If we do not create a metrics adapter, Metrics Aggregator only knows about CPU and memory usage related to containers and nodes. To make things more complicated, that information is limited only to the last few minutes. Since HPA is just concerned about Pods and containers inside them, we are limited to only two metrics. When we create an HPA, it will scale or de-scale our Pods if memory or CPU consumption of the containers that constitute those Pods is above or below predefined thresholds.
Metrics Server periodically fetches information (CPU and memory) from Kubelets running inside worker nodes.
Those metrics are passed to Metrics Aggregator which, in this scenario, does not add any additional value. From there on, HPAs periodically consult the data in the Metrics Aggregator (through its API endpoint). When there is a discrepancy...
