feat: Implement Zero-Gap Hot-to-Cold Time-Series Migration

[Mosas2000]

Area

TimescaleDB lifecycle and data retention

Problem

Retention and archival can create gaps or inconsistent reads while continuous aggregates, Redis caches, exports, and audit references still point at hot data.

Scope

Implement a zero-gap migration protocol for hot-to-cold time-series data with manifest checkpoints, dual-read verification, immutable archive objects, cache invalidation, and atomic range cutover.

Acceptance criteria

• Readers see a complete range during migration and after restart.
• Every archived segment has checksums, schema version, and row counts.
• Continuous aggregates and alert history remain correct across the boundary.
• Failed migration rolls back or resumes without duplicate rows.
• Restore drills prove the archive can reconstruct API results.

[stableprogrammer]

I have production experience with TimescaleDB retention, continuous aggregates, and zero-downtime archival patterns that keep readers consistent across hot/cold boundaries. I’ll deliver the zero-gap migration protocol with manifest checkpoints, dual-read verification, immutable archives, cache invalidation, and atomic cutover so ranges stay complete and failed migrations resume without duplicates.

[grantfox-oss]

🦊 GrantFox — @stableprogrammer has been assigned to this issue as part of the Third Campaign campaign!

Next steps:

1. Open a Pull Request referencing this issue (e.g., Closes #1021)
2. Your PR will be reviewed by the StellaBridge maintainers

Good luck! Track your progress on GrantFox.

[grantfox-oss]

🎉 This issue has been marked as completed on GrantFox as part of the Third Campaign campaign!

@stableprogrammer's PR #1107 was approved and merged by @Mosas2000.

🏆 @stableprogrammer: You earned 35 FoxPoints for this contribution! Your current tier: Explorer (389 total points). Track your full progress on GrantFox.

👏 Great work, @stableprogrammer! Keep contributing to StellaBridge.