Cloud AI Platform v1 API - Class Featurestore (2.12.0)

Reference documentation and code samples for the Cloud AI Platform v1 API class Featurestore.

Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top-level container for your features and their values.

Output only. Timestamp when this Featurestore was created.

Optional. Customer-managed encryption key spec for data storage. If set, both of the online and offline data storage will be secured by this key.

Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

FeaturestoreName-typed view over the Name resource name property.

Optional. The labels with user-defined metadata to organize your Featurestore.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.

See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Featurestore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.

Output only. Name of the Featurestore. Format: projects/{project}/locations/{location}/featurestores/{featurestore}

Optional. Config for online storage resources. The field should not co-exist with the field of OnlineStoreReplicationConfig. If both of it and OnlineStoreReplicationConfig are unset, the feature store will not have an online store and cannot be used for online serving.

Output only. State of the featurestore.

Output only. Timestamp when this Featurestore was last updated.