Data retention implementation
Review the retention promise against a restored system
The design must explain every relevant copy and what happens after failure. A successful normal deletion run is necessary but incomplete evidence.
In this article
Inspect policy and data scope
Identify the approved data categories, trigger events and exceptions. Confirm that the responsible owner has resolved ambiguous legacy records and any legal or business requirements.
Trace primary records, attachments, indexes, logs, exports and provider copies. Each in-scope destination needs an owner and an implemented treatment.
Check claims of de-identification separately. Removing obvious identifiers does not automatically establish that remaining data cannot be linked back to a person.
Follow partial execution
Interrupt one destination and verify that the action remains incomplete with a recoverable state. Repeated execution should continue safely without recreating removed data.
Add a hold after selection and inspect the action-boundary decision. Review who can change the hold or override a failed result.
For object storage, inspect versions, delete markers and protection settings under the chosen service's semantics. A current object disappearing is not proof that every version is gone.
Rehearse restoration and reindexing
Restore a synthetic pre-deletion backup into isolation and apply the documented retention reconciliation before exposing it. Verify that derived systems do not republish the removed record.
Check how the retention ledger or equivalent decision evidence itself survives recovery. A control restored to an older state may forget deletions made after the backup.
Review the actual backup lifecycle and any limits on selective removal. User-facing claims must reflect that approved treatment accurately.
Inspect evidence and operations
Ensure completion metrics distinguish held, failed and fully handled records. Logs should preserve necessary action evidence without becoming another full copy of the deleted data.
Review concurrency, stop conditions and support procedures for unexpected scope. Destructive execution needs bounded, explainable progress.
Approve the design when the team can demonstrate the intended lifecycle across failure and recovery, with remaining exceptions owned. A scheduler's green status or a smaller primary table does not establish the full promise.
Primary sources
AWS: object lifecycle managementAWS: Object LockReferences checked 11 September 2026.