When scaling Go microservices, CPU utilization isn't the only metric. In this post, I dive deeply into configuring Custom Metrics Autoscaling using KEDA. By combining Go's highly concurrent context-based cancellation with Prometheus metrics (like active HTTP requests or pending Kafka messages), we can achieve true zero-to-n scaling. I discuss common pitfalls, such as connection draining during pod termination and how to properly configure readiness and liveness probes to ensure zero downtime deployments under heavy load.