A single Machine Learning project can inadvertently tie your entire application to a specific cloud vendor's feature serving solution, crippling your multi-cloud strategy. This talk introduces Feast [1], the open-source Feature Store, and explains its function as a vendor-neutral Data Gateway. We will show how Feast acts as an abstraction layer, allowing models to consistently retrieve features without worrying about the underlying data sources.

[1] https://github.com/feast-dev/feast/