Horizontal Pod Autoscaling (HPA)

Horizontal Pod Autoscaling (HPA) 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

注意:

API 版本对照表

Kubernetes 版本 autoscaling API 版本 支持的 metrics
v1.5+ autoscaling/v1 CPU
v1.6+ autoscaling/v2beta1 Memory及自定义

示例

# 创建 pod 和 service
$ kubectl run php-apache --image=k8s.gcr.io/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    MINPODS   MAXPODS   REPLICAS   AGE
php-apache   Deployment/php-apache/scale   0% / 50%  1         10        1          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   REPLICAS   AGE
php-apache   Deployment/php-apache/scale   305% / 50%  305%      1         10        1          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       MINPODS   MAXPODS   REPLICAS   AGE
php-apache   Deployment/php-apache/scale   0% / 50%     1         10        1          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

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/v1
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:

HPA 最佳实践

  • 为容器配置 CPU Requests
  • HPA 目标设置恰当,如设置 70% 给容器和应用预留 30% 的余量
  • 保持 Pods 和 Nodes 健康(避免 Pod 频繁重建)
  • 保证用户请求的负载均衡
  • 使用 kubectl top nodekubectl top pod 查看资源使用情况
© Pengfei Ni all right reserved,powered by GitbookUpdated at 2018-08-13 08:16:52

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