Understand scaler configurations

  • 5 minutes

The v2 version of the HPA API allows you to fine-tune some aspects of its behavior by using a new key in the YAML file called spec.behavior. It accepts two other keys: scaleDown and scaleUp, which define how the HPA behaves when scaling down and when scaling up.

The following values are allowed for each of these keys:

Key Type Description
stabilizationWindowSeconds int The period in which the HPA looks for metrics to compute the desired state. The default value for scaleDown is five minutes and there's no stabilization window for scaleUp.
selectPolicy string The selected type of policy to use, this value can be Min, Max, or Disabled.
policies array of HPAScalingPolicy An array of possible policies to apply.

The HPAScalingPolicy object is defined as an object with the following keys:

Key Type Description
type string Type of policy, can be Percent or Pods.
value int Value of the policy.
periodSeconds int Amount of time required before this policy can be applied again.

Scaling policies allow you to fine-tune the way the scaling works. For example, you can completely disable the scale down operation by setting a scaleDown policy to Disabled, as shown in the following example:

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: contoso-website
  namespace: hpa-contoso
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: contoso-website
  minReplicas: 1
  maxReplicas: 10
  behavior:
    scaleDown:
      selectPolicy: Disabled
  metrics:
    - type: Resource
      resource:
        name: cpu
        target:
          type: Utilization
          averageUtilization: 20
    - type: Resource
      resource:
        name: memory
        target:
          type: Utilization
          averageUtilization: 50

You can also set the number of replicas to scale out at a time by defining a scaleUp policy, like this:

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: contoso-website
  namespace: hpa-contoso
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: contoso-website
  minReplicas: 1
  maxReplicas: 10
  behavior:
    scaleUp:
      selectPolicy: Max
      stabilizationWindowSeconds: 120
      policies:
        - type: Percent
          value: 30
          periodSeconds: 60
        - type: Pods
          value: 7
          periodSeconds: 90
  metrics:
    - type: Resource
      resource:
        name: cpu
        target:
          type: Utilization
          averageUtilization: 20
    - type: Resource
      resource:
        name: memory
        target:
          type: Utilization
          averageUtilization: 50

In this manifest, you're telling the HPA to look for the last 120 seconds of metrics to calculate the desired state and get the highest of these values. Once it does, it calculates 30% of the existing pods, rounds this number up, and compares it with the fixed value of seven pods. Since the selectPolicy is set to Max, it takes the larger number of those two numbers and applies that policy, then waits periodSeconds before applying any policies again.

For example, let's say the website is running with 18 pods, and then it experience a spike that lasts for about 120 seconds. The desired state is computed by calculating 30% of the current running pods, which is 5.4 (rounded to 6). This value is compared to the number of pods in the second policy, which is 7. Since the selectPolicy key is set to Max, it uses the larger value of those two values. Then, the HPA scales by 7 and waits 90 seconds before scaling up again. If the spike continued up to 25 pods, the calculation is done again. 30% of 25 pods is 7.5 (rounded to 8), which is greater than 7. Now, the HPA creates eight new pods and waits for 60 seconds before scaling up again.

Check your knowledge

1.

What is the stabilization window?

2.

What are the three values for selectPolicies?

3.

When should you define behavior to your HPA?