Feast is the bridge between your data and your machine learning models. It allows teams to register, ingest, serve, and monitor features in production.
Feast provides a registry through which to explore, develop, collaborate on, and publish new feature definitions. The registry is the central interface for all interactions with the feature store.
Easily ingest data from both batch and streaming sources into both online and offline feature stores, automating data management and making features available for serving.
A feature retrieval interface that provides a consistent view of features in stores. Feast provides a point-in-time correct interface for training data, and a low-latency API for online serving.
Feast allows teams to confidently operate machine learning systems by publishing operational metrics, statistics, and logs to their existing production monitoring infrastructure.
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