Respan
LLM tracing, evals, and gateway
Datadog LLM Observability is a comprehensive monitoring platform designed to help teams deliver LLM applications to production faster with end-to-end tracing across AI agents, structured experiments, and robust quality and security evaluations. The platform provides complete visibility into inputs, outputs, latency, token usage, and errors across AI agent workflows. It features structured experiment management for testing prompt changes, model swaps, and parameter tuning, along with quality evaluations including hallucination detection and output clustering for drift identification. Security features include sensitive data scanning and prompt injection detection. As part of the broader Datadog platform, LLM Observability integrates seamlessly with APM and Real User Monitoring for unified full-stack visibility, allowing teams to correlate LLM workloads with backend services, infrastructure, and user sessions.
Core capabilities this platform advertises.
What this tool does well, and the limitations to keep in mind.
Pros
Cons
Enterprise teams already using Datadog who want to add LLM monitoring
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Side-by-side comparisons with other tools in this category.
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