Model Registry: Source of Truth for Deployed Models
A model registry is the source of truth for which trained model runs where, turning anonymous artifact files into versioned, staged assets. It matters when you deploy multiple models or need instant rollbacks.
A model registry is the source of truth for which trained model runs in which environment, turning anonymous artifact files into versioned, staged software assets. It becomes essential once you deploy multiple models, share artifacts across teams, or need to roll back a production failure without retraining from scratch. The common footgun is treating the registry as passive cloud storage; without enforced stage transitions, lineage tracking, and metadata, you simply recreate the chaos of scattered notebook exports and untracked pickle files.
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