OpenTelemetry has crossed an important threshold: according to the latest CNCF survey, nearly 49% of organizations now run OpenTelemetry in production. As adoption accelerates, a new challenge emerges — “supports OpenTelemetry” is no longer a meaningful signal of quality. It can describe anything from emitting a few spans to providing a well-designed, stable, and interoperable observability interface.

This talk introduces a community-driven OpenTelemetry Support Maturity Model that moves the conversation beyond checkboxes. Instead of asking whether OpenTelemetry is supported, the model helps answer how well it is integrated, modeled, and evolved over time across dimensions such as integration surface, semantic conventions, trace modeling, multi-signal observability, stability, and signal quality.

We ground the model in practice by applying it to widely used Kubernetes ingress controllers — components that sit on the critical path of every request. The goal is not to rank projects, but to give platform engineers a framework to evaluate integrations and maintainers a guide to improving OpenTelemetry support intentionally, helping align the ecosystem around what “good” support should mean going forward.

As OpenTelemetry adoption continues to grow, the ecosystem increasingly needs a shared way to reason about quality and maturity, not just feature presence. This talk introduces a practical maturity model that helps align platform engineers, maintainers, and contributors around what “good OpenTelemetry support” means in practice.

For platform engineers, the model provides a structured framework for evaluating integrations, comparing trade-offs, and making informed architectural decisions without relying on vague claims or vendor-specific guidance.
For maintainers, it offers a concrete guide for prioritizing improvements, documenting intent, and evolving OpenTelemetry support in a predictable, user-centered way.
For the broader OpenTelemetry community, the model establishes a shared vocabulary that complements existing efforts like Instrumentation Score and the Ecosystem Explorer, helping drive more consistent, interoperable, and maintainable integrations over time.

By grounding the model in real-world evaluations, this work aims to strengthen collaboration between users and maintainers and support a healthier, more transparent OpenTelemetry ecosystem.