# Vertex AI Feature Group

> A Vertex AI feature group is free metadata that defines features over BigQuery tables for the current-generation Feature Store. Cost lives in the BigQuery storage underneath and in any feature online store serving those features. ZopNight inventories feature groups via Cloud Asset Inventory to map the ML feature pipeline end to end across GCP.

Source: https://zop.dev/integrations/gcp/vertex-feature-group
Updated: 2026-08-19

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A feature group organizes feature definitions over BigQuery data for the newer Vertex AI Feature Store. The group itself is metadata; serving and storage bill through associated resources.

## Definitions over BigQuery, priced accordingly

A feature group is the current-generation Feature Store's registration layer: it declares which columns of a BigQuery table or view are features and which entity keys them. Nothing in that declaration meters. The data never leaves BigQuery, where it bills as ordinary BigQuery storage, and low-latency serving only starts costing money once a feature online store syncs those values into provisioned serving nodes.

## Feature groups in the pipeline map

ZopDev inventories feature groups via Cloud Asset Inventory to map the ML feature pipeline. The group is the join point between a warehouse asset and the models consuming it: from a group, ZopNight's topology reaches back to the BigQuery source table and forward to the online stores serving it. That mapping is what makes feature-related spend attributable at all. Without it, feature storage reads as anonymous warehouse growth.

## Drift between declared and served features

The hygiene patterns worth catching are all indirect. Groups declare features no model has read in months while the source tables keep accruing warehouse storage. Groups point at tables refreshed by scheduled queries whose downstream consumers vanished, leaving compute running to maintain data nobody fetches. And parallel teams define overlapping groups over the same table, doubling the maintenance surface. None of these bill on the group itself; each marks upstream storage and refresh compute doing unclaimed work.

## Feature groups in the console

Google Cloud console → Vertex AI → Feature Store, in its feature groups view, lists each group with its BigQuery source and declared features. Following a group through to its online stores shows whether the declared features are actually being served anywhere. A group row can be deleted at any time without touching the underlying BigQuery data it described.