model registry

Reproducibility is what separates an ML platform from a pile of notebooks. The signal is tracking the full provenance (data, code, config, metrics) and a registry that governs promotion. Here is what to track and why each piece matters.

'Which model is in prod right now, and how did it get there?' should be a one-second lookup with an audit trail. If it isn't, you have a rollback and compliance problem already. Here is the promotion pipeline.

Promotion is the easy part. Governance is who is allowed to ship what, on whose sign-off, with what documented, and how a model gets retired. Here is the control plane an auditor actually asks for.