Traceloop

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Traceloop builds and maintains OpenLLMetry, an Apache 2.0 licensed set of OpenTelemetry extensions that has become the de facto open standard for instrumenting language model applications, with more than 7,200 GitHub stars. Rather than defining a proprietary trace format, it contributes the semantic conventions for LLM observability to OpenTelemetry itself, so token usage, latency and cost per request or per feature arrive as ordinary OTel spans. The consequence is the product's whole argument: no lock in. Instrumented traces flow to Datadog, New Relic, Honeycomb, Grafana, Sentry, a self run collector, or Traceloop's own managed platform, and switching backends does not mean reinstrumenting. SDKs cover Python, TypeScript, Go and Ruby, and instrumentations ship for more than twenty model providers including OpenAI, Anthropic, Gemini, Bedrock and Ollama, for vector databases including Pinecone and Chroma, and for frameworks including LangChain, LlamaIndex and CrewAI. A native OpenTelemetry based gateway called Hub offers an alternative connection path. The managed platform adds what the open library deliberately does not: dashboards, alerting, evaluation and full trace visibility into RAG pipelines. Its most distinctive capability is turning production failures into reproducible test cases, which closes the loop between observing a problem and being able to test the fix rather than leaving a trace to be read by hand. Where it separates from most of this category is deployment. Traceloop holds SOC 2 and HIPAA certification and supports air gapped deployment, aimed explicitly at healthcare and financial services buyers for whom cloud only observability is not viable. Most competitors in LLM observability are SaaS first, so for a regulated buyer the practical shortlist is much shorter than the category's length suggests.