Evaluation and observabilityOpen sourceUpdated 2026
OpenTelemetry
Advanced · Observability standard/tooling
Open standard and ecosystem for traces, metrics, and logs increasingly used in LLM app observability.
Best for
Engineering teams that want AI telemetry to fit existing observability systems.
Why use it
Useful when LLM apps should share tracing and monitoring practices with the rest of the stack.
Tradeoffs
Not an LLM-specific eval product; you will need app-specific spans and dashboards.
Key features
- Traces
- Metrics
- Logs
Alternatives
Langfuse, Phoenix, LangSmith
Where it fits
OpenTelemetry belongs in the evaluation and observability layer of an open AI stack. Evaluate it against your model runtime, privacy needs, deployment target, and the amount of operational complexity your team can support.
CategoryEvaluation and observabilityLicenseApache 2.0DeploymentObservability standard/toolingModeOpen standard
OpenTelemetry →Recommendation
Use OpenTelemetry when LLM app traces should join your existing observability stack.