Horizontal Pod Autoscaler

Using the Kubernetes Horizontal Pod Autoscaler feature (HPA), you can configure your cluster to automatically scale the services it's running up or down.

Note: Clusters created in Rancher v2.0.7 and higher have all the requirements needed (metrics-server and Kubernetes cluster configuration) to use Horizontal Pod Autoscaler.

Why Use Horizontal Pod Autoscaler?

Using HPA, you can automatically scale the number of pods within a replication controller, deployment, or replica set up or down. HPA automatically scales the number of pods that are running for maximum efficiency. Factors that affect the number of pods include:

A minimum and maximum number of pods allowed to run, as defined by the user.
Observed CPU/memory use, as reported in resource metrics.
Custom metrics provided by third-party metrics application like Prometheus, Datadog, etc.

HPA improves your services by:

Releasing hardware resources that would otherwise be wasted by an excessive number of pods.
Increase/decrease performance as needed to accomplish service level agreements.

How HPA Works

HPA Schema

HPA is implemented as a control loop, with a period controlled by the kube-controller-manager flags below:

Flag	Default	Description
`--horizontal-pod-autoscaler-sync-period`	`30s`	How often HPA audits resource/custom metrics in a deployment.
`--horizontal-pod-autoscaler-downscale-delay`	`5m0s`	Following completion of a downscale operation, how long HPA must wait before launching another downscale operations.
`--horizontal-pod-autoscaler-upscale-delay`	`3m0s`	Following completion of an upscale operation, how long HPA must wait before launching another upscale operation.

For full documentation on HPA, refer to the Kubernetes Documentation.

Horizontal Pod Autoscaler API Objects

HPA is an API resource in the Kubernetes autoscaling API group. The current stable version is autoscaling/v1, which only includes support for CPU autoscaling. To get additional support for scaling based on memory and custom metrics, use the beta version instead: autoscaling/v2beta1.

For more information about the HPA API object, see the HPA GitHub Readme.

kubectl Commands

You can create, manage, and delete HPAs using kubectl:

Creating HPA
With manifest: kubectl create -f <HPA_MANIFEST>
Without manifest (Just support CPU): kubectl autoscale deployment hello-world --min=2 --max=5 --cpu-percent=50
Getting HPA info
Basic: kubectl get hpa hello-world
Detailed description: kubectl describe hpa hello-world
Deleting HPA
kubectl delete hpa hello-world

HPA Manifest Definition Example

The following snippet demonstrates use of different directives in an HPA manifest. See the list below the sample to understand the purpose of each directive.

apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
metadata:
  name: hello-world
spec:
  scaleTargetRef:
    apiVersion: extensions/v1beta1
    kind: Deployment
    name: hello-world
  minReplicas: 1
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      targetAverageUtilization: 50
  - type: Resource
    resource:
      name: memory
      targetAverageValue: 100Mi

Directive | Description
---------|----------| apiVersion: autoscaling/v2beta1 | The version of the Kubernetes autoscaling API group in use. This example manifest uses the beta version, so scaling by CPU and memory is enabled. | name: hello-world | Indicates that HPA is performing autoscaling for the hello-word deployment. | minReplicas: 1 | Indicates that the minimum number of replicas running can't go below 1. | maxReplicas: 10 | Indicates the maximum number of replicas in the deployment can't go above 10. targetAverageUtilization: 50 | Indicates the deployment will scale pods up when the average running pod uses more than 50% of its requested CPU. targetAverageValue: 100Mi | Indicates the deployment will scale pods up when the average running pod uses more that 100Mi of memory.

Configuring HPA to Scale Using Resource Metrics

Clusters created in Rancher v2.0.7 and higher have all the requirements needed (metrics-server and Kubernetes cluster configuration) to use Horizontal Pod Autoscaler. Run the following commands to check if metrics are available in your installation:

$ kubectl top nodes
NAME                              CPU(cores)   CPU%      MEMORY(bytes)   MEMORY%
node-controlplane   196m         9%        1623Mi          42%
node-etcd           80m          4%        1090Mi          28%
node-worker         64m          3%        1146Mi          29%
$ kubectl -n kube-system top pods
NAME                                   CPU(cores)   MEMORY(bytes)
canal-pgldr                            18m          46Mi
canal-vhkgr                            20m          45Mi
canal-x5q5v                            17m          37Mi
canal-xknnz                            20m          37Mi
kube-dns-7588d5b5f5-298j2              0m           22Mi
kube-dns-autoscaler-5db9bbb766-t24hw   0m           5Mi
metrics-server-97bc649d5-jxrlt         0m           12Mi
$ kubectl -n kube-system logs -l k8s-app=metrics-server
I1002 12:55:32.172841       1 heapster.go:71] /metrics-server --source=kubernetes.summary_api:https://kubernetes.default.svc?kubeletHttps=true&kubeletPort=10250&useServiceAccount=true&insecure=true
I1002 12:55:32.172994       1 heapster.go:72] Metrics Server version v0.2.1
I1002 12:55:32.173378       1 configs.go:61] Using Kubernetes client with master "https://kubernetes.default.svc" and version
I1002 12:55:32.173401       1 configs.go:62] Using kubelet port 10250
I1002 12:55:32.173946       1 heapster.go:128] Starting with Metric Sink
I1002 12:55:32.592703       1 serving.go:308] Generated self-signed cert (apiserver.local.config/certificates/apiserver.crt, apiserver.local.config/certificates/apiserver.key)
I1002 12:55:32.925630       1 heapster.go:101] Starting Heapster API server...
[restful] 2018/10/02 12:55:32 log.go:33: [restful/swagger] listing is available at https:///swaggerapi
[restful] 2018/10/02 12:55:32 log.go:33: [restful/swagger] https:///swaggerui/ is mapped to folder /swagger-ui/
I1002 12:55:32.928597       1 serve.go:85] Serving securely on 0.0.0.0:443

