Traceloop OpenLLMetry
Overview
Open-source OpenTelemetry instrumentation for tracing and monitoring LLM and GenAI apps across common providers and observability backends.
Traceloop OpenLLMetry is an open-source observability tool for LLM and GenAI applications built on OpenTelemetry. It helps developers instrument AI workflows with Python or TypeScript examples, trace LLM calls, and route telemetry into observability platforms such as Datadog, New Relic, Grafana Tempo, Honeycomb, Splunk, Dynatrace, Instana, Traceloop, and Highlight. It is best suited for engineering teams that already operate LLM applications, RAG systems, or agent workflows and want vendor-neutral tracing and monitoring rather than a standalone end-user agent.
AI Agent Store research
What the evidence says about Traceloop OpenLLMetry
OpenLLMetry is positioned as open-source observability for LLM and GenAI applications using OpenTelemetry, with setup examples for Python and TypeScript and integrations across LLM providers, frameworks, and observability backends. Sources: official-product, github-repository, youtube-signoz.
Verified September 1, 2026
Verified capabilities
- OpenTelemetry-based LLM observability
Provides open-source observability for LLM and GenAI applications with OpenTelemetry as the underlying telemetry standard.[1]
- Python and TypeScript instrumentation examples
The official page shows Python and TypeScript initialization examples, including Traceloop initialization and workflow decorators around an OpenAI chat-completion workflow.[1]
- Observability backend compatibility
The product page lists observability platforms including Instana, Dynatrace, Grafana Tempo, Honeycomb, New Relic, Datadog, Splunk, Traceloop, and Highlight.[1]
- LLM provider and framework coverage
The official page lists provider and framework names including Anthropic, Bedrock, Chroma, Cohere, Gemini, LangChain, LlamaIndex, Mistral AI, Ollama, OpenAI, together.ai, and Watsonx.[1]
Where it fits best
- Engineering teams adding observability to LLM, GenAI, RAG, or agent-style applications.[1]
- Teams that want to monitor LLM performance, resource use, and production issues through OpenTelemetry-based telemetry.[1]
- Organizations already using observability tools such as Datadog, New Relic, Dynatrace, Grafana Tempo, Honeycomb, Splunk, Instana, Traceloop, or Highlight.[1]
Buying and deployment notes
OpenLLMetry is presented in the supplied sources as an open-source project; no paid pricing table or hosted plan price is provided in the supplied context.[1]
Platforms: Python, TypeScript, OpenTelemetry-compatible observability platforms[1]
Deployment: Open-source SDK instrumentation inside an application, Telemetry export to supported observability platforms[1]
Important considerations
- The official page excerpt shows Python and TypeScript setup examples; teams using other languages should verify SDK support before adoption.[1]
- OpenLLMetry is observability instrumentation rather than a model-hosting platform or standalone end-user agent; it is intended to send LLM telemetry into observability workflows.[1]
- The supplied sources do not provide a published paid pricing table, support SLA, or managed-service pricing for OpenLLMetry itself.[1]
Sources and research method (1)
We record only claims tied to public sources checked by our team or listing workflow. Counts above are derived directly from this profile, not a subjective rating.
- Open-source Observability for LLMs with OpenTelemetryOfficial site · checked 2026-09-01
Autonomy level
1%
Comparisons
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Some of the use cases of Traceloop OpenLLMetry:
- Tracing LLM application workflows
- Monitoring GenAI app performance
- Debugging RAG and agent pipelines
- Exporting LLM telemetry to observability stacks
- Standardizing observability across LLM providers
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Popularity level: 69%
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