Container Service for Kubernetes:Deploy AHPA

Step 1: Install the AHPA Controller

1. Log on to the ACK console. In the left navigation pane, click Clusters.

2. On the Clusters page, find the one you want to manage and click its name. In the left navigation pane, click Add-ons.

3. On the Component Management page, find the AHPA Controller component, click Install on its card, and follow the on-screen prompts to complete the installation.

Step 2: Configure the Prometheus data source

1. Log on to the ARMS console.

2. In the left navigation pane, choose Managed Service for Prometheus > Instances.

3. At the top of the Instances page, select the region of the Prometheus instance, and then click the name of the target instance. The instance name is the same as the ACK cluster name.

4. On the Settings page, in the HTTP API URL (Grafana Read URL) section, record the values for the following configuration items.

   • (Optional) If a token is enabled, record the access token.

   • Record the Internal Network endpoint (Prometheus URL).

5. Set the Prometheus query endpoint in the ACK cluster.

   1. Create a file named application-intelligence.yaml with the following content.

      • prometheusUrl: The endpoint of Managed Service for Prometheus.

      • token: The access token for Prometheus.

      apiVersion: v1
      kind: ConfigMap
      metadata:
        name: application-intelligence
        namespace: kube-system
      data:
        prometheusUrl: "http://cn-hangzhou-intranet.arms.aliyuncs.com:9443/api/v1/prometheus/da9d7dece901db4c9fc7f5b9c40****/158120454317****/cc6df477a982145d986e3f79c985a****/cn-hangzhou"
        token: "eyJhxxxxx"

      Note

      To view the AHPA dashboard in Managed Service for Prometheus, you also need to configure the following fields in this ConfigMap:

      • prometheus_writer_url: The private endpoint for Remote Write.

      • prometheus_writer_ak: The AccessKey ID of your Alibaba Cloud account.

      • prometheus_writer_sk: The AccessKey secret of your Alibaba Cloud account.

      For more information, see Enable the Prometheus dashboard for AHPA.

   2. Run the following command to deploy the `application-intelligence` configuration.

      kubectl apply -f application-intelligence.yaml

Step 3: Deploy a test service

The test service includes fib-deployment, fib-svc, and fib-loader, which simulates request peaks and troughs. A Horizontal Pod Autoscaler (HPA) resource is also deployed to compare its scaling results with those of AHPA.

apiVersion: apps/v1
kind: Deployment
metadata:
  name: fib-deployment
  namespace: default
  annotations:
    k8s.aliyun.com/eci-use-specs: "1-2Gi"
spec:
  replicas: 1
  selector:
    matchLabels:
      app: fib-deployment
  strategy:
    rollingUpdate:
      maxSurge: 25%
      maxUnavailable: 25%
    type: RollingUpdate
  template:
    metadata:
      creationTimestamp: null
      labels:
        app: fib-deployment
    spec:
      containers:
      - image: registry.cn-huhehaote.aliyuncs.com/kubeway/knative-sample-fib-server:20200820-171837
        imagePullPolicy: IfNotPresent
        name: user-container
        ports:
        - containerPort: 8080
          name: user-port
          protocol: TCP
        resources:
          limits:
            cpu: "1"
            memory: 2000Mi
          requests:
            cpu: "1"
            memory: 2000Mi
---
apiVersion: v1
kind: Service
metadata:
  name: fib-svc
  namespace: default
spec:
  ports:
  - name: http
    port: 80
    protocol: TCP
    targetPort: 8080
  selector:
    app: fib-deployment
  sessionAffinity: None
  type: ClusterIP
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: fib-loader
  namespace: default
spec:
  progressDeadlineSeconds: 600
  replicas: 1
  revisionHistoryLimit: 10
  selector:
    matchLabels:
      app: fib-loader
  strategy:
    rollingUpdate:
      maxSurge: 25%
      maxUnavailable: 25%
    type: RollingUpdate
  template:
    metadata:
      creationTimestamp: null
      labels:
        app: fib-loader
    spec:
      containers:
      - args:
        - -c
        - |
          /ko-app/fib-loader --service-url="http://fib-svc.${NAMESPACE}?size=35&interval=0" --save-path=/tmp/fib-loader-chart.html
        command:
        - sh
        env:
        - name: NAMESPACE
          valueFrom:
            fieldRef:
              apiVersion: v1
              fieldPath: metadata.namespace
        image: registry.cn-huhehaote.aliyuncs.com/kubeway/knative-sample-fib-loader:20201126-110434
        imagePullPolicy: IfNotPresent
        name: loader
        ports:
        - containerPort: 8090
          name: chart
          protocol: TCP
        resources:
          limits:
            cpu: "8"
            memory: 16000Mi
          requests:
            cpu: "2"
            memory: 4000Mi
---
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
  name: fib-hpa
  namespace: default
spec:
  maxReplicas: 50
  minReplicas: 1
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: fib-deployment
  targetCPUUtilizationPercentage: 50
---

Step 4: Deploy AHPA

Configure an elastic policy by submitting an `AdvancedHorizontalPodAutoscaler` resource.