If you have created your cluster in Rancher v2.0.6 or before, please refer to Manual installation

Configuring HPA to Scale Using Custom Metrics (Prometheus)

You can also configure HPA to autoscale based on custom metrics provided by third-party software. The most common use case for autoscaling using third-party software is based on application-level metrics (i.e., HTTP requests per second). HPA uses the custom.metrics.k8s.io API to consume these metrics. This API is enabled by deploying a custom metrics adapter for the metrics collection solution.

For this example, we are going to use Prometheus. We are beginning with the following assumptions:

Prometheus is deployed in the cluster.
Prometheus is configured correctly and collecting proper metrics from pods, nodes, namespaces, etc.
Prometheus is exposed at the following URL and port: http://prometheus.mycompany.io:80

Prometheus is available for deployment in the Rancher v2.0 catalog. Deploy it from Rancher catalog if it isn't already running in your cluster.

For HPA to use custom metrics from Prometheus, package k8s-prometheus-adapter is required in the kube-system namespace of your cluster. To install k8s-prometheus-adapter, we are using the Helm chart available at banzai-charts.

Initialize Helm in your cluster. # kubectl -n kube-system create serviceaccount tiller kubectl create clusterrolebinding tiller --clusterrole cluster-admin --serviceaccount=kube-system:tiller helm init --service-account tiller
Clone the banzai-charts repo from GitHub: # git clone https://github.com/banzaicloud/banzai-charts
Install the prometheus-adapter chart, specifying the Prometheus URL and port number. # helm install --name prometheus-adapter banzai-charts/prometheus-adapter --set prometheus.url="http://prometheus.mycompany.io",prometheus.port="80" --namespace kube-system
Check that prometheus-adapter is running properly. Check the service pod and logs in the kube-system namespace.
Check that the service pod is Running. Enter the following command. # kubectl get pods -n kube-system From the resulting output, look for a status of Running. NAME READY STATUS RESTARTS AGE ... prometheus-adapter-prometheus-adapter-568674d97f-hbzfx 1/1 Running 0 7h ...
Check the service logs to make sure the service is running correctly by entering the command that follows. # kubectl logs prometheus-adapter-prometheus-adapter-568674d97f-hbzfx -n kube-system Then review the log output to confirm the service is running. {{% accordion id="prometheus-logs" label="Prometheus Adaptor Logs" %}} ... I0724 10:18:45.696679 1 round_trippers.go:436] GET https://10.43.0.1:443/api/v1/namespaces/default/pods?labelSelector=app%3Dhello-world 200 OK in 2 milliseconds I0724 10:18:45.696695 1 round_trippers.go:442] Response Headers: I0724 10:18:45.696699 1 round_trippers.go:445] Date: Tue, 24 Jul 2018 10:18:45 GMT I0724 10:18:45.696703 1 round_trippers.go:445] Content-Type: application/json I0724 10:18:45.696706 1 round_trippers.go:445] Content-Length: 2581 I0724 10:18:45.696766 1 request.go:836] Response Body: {"kind":"PodList","apiVersion":"v1","metadata":{"selfLink":"/api/v1/namespaces/default/pods","resourceVersion":"6237"},"items":[{"metadata":{"name":"hello-world-54764dfbf8-q6l82","generateName":"hello-world-54764dfbf8-","namespace":"default","selfLink":"/api/v1/namespaces/default/pods/hello-world-54764dfbf8-q6l82","uid":"484cb929-8f29-11e8-99d2-067cac34e79c","resourceVersion":"4066","creationTimestamp":"2018-07-24T10:06:50Z","labels":{"app":"hello-world","pod-template-hash":"1032089694"},"annotations":{"cni.projectcalico.org/podIP":"10.42.0.7/32"},"ownerReferences":[{"apiVersion":"extensions/v1beta1","kind":"ReplicaSet","name":"hello-world-54764dfbf8","uid":"4849b9b1-8f29-11e8-99d2-067cac34e79c","controller":true,"blockOwnerDeletion":true}]},"spec":{"volumes":[{"name":"default-token-ncvts","secret":{"secretName":"default-token-ncvts","defaultMode":420}}],"containers":[{"name":"hello-world","image":"rancher/hello-world","ports":[{"containerPort":80,"protocol":"TCP"}],"resources":{"requests":{"cpu":"500m","memory":"64Mi"}},"volumeMounts":[{"name":"default-token-ncvts","readOnly":true,"mountPath":"/var/run/secrets/kubernetes.io/serviceaccount"}],"terminationMessagePath":"/dev/termination-log","terminationMessagePolicy":"File","imagePullPolicy":"Always"}],"restartPolicy":"Always","terminationGracePeriodSeconds":30,"dnsPolicy":"ClusterFirst","serviceAccountName":"default","serviceAccount":"default","nodeName":"34.220.18.140","securityContext":{},"schedulerName":"default-scheduler","tolerations":[{"key":"node.kubernetes.io/not-ready","operator":"Exists","effect":"NoExecute","tolerationSeconds":300},{"key":"node.kubernetes.io/unreachable","operator":"Exists","effect":"NoExecute","tolerationSeconds":300}]},"status":{"phase":"Running","conditions":[{"type":"Initialized","status":"True","lastProbeTime":null,"lastTransitionTime":"2018-07-24T10:06:50Z"},{"type":"Ready","status":"True","lastProbeTime":null,"lastTransitionTime":"2018-07-24T10:06:54Z"},{"type":"PodScheduled","status":"True","lastProbeTime":null,"lastTransitionTime":"2018-07-24T10:06:50Z"}],"hostIP":"34.220.18.140","podIP":"10.42.0.7","startTime":"2018-07-24T10:06:50Z","containerStatuses":[{"name":"hello-world","state":{"running":{"startedAt":"2018-07-24T10:06:54Z"}},"lastState":{},"ready":true,"restartCount":0,"image":"rancher/hello-world:latest","imageID":"docker-pullable://rancher/hello-world@sha256:4b1559cb4b57ca36fa2b313a3c7dde774801aa3a2047930d94e11a45168bc053","containerID":"docker://cce4df5fc0408f03d4adf82c90de222f64c302bf7a04be1c82d584ec31530773"}],"qosClass":"Burstable"}}]} I0724 10:18:45.699525 1 api.go:74] GET http://prometheus-server.prometheus.34.220.18.140.xip.io/api/v1/query?query=sum%28rate%28container_fs_read_seconds_total%7Bpod_name%3D%22hello-world-54764dfbf8-q6l82%22%2Ccontainer_name%21%3D%22POD%22%2Cnamespace%3D%22default%22%7D%5B5m%5D%29%29+by+%28pod_name%29&time=1532427525.697 200 OK I0724 10:18:45.699620 1 api.go:93] Response Body: {"status":"success","data":{"resultType":"vector","result":[{"metric":{"pod_name":"hello-world-54764dfbf8-q6l82"},"value":[1532427525.697,"0"]}]}} I0724 10:18:45.699939 1 wrap.go:42] GET /apis/custom.metrics.k8s.io/v1beta1/namespaces/default/pods/%2A/fs_read?labelSelector=app%3Dhello-world: (12.431262ms) 200 [[kube-controller-manager/v1.10.1 (linux/amd64) kubernetes/d4ab475/system:serviceaccount:kube-system:horizontal-pod-autoscaler] 10.42.0.0:24268] I0724 10:18:51.727845 1 request.go:836] Request Body: {"kind":"SubjectAccessReview","apiVersion":"authorization.k8s.io/v1beta1","metadata":{"creationTimestamp":null},"spec":{"nonResourceAttributes":{"path":"/","verb":"get"},"user":"system:anonymous","group":["system:unauthenticated"]},"status":{"allowed":false}} ... {{% /accordion %}}
Check that the metrics API is accessible from kubectl.
