Lunary vs Sentry
Updated March 10, 2026
Overview
Lunary is an open-source LLM observability platform for monitoring AI applications in production. It provides request tracing, cost tracking, user analytics, and prompt management with a clean dashboard. Lunary can be self-hosted for data privacy and offers a managed cloud option.
Sentry provides runtime error monitoring and performance observability for AI applications. Its LLM monitoring capabilities track model calls, token usage, and latency alongside traditional error tracking. Sentry helps teams catch and debug issues in production AI pipelines with detailed stack traces and context.
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Production-ready platform
- Good performance
- Active development
- Strong features
Cons
- Enterprise pricing varies
- Setup complexity
- Learning curve required
Pros
- Developer-friendly platform
- Production-ready
- Good performance
- Active development
Cons
- Enterprise pricing varies
- Setup complexity
- Learning curve
Compare Lunary and Sentry on your own traffic
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 500+ models through one gateway.