The Complete HorizontalPodAutoscaler Flow of Events

In this lesson, we will describe the complete flow of HPA events.

Complete HPA flow of events #

Metrics Server is fetching memory and CPU data from Kubelets running on the worker nodes. In parallel, Prometheus Adapter is fetching data from Prometheus Server which, as you already know, pulls data from different sources. Data from both Metrics Server and Prometheus Adapter is combined in Metrics Aggregator.

🔍 HPA is periodically evaluating metrics defined as scaling criteria. It’s fetching data from Metrics Aggregator, and it does not really care whether they’re coming from Metrics Server, Prometheus Adapter, or any other tool we could have used.

HPA manipulation #

Once scaling criteria are met, HPA manipulates Deployments and StatefulSets by changing their number of replicas. As a result, rolling updates are performed by creating and updating ReplicaSets which, in turn, create or remove Pods.

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