Stop staring at dashboards: Let your Go API diagnose itself

A developer built mAPI-ng, an open-source Go API that diagnoses its own performance issues by correlating RED metrics with runtime signals and ranking likely causes. The tool aims to eliminate the 'Observability Tax' of configuring separate monitoring stacks, offering evidence-backed diagnosis with a 'Rules this out' feature to avoid false positives.

Every Gopher knows the drill: An endpoint gets slow. A spike of 500s appears. You open Grafana. You stare at 12 different panels. You cross-reference Prometheus metrics with traces. You guess it might be GC pressure or a connection pool saturation. What if your API just told you what’s wrong? I built mAPI-ng because I was tired of the “Observability Tax”: the hours spent configuring OTel, Prometheus, and Grafana just to get basic answers. mAPI-ng doesn’t just show graphs; it interprets them. It correlates RED metrics Rate, Errors, Duration with Go runtime signals, instance health, and downstream IO. When an endpoint fails, it ranks the most likely causes: Every diagnosis comes with a “Rules this out” line. If the evidence doesn’t fit, it tells you, avoiding the “AI hallucinations” of black-box tools. I’m a “Code Alchemist” at heart—I like things that work out of the box. To instrument your app: No YAML hell. No Prometheus to manage. It uses ClickHouse for high-performance, compact storage. I believe observability should be a right, not a luxury. The entire stack is MIT licensed and self-hostable with a simple make up. If you prefer the “easy mode”, there’s a hosted version at mapi-ng.com with a forever-free tier , but you’ll never be locked in. If you have Docker installed, you can see it in action with a sample “leaky” API: git clone https://github.com/arhuman/maping cd maping make local make generate-traffic Open localhost:8080 and watch the diagnosis engine work. I’m looking for feedback from fellow Gophers Does this approach to “evidence-backed diagnosis” make sense for your workflow? What’s the one thing that always kills your on-call nights? GitHub: arhuman/maping https://github.com/arhuman/maping