MLflow
Open platform for the ML lifecycle: experiment tracking, model registry, packaging, evaluation, and production monitoring.
Why it is included
De facto OSS standard for experiment tracking and model registry; strong uptake for LLM eval and tracing integrations.
Best for
Teams that need reproducible runs, artifact versioning, and a path from notebook to governed deployment.
Strengths
- Tracking + registry
- Large ecosystem
- Vendor-neutral
Limitations
- Production hardening still needs your infra choices (DB, auth)
Good alternatives
Weights & Biases (commercial) · Neptune · TensorBoard alone
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