If you are accessing the cluster directly, enter your Server URL in the kubectl config in the following format: https://<Kubernetes_URL>:6443. # kubectl get --raw /apis/custom.metrics.k8s.io/v1beta1 If the API is accessible, you should receive output that's similar to what follows. {{% accordion id="custom-metrics-api-response" label="API Response" %}} {"kind":"APIResourceList","apiVersion":"v1","groupVersion":"custom.metrics.k8s.io/v1beta1","resources":[{"name":"pods/fs_usage_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_rss","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/spec_cpu_period","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/cpu_cfs_throttled","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_io_time","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_read","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_sector_writes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/cpu_user","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/last_seen","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/tasks_state","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/spec_cpu_quota","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/start_time_seconds","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_limit_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_write","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_cache","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_usage_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/cpu_cfs_periods","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/cpu_cfs_throttled_periods","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_reads_merged","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_working_set_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/network_udp_usage","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_inodes_free","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_inodes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_io_time_weighted","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_failures","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_swap","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/spec_cpu_shares","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/spec_memory_swap_limit_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/cpu_usage","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_io_current","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_writes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_failcnt","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_reads","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_writes_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_writes_merged","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/network_tcp_usage","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_max_usage_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/spec_memory_limit_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/spec_memory_reservation_limit_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/cpu_load_average_10s","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/cpu_system","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_reads_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_sector_reads","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]}]} {{% /accordion %}}
If you are accessing the cluster through Rancher, enter your Server URL in the kubectl config in the following format: https://<RANCHER_URL>/k8s/clusters/<CLUSTER_ID>. Add the suffix /k8s/clusters/<CLUSTER_ID> to API path. # kubectl get --raw /k8s/clusters/<CLUSTER_ID>/apis/custom.metrics.k8s.io/v1beta1 If the API is accessible, you should receive output that's similar to what follows. {{% accordion id="custom-metrics-api-response-rancher" label="API Response" %}} {"kind":"APIResourceList","apiVersion":"v1","groupVersion":"custom.metrics.k8s.io/v1beta1","resources":[{"name":"pods/fs_usage_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_rss","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/spec_cpu_period","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/cpu_cfs_throttled","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_io_time","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_read","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_sector_writes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/cpu_user","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/last_seen","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/tasks_state","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/spec_cpu_quota","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/start_time_seconds","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_limit_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_write","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_cache","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_usage_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/cpu_cfs_periods","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/cpu_cfs_throttled_periods","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_reads_merged","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_working_set_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/network_udp_usage","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_inodes_free","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_inodes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_io_time_weighted","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_failures","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_swap","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/spec_cpu_shares","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/spec_memory_swap_limit_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/cpu_usage","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_io_current","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_writes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_failcnt","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_reads","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_writes_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_writes_merged","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/network_tcp_usage","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/memory_max_usage_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/spec_memory_limit_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/spec_memory_reservation_limit_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/cpu_load_average_10s","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/cpu_system","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_reads_bytes","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]},{"name":"pods/fs_sector_reads","singularName":"","namespaced":true,"kind":"MetricValueList","verbs":["get"]}]} {{% /accordion %}}

