Observability

MLflow Tracing

Native LLM tracing and evaluation integrated into the MLflow open-source ecosystem.

Overview

MLflow’s tracing capability captures LLM function calls, parameters, and outputs as native spans within the MLflow UI. It integrates with existing ML experiments, model registries, and evaluation datasets for unified lifecycle management.

Best for

existing MLflow stacks
unified ML/LLM lifecycle
experiment tracking

Trade-offs

vs Arize Phoenix

MLflow excels at unifying traditional ML and LLM workflows in one open-source platform, while Phoenix offers deeper vector analytics and standalone LLM debugging features.

What XeroHack pre-wires

When you pick MLflow Tracing in the interview, the engine emits these files into your scaffold:

decorator-based tracing
experiment linking
metric logging

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