postgres-and-relational-data-modeling

Postgres And Relational Data Modeling

Use When

• Relational persistence is core to the product
• Schema or query performance issues appear

Workflow

1. Model entities, constraints, and ownership boundaries
2. Plan migrations with expand-migrate-contract
3. Define indexes and query paths for hot endpoints
4. Add connection pooling and timeout policies
5. Validate backup, restore, and replication assumptions

Required Checks

• Migrations are backward compatible during rollout
• Indexes reviewed for read/write paths
• Secrets and credentials are not embedded in app code
• Restore drill documented for critical tables

Decision Framework

• Prefer explicit contracts and compatibility rules before implementation.
• If dependency risk is high, require timeout, retry, and fallback strategy per call path.
• If async messaging is used, require idempotency, replay, and dead-letter handling.
• If traffic patterns are volatile, require load, failover, and scaling validation before ship.

Common Rationalizations And Rebuttals

• "Retries will handle failures automatically." -> Unbounded retries can amplify outages; use budgets.
• "We can skip runbooks for now." -> Operational ambiguity delays incident recovery.
• "Contract changes are minor." -> Small breaking changes cause broad downstream regressions.

Evidence Pack

• Contract compatibility note and migration strategy (if applicable)
• Failure-mode test evidence for dependency degradation and recovery
• Observability snapshot (latency, error, saturation, or queue health)
• Rollout and rollback steps with clear trigger thresholds

Exit Criteria

• Workflow is production-ready with verified evidence
• Operational and security guardrails are in place
• Release and rollback expectations are documented