Testing HPAs with a Service Deployment

For HPA to work correctly, service deployments should have resources request definitions for containers. Follow this hello-world example to test if HPA is working correctly.

Configure kubectl to connect to your Kubernetes cluster.
Copy the hello-world deployment manifest below. {{% accordion id="hello-world" label="Hello World Manifest" %}}

apiVersion: apps/v1beta2
kind: Deployment
metadata:
  labels:
    app: hello-world
  name: hello-world
  namespace: default
spec:
  replicas: 1
  selector:
    matchLabels:
      app: hello-world
  strategy:
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
    type: RollingUpdate
  template:
    metadata:
      labels:
        app: hello-world
    spec:
      containers:
      - image: rancher/hello-world
        imagePullPolicy: Always
        name: hello-world
        resources:
          requests:
            cpu: 500m
            memory: 64Mi
        ports:
        - containerPort: 80
          protocol: TCP
      restartPolicy: Always
---
apiVersion: v1
kind: Service
metadata:
  name: hello-world
  namespace: default
spec:
  ports:
  - port: 80
    protocol: TCP
    targetPort: 80
  selector:
    app: hello-world

Deploy it to your cluster.

```

kubectl create -f 

```
Copy one of the HPAs below based on the metric type you're using: {{% accordion id="service-deployment-resource-metrics" label="Hello World HPA: Resource Metrics" %}}

apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
metadata:
  name: hello-world
  namespace: default
spec:
  scaleTargetRef:
    apiVersion: extensions/v1beta1
    kind: Deployment
    name: hello-world
  minReplicas: 1
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      targetAverageUtilization: 50
  - type: Resource
    resource:
      name: memory
      targetAverageValue: 1000Mi

{{% /accordion %}} {{% accordion id="service-deployment-custom-metrics" label="Hello World HPA: Custom Metrics" %}}

apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
metadata:
  name: hello-world
  namespace: default
spec:
  scaleTargetRef:
    apiVersion: extensions/v1beta1
    kind: Deployment
    name: hello-world
  minReplicas: 1
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      targetAverageUtilization: 50
  - type: Resource
    resource:
      name: memory
      targetAverageValue: 100Mi
  - type: Pods
    pods:
      metricName: cpu_system
      targetAverageValue: 20m

View the HPA info and description. Confirm that metric data is shown. {{% accordion id="hpa-info-resource-metrics" label="Resource Metrics" %}}
Enter the following commands. # kubectl get hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE hello-world Deployment/hello-world 1253376 / 100Mi, 0% / 50% 1 10 1 6m # kubectl describe hpa Name: hello-world Namespace: default Labels: <none> Annotations: <none> CreationTimestamp: Mon, 23 Jul 2018 20:21:16 +0200 Reference: Deployment/hello-world Metrics: ( current / target ) resource memory on pods: 1253376 / 100Mi resource cpu on pods (as a percentage of request): 0% (0) / 50% Min replicas: 1 Max replicas: 10 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 memory resource ScalingLimited False DesiredWithinRange the desired count is within the acceptable range Events: <none> {{% /accordion %}} {{% accordion id="hpa-info-custom-metrics" label="Custom Metrics" %}}
Enter the following command. # kubectl describe hpa You should receive the output that follows. Name: hello-world Namespace: default Labels: <none> Annotations: <none> CreationTimestamp: Tue, 24 Jul 2018 18:36:28 +0200 Reference: Deployment/hello-world Metrics: ( current / target ) resource memory on pods: 3514368 / 100Mi "cpu_system" on pods: 0 / 20m resource cpu on pods (as a percentage of request): 0% (0) / 50% Min replicas: 1 Max replicas: 10 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 memory resource ScalingLimited False DesiredWithinRange the desired count is within the acceptable range Events: <none> {{% /accordion %}}
Generate a load for the service to test that your pods autoscale as intended. You can use any load-testing tool (Hey, Gatling, etc.), but we're using Hey.
Test that pod autoscaling works as intended.

