Set up and manage feature stores for ML systems. Covers Feast, Hopsworks, and Tecton configuration, online and offline store architecture, feature materialization (batch and streaming), point-in-time correct feature retrieval for training, real-time feature serving for inference, feature freshness and staleness management, feature sharing across teams, feature registry and catalog, feature lineage and provenance, feature store monitoring, and migration strategies. Use when building feature infrastructure, sharing features across models, or serving features in production.
