Bạn có thắc mặc HPA sẽ scale download như thế nào không?
Here are some additional details on how the Horizontal Pod Autoscaler (HPA) handles pod terminations when scaling down:
- The HPA controller gets metric values from either the resource metrics API (for CPU/memory) or external metrics API (for custom metrics). It compares to target values.
- Scaling operations are controlled by the upscale/downscale stabilization window – the HPA will wait this long between scale operations. Defaults to 15 seconds.
- The HPA increments or decrements the replica count on the target resource (Deployment, ReplicaSet, etc) via the scale subresource.
- The controller for that resource handles terminating pods to reach the new replica count. It uses the standard Kubernetes pod termination process.
- To decide which pods to terminate, the controller will try to balance across failure zones if available, as well as terminate newest pods first.
- The pod graceful termination timeout defines the maximum time Kubernetes will wait for a pod to exit normally after a SIGTERM. Default is 30s.
- Kubernetes uses SIGKILL after the grace period to forcibly terminate pods still running. This defaults to 30s after SIGTERM.
- The HPA has cooldown periods that restrict how often it can trigger scaling operations. Defaults to 5 minutes for downscaling.
So in summary, the HPA adjusts replica counts, the pod controllers gracefully terminate pods to reach desired counts, using configurable delays and grace periods to avoid disruptions.
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