HPA

Kubernetes: HorizontalPodAutoscaler evaluation based on Prometheus metric

HorizontalPodAutoscaler (HPA) allow you to dynamically scale the replica count of your Deployment based on basic CPU/memory resource metrics from the metrics-server.  If you want scaling based on more advanced scenarios and you are already using the Prometheus stack, the prometheus-adapter provides this enhancement. The prometheus-adapter takes basic Prometheus metrics, and then synthesizes custom API Kubernetes: HorizontalPodAutoscaler evaluation based on Prometheus metric

Kubernetes: implementing and testing a HorizontalPodAutoscaler

HorizontalPodAutoscaler (HPA) allow you to dynamically scale the replica count of your Deployment based on criteria such as memory or CPU utilization, which make it great way to manage spikes in utilization while still keeping your cluster size and infrastructure costs managed effectively. In order for HPA to evaluate CPU and memory utilization and take Kubernetes: implementing and testing a HorizontalPodAutoscaler