- Added new `audit_log` table with supporting migration (048)
- Implemented centralized `create_audit_log` helper to record key admin actions
- Logged events include:
- Site setting changes (sensitive data masked)
- User updates and deletions
- Added API endpoint `GET /api/admin/audit-trail` for viewing recent audit entries
- Created new frontend section in Settings for viewing the Audit Trail
- Displays timestamp, user, action, and details with safe HTML escaping
- Updated backend structure for better modularity and security
Files:
`backend/migrations/048_create_audit_log_table.sql`,
`backend/audit_logger.py`,
`backend/admin_routes.py`,
`frontend/settings-new.html`,
`frontend/settings-new.js`
Fixes & Enhancements
* Resolved five critical Apprise notification issues:
• Ensured configuration reload during scheduled jobs
• Fixed warranty data fetching for Apprise-only users
• Refactored notification dispatch logic with dedicated helpers
• Corrected handler scoping via Flask app context
• Wrapped scheduler jobs with Flask app context to prevent context errors
→ Verified: Scheduled Apprise notifications now work reliably for "Apprise only" and "Both" channels.
* Added support for SMTP\_FROM\_ADDRESS environment variable, allowing sender address customization independent of SMTP username. (PR #115)
* Fixed duplicate scheduled notifications in multi-worker environments:
• Strengthened should\_run\_scheduler() logic
• Now guarantees exactly one scheduler instance across all Gunicorn modes.
* Fixed stale database connection handling in scheduled jobs:
• Fresh connection acquired each run, properly released via try/finally
• Eliminates "server closed the connection" errors.
* Definitive scheduler logic fix for all memory modes (ultra-light, optimized, performance):
• Single-worker runs scheduler if GUNICORN\_WORKER\_ID is unset
• Multi-worker: only worker 0 runs scheduler.
Impact
* Apprise and Email notifications are now stable, reliable, and production-ready
* No more duplicate or missed notifications across all memory modes
* Improved system efficiency and robustness
