Volumetric Check Permissions¶
This page covers the team permissions required to view, create, edit, archive, and delete a Volumetric check on a source datastore. For the full reference of user roles, see User Roles. For the canonical matrix of every team-permission-gated action, see Team Permissions Overview.
Permission Matrix¶
The table below shows which team permissions can perform each action on a datastore the user has access to:
Key Details¶
- Viewing is available to all team permissions, including Reporter and Viewer.
- Draft work is available from the Drafter permission upward: creating a check as Draft, editing it while it stays Draft, and restoring an archived check as Draft.
- Validating a check requires the Author permission. A Drafter does not see the Validate button and saves work as a Draft without validating it.
- Anything that puts a check into evaluation requires at least the Author permission: creating or activating an Active check, editing an Active check, archiving, restoring as Active, and deleting permanently.
- Editing the limits from the Observability chart (the Edit Thresholds button) requires the Author permission. See Edit Threshold.
- The same rules apply through the API. The API page lists the permission each endpoint requires.
- Admins bypass team permissions and can manage checks on every datastore in the workspace. Managers do not bypass team permissions: like Members, they need the required permission in at least one team assigned to the datastore.
Team Context
Permissions are evaluated against the datastore's team assignments. A user must have the required team permission in at least one team that the datastore belongs to. For more details on how teams work, see the Team Permissions page.
See Also¶
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How It Works
The complete reference: definition, when the check is evaluated, the properties, the history it needs, and AI Managed Volumetric checks.
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Comparisons
What Absolute Value, Absolute Change, and Percentage Change measure, and what each one compares against.
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Anomaly Reporting
What the Shape Anomaly reports, how to read the numbers in the message, and why there is nothing to report per row.
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Examples
Three production scenarios: a load that adds no rows, a weekly growth band, and a fixed volume range.
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Best Practices
Guidelines for choosing the comparison and Measurement Period, scheduling the Scan, and working with AI Managed checks.