HPA Policies

Horizontal Pod Autoscaling (HPA) in Kubernetes implements horizontal scaling of pods. In a CCE HPA policy, you can configure different cooldown time windows and scaling thresholds for different applications based on the Kubernetes HPA.

Prerequisites

The following add-on has been installed in the cluster:

Kubernetes Metrics Server: provides basic resource usage metrics, such as container CPU and memory usage.
Cloud Native Cluster Monitoring
- Auto scaling based on basic resource metrics: Prometheus needs to be registered as a metrics API. For details, see Providing Resource Metrics Through the Metrics API.

Creating an HPA Policy

Log in to the CCE console and click the cluster name to access the cluster console.
In the navigation pane on the left, choose Policies. On the Scaling Policies, click the HPA Policies tab and then Create HPA Policy in the upper right corner.
Configure basic information.
- Policy Name: Enter a name for the policy.
- Namespace: Select the namespace that the workload belongs to.
- Associated Workload: Select the workload that the policy is configured for.

Configure other parameters.

**Table 1** HPA policy parameters
Parameter	Description
Pod Range	Minimum and maximum numbers of pods. When a policy is triggered, the pods are scaled within this range.
Scaling Behavior	Default: Scale workloads using the Kubernetes default behavior. For details, see Default Behavior. Custom: Scale workloads using custom policies such as stabilization window, steps, and priorities. Unspecified parameters use the values recommended by Kubernetes. Disable scale-out/scale-in: Select whether to disable scale-out or scale-in. Stabilization Window: a period during which CCE continuously checks whether the metrics used for scaling keep fluctuating. CCE triggers scaling if the desired state is not maintained for the entire window. This window restricts the unwanted flapping of pod count due to metric changes. Step: specifies the scaling step. You can set the number or percentage of pods to be scaled in or out within a specified period. If there are multiple policies, you can select the policy that maximizes or minimizes the number of pods.
System Policy	Metric: You can select CPU usage or Memory usage. NOTE: Usage = CPUs or memory used by pods/Requested CPUs or memory Desired Value: Enter the desired average resource usage. This parameter indicates the desired value of the selected metric. Number of pods to be scaled (rounded up) = (Current metric value/Desired value) x Number of current pods NOTE: When calculating the number of pods to be added or reduced, the HPA policy uses the maximum number of pods in the last 5 minutes. Tolerance Range: Scaling is not triggered when the metric value is within the tolerance range. The desired value must be within the tolerance range. If the metric value is greater than the scale-in threshold and less than the scale-out threshold, no scaling is triggered. This parameter is only supported in clusters v1.15 or later.