Model retention as a policy decision separate from audit immutability
Stakeholders confuse append-only records with keeping every payload forever, while the archive has a fictional bounded retention agreement.
- Focused work estimate
- 5h + prerequisites
- Priority in the scenario
- Medium
- Engineering practice
- Data lifecycle · Policy modeling
Estimated field mix
- Privacy engineering50%
- System design30%
- Storage systems20%
Field percentages are editorial estimates of the ticket's engineering focus. They total 100%; they are not measured time, proficiency scores, or ownership evidence.
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Project context
A fictional procurement platform keeps append-only action records. Operators want fast recent search and affordable old records without losing provenance or leaking tenant data.
Setup prerequisites
- Create synthetic audit events and local storage/search adapters.
- Use an explicit fictional retention policy, not legal advice.
Preceding work
Complete these dependencies, or supply their agreed outputs before taking this ticket.
- AARCHIVE-101 · Define which audit questions require indexed search versus archive retrieval
- AARCHIVE-102 · Calculate archive storage growth from event size and retention assumptions
- AARCHIVE-103 · Choose hot and cold archive boundaries with a reviewable decision record
- AARCHIVE-104 · Define an immutable archive segment manifest
- AARCHIVE-105 · Specify search indexing as a rebuildable projection of archived events
- AARCHIVE-106 · Authorize archive retrieval before issuing object capabilities
- AARCHIVE-107 · Define archive query pagination across hot and cold boundaries
Acceptance criteria
- Specify retention scope, expiry and hold behavior.
- Preserve authorized deletion facts without claiming deleted bytes remain available.
- Identify which policy decisions need external approval before implementation.
Implementation constraints
- Use a fictional policy and synthetic data; make no legal compliance claim.
Verification to include
- Apply expiry to an eligible segment in the model.
- Apply a hold and show that deletion remains blocked.
Deliverables
- Retention model and policy-state probe
Rollout and recovery
Review policy before any delete implementation; keep proposed deletion plans read-only.
Value of the work
For the engineer: Practice storage tradeoffs, provenance and data-lifecycle decisions.
For the team: Review archive cost and retrieval guarantees before committing to infrastructure.
Evidence boundaries
Outcome Evidence: Tests, patches, and runbooks are requested deliverables. They become Outcome Evidence only through a qualified Mission and immutable Evidence IDs.
Ownership Evidence: Independent adaptation must be observed under a declared verification policy and cite immutable Evidence IDs. Completing a planning ticket establishes no Ownership Evidence.