Model Registry
A centralized repository for managing, versioning, and tracking machine learning models.
Overview
A model registry is a centralized system for storing, versioning, and managing machine learning models throughout their lifecycle. It tracks model metadata including training parameters, performance metrics, data lineage, and deployment status, providing a single source of truth for all models in an organization.
Key Details
Tools like MLflow Model Registry, Weights & Biases, and cloud-native solutions (AWS SageMaker, Azure ML, Vertex AI) provide model registries. Key features include model versioning, stage transitions (staging, production, archived), approval workflows, and integration with CI/CD pipelines. A model registry is essential for reproducibility and governance in production ML systems.