1. Create a file named ahpa-demo.yaml with the following content.

   apiVersion: autoscaling.alibabacloud.com/v1beta1
   kind: AdvancedHorizontalPodAutoscaler
   metadata:
     name: ahpa-demo
   spec:
     scaleStrategy: observer
     metrics:
     - type: Resource
       resource:
         name: cpu
         target:
           type: Utilization
           averageUtilization: 40
     scaleTargetRef:
       apiVersion: apps/v1
       kind: Deployment
       name: fib-deployment 
     maxReplicas: 100
     minReplicas: 2
     stabilizationWindowSeconds: 300
     prediction:
       quantile: 0.95
       scaleUpForward: 180
     instanceBounds:
     - startTime: "2021-12-16 00:00:00"
       endTime: "2031-12-16 00:00:00"
       bounds:
       - cron: "* 0-8 ? * MON-FRI"
         maxReplicas: 15
         minReplicas: 4
       - cron: "* 9-15 ? * MON-FRI"
         maxReplicas: 15
         minReplicas: 10
       - cron: "* 16-23 ? * MON-FRI"
         maxReplicas: 20
         minReplicas: 15

   The following describes some of the parameters:

   Parameter	Required	Description
   scaleTargetRef	Yes	Specifies the target deployment.
   metrics	Yes	Configures the scaling metrics. Supported metrics include CPU, GPU, Memory, QPS, and RT.
   target	Yes	The target threshold. For example, averageUtilization: 40 indicates that the target CPU utilization is 40%.
   scaleStrategy	No	Sets the scaling mode. The default value is observer. auto: AHPA performs scaling operations. observer: AHPA only observes but does not perform scaling actions. You can use this mode to check if AHPA works as expected. proactive: Only proactive prediction takes effect. reactive: Only reactive prediction takes effect.
   maxReplicas	Yes	The maximum number of replicas for scale-out.
   minReplicas	Yes	The minimum number of replicas for scale-in.
   stabilizationWindowSeconds	No	The cooldown time for scale-in. The default value is 300 seconds.
   prediction. quantile	Yes	The prediction quantile. A higher value indicates a more conservative prediction, meaning a higher probability that the actual metric value will be below the target value. The value must be between 0 and 1, and supports two decimal places. The default value is 0.99. A value from 0.90 to 0.99 is recommended.
   prediction. scaleUpForward	Yes	The time required for a pod to become Ready (cold start time).
   instanceBounds	No	The bounds for the number of instances during a scaling period. startTime: The start time. endTime: The end time.
   instanceBounds. bounds. cron	No	Configures a scheduled task. The cron expression represents a set of times. It uses five space-separated fields. For example, - cron: "* 0-8 ? * MON-FRI" indicates that the task runs from 00:00 to 08:59 every Monday to Friday.

   The following table describes the fields in a cron expression. For more information, see Scheduled tasks.

   Field name	Required	Allowed values	Allowed special characters
   Minutes	Yes	0 to 59	* / , -
   Hours	Yes	0 to 23	* / , -
   Day of Month	Yes	1 to 31	* / , – ?
   Month	Yes	1 to 12 or JAN to DEC	* / , -
   Day of Week	No	0 to 6 or SUN to SAT	* / , – ?

   Note

   • The values for the Month and Day of Week fields are not case-sensitive. For example, SUN, Sun, and sun have the same effect.

   • If the Day of Week field is not configured, the default value is *.

   • Special characters:

     • *: Indicates all possible values.

     • /: Specifies an increment for a numeric value.

     • ,: Lists enumerated values.

     • -: Indicates a range.

     • ?: Indicates that no specific value is specified.

2. Run the following command to create the AHPA elastic policy.

   kubectl apply -f ahpa-demo.yaml

Step 5: View the prediction results

To view the AHPA elastic prediction results, enable the Prometheus dashboard for AHPA.

This topic uses the observer mode as an example. In this mode, the results are compared with the HPA policy. This comparison provides a reference for the actual resources that the application requires and helps you verify whether the AHPA prediction results meet expectations.

Related documents

• To use Managed Service for Prometheus to monitor GPU metrics and implement predictive scaling with AHPA based on GPU metrics, see Use AHPA to perform predictive scaling based on GPU metrics.

• To view the dashboards provided by Managed Service for Prometheus, see Enable the Prometheus dashboard for AHPA.