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The short answer
Retain evaluation evidence according to a defined investigation purpose, access policy, and deletion process. Keep enough versioned material to explain results without copying unnecessary sensitive content into every artifact. Choose durations through the organization’s applicable requirements; a technical guide cannot supply a universal retention period.
What to take away
- Inventory raw and derived evidence copies.
- Retain fields only for a documented purpose.
- Test deletion across exports and regression derivatives.
Sources checked . Research synthesis and Rubrex recommendations. Examples and local experiments are labeled; they are not client results.
Inventory artifacts before choosing durations
OpenTelemetry’s sensitive-data guidance recommends collecting only data serving an observability purpose and reviewing whether attributes remain necessary. The same minimization principle is useful for evaluation evidence, although retention decisions require the organization’s own applicable policies and obligations.
List raw prompts, source documents, outputs, traces, labels, reviewer notes, metric tables, exports, and caches. Identify which contain sensitive material or references to it. A summarized finding can still expose a customer identifier, and a derived dataset can preserve content that was deleted from the original trace store.
Connect each retained field to a purpose
For each artifact, write why it is needed, who can access it, what less detailed representation might suffice, and what event ends that need. Preserve version manifests and aggregate counts where they can support historical explanation without retaining complete conversation content.
Use controlled references, redacted excerpts, or synthetic reproductions when those preserve the relevant failure mechanism. Test whether the sanitized case still demonstrates the issue. Removing every identifying field may protect data while making the case impossible to interpret; the objective is a justified balance documented by the responsible owner.
Test deletion across the evidence graph
In an illustrative retention drill, a synthetic customer marker appears in a prompt, tool trace, reviewer note, exported CSV, and copied regression case. Deleting only the raw prompt leaves several copies. The expected check follows that marker through every known storage path and records which artifacts must be removed or transformed.
Keep deletion of sensitive content distinct from preserving a non-sensitive audit record that the deletion occurred. Verify permissions and any allowed exceptions through the organization’s process. Do not claim complete deletion solely because a dashboard no longer displays the original record.
| Case or record | Expected check | Decision |
|---|---|---|
| Raw prompt deleted; CSV still contains marker | Sensitive copy remains downstream | Deletion drill not complete |
| Sanitized regression preserves the defect | No unnecessary original content retained | Validate the reproduced mechanism |
| Historical case evidence removed | Full reconstruction no longer possible | Qualify the report’s reproducibility claim |
Preserve interpretability after minimization
After redaction or deletion, test whether historical metrics can still be explained at the level the report promises. If case evidence is no longer available, qualify that limit rather than implying full reproducibility. Keep the retention-policy version associated with the evaluation release.
Assign owners for new export paths and recurring evidence reviews. Reassess collection after adding a tool, reviewer integration, or observability destination. A short retention duration does not prevent unnecessary exposure before deletion, so minimize at collection and validate downstream handling as separate controls.
Limits of the evidence
The marker drill is proposed and no storage system was tested. This article gives technical evidence-management guidance, not legal advice or a mandated retention schedule. Unknown copies, backups, and external destinations can limit deletion and reproducibility claims.
Common questions
What is the correct retention period?
There is no universal technical answer. The responsible organization must choose it using its purposes and applicable requirements, then implement and verify that policy.
Can hashes replace all retained evidence?
Hashes can identify matching artifacts but do not explain task meaning or guarantee anonymity. Decide what evidence is needed and assess the data implications of the representation.
Sources & further reading
Primary sources behind this briefing. A source’s findings apply to its own study conditions; publication on arXiv does not establish peer review.
- OpenTelemetry: Handling sensitive data OpenTelemetry · Living reference · Maintained documentationReviewed: data minimization and redaction considerations; no legal retention-duration advice. Accessed October 16, 2026.
Questions or corrections? Write to Rubrex. Read our editorial approach.