#Autoscaling

K8s Intermediate #6: Autoscaling — HPA / VPA / Cluster Autoscaler

The model covered through [#5](/en/posts/k8s-intermediate-5) was at the dimension of a single Pod's resources and health signals. But operational load swings with time, user patterns, and events, and having a person manually adjust `replicas` each time quickly hits a wall. This post walks through the three dimensions of autoscaling that fill that gap — `HPA` which auto-scales Pod count, `VPA` which auto-recommends and adjusts a Pod's resource requests/limits, and `Cluster Autoscaler` which auto-adds and removes nodes themselves — in one cycle. The metrics-server precondition, HPA's `autoscaling/v2` manifest and algorithm, the asymmetric `behavior` of scale up/down, custom metrics and KEDA, VPA's three components, HPA/VPA conflict, Karpenter — all included.