To Test Autoscaling Using Resource Metrics: {{% accordion id="observe-upscale-2-pods-cpu" label="Upscale to 2 Pods: CPU Usage Up to Target" %}} Use your load testing tool to to scale up to two pods based on CPU Usage.
View your HPA. # kubectl describe hpa You should receive output similar to what follows. Name: hello-world Namespace: default Labels: <none> Annotations: <none> CreationTimestamp: Mon, 23 Jul 2018 22:22:04 +0200 Reference: Deployment/hello-world Metrics: ( current / target ) resource memory on pods: 10928128 / 100Mi resource cpu on pods (as a percentage of request): 56% (280m) / 50% Min replicas: 1 Max replicas: 10 Conditions: Type Status Reason Message ---- ------ ------ ------- AbleToScale True SucceededRescale the HPA controller was able to update the target scale to 2 ScalingActive True ValidMetricFound the HPA was able to successfully calculate a replica count from cpu resource utilization (percentage of request) ScalingLimited False DesiredWithinRange the desired count is within the acceptable range Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal SuccessfulRescale 13s horizontal-pod-autoscaler New size: 2; reason: cpu resource utilization (percentage of request) above target
Enter the following command to confirm you've scaled to two pods. # kubectl get pods You should receive output similar to what follows: NAME READY STATUS RESTARTS AGE hello-world-54764dfbf8-k8ph2 1/1 Running 0 1m hello-world-54764dfbf8-q6l4v 1/1 Running 0 3h {{% /accordion %}} {{% accordion id="observe-upscale-3-pods-cpu-cooldown" label="Upscale to 3 pods: CPU Usage Up to Target" %}} Use your load testing tool to upspace to 3 pods based on CPU usage with horizontal-pod-autoscaler-upscale-delay set to 3 minutes.
Enter the following command. # kubectl describe hpa You should receive output similar to what follows Name: hello-world Namespace: default Labels: <none> Annotations: <none> CreationTimestamp: Mon, 23 Jul 2018 22:22:04 +0200 Reference: Deployment/hello-world Metrics: ( current / target ) resource memory on pods: 9424896 / 100Mi resource cpu on pods (as a percentage of request): 66% (333m) / 50% Min replicas: 1 Max replicas: 10 Conditions: Type Status Reason Message ---- ------ ------ ------- AbleToScale True SucceededRescale the HPA controller was able to update the target scale to 3 ScalingActive True ValidMetricFound the HPA was able to successfully calculate a replica count from cpu resource utilization (percentage of request) ScalingLimited False DesiredWithinRange the desired count is within the acceptable range Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal SuccessfulRescale 4m horizontal-pod-autoscaler New size: 2; reason: cpu resource utilization (percentage of request) above target Normal SuccessfulRescale 16s horizontal-pod-autoscaler New size: 3; reason: cpu resource utilization (percentage of request) above target
Enter the following command to confirm three pods are running. # kubectl get pods You should receive output similar to what follows. NAME READY STATUS RESTARTS AGE hello-world-54764dfbf8-f46kh 0/1 Running 0 1m hello-world-54764dfbf8-k8ph2 1/1 Running 0 5m hello-world-54764dfbf8-q6l4v 1/1 Running 0 3h {{% /accordion %}} {{% accordion id="observe-downscale-1-pod" label="Downscale to 1 Pod: All Metrics Below Target" %}} Use your load testing to to scale down to 1 pod when all metrics are below target for horizontal-pod-autoscaler-downscale-delay (5 minutes by default).
Enter the following command. # kubectl describe hpa You should receive output similar to what follows. Name: hello-world Namespace: default Labels: <none> Annotations: <none> CreationTimestamp: Mon, 23 Jul 2018 22:22:04 +0200 Reference: Deployment/hello-world Metrics: ( current / target ) resource memory on pods: 10070016 / 100Mi resource cpu on pods (as a percentage of request): 0% (0) / 50% Min replicas: 1 Max replicas: 10 Conditions: Type Status Reason Message ---- ------ ------ ------- AbleToScale True SucceededRescale the HPA controller was able to update the target scale to 1 ScalingActive True ValidMetricFound the HPA was able to successfully calculate a replica count from memory resource ScalingLimited False DesiredWithinRange the desired count is within the acceptable range Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal SuccessfulRescale 10m horizontal-pod-autoscaler New size: 2; reason: cpu resource utilization (percentage of request) above target Normal SuccessfulRescale 6m horizontal-pod-autoscaler New size: 3; reason: cpu resource utilization (percentage of request) above target Normal SuccessfulRescale 1s horizontal-pod-autoscaler New size: 1; reason: All metrics below target {{% /accordion %}}
To Test Autoscaling Using Custom Metrics: {{% accordion id="custom-observe-upscale-2-pods-cpu" label="Upscale to 2 Pods: CPU Usage Up to Target" %}} Use your load testing tool to upscale two pods based on CPU usage.
Enter the following command. # kubectl describe hpa You should receive output similar to what follows. Name: hello-world Namespace: default Labels: <none> Annotations: <none> CreationTimestamp: Tue, 24 Jul 2018 18:01:11 +0200 Reference: Deployment/hello-world Metrics: ( current / target ) resource memory on pods: 8159232 / 100Mi "cpu_system" on pods: 7m / 20m resource cpu on pods (as a percentage of request): 64% (321m) / 50% Min replicas: 1 Max replicas: 10 Conditions: Type Status Reason Message ---- ------ ------ ------- AbleToScale True SucceededRescale the HPA controller was able to update the target scale to 2 ScalingActive True ValidMetricFound the HPA was able to successfully calculate a replica count from cpu resource utilization (percentage of request) ScalingLimited False DesiredWithinRange the desired count is within the acceptable range Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal SuccessfulRescale 16s horizontal-pod-autoscaler New size: 2; reason: cpu resource utilization (percentage of request) above target
