Reading up on observability
7 deep · digging since dec 22, 25
- GitHub - HugoRCD/evlog: Logging that makes sense. Wide events, structured errors, zero chaos.
evlog is a TypeScript-first logging library that collapses multiple log lines into one structured wide event per request with context and self-documenting errors.
- GitHub - tobilg/ai-observer: Unified local observability for AI coding assistants
AI Observer is a self-hosted, single-binary OpenTelemetry observability backend that tracks token usage, costs, latency, and errors across multiple AI coding assistants via a local dashboard.
- On Friday Deploys: Sometimes that Puppy Needs Murdering (xpost) – charity.wtf
Friday deploy freezes are pragmatic when teams lack good observability, but pretending they're virtuous hides a technical debt hack.
- Logging sucks | Hacker News
Structured, high-cardinality logs with consistent schemas and correlation IDs improve debugging over traditional unstructured logs in distributed systems.
Takes
my self-hosted observability stack pairs well with agents
@marckohlbrugge
🚀Introducing Motus Tracing: open-source observability for AI agents. Without traces, an agent is a black box that burns tokens. Yet most agent observability and tracing stacks today live behind accounts and subscription tiers. Motus Tracing is fully open source. Capture every model call, tool call, sandbox interaction, sub-agent action, retry, and error, for any agent framework. One unified interface from development to production. Same spans for debugging, evals, and Learning Agents. Blog:
@JiaZhihao
Configured Grafana for all my projects Managed APMs are fine for typical SaaS where most visitors are paying you. But they get expensive quick if you have high traffic sites like job boards, etc. Now self-hosting, own the data, and can give my AI agents direct access for troubleshooting 👌
@marckohlbrugge