Monitor BigQuery Reservations
Viewing project and reservation slot usage using INFORMATION_SCHEMA
Project and reservation usage information is available for querying with INFORMATION_SCHEMA.JOBS*
views.
Reservation names are stored in the reservation_id
field of the schema of INFORMATION_SCHEMA.JOBS*
views.
Viewing project and reservation slot usage using the Google Cloud console
The Google Cloud console includes charts that display slot usage. For more information, see the Admin Resource Charts introduction documentation.
Viewing project and reservation slot usage in Cloud Monitoring
Information is available from the "Slots Allocated" metric in Cloud Monitoring. This metric information includes a per-reservation and per-job-type breakdown of slot usage. The information can also be visualized by using the custom charts metric explorer.
Additionally, you can monitor how your slots are consumed by using the following tools:
- Audit logs, specifically slot-ms consumed
- Jobs API
Viewing your flat-rate bill
To view your flat-rate bill in real time:
- In the Google Cloud console, go to the Billing portal.
- Navigate to the Reports section.
- Optionally, set the following settings under filters:
- Group by SKU.
- Filter for "BigQuery".
Google Cloud console displays your BigQuery flat-rate spend for each region and for each commitment type (annual and monthly):
Reservation cost attribution
This feature lets you attribute reservation fees back to the specific query usage across any projects that used the reservation. This results in more accurate net costs on a per-project basis.
All BigQuery Reservations API customers have an "Analysis Slots Attribution" line item in their Cloud Billing data, indicating the share of the reserved slots consumed in each project. This includes both the Billing portal and the Cloud Billing export. The cost for this new item is zero. The changes don't affect your invoice totals.
Audit logs
Creating, deleting, and updating resources related to BigQuery Reservations are recorded in the owner project's audit logs. See the BigQuery audit log section for more information.