5 free resources on this topic. Everything here is free and hand-picked. You can also search within this topic.
Open-source, vendor-neutral observability framework for cloud-native software. It provides a single set of APIs, libraries, agents, and collector services to capture distributed traces, metrics, and logs, built on the earlier OpenTracing and OpenCensus projects.
Honeycomb announcement of AI Ecosystem, a fleet-wide view of AI agent performance and cost, and Canvas connectors that bring code, tickets and context into investigations. Free to read; the product itself is commercial.
Monitoring for AI agents in production. Traces every run and tool call, groups repeated failures into one issue, and simulates a change on a pull request before you merge.
Why I recommend it: Free tier available; paid plans start around $150/month. Built for engineering teams shipping customer-facing agents — not something a job seeker will use, but useful if you build with AI.
Observability platform with a free-forever tier for distributed tracing, metrics, OpenTelemetry support and AI-assisted debugging. Useful for engineers learning modern observability and incident response.
Free ebook on building, monitoring, and troubleshooting AI agents in production: what to instrument, where agents fail, and the practices teams use to keep them reliable.
Why I recommend it: Useful even if you never build an agent yourself — it shows what serious teams actually worry about, which is good language to have in an interview about AI work.
