OpenTelemetry's Graduation: What It Took (Grafana ❤️🔥 OpenTelemetry Community Call #8)

Mon, 22 Jun 2026 16:00:00 +0100

OpenTelemetry graduated from the CNCF — so for this community call I gathered a panel of people who were in the room for it to talk about what graduation actually means, what it took to get there, and where the project goes next. We covered the roughly two-year road to graduation, why semantic conventions are so genuinely hard, the state of the signals (traces, metrics, logs — and the newer profiles), AI’s double-edged impact on the project, and the most practical ways for new contributors to get involved.

What we covered

🎓 What graduation actually took

Graduation from the CNCF took about two years, with OTel evaluated on traces, metrics, and logs across the major server-side languages. Profiling, mobile, and other newer signals were explicitly out of scope for the graduation criteria. One of the most concrete pieces of CNCF feedback: stop camping on 0.x versions for components that are actually production-ready. The fix is to mark maintained, stable packages as 1.0 (reserving 2.0 for future breaking changes) — which unblocks the enterprises that simply aren’t allowed to ship anything still labeled “beta.”

📚 Documentation that’s actually findable

A recurring theme was that the documentation bar isn’t just “does it exist” — it’s “can someone find it.” Collector component docs are spread across 100+ GitHub repos, which makes discovery painful. The stopgap is an auto-updated component list with metadata on the OpenTelemetry website that links out to the relevant READMEs; the longer-term answer is the Ecosystem Explorer project, which aims to unify instrumentation details, versioning, and component metadata in one place.

🏷️ Why semantic conventions are so hard

Semantic conventions define normalized attribute names so that the same event — say, an HTTP request — looks identical no matter the language or library that produced it. The naming debates are slow for real reasons: the database SIG took over a year to stabilize a single set of attributes. The process is propose names → check them against all the major databases → build a proof-of-concept in three or more languages → iterate. A name that’s obvious for one database may not even exist as a concept in another. (OTel itself is the product of merging OpenTracing, OpenCensus, and Elastic Common Schema — and yes, the name was chosen specifically because it’s boring and self-describing. Everything is named what it does.)

🧳 Signals, baggage, and stability

All three original signals — traces, metrics, and logs — are now stable, and that includes baggage: a context-propagation mechanism that carries a small “bag” of attributes (trace ID, span ID, and more) across network hops. It was originally built for tracing but designed to be reusable for other cross-cutting concerns like security and feature flags, and it sat largely unused while the rest of OTel was being finished. Profiles, meanwhile, hit alpha at KubeCon in March and are treated as a bonus on top of the graduation baseline rather than part of it.

🤖 AI’s impact on OpenTelemetry — the good and the painful

The good: the explosion of GenAI and agentic systems is creating real demand for OTel-style observability. The Gen AI SIG is growing fast to standardize telemetry for AI systems, and there’s a whole crop of AI-observability startups building on OpenTelemetry. Maintainers are also using AI coding tools to move faster — the Weaver tool is being developed to constrain the problem space so AI-generated instrumentation code is more accurate, with the goal of going from spec to implementation with coding tools.

The painful: a massive influx of low-quality, AI-generated PRs across all of open source. Some are genuinely malicious (bot accounts farming credibility for supply-chain attacks); others are just thoughtless. One proposed mitigation is to cap the number of open PRs per contributor without merge rights to something like three to five.

🚀 Post-graduation priorities and how to get involved

The post-graduation backlog (“postgrad app”) focuses on stability cleanup, easier deployment, and self-observability. The deployment north star is something close to apt-get install opentelemetry that auto-instruments everything — including outside Kubernetes. New stable YAML-based collector config lets operators manage all languages from a single file, and the Blueprint project pairs a specific challenge with OTel guidelines and concrete implementation steps.

If you want in, the panel was refreshingly practical about the fastest path to approver/maintainer status:

Review other people’s PRs in your subject area.
Ask maintainers “what can I take off your plate?” rather than only filing your own issues.
Quality over quantity — AI-heavy contributions you can’t explain won’t earn status.
Localization is one of the easiest entry points; around ten language teams are active and docs translation is always welcome.

We also went around the panel on how everyone got started — from debugging giant distributed systems, to a beginner-questions live stream, to Elastic Common Schema work, to copy-editing PRs as a former librarian. The throughline: pick a small, real thing, do it well, and document your learning journey as you go.

Resources

Thanks to the panel — Ted Young, Marylia Gutierrez, Imma Valls, Tiffany Hrabusa, and Tiffany Jernigan — for joining, and to everyone who showed up live with questions.

Cncf on Nicole van der Hoeven