# Vertex AI Metadata Store

> Vertex AI metadata stores bill per GB of lineage metadata (artifacts, executions, and the links between them), which makes them one of the cheapest Vertex resources. ZopNight inventories every metadata store via Cloud Asset Inventory because the lineage graph documents how the expensive resources relate: which jobs produced which models on which endpoints.

Source: https://zop.dev/integrations/gcp/vertex-metadata-store
Updated: 2026-08-19

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A metadata store records ML lineage: artifacts, executions, and the relationships between them, billed per GB of metadata. Cost is minor, but the store documents how other expensive resources relate.

## Lineage records billed by the gigabyte

A metadata store meters on stored metadata volume: the artifacts, executions, and contexts that ML Metadata accumulates as pipelines run, charged per GB. Set against endpoints and training jobs, the sums are trivial; even a busy pipeline history amounts to modest storage. The significance of this row is informational rather than financial.

## Why ZopNight keeps the lineage graph

ZopDev inventories metadata stores via Cloud Asset Inventory for complete ML topology. Lineage answers questions cost tooling otherwise cannot: which pipeline produced the model an endpoint is serving, which datasets fed a given training run, and whether an expensive resource has any living downstream consumer. When an idle-endpoint recommendation needs the confidence that nothing depends on a deployment, this graph is the context that supplies it.

## Metadata accumulation without ceremony

Even a cheap meter benefits from hygiene. Pipeline-heavy projects pile up execution records for experiments concluded long ago. Default stores collect lineage from every run in the project without anyone owning retention. And deleted pipelines leave artifact rows pointing at Cloud Storage objects that may themselves deserve cleanup, often the more valuable find, since those referenced artifacts bill at real storage rates while the metadata about them costs next to nothing. Pruning the graph is safe: it informs no running system. Worth knowing: a default store appears per project and region the first time a pipeline runs, so most Vertex projects carry one whether or not anyone chose to create it.

## Metadata stores in the console

Google Cloud console → Vertex AI → Metadata opens the ML Metadata browser for the region's store, where artifacts and executions can be traced through their relationships. That is the same graph ZopNight folds into its ML topology.