Enter the following command to confirm two pods are running. # kubectl get pods You should receive output similar to what follows. NAME READY STATUS RESTARTS AGE hello-world-54764dfbf8-5pfdr 1/1 Running 0 3s hello-world-54764dfbf8-q6l82 1/1 Running 0 6h {{% /accordion %}} {{% accordion id="observe-upscale-3-pods-cpu-cooldown-2" label="Upscale to 3 Pods: CPU Usage Up to Target" %}} Use your load testing tool to scale up to three pods when the cpu_system usage limit is up to target.
Enter the following command. # kubectl describe hpa You should receive output similar to what follows: Name: hello-world Namespace: default Labels: <none> Annotations: <none> CreationTimestamp: Tue, 24 Jul 2018 18:01:11 +0200 Reference: Deployment/hello-world Metrics: ( current / target ) resource memory on pods: 8374272 / 100Mi "cpu_system" on pods: 27m / 20m resource cpu on pods (as a percentage of request): 71% (357m) / 50% Min replicas: 1 Max replicas: 10 Conditions: Type Status Reason Message ---- ------ ------ ------- AbleToScale True SucceededRescale the HPA controller was able to update the target scale to 3 ScalingActive True ValidMetricFound the HPA was able to successfully calculate a replica count from cpu resource utilization (percentage of request) ScalingLimited False DesiredWithinRange the desired count is within the acceptable range Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal SuccessfulRescale 3m horizontal-pod-autoscaler New size: 2; reason: cpu resource utilization (percentage of request) above target Normal SuccessfulRescale 3s horizontal-pod-autoscaler New size: 3; reason: pods metric cpu_system above target
Enter the following command to confirm three pods are running. # kubectl get pods
You should receive output similar to what follows: # kubectl get pods NAME READY STATUS RESTARTS AGE hello-world-54764dfbf8-5pfdr 1/1 Running 0 3m hello-world-54764dfbf8-m2hrl 1/1 Running 0 1s hello-world-54764dfbf8-q6l82 1/1 Running 0 6h {{% /accordion %}} {{% accordion id="observe-upscale-4-pods" label="Upscale to 4 Pods: CPU Usage Up to Target" %}} Use your load testing tool to upscale to four pods based on CPU usage. horizontal-pod-autoscaler-upscale-delay is set to three minutes by default.
Enter the following command. # kubectl describe hpa You should receive output similar to what follows. Name: hello-world Namespace: default Labels: <none> Annotations: <none> CreationTimestamp: Tue, 24 Jul 2018 18:01:11 +0200 Reference: Deployment/hello-world Metrics: ( current / target ) resource memory on pods: 8374272 / 100Mi "cpu_system" on pods: 27m / 20m resource cpu on pods (as a percentage of request): 71% (357m) / 50% Min replicas: 1 Max replicas: 10 Conditions: Type Status Reason Message ---- ------ ------ ------- AbleToScale True SucceededRescale the HPA controller was able to update the target scale to 3 ScalingActive True ValidMetricFound the HPA was able to successfully calculate a replica count from cpu resource utilization (percentage of request) ScalingLimited False DesiredWithinRange the desired count is within the acceptable range Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal SuccessfulRescale 5m horizontal-pod-autoscaler New size: 2; reason: cpu resource utilization (percentage of request) above target Normal SuccessfulRescale 3m horizontal-pod-autoscaler New size: 3; reason: pods metric cpu_system above target Normal SuccessfulRescale 4s horizontal-pod-autoscaler New size: 4; reason: cpu resource utilization (percentage of request) above target
Enter the following command to confirm four pods are running. # kubectl get pods You should receive output similar to what follows. NAME READY STATUS RESTARTS AGE hello-world-54764dfbf8-2p9xb 1/1 Running 0 5m hello-world-54764dfbf8-5pfdr 1/1 Running 0 2m hello-world-54764dfbf8-m2hrl 1/1 Running 0 1s hello-world-54764dfbf8-q6l82 1/1 Running 0 6h {{% /accordion %}}
{{% accordion id="custom-metrics-observe-downscale-1-pod" label="Downscale to 1 Pod: All Metrics Below Target" %}} Use your load testing tool to scale down to one pod when all metrics below target for horizontal-pod-autoscaler-downscale-delay.
Enter the following command. # kubectl describe hpa You should receive similar output to what follows. Name: hello-world Namespace: default Labels: <none> Annotations: <none> CreationTimestamp: Tue, 24 Jul 2018 18:01:11 +0200 Reference: Deployment/hello-world Metrics: ( current / target ) resource memory on pods: 8101888 / 100Mi "cpu_system" on pods: 8m / 20m resource cpu on pods (as a percentage of request): 0% (0) / 50% Min replicas: 1 Max replicas: 10 Conditions: Type Status Reason Message ---- ------ ------ ------- AbleToScale True SucceededRescale the HPA controller was able to update the target scale to 1 ScalingActive True ValidMetricFound the HPA was able to successfully calculate a replica count from memory resource ScalingLimited False DesiredWithinRange the desired count is within the acceptable range Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal SuccessfulRescale 10m horizontal-pod-autoscaler New size: 2; reason: cpu resource utilization (percentage of request) above target Normal SuccessfulRescale 8m horizontal-pod-autoscaler New size: 3; reason: pods metric cpu_system above target Normal SuccessfulRescale 5m horizontal-pod-autoscaler New size: 4; reason: cpu resource utilization (percentage of request) above target Normal SuccessfulRescale 13s horizontal-pod-autoscaler New size: 1; reason: All metrics below target
Enter the following command to confirm a single pods is running. # kubectl get pods You should receive output similar to what follows. NAME READY STATUS RESTARTS AGE hello-world-54764dfbf8-q6l82 1/1 Running 0 6h
{{% /accordion %}}

