The average Kubernetes cluster runs at 13% CPU utilization and 20% memory utilization. That means 87% of provisioned compute sits idle. Three autoscalers exist to close that gap — VPA, HPA, and KEDA — and each attacks the problem from a different angle. VPA shrinks oversized pods. HPA adds and removes pod replicas. KEDA extends HPA with event-driven triggers and the ability to scale to zero. Choosing the wrong autoscaler does not just leave money on the table. It creates production incidents. VPA evicts pods to resize them, which restarts JVM applications cold. HPA thrashes replica counts without stabilization windows, causing 5xx errors during scale-down. KEDA's scale-to-zero adds cold start latency that breaks SLA commitments. The cost savings are real, but only if the autoscaler matches the workload. Your Cluster Is Running at 13% CPU. The Autoscaler Choice Determines What Happens Next The CNCF 2024 Kubernetes Benchmark Report analyzed 4,000 clusters. Average CPU utilization: 13%.…