Add integration tests for migration categories and execution
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- Implemented MigrationCategoryTests to validate migration categorization for startup, release, seed, and data migrations. - Added tests for edge cases, including null, empty, and whitespace migration names. - Created StartupMigrationHostTests to verify the behavior of the migration host with real PostgreSQL instances using Testcontainers. - Included tests for migration execution, schema creation, and handling of pending release migrations. - Added SQL migration files for testing: creating a test table, adding a column, a release migration, and seeding data.
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# ADR-0001: PostgreSQL for Control-Plane Storage
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## Status
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Accepted
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## Date
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2025-12-04
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## Authors
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- Platform Team
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## Deciders
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- Architecture Guild
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- Platform Team
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## Context
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StellaOps control-plane services (Authority, Scheduler, Notify, Concelier/Excititor, Policy) require persistent storage for:
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- Identity and authorization data (users, roles, tokens, sessions)
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- Job scheduling and execution state
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- Notification rules, templates, and delivery tracking
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- Vulnerability advisories and VEX statements
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- Policy packs, rules, and evaluation history
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**Triggers for this decision:**
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1. **Licensing trust & ecosystem stability** — PostgreSQL is licensed under the permissive PostgreSQL License (similar to MIT/BSD), OSI-approved, with no vendor lock-in concerns. MongoDB's SSPL license (2018) is not OSI-approved and creates uncertainty for self-hosted/sovereign deployments. For a platform emphasizing sovereignty and auditability, database licensing must be beyond reproach.
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2. **Schema complexity** — Control-plane domains have well-defined, relational schemas with referential integrity requirements (foreign keys, cascading deletes, constraints).
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3. **Query patterns** — Complex joins, aggregations, and window functions are common (e.g., finding all images affected by a newly published CVE).
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4. **ACID requirements** — Job scheduling, token issuance, and notification delivery require strong transactional guarantees.
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5. **Multi-tenancy** — Row-level security (RLS) needed for tenant isolation without schema-per-tenant overhead.
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6. **Migration tooling** — Need deterministic, forward-only migrations with advisory lock coordination for multi-instance deployments.
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7. **Air-gap operation** — All schema and data must be embeddable in assemblies without external network dependencies.
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8. **Auditability** — PostgreSQL's mature ecosystem includes proven audit logging, compliance tooling, and forensic capabilities trusted by regulated industries.
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## Decision
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**Adopt PostgreSQL (≥15) as the primary database for all StellaOps control-plane domains.**
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Key architectural choices:
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### 1. Per-Module Schema Isolation
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Each module owns exactly one PostgreSQL schema:
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| Schema | Owner | Description |
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|--------|-------|-------------|
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| `auth` | Authority | Identity, authentication, authorization, licensing |
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| `vuln` | Concelier | Vulnerability advisories, sources, affected packages |
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| `vex` | Excititor | VEX statements, graphs, observations, consensus |
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| `scheduler` | Scheduler | Jobs, triggers, workers, execution history |
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| `notify` | Notify | Channels, templates, rules, deliveries |
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| `policy` | Policy | Policy packs, rules, risk profiles |
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| `audit` | Shared | Cross-cutting audit log (optional) |
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**Rationale:**
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- Clear ownership boundaries
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- Independent migration lifecycles
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- Schema-level access control
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- Simplified testing and development
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### 2. Multi-Tenancy via tenant_id Column
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Single database, single schema set, `tenant_id` column on all tenant-scoped tables.
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```sql
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-- Session-level tenant context
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SET app.tenant_id = '<tenant-uuid>';
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-- Row-level security (defense in depth)
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CREATE POLICY tenant_isolation ON <table>
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USING (tenant_id = current_setting('app.tenant_id')::uuid);
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```
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**Rationale:**
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- Simplest operational model
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- Shared connection pooling
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- Easy cross-tenant queries for admin operations
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- Composite indexes on `(tenant_id, ...)` for query performance
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### 3. Forward-Only Migrations with Advisory Locks
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Migrations are embedded in assemblies and executed at startup with PostgreSQL advisory locks:
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```sql
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SELECT pg_try_advisory_lock(hashtext('auth')); -- Per-schema lock
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```
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**Migration categories:**
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- **Startup (001-099)**: Automatic, non-breaking DDL
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- **Release (100-199)**: Manual CLI, breaking changes
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- **Seed (S001-S999)**: Reference data
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- **Data (DM001-DM999)**: Batched background jobs
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**Rationale:**
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- No down migrations needed (forward-only with fix-forward)
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- Advisory locks prevent concurrent migrations across instances
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- Checksum validation catches unauthorized modifications
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- Air-gap compatible (no external migration service needed)
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### 4. RustFS for Binary Artifacts
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PostgreSQL stores metadata and indexes; RustFS stores binary artifacts (SBOMs, attestations, reports):
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```
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PostgreSQL: Schema definitions, relationships, indexes, audit trails
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RustFS: sbom.cdx.json.zst, inventory.cdx.pb, bom-index.bin, *.dsse.json
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```
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**Rationale:**
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- Right tool for each job
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- PostgreSQL excellent for structured queries
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- Object storage better for large binary blobs
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- Clear separation of concerns
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## Consequences
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### Positive
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1. **Licensing trust** — PostgreSQL License is permissive, OSI-approved, and universally accepted. No vendor lock-in, no license ambiguity for sovereign deployments. Trusted by governments, regulated industries, and security-conscious organizations.
