Context

I'm one of the maintainers of github.com/langfuse/langfuse. livekit is growing in popularity and I've gotten multiple requests by community members who'd like to get traces of their livekit applications in order to evaluate them.

Suggestion

I'd suggest to follow the example of the AI SDK (docs) by adding native Opentelemetry-based instrumentation to livekit. Thereby, the implementation is vendor-agnostic and teams can use an LLM-specific backend like Langfuse (tracing, evals, prompt management) or their traditional observability platforms (Grafana, Datadog, ...).

Potential addition next to traces: Exporting metrics (livekit docs) via OpenTelemetry would allow teams to easily track them within their observability stack.

Resources

• https://opentelemetry.io/blog/2025/ai-agent-observability/
• https://opentelemetry.io/docs/specs/semconv/gen-ai/
• https://langfuse.com/docs/opentelemetry/get-started
• https://github.com/orgs/langfuse/discussions/5235