Can HPA use custom metrics?

Yes, the Horizontal Pod Autoscaler (HPA) can use custom metrics for scaling. This allows you to define specific application metrics that are relevant to your workload, such as:

• Request latency
• Queue length
• Custom business metrics (e.g., number of active users)

How to Use Custom Metrics:

1. Metrics Server: Ensure you have a metrics server or an adapter that can expose your custom metrics to the Kubernetes Metrics API.

2. HPA Configuration: In your HPA configuration, specify the custom metric you want to use for scaling. Here’s a simplified example:

apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
  name: my-app-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: my-app
  minReplicas: 1
  maxReplicas: 10
  metrics:
  - type: Object
    object:
      metric:
        name: custom_metric_name
      target:
        type: AverageValue
        averageValue: 100

Benefits:

Using custom metrics allows for more precise scaling based on the specific needs and performance characteristics of your application, leading to better resource utilization and responsiveness.