Artifacts & Registry
What a model artifact contains, the registry lifecycle from candidate to archived, and promotion judged on quality, latency, memory, cost and robustness rather than one offline score.
A weights file alone is not a model. The artifact is parameters, architecture, fitted preprocessing, feature order, version and training metadata — and serving needs all of it.
The registry is a state machine over artifacts — Candidate, Registry, Staging, Production, Archived — that stores lineage, metrics, approvals and the feature-definition version, so "which model is live" has one answer.
A challenger is promoted on quality, latency, memory, cost, robustness and — where relevant — fairness, compared against the champion on the same slice with the same threshold policy. One improved offline number is not a reason to ship.
Hashes and signatures prove the bytes serving loads are the bytes that were evaluated. Deserialisation formats that execute code on load, and a serving process that loads the wrong file, are the two ways that proof gets skipped.
The normaliser's means and standard deviations, the encoder's vocabulary, the imputation values, the feature order and the threshold are fitted on the training fold and ship with the weights. Recomputing any of them at serving time is a different model.