Conclusion

Horizontal Pod Autoscaling is a great way to automate the number of pod you have deployed for maximum efficiency. You can use it to accommodate deployment scale to real service load and to meet service level agreements.

By adjusting the horizontal-pod-autoscaler-downscale-delay and horizontal-pod-autoscaler-upscale-delay flag values, you can adjust the time needed before kube-controller scales your pods up or down.

We've demonstrated how to setup an HPA based on custom metrics provided by Prometheus. We used the cpu_system metric as an example, but you can use other metrics that monitor service performance, like http_request_number, http_response_time, etc.

Manual Installation

Note: This is only applicable to clusters created in versions before Rancher v2.0.7.

Before you can use HPA in your Kubernetes cluster, you must fulfill some requirements.

Requirements

Be sure that your Kubernetes cluster services are running with these flags at minimum:

kube-api: requestheader-client-ca-file
kubelet: read-only-port at 10255
kube-controller: Optional, just needed if distinct values than default are required.
horizontal-pod-autoscaler-downscale-delay: "5m0s"
horizontal-pod-autoscaler-upscale-delay: "3m0s"
horizontal-pod-autoscaler-sync-period: "30s"

For an RKE Kubernetes cluster definition, add this snippet in the services section. To add this snippet using the Rancher v2.0 UI, open the Clusters view and select Ellipsis (...) > Edit for the cluster in which you want to use HPA. Then, from Cluster Options, click Edit as YAML. Add the following snippet to the services section:

services:
...
  kube-api:
    extra_args:
      requestheader-client-ca-file: "/etc/kubernetes/ssl/kube-ca.pem"
  kube-controller:
    extra_args:
      horizontal-pod-autoscaler-downscale-delay: "5m0s"
      horizontal-pod-autoscaler-upscale-delay: "1m0s"
      horizontal-pod-autoscaler-sync-period: "30s"
  kubelet:
    extra_args:
      read-only-port: 10255

Once the Kubernetes cluster is configured and deployed, you can deploy metrics services.

Note: kubectl command samples in the sections that follow were tested in a cluster running Rancher v2.0.6 and Kubernetes v1.10.1.

Configuring HPA to Scale Using Resource Metrics

To create HPA resources based on resource metrics such as CPU and memory use, you need to deploy the metrics-server package in the kube-system namespace of your Kubernetes cluster. This deployment allows HPA to consume the metrics.k8s.io API.

Prerequisite: You must be running kubectl 1.8 or later.

