F1: Deploy Validation at Scale

## Summary
Validate deploy success rate across hundreds of live projects. Current data is based on a limited sample — before treating it as reliable, validate at scale.

## Acceptance Criteria
- [ ] Deploy validation test suite running continuously across live projects
- [ ] Correctness/compliance checks distinct from pass/fail (e.g. flag app code in ConfigMap, app needing PV deployed without volume)
- [ ] Mid-point checkpoint (Sprint 4) with partial success-rate estimate
- [ ] Final success-rate figure locked by Sprint 5
- [ ] Compliance enforcement moves from flagging → blocking by Sprint 5

## Notes
- Runs as continuous background track across all sprints
- Checkpoints in Sprint 2 (informal) and Sprint 4 (real estimate)
- Independent of GitHub Actions generation track

## Success Metrics
- Validated success rate at scale
- % of deploys passing compliance/correctness checks
- Deploy abandonment rate
- Variance in deploy behavior across repeated deploys of unchanged code (target: zero)

No files, tests, or entry points are named. Start by locating the existing deploy validation flow and the live-project deployment path, then map how correctness/compliance checks and pass/fail results are recorded. Done means continuous scale validation, Sprint 2 and Sprint 4 checkpoints, a locked Sprint 5 success rate, and compliance enforcement moving from flagging to blocking.

Written by the indexing model from the issue text.