Traceloop
LLM observability platform built on OpenTelemetry (OpenLLMetry). Automatically instruments LLM calls (OpenAI, Anthropic, Bedrock, etc.), vector DB queries, and agent workflows. Provides distributed traces, metrics, and prompt tracking for AI applications.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
HTTPS enforced for trace export. API key has no scope control. SOC 2 Type II. LLM prompt/response data is sent to Traceloop's servers — review data handling policy if processing sensitive content.
⚡ Reliability
Best When
You want automatic LLM call instrumentation with minimal code changes and OpenTelemetry compatibility, especially for non-LangChain agent frameworks.
Avoid When
You're deeply invested in LangChain and LangSmith provides all the observability you need.
Use Cases
- • Instrument agent workflows to trace every LLM call, tool use, and retrieval step with automatic OpenTelemetry integration
- • Track prompt versions and response quality across model upgrades without changing application code
- • Identify latency bottlenecks in agent pipelines by tracing the full execution tree from user query to response
- • Monitor token usage and costs per agent session, user, or workflow type for budget management
- • Use OpenLLMetry SDK to send traces to any OpenTelemetry-compatible backend (Jaeger, Honeycomb, Datadog)
Not For
- • Teams already using LangSmith and deeply integrated with LangChain ecosystem — LangSmith has tighter integration with LangChain
- • Production monitoring at very high scale — Traceloop is more focused on development and debugging than production alerting
- • Non-LLM application observability — use standard OpenTelemetry tools for general observability
Interface
Authentication
API key set as environment variable (TRACELOOP_API_KEY). SDK patches LLM client libraries automatically — no explicit instrumentation calls needed after initialization.
Pricing
Free tier suitable for development and small deployments. OpenLLMetry (the SDK) is MIT licensed and can export to any OTel backend without using Traceloop's hosted service.
Agent Metadata
Known Gotchas
- ⚠ SDK auto-patches LLM client libraries at import time — agents must initialize Traceloop before importing openai, anthropic, etc. to ensure instrumentation
- ⚠ Sampling is not enabled by default — agents in high-volume production sending every trace can incur significant costs; configure trace sampling rates
- ⚠ Some LLM provider SDKs (e.g., streaming responses) may not be fully instrumented — check support matrix for your specific client version
- ⚠ Traceloop sends traces asynchronously — agents that exit immediately after LLM calls may drop the last few traces if the export queue hasn't flushed
- ⚠ The OpenLLMetry SDK can also export to Jaeger, Honeycomb, or any OTLP endpoint — useful if you don't want to use Traceloop's hosted platform
Alternatives
Full Evaluation Report
Detailed scoring breakdown, competitive positioning, security analysis, and improvement recommendations for Traceloop.
Scores are editorial opinions as of 2026-03-06.