2 — Scheduler Performance

Kubernetes

A book-shaped table of contents for Kubernetes: cloud-native foundations, the CKAD/CKA/CKS certification tracks, control-plane internals, platform tooling, multi-cluster architecture, and MAANG-level system design and interview prep — cross-linking the existing Prometheus, Observability, and Platform Engineering chapters instead of duplicating them.

3 — Cluster Autoscaler

Why Cluster Autoscaler scales purely on unschedulable pending pods rather than utilization metrics, making it reactive by design and blind to a burst until pods have already failed to schedule.

6 — Horizontal Pod Autoscaler

Why HPA's polling-interval and stabilization-window defaults make it structurally too slow for sub-minute traffic spikes, forcing teams toward custom metrics or KEDA to react in time.

4 — Karpenter

Why Karpenter provisions right-sized nodes directly from pending pod shape instead of scaling pre-defined node groups, collapsing the ASG-and-node-group abstraction Cluster Autoscaler depends on.

9 — Large Cluster Design

Why Kubernetes' official node-count ceiling is really an etcd write-throughput and API server watch-fanout limit, which is why hyperscalers split fleets into many smaller clusters instead of pushing past it.