langfuse
About Langfuse
Open-source LLM observability and engineering platform for tracing, evaluating, and debugging AI applications. Langfuse provides production-grade monitoring with trace spans, cost tracking, prompt management, evaluation datasets, and a playground, all with no per-seat fees and a self-hostable MIT-licensed core.
Key Capabilities
Open-source MIT core, self-host for free or use the managed cloud with generous free tier
End-to-end LLM tracing with nested spans, latency tracking, and token cost attribution across providers
No per-seat pricing, entire teams get observability access without multiplying costs
Integrated prompt management, evaluation datasets, and playground for iterating on AI behavior in production
Standout Features
LLM Tracing
Nested trace spans capture every LLM call, tool invocation, and retrieval step, with latency, token counts, and cost attribution across OpenAI, Anthropic, and other providers.
Evaluation & Datasets
Build evaluation datasets, run LLM-as-judge scoring, and track quality metrics over time to catch regressions before they reach users.
Prompt Management
Version-controlled prompt templates with A/B testing, rollback, and production deployment, manage prompts as code without redeploying your application.
Perfect for
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Community Buzz
EVERY TOOL VIBE-CODERS SHOULD KNOW ABOUT: @claudeai for coding + debugging, @cursor_ai as AI code editor, @Replit for cloud coding + deployment.
Claude for coding ($20/mo), Supabase for backend (Free), Vercel for deploying (Free), Stripe for payments. The full vibe coder stack for under $35/mo.
The entire AI coding industry just got exposed. Someone leaked the system architecture of every major tool, 30,000+ lines of hidden instructions.
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