SCALING KUBERNETES PODS WITH KEDA BASED ON AMAZON SQS QUEUE DEPTH

Summary from the TLDR DevOps newsletter

This article walks through how to use KEDA to scale Kubernetes worker pods based on Amazon SQS queue depth rather than CPU or memory usage. The core idea is that in queue-driven systems, the number of messages waiting is a more accurate signal of demand than infrastructure utilization. KEDA calculates desired replica counts using the formula: outstanding messages divided by a configured per-pod target. It can scale deployments all the way down to zero when queues are empty.