Anomaly

Flows let you automate how anomalies are cleaned up over time. Under Anomaly actions, you can choose between two cleanup options:

• Archive → Move inactive anomalies out of the active queue
• Delete → Permanently remove inactive anomalies

Use these actions to keep your anomaly list lean, relevant, and manageable—without manually closing out each record.

Archive

Use the Archive action to automatically move anomalies into an archived state when they’ve been inactive for a set amount of time. This is ideal for organizations that prefer to keep a historical record but don’t need old anomalies cluttering the active view.

How It Works

The Archive action identifies anomalies with no updates or comments during the chosen Inactivity Period and archives them using the reason you specify.

💡 Why archive instead of delete?
Archiving lets you clean up the active queue without losing historical context.

Inactivity Period

Choose how long an anomaly must remain untouched before being archived.

Options include:

• Week
• Month
• Quarter
• Year

Note

Anomalies are archived automatically if they have no updates or comments during the selected inactivity period.

Archive Reason

Define why these anomalies are being archived:

• Resolved — The anomaly represents a valid data quality issue that has been fixed.
• Invalid — The anomaly wasn’t a legitimate issue.
• Discarded — The anomaly is no longer relevant or under review. (Most common for automation.)

Assign Additional Tags

Automatically apply tags to anomalies archived through this flow. Useful for labeling cleanup runs (e.g., auto-archive-q4).

Comment (Optional)

Provide a note that will appear on every archived anomaly, giving future reviewers context.

Filter Conditions

You can narrow down which anomalies should be archived:

• Source Datastores — Archive anomalies from selected datastores only

• Anomaly Tags — Archive anomalies labeled with specific tags

Delete

The Delete action permanently removes anomalies after a set inactivity period. Use this when you don't need to retain historical anomaly records—e.g., for ephemeral data or noise cleanup.

Warning

Delete permanently removes anomalies from the system. This cannot be undone.

How It Works

The Delete action looks for anomalies that have had no updates or comments during the selected Inactivity Period and permanently removes them. This helps you clear out old or unnecessary anomalies that you no longer need.

⚠️ Why delete instead of archive?
Delete removes the anomaly completely, which is useful when you don’t need to keep any record of it.

Inactivity Period

Define how long an anomaly must remain inactive before deletion.

Options include:

• Week
• Month
• Quarter
• Year

Note

Anomalies are deleted if they have no updates or comments during the selected inactivity period.

Source Datastores

Delete anomalies originating from specific datastores.

Anomaly Statuses

Target anomaly states such as:

• Active
• Acknowledged
• Resolved
• Duplicate
• Invalid
• Discarded

Anomaly Tags

Delete anomalies that carry specific tags (e.g., test-data, noise).

📘 When to Use Archive vs Delete

Action	Best for	Keeps history?	Suitable for
Archive	Cleaning up long-ignored anomalies while retaining context	✅ Yes	Audit needs, compliance workflows, long-term reference
Delete	Removing noise or temporary anomalies completely	❌ No	Test data cleanup, non-critical anomalies, high-volume events