CPU and memory metrics often fail to capture real workload pressure in event-driven Kubernetes systems. This guide walks through using KEDA (Kubernetes Event-Driven Autoscaling) to scale worker pods based on Amazon SQS queue depth on EKS. It covers installation via Helm, IAM permissions with least-privilege access, configuring TriggerAuthentication and ScaledObject manifests, the replica calculation formula (ceil(outstanding messages / queueLength)), verification steps, common troubleshooting scenarios (no scale-out, too many pods, never scales to zero), and production tuning tips for cooldowns, HPA behavior, and in-flight message handling.
Table of contents
1. Prerequisites2. Architecture and Request Flow3. Implementation Steps4. Replica Calculation Logic5. Verification6. Troubleshooting Common Issues7. Production Tuning Tips192 Impressions