What You Need to Know About Kubernetes Autoscaling

Cluster Autoscaler

CA adjusts the size of a Kubernetes cluster automatically by adding or removing compute nodes based on the demand for resources by the workloads running on the cluster. Its goal is to keep a sufficient amount of resources running and to keep idle resources to a minimum.

Vertical Pod Autoscaler

VPA automatically adjusts container resource requests and limits within a pod based on the containers' actual resource utilization.

Because HPA relies on metrics such as CPU and memory usage to determine when to scale pods, there may be a delay between the time demand increases and the time additional pods are up to meet it. This delay can potentially slow down response times, temporarily reducing performance for end users.

Horizontal Pod Autoscaler

HPA adjusts the number of replicas of a deployment or replica set based on pod resource utilization. HorizontalPodAutoscaler automatically changes the number of replicas in response to changes in traffic or demand.

If your application experiences sudden spikes in traffic, HPA may be the better choice. If it has stable traffic but varying resource requirements, you should probably go with VPA.

VPA can also increase overhead and complexity in a Kubernetes cluster, since it continuously monitors and adjusts pod resource allocation based on current utilization.