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2. **Ecosystem stability** — 30+ years of development, included in all major distributions, no license rug-pulls. Community governance ensures long-term trust.
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3. **Relational integrity** — Foreign keys, constraints, and transactions ensure data consistency.
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4. **Query flexibility** — Complex joins, CTEs, window functions, and full-text search available natively.
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5. **Operational maturity** — Well-understood backup, replication, and monitoring ecosystem.
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6. **Row-level security** — Built-in multi-tenancy support without application-layer hacks.
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7. **Schema evolution** — Mature migration tooling with online DDL capabilities.
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8. **Performance** — Excellent query planning, connection pooling (PgBouncer), and indexing options.
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9. **Auditability** — Proven audit logging extensions (pgAudit), compliance certifications, forensic tooling.
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### Negative
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1. **Schema rigidity** — Changes require migrations; less flexible than document stores for rapidly evolving schemas.
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2. **Operational overhead** — Requires PostgreSQL expertise for tuning, vacuuming, and monitoring.
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3. **Connection limits** — Need PgBouncer for high-concurrency workloads.
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### Follow-up Actions
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- [x] Create `docs/db/` documentation directory with specification, rules, and conversion plan
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- [x] Define migration infrastructure in `StellaOps.Infrastructure.Postgres`
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- [ ] Complete phased conversion from MongoDB per `docs/db/tasks/PHASE_*.md`
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- [ ] Update deployment guides for PostgreSQL requirements
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- [ ] Add PostgreSQL health checks to all control-plane services
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### Rollback Criteria
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Revert to MongoDB (or hybrid) if:
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- Migration performance unacceptable (> 60s startup time)
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- Query complexity exceeds PostgreSQL capabilities
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- Operational burden exceeds team capacity
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## Alternatives Considered
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### Option A: Continue with MongoDB
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**Pros:**
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- Already in use for some components
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- Flexible schema
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- Good for document-centric workloads
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**Cons:**
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- **Licensing uncertainty** — MongoDB's SSPL (Server Side Public License, 2018) is not OSI-approved. Creates legal ambiguity for sovereign/self-hosted deployments, especially in regulated industries and government contexts where license provenance matters.
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- **Ecosystem trust erosion** — SSPL switch caused major distributions (Debian, Fedora, RHEL) to drop MongoDB packages. Sovereign customers may have policies against non-OSI licenses.
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- No referential integrity (app-enforced)
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- Limited join capabilities
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- Multi-tenancy requires additional logic
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- No row-level security
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- Less mature migration tooling
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**Rejected because:** Licensing uncertainty is incompatible with StellaOps' sovereign-first positioning. Control-plane domains are also fundamentally relational with strong consistency requirements.
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### Option B: Hybrid (PostgreSQL + MongoDB)
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**Pros:**
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- Use each database for appropriate workloads
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- Gradual migration possible
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**Cons:**
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- Two databases to operate and monitor
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- Complex deployment
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- Cross-database consistency challenges
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- Higher operational burden
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**Rejected because:** Unified PostgreSQL approach is simpler and sufficient for all control-plane needs.
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### Option C: CockroachDB / YugabyteDB
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**Pros:**
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- PostgreSQL-compatible
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- Built-in horizontal scaling
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- Multi-region capabilities
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**Cons:**
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- Additional operational complexity
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- Less mature than PostgreSQL
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- Overkill for current scale
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- Air-gap deployment challenges
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**Rejected because:** PostgreSQL provides sufficient scale and simpler operations for current requirements. Can revisit if horizontal scaling becomes necessary.
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## References
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- [`docs/db/README.md`](../db/README.md) — Database documentation index
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- [`docs/db/SPECIFICATION.md`](../db/SPECIFICATION.md) — Schema design specification
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- [`docs/db/MIGRATION_STRATEGY.md`](../db/MIGRATION_STRATEGY.md) — Migration execution strategy
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- [`docs/db/RULES.md`](../db/RULES.md) — Database coding rules
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- [`docs/07_HIGH_LEVEL_ARCHITECTURE.md`](../07_HIGH_LEVEL_ARCHITECTURE.md) — High-level architecture overview
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@@ -34,8 +34,15 @@ Small, module-local refactors that do not modify public behaviour can live in co
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- [ ] Consequences call out migration or rollback steps.
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- [ ] Announcement posted to Docs Guild updates (or sprint log).
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## ADR Index
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| ADR | Title | Status | Date |
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|-----|-------|--------|------|
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| [0001](./0001-postgresql-for-control-plane.md) | PostgreSQL for Control-Plane Storage | Accepted | 2025-12-04 |
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## Related resources
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- [Docs Guild Task Board](../TASKS.md)
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- [High-Level Architecture Overview](../07_HIGH_LEVEL_ARCHITECTURE.md)
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- [Database Documentation](../db/README.md)
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- [Coding Standards](../18_CODING_STANDARDS.md)
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- [Release Engineering Playbook](../13_RELEASE_ENGINEERING_PLAYBOOK.md)
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