new HPA API version: autoscaling/v2
2 min read | by Jordi Prats
Since Kubernetes v1.23 we can now switch to autoscaling/v2, it provides a nicer way of setting the metrics it's going to use to autoscale replicas: External metrics becomes a first-class citizen
With the previous API version (autoscaling/v1) there wasn't a direct way of configuring external metrics since it's attributes were just intended for the CPU/memory use case:
apiVersion: autoscaling/v1 kind: HorizontalPodAutoscaler metadata: name: demo-targetCPUUtilizationPercentage spec: maxReplicas: 1 minReplicas: 2 scaleTargetRef: apiVersion: apps/v1 kind: Deployment name: demo-autoscale targetCPUUtilizationPercentage: 50 With the introduction of autoscaling/v2beta1 we could configure external metrics (Prometheus, Datadog): It was using annotations to be able to keep using the autoscaling/v1 for persistence
With the introduction of autoscaling/v2 we have the spec.metrics attribute that allows us to use metrics from different sources to configure it. We can adapt the previous example (autoscaling/v1) to use the new API version as follows:
apiVersion: autoscaling/v2 kind: HorizontalPodAutoscaler metadata: name: demo-targetCPUUtilizationPercentage spec: maxReplicas: 1 minReplicas: 2 scaleTargetRef: apiVersion: apps/v1 kind: Deployment name: demo-autoscale metrics: - resource: name: cpu target: averageUtilization: 80 type: Utilization type: Resource If we need use an external metric, we can set it in a similar way we configure the CPU and memory metrics:
apiVersion: autoscaling/v2 kind: HorizontalPodAutoscaler metadata: name: demo-externalmetrics spec: minReplicas: 2 maxReplicas: 22 scaleTargetRef: apiVersion: apps/v1 kind: Deployment name: demo-autoscale metrics: - type: External external: metric: name: kubernetes.kubelet.cpu.usage selector: matchLabels: cluster_name: example target: averageValue: "50" type: AverageValue Posted on 22/06/2022