SAG / ARCHITECTURE NOTE
Customer Data Cache Lifetime: Preserving Speed and Logout Boundaries
An operational approach that links brief reuse of authenticated data with its removal when accounts change. Storing reports in persistent storage can leave sensitive data behind after logout. Fast retrieval and data retention carry the same responsibility.
What Is Customer Cache Lifetime?
It is an operational approach that links brief reuse of authenticated data with its removal when accounts change. This note treats customer cache lifetime in terms of the responsibilities of input, transformation, and output rather than as a feature name. To trust an analysis result, it must be possible to trace what data was received, what was checked, and how far the conclusions can go.
Why Is This Technology Needed?
Storing reports in persistent storage can leave sensitive data behind after logout. Fast retrieval and data retention carry the same responsibility.
Design Principles and Data Flow
Limit the validity period and number of entries in the memory cache, and clear it on authentication failure and logout. Distinguish shared HTTP caches from caches for personal screens.
Authentication lookup → Limited memory cache → Account-boundary invalidation
Each stage should not relabel the success of the previous stage as its own achievement. If data identifiers, periods, and validation status are recorded continuously, you can locate where omissions and errors occurred and determine what needs to be checked again.
Connection to the SAG Architecture
The SAG customer cache reuses data in memory and clears it on authentication failure and logout. Reports are not stored in the browser’s persistent storage.
SAG’s operational value lies in connecting these relationships to pages and questions, comparison results, and improvement work. Instead of reading only the numbers, customers can review both what needs improvement and the grounds for their decisions. Patterns that require additional application should be interpreted within the scope of the relevant paragraph.
Illustrative Example and Criteria for Evaluation
Use the cache for illustrative same-month navigation, but do not provide existing data to a new account. A matching URL is not a reason to reuse data across user boundaries.
The example above is intended to explain structure and calculation; it is not measured performance from a specific customer. Actual reports should link the selected period, targets, observation conditions, and original records so that the same judgment can be checked again.
Practical Verification Checklist
| Flow stage | Item to check |
|---|---|
| Authentication lookup | Clear at account boundaries |
| Limited memory cache | Check for persistent storage |
| Account-boundary invalidation | Verify expiration and maximum item count |
Check that the same meaning is maintained not only with normal inputs, but also with empty, duplicate, and differently conditioned data. Connecting verification items to completion criteria can reduce the gap between feature descriptions and actual operations.
Limitations and Points to Consider When Applying
Even a short-lived cache can briefly display stale values. Define forced refresh after changes and the expiration conditions.
Research and Official Documentation
- IETF HTTP Caching RFC 9111 — Defines criteria for HTTP cache reuse and revalidation, which should be distinguished from an in-memory screen cache.
External materials provide background on the design topic above; they do not certify every SAG implementation or customer outcome. The interpretation of how this note applies and the illustrative example are organized around SAG’s operational structure. Materials checked: 2026-10-06.
Further Reading and Feature Information
- Related architecture note
- Try the service connected to customer cache lifetime
- Feature FAQ
- Discuss implementation scope
How to Continue Reading About This Technology
Explore tenant permissions, job retries, cache, and approval history.
SAG / KNOWLEDGE LINKS