Connect to your Kubernetes cluster using kubectl.
Clone the GitHub metrics-server repo: # git clone https://github.com/kubernetes-incubator/metrics-server
Install the metrics-server package. # kubectl create -f metrics-server/deploy/1.8+/
Check that metrics-server is running properly. Check the service pod and logs in the kube-system namespace.
Check the service pod for a status of running. Enter the following command: # kubectl get pods -n kube-system Then check for the status of running. NAME READY STATUS RESTARTS AGE ... metrics-server-6fbfb84cdd-t2fk9 1/1 Running 0 8h ...
Check the service logs for service availability. Enter the following command: # kubectl -n kube-system logs metrics-server-6fbfb84cdd-t2fk9 Then review the log to confirm that that the metrics-server package is running. {{% accordion id="metrics-server-run-check" label="Metrics Server Log Output" %}} I0723 08:09:56.193136 1 heapster.go:71] /metrics-server --source=kubernetes.summary_api:'' I0723 08:09:56.193574 1 heapster.go:72] Metrics Server version v0.2.1 I0723 08:09:56.194480 1 configs.go:61] Using Kubernetes client with master "https://10.43.0.1:443" and version I0723 08:09:56.194501 1 configs.go:62] Using kubelet port 10255 I0723 08:09:56.198612 1 heapster.go:128] Starting with Metric Sink I0723 08:09:56.780114 1 serving.go:308] Generated self-signed cert (apiserver.local.config/certificates/apiserver.crt, apiserver.local.config/certificates/apiserver.key) I0723 08:09:57.391518 1 heapster.go:101] Starting Heapster API server... [restful] 2018/07/23 08:09:57 log.go:33: [restful/swagger] listing is available at https:///swaggerapi [restful] 2018/07/23 08:09:57 log.go:33: [restful/swagger] https:///swaggerui/ is mapped to folder /swagger-ui/ I0723 08:09:57.394080 1 serve.go:85] Serving securely on 0.0.0.0:443 {{% /accordion %}}
Check that the metrics api is accessible from kubectl.
If you are accessing the cluster through Rancher, enter your Server URL in the kubectl config in the following format: https://<RANCHER_URL>/k8s/clusters/<CLUSTER_ID>. Add the suffix /k8s/clusters/<CLUSTER_ID> to API path. # kubectl get --raw /k8s/clusters/<CLUSTER_ID>/apis/metrics.k8s.io/v1beta1 If the the API is working correctly, you should receive output similar to the output below. {"kind":"APIResourceList","apiVersion":"v1","groupVersion":"metrics.k8s.io/v1beta1","resources":[{"name":"nodes","singularName":"","namespaced":false,"kind":"NodeMetrics","verbs":["get","list"]},{"name":"pods","singularName":"","namespaced":true,"kind":"PodMetrics","verbs":["get","list"]}]}
If you are accessing the cluster directly, enter your Server URL in the kubectl config in the following format: https://<K8s_URL>:6443. # kubectl get --raw /apis/metrics.k8s.io/v1beta1 If the the API is working correctly, you should receive output similar to the output below. {"kind":"APIResourceList","apiVersion":"v1","groupVersion":"metrics.k8s.io/v1beta1","resources":[{"name":"nodes","singularName":"","namespaced":false,"kind":"NodeMetrics","verbs":["get","list"]},{"name":"pods","singularName":"","namespaced":true,"kind":"PodMetrics","verbs":["get","list"]}]}

Assigning Additional Required Roles to Your HPA

By default, HPA reads resource and custom metrics with the user system:anonymous. Assign system:anonymous to view-resource-metrics and view-custom-metrics in the ClusterRole and ClusterRoleBindings manifests. These roles are used to access metrics.

To do it, follow these steps:

Configure kubectl to connect to your cluster.
Copy the ClusterRole and ClusterRoleBinding manifest for the type of metrics you're using for your HPA. {{% accordion id="cluster-role-resource-metrics" label="Resource Metrics: ApiGroups resource.metrics.k8s.io" %}} apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRole metadata: name: view-resource-metrics rules: - apiGroups: - metrics.k8s.io resources: - pods - nodes verbs: - get - list - watch --- apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding metadata: name: view-resource-metrics roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: view-resource-metrics subjects: - apiGroup: rbac.authorization.k8s.io kind: User name: system:anonymous {{% /accordion %}} {{% accordion id="cluster-role-custom-resources" label="Custom Metrics: ApiGroups custom.metrics.k8s.io" %}}

``` apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRole metadata: name: view-custom-metrics rules: - apiGroups: - custom.metrics.k8s.io resources: - "*" verbs: - get - list - watch

apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding metadata: name: view-custom-metrics roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: view-custom-metrics subjects: - apiGroup: rbac.authorization.k8s.io kind: User name: system:anonymous {{% /accordion %}} 1. Create them in your cluster using one of the follow commands, depending on the metrics you're using. # kubectl create -f # kubectl create -f ```

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Why Use Horizontal Pod Autoscaler?

How HPA Works

Horizontal Pod Autoscaler API Objects

kubectl Commands

HPA Manifest Definition Example

Configuring HPA to Scale Using Resource Metrics

Configuring HPA to Scale Using Custom Metrics (Prometheus)

Testing HPAs with a Service Deployment

kubectl create -f 

Conclusion

Manual Installation

Requirements

Configuring HPA to Scale Using Resource Metrics

Assigning Additional Required Roles to Your HPA