Langfuse vs MLflow

TL;DR: Both are open-source observability platforms, but MLflow is a comprehensive ML lifecycle tool (experiment tracking, model registry, gateway) that expanded into LLM observability, while Langfuse is purpose-built specifically for LLM application debugging and monitoring. MLflow suits teams needing end-to-end ML operations alongside LLM features, whereas Langfuse offers deeper LLM-specific capabilities like advanced prompt management and is explicitly designed for self-hosting at enterprise scale. Choose based on whether you need broader ML infrastructure (MLflow) or specialized LLM tooling (Langfuse).