kubernetes vertical pod autoscaler
A vertical pod autoscaler works by collecting metrics (using the metrics server), and then analyzing those metrics over a period of time to understand the resource requirements of the running pods. It considers factors such as historical usage patterns, spikes in resource consumption, and the configured target utilization levels. Once this analysis is complete, the VPA controller generates recommendations for adjusting the resource requests (CPU and memory) of the pods. It may recommend increasing or decreasing resource requests to better match the observed usage. This is the basis of how a VPA works. However, this is not the end of the job for the VPA, as it has to constantly monitor and create a feedback loop where the VPA regularly adjusts pod resources based on the latest metrics.