docker - Kubernetes 自动缩放内存不起作用，但适用于 CPU

Question

我使用的yaml如下所示

    apiVersion: v1
    kind: Service
    metadata:
      name: xxx-svc
      labels:
        app: xxxxxx
    spec:
      type: NodePort
      ports:
      - port: 8080
      selector:
        app: xxxxxx
    ---
    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: my-xxx
      labels:
        app: xxxxxx
    spec:
      selector:
        matchLabels:
          app: xxxxxx
      template:
        metadata:
          labels:
            app: xxxxxx
        spec:
          containers:
          - name: xxxxxx
            image: yyy/xxxxxx:latest
            ports:
            - containerPort: 8080
            resources:
              requests:
                cpu: "100m"
                memory: "504Mi"
              limits:
                cpu: "100m"
                memory: "504Mi"
    ---
    apiVersion: autoscaling/v2beta2
    kind: HorizontalPodAutoscaler
    metadata:
      name: xxxxxx
    spec:
      scaleTargetRef:
        apiVersion: apps/v1
        kind: Deployment
        name: my-xxx
      minReplicas: 1
      maxReplicas: 3
      metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 50
  - type: Resource
    resource:
      name: memory
      target:
        type: Value
        averageValue: 500Mi

服务、HPA、部署一切都已成功部署，但是当我检查 hpa(kubectl get hpa)时，我得到的结果低于结果

NAME        REFERENCE              TARGETS                   MINPODS   
MAXPODS   REPLICAS   AGE

xxxxxx   Deployment/my-xxx   unknown/500Mi, 1%/50%   1         3         3          69m

我得到(kubectl描述hpa)的原因是

Warning FailedComputeMetricsReplicas 21m (x4 over 22m) horizontal-pod-autoscaler failed to get memory utilization: missing request for memory

内存未知但 CPU 正在工作的原因可能是什么

Answer 1

原因:

Warning FailedComputeMetricsReplicas 21m (x4 over 22m) horizontal-pod-autoscaler failed to get memory utilization: missing request for memory

Kubernetes HPA 默认情况下不适用于内存，您需要为内存创建自定义指标，然后使用它。我找到了一些额外的信息here人们如何尝试解决同样的问题。

Pod Memory Based AutoScaling

In this section, we are discussing how you can deploy autoscaling on the basis of memory that pods are consuming. We have used the command “kubectl top pod” to get the utilized pod memory and applied the logic.

• Get the average pod memory of the running pods: Execute the script as follows: