Software Development
MLflow MLOps Migration
Guided workflow for taking any ML codebase — including one with no experiment tracking at all, or one full of MLflow 2-era idioms — to a production-grade open-source MLflow 3 setup with dev/staging/prod environments, registry-based promotion, and served models. Walks seven phases with a developer who may have zero MLflow 3 experience — assess the codebase (scripted read-only audit), model the registry domain (per-environment model names, aliases, gates), stand up tracking per environment, restructure training code to MLflow 3 idioms, wire evaluation-gated promotion, serve and smoke-test, then run the ongoing MLOps loop. Use when asked to set up MLflow, migrate to MLflow 3, productionize model training and serving, or design a dev/staging/prod MLOps cycle. Pairs with the sibling mlflow-3 rule pack for every API decision.
- Publisher / source
- pproenca/dot-skills (found on skills.sh)
- Upstream record
- pproenca/dot-skills
- Version
- Version 2
- Published
- Publication review
- Approved for publication
- Content fingerprint
5641b0195a0b1e207374e82ada71de5781b374117671119c2a6dd508c81c9596