docs: add parity report templates for vulnerabilities and scheduler

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StellaOps Bot
2025-12-06 09:25:58 +00:00
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# Scheduler Parity Report · 2025-12-14
## Scope
- Backfill and parity verification for Scheduler (Sprint 3402 · PG-T2.9T2.11).
- Compare MongoDB source vs PostgreSQL target for job/trigger/lease history.
## Inputs
- Mongo snapshot: <path or connection string>
- Postgres target: <connection>
- Backfill tool: `Scheduler.Backfill` (version/hash)
- Config: `Persistence:Scheduler=Postgres` after backfill? yes/no
## Methods
- Backfill steps:
1) Restore Mongo snapshot (if applicable)
2) Run Scheduler.Backfill CLI
3) Capture logs and row counts per table
- Parity checks:
- Table counts: jobs, triggers, leases, job_history, metrics
- Trigger next_fire_at sampling (top 100 by tenant)
- Determinism checks: order by next_fire_at, tenant_id, id
- Advisory-lock contention smoke: Acquire/Release sequence on Postgres
- Optional clean-start path: if start-clean approved, document rationale and skip Mongo counts.
## Results
- Counts Mongo/Postgres:
- Jobs: <n>/<n>
- Triggers: <n>/<n>
- Leases: <n>/<n>
- Job history: <n>/<n>
- Metrics: <n>/<n>
- Determinism sample: pass/fail; details
- Lock smoke: pass/fail; details
- Issues found: <list>
## Verdict
- Parity status: PASS / FAIL / START-CLEAN (approved)
- Cutover readiness: YES/NO
## Next Actions
- If PASS: mark PG-T2.9T2.11 DONE and flip Scheduler to Postgres-only.
- If FAIL: log defects + owners; rerun after fixes.
- If START-CLEAN: ensure configs set to Postgres-only and document empty baseline.

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# Vulnerability Parity Report · 2025-12-11
## Scope
- Dual-import parity between MongoDB and PostgreSQL for Concelier vulnerability index (Sprint 3405 · PG-T5b.35b.6).
- Sample size: 10k advisories + associated affected records; SBOM set: TBD (list below).
## Inputs
- Mongo source: <connection / dump path>
- Postgres target: <connection>
- Dual-import mode: enabled/disabled (state)
- SBOM sample set:
- TODO: populate paths (e.g., tests/fixtures/sbom/...)
## Methods
- Importers used: NVD, OSV, GHSA, vendor.
- Comparison queries:
- Advisory count by source
- Affected count by PURL and version range
- CVSS vectors/score deltas
- KEV flags count
- Full-text search sample (top 20 queries)
- Matching check:
- Run matching against SBOM set with Mongo backend
- Run matching against SBOM set with Postgres backend
- Diff findings: <path>
## Results
- Counts:
- Advisories Mongo: <n>
- Advisories Postgres: <n>
- Affected Mongo: <n>
- Affected Postgres: <n>
- CVSS rows Mongo/Postgres: <n>/<n>
- KEV rows Mongo/Postgres: <n>/<n>
- Findings parity on SBOM set:
- Total findings Mongo/Postgres: <n>/<n>
- Deltas: <n> (list top examples)
- Performance snapshot:
- Import time (Postgres): <>
- Match time per SBOM (avg/p95): <>
## Verdict
- Parity status: PASS / FAIL
- Required fixes: <list or "none">
- Blocking issues: <list>
## Next Actions
- If PASS: proceed to PG-T5b.5 (perf tuning) and schedule PG-T5b.6 cutover window.
- If FAIL: capture defects and owners; rerun parity after fixes.