Registry

The Feast feature registry is a central catalog of all feature definitions and their related metadata. Feast uses the registry to store all applied Feast objects (e.g. Feature views, entities, etc). It allows data scientists to search, discover, and collaborate on new features. The registry exposes methods to apply, list, retrieve and delete these objects, and is an abstraction with multiple implementations.

Feast comes with built-in file-based and sql-based registry implementations. By default, Feast uses a file-based registry, which stores the protobuf representation of the registry as a serialized file in the local file system. For more details on which registries are supported, please see Registries.

Updating the registry

We recommend users store their Feast feature definitions in a version controlled repository, which then via CI/CD automatically stays synced with the registry. Users will often also want multiple registries to correspond to different environments (e.g. dev vs staging vs prod), with staging and production registries with locked down write access since they can impact real user traffic. See Running Feast in Production for details on how to set this up.

Accessing the registry from clients

Users can specify the registry through a feature_store.yaml config file, or programmatically. We often see teams preferring the programmatic approach because it makes notebook driven development very easy:

Option 1: programmatically specifying the registry

repo_config = RepoConfig(
    registry=RegistryConfig(path="gs://feast-test-gcs-bucket/registry.pb"),
    project="feast_demo_gcp",
    provider="gcp",
    offline_store="file",  # Could also be the OfflineStoreConfig e.g. FileOfflineStoreConfig
    online_store="null",  # Could also be the OnlineStoreConfig e.g. RedisOnlineStoreConfig
)
store = FeatureStore(config=repo_config)

Option 2: specifying the registry in the project's feature_store.yaml file

project: feast_demo_aws
provider: aws
registry: s3://feast-test-s3-bucket/registry.pb
online_store: null
offline_store:
  type: file

Instantiating a FeatureStore object can then point to this:

store = FeatureStore(repo_path=".")

The file-based feature registry is a Protobuf representation of Feast metadata. This Protobuf file can be read programmatically from other programming languages, but no compatibility guarantees are made on the internal structure of the registry.