Episode 52 — Autoscaling: availability, cost control, and risk of runaway scaling
Autoscaling appears in CloudNetX scenarios as an availability and cost control mechanism, but the exam expects you to recognize that autoscaling is only as good as the signals and guardrails behind it. This episode defines autoscaling as automatically adding or removing capacity in response to measured demand, then explains the difference between scaling out and scaling in, and how these behaviors interact with health checks and load balancing. The first paragraph focuses on why autoscaling helps: it can maintain service responsiveness during demand spikes, reduce downtime from capacity exhaustion, and avoid paying for peak capacity all the time. It also introduces the idea that autoscaling is a policy decision, not a magic feature, because triggers, cooldowns, and maximum limits determine whether the system behaves predictably.
