Kubernetes HPA 如何评估内存指标

Question

apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
  name: backend-hpa
spec:
  maxReplicas: 10
  minReplicas: 3
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: backend
  metrics:
  - type: Resource
    resource:
      name: memory
      target:
        type: Utilization
        averageUtilization: 70
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
  behavior:
    scaleDown:
      stabilizationWindowSeconds: 300
      policies:
      - type: Pods
        value: 1
        periodSeconds: 100
    scaleUp:
      stabilizationWindowSeconds: 60
      policies:
      - type: Pods
        value: 2
        periodSeconds: 35

我对如何计算内存利用率感到困惑？ 70%是基于什么阈值？

➜ kd hpa       
Name:                                                     prod-backend-hpa-v1
Namespace:                                                prod
Labels:                                                   argocd.argoproj.io/instance=ccl-backend-prod
Annotations:                                              <none>
CreationTimestamp:                                        Mon, 13 Sep 2021 17:39:44 -0700
Reference:                                                Deployment/prod-backend-v1
Metrics:                                                  ( current / target )
  resource memory on pods  (as a percentage of request):  31% (85408426666m) / 70%
  resource cpu on pods  (as a percentage of request):     0% (1m) / 70%
Min replicas:                                             3
Max replicas:                                             10
Behavior:
  Scale Up:
    Stabilization Window: 60 seconds
    Select Policy: Max
    Policies:
      - Type: Pods  Value: 2  Period: 35 seconds
  Scale Down:
    Stabilization Window: 300 seconds
    Select Policy: Max
    Policies:
      - Type: Pods  Value: 1  Period: 100 seconds
Deployment pods:    3 current / 3 desired
Conditions:
  Type            Status  Reason            Message
  ----            ------  ------            -------
  AbleToScale     True    ReadyForNewScale  recommended size matches current size
  ScalingActive   True    ValidMetricFound  the HPA was able to successfully calculate a replica count from memory resource utilization (percentage of request)
  ScalingLimited  True    TooFewReplicas    the desired replica count is less than the minimum replica count
Events:           <none>

这怎么样

resource memory on pods  (as a percentage of request):  31% (85408426666m) / 70%

计算?

我的部署具有以下requests/limits设置

  Containers:
   backend:
    Port:       8080/TCP
    Host Port:  0/TCP
    Command:
      web
    Limits:
      cpu:     1
      memory:  1Gi
    Requests:
      cpu:      200m
      memory:   256Mi

我现在的pods

➜ k top po
W0914 13:38:13.793286 3006942 top_pod.go:140] Using json format to get metrics. Next release will switch to protocol-buffers, switch early by passing --use-protocol-buffers flag
NAME                              CPU(cores)   MEMORY(bytes)   
prod-backend-v1-7858bddc4-5t8r5   1m           80Mi            
prod-backend-v1-7858bddc4-67llh   1m           81Mi            
prod-backend-v1-7858bddc4-98wj2   1m           82Mi

所以好像31%的计算方式是81/256 ~31%.

但是这样做正确吗？

我认为 81/LIMIT = 81/1024 = ~8%.

在逻辑上是正确的

Answer 1

类型=利用率&& `averageUtilization:70`

是所有相关 pods 的资源指标平均值的目标值，表示为 资源请求值 的百分比 pods。目前仅对 Resource metric source type

有效

type=AverageValue && `averageValue: 500Mi`

averageValue 是所有相关 pods 指标平均值的目标值（作为数量）

所以我的 HPA 内存指标变成了：

apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
  name: backend-hpa
spec:
  maxReplicas: 10
  minReplicas: 3
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: backend
  metrics:
  - type: Resource
    resource:
      name: memory
      target:
        type: AverageValue
        averageValue: 500Mi # averageValue is the target value of the average of the metric across all relevant pods (as a quantity), https://www.pulumi.com/docs/reference/pkg/kubernetes/autoscaling/v2beta2/horizontalpodautoscalerlist/#metrictarget
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70 # represented as a percentage of the requested value of the resource for the pods.
  behavior:
    scaleDown:
      stabilizationWindowSeconds: 300
      policies:
      - type: Pods
        value: 1
        periodSeconds: 100
    scaleUp:
      stabilizationWindowSeconds: 60
      policies:
      - type: Pods
        value: 2
        periodSeconds: 35

更多信息： https://www.pulumi.com/docs/reference/pkg/kubernetes/autoscaling/v2beta2/horizontalpodautoscalerlist/#metrictarget

Kubernetes HPA 如何评估内存指标

How memory metric is evaluated by Kubernetes HPA

kubernetes

hpa

我对如何计算内存利用率感到困惑？ 70%是基于什么阈值？

但是这样做正确吗？

类型=利用率&& averageUtilization:70

type=AverageValue && averageValue: 500Mi

类型=利用率&& `averageUtilization:70`

type=AverageValue && `averageValue: 500Mi`