来判断HorizontalPodAutoscaler是否可以扩展(AbleToScale)、是否开启扩展(ScalingActive)以及是否受到限制(ScalingLimitted)。

$ kubectl describe hpa cm-test
Name:                           cm-test
Namespace:                      prom
Labels:                         <none>
Annotations:                    <none>
CreationTimestamp:              Fri, 16 Jun 2017 18:09:22 +0000
Reference:                      ReplicationController/cm-test
Metrics:                        ( current / target )
  "http_requests" on pods:      66m / 500m
Min replicas:                   1
Max replicas:                   4
ReplicationController pods:     1 current / 1 desired
Conditions:
  Type                  Status  Reason                  Message
  ----                  ------  ------                  -------
  AbleToScale           True    ReadyForNewScale        the last scale time was sufficiently old as to warrant a new scale
  ScalingActive         True    ValidMetricFound        the HPA was able to successfully calculate a replica count from pods metric http_requests
  ScalingLimited        False   DesiredWithinRange      the desired replica count is within the acceptible range
Events:

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