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Google Vertex AI connector

Beta — implemented and listed for early use. Confirm the first sync in a non-production window before relying on it for close.

Connect Google Cloud BigQuery billing export to pull Vertex AI spend (Beta).

Status: Beta · Claim C-22

Overview

Connect Google Cloud BigQuery billing export to pull Vertex AI spend (Beta).

Data pulled

  • Daily net spend by SKU from the detailed billing export table
  • Filtered to service.description = Vertex AI
  • Token counts are not in the export (cost only)

Authentication & credential storage

Meridian stores the following fields for this connector (values encrypted at rest):

  • service_account_json
  • project_id
  • dataset_id
  • billing_account_id
  • Credentials are encrypted with AES-256-GCM using a KMS-wrapped data encryption key (DEK) and stored in vendor_connections.credentials_encrypted.
  • Meridian never returns the plaintext key after save. Revocation is disconnect: deactivate or delete the vendor connection — sync stops and the encrypted blob is no longer used.
  • Grant the service account roles/bigquery.jobUser and roles/bigquery.dataViewer on the billing-export dataset.

Sync schedule & behavior

Billing-export lag is typically 1–6 hours. Syncs automatically every 6 hours; manual sync anytime. There is no per-connection frequency setting.

Setup steps

  1. Enable detailed Cloud Billing export to BigQuery.
  2. Create a service account with BigQuery job and data viewer roles; download the JSON key.
  3. Connect GCP Vertex AI in Meridian with project, dataset, billing account id, and service account JSON.

Troubleshooting

  • Table not found: confirm the export table name matches gcp_billing_export_resource_v1_{billing_account}.
  • Permission denied: add bigquery.jobUser and bigquery.dataViewer.

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