谁能解释这种 Kubernetes HPA 行为？

Question

所以这发生在 EKS K8s v1.15 上。您可以在描述输出中看到 api 版本。 millicpu 在 80 到 120 之间徘徊......这与 HPA 的副本计数完全不匹配......

这是 YAML：

apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
metadata:
  name: sequencer
  namespace: djin-content
spec:
  minReplicas: 1
  maxReplicas: 10
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: sequencer
  metrics:
  - type: Pods
    pods:
      metricName: cpu_usage
      targetAverageValue: 500

这里是 kubectl 描述：

[root@ip-10-150-53-173 ~]# kubectl describe hpa -n djin-content
Name:                   sequencer
Namespace:              djin-content
Labels:                 <none>
Annotations:            kubectl.kubernetes.io/last-applied-configuration:
                          {"apiVersion":"autoscaling/v2beta1","kind":"HorizontalPodAutoscaler","metadata":{"annotations":{},"name":"sequencer","namespace":"djin-con...
CreationTimestamp:      Wed, 05 Aug 2020 20:40:37 +0000
Reference:              Deployment/sequencer
Metrics:                ( current / target )
  "cpu_usage" on pods:  122m / 500
Min replicas:           1
Max replicas:           10
Deployment pods:        7 current / 7 desired
Conditions:
  Type            Status  Reason              Message
  ----            ------  ------              -------
  AbleToScale     True    SucceededRescale    the HPA controller was able to update the target scale to 4
  ScalingActive   True    ValidMetricFound    the HPA was able to successfully calculate a replica count from pods metric cpu_usage
  ScalingLimited  False   DesiredWithinRange  the desired count is within the acceptable range
Events:
  Type    Reason             Age                  From                       Message
  ----    ------             ----                 ----                       -------
  Normal  SuccessfulRescale  34m                  horizontal-pod-autoscaler  New size: 10; reason: pods metric cpu_usage above target
  Normal  SuccessfulRescale  15m (x2 over 34m)    horizontal-pod-autoscaler  New size: 6; reason: pods metric cpu_usage above target
  Normal  SuccessfulRescale  10m                  horizontal-pod-autoscaler  New size: 5; reason: All metrics below target
  Normal  SuccessfulRescale  9m51s (x2 over 23m)  horizontal-pod-autoscaler  New size: 3; reason: All metrics below target
  Normal  SuccessfulRescale  5m (x2 over 16m)     horizontal-pod-autoscaler  New size: 4; reason: pods metric cpu_usage above target
  Normal  SuccessfulRescale  4m45s (x2 over 15m)  horizontal-pod-autoscaler  New size: 5; reason: pods metric cpu_usage above target
  Normal  SuccessfulRescale  4m30s                horizontal-pod-autoscaler  New size: 7; reason: pods metric cpu_usage above target

自定义指标 API 已填充 correctly/frequently 和运行。部署目标工作完美......我已经为这个 API 和副本计算遍历了整个 k8s 代码库，这没有意义......

Answer 1

指标似乎不匹配，您有 122m（毫核）vs / 500 原始数据。

  "cpu_usage" on pods:  122m / 500

您没有指定计算自定义指标的内容，可能是将额外的 0 添加到 122m 使其成为 1220 / 500（我假设 cpu_usage 是自定义指标，因为常规指标服务器指标只是 cpu) 但您可以尝试：

targetAverageValue: 500m

在 CPU 使用情况下执行 HPA 的更常见方法是使用来自指标服务器的 CPU 利用率百分比。

apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
  name: php-apache
  namespace: default
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: php-apache
  minReplicas: 1
  maxReplicas: 10
  targetCPUUtilizationPercentage: 50
...

缩放活动由 K8s 控制平面中的 kube-controlller-manager 管理，如果您启用了 EKS 控制平面日志，您还可以查看那里以找到更多信息。

✌️

Answer 2

前段时间找到了这个问题的答案，忘记更新了。在一个著名的 k8s 项目问题中就这个话题进行了长时间的辩论。它本质上是 k8s HPA 目标（功能？）中的设计错误：https://github.com/kubernetes/kubernetes/issues/78761#issuecomment-670815813

谁能解释这种 Kubernetes HPA 行为？

Can anyone explain this Kubernetes HPA behavior?

kubernetes

amazon-eks

hpa