Historical data in the database currently accumulates indefinitely and serves no purpose. Old records should be periodically cleaned up.
Approach:
Define a retention policy (e.g., keep data for the last N days/weeks/months)
Implement a cleanup routine on the server (scheduled task or on-startup job)
Identify which tables/collections contain date-bound data (daily menus, selections, etc.)
Add a configurable retention period via environment variable
Log cleanup actions for auditability
Consider keeping aggregated statistics even after raw data is purged
## Feature: Clean Up Old Data from Database
**Source:** TODO.md line 33
### Implementation Notes
Historical data in the database currently accumulates indefinitely and serves no purpose. Old records should be periodically cleaned up.
**Approach:**
1. Define a retention policy (e.g., keep data for the last N days/weeks/months)
2. Implement a cleanup routine on the server (scheduled task or on-startup job)
3. Identify which tables/collections contain date-bound data (daily menus, selections, etc.)
4. Add a configurable retention period via environment variable
5. Log cleanup actions for auditability
6. Consider keeping aggregated statistics even after raw data is purged
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Feature: Clean Up Old Data from Database
Source: TODO.md line 33
Implementation Notes
Historical data in the database currently accumulates indefinitely and serves no purpose. Old records should be periodically cleaned up.
Approach:
Nově se již používají pro statistiky, tj. chceme je zachovat.