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Database Migrations taste

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Database Migrations taste

  • Keep every schema change in a versioned migration file committed next to the code that needs it. Confidence: 0.95
  • Write migrations in plain SQL rather than ORM-generated diffs you have not read. Confidence: 0.80
  • Never edit a migration that has already run in a shared environment; add a new one instead. Confidence: 0.95
  • Use the expand and contract pattern: add the new column, backfill, switch reads, then drop the old column in a later release. Confidence: 0.90
  • Make every migration safe to run while the previous app version is still serving traffic. Confidence: 0.90
  • Add new columns as nullable or with a constant default to avoid long table rewrites. Confidence: 0.85
  • Create indexes on large Postgres tables with CREATE INDEX CONCURRENTLY outside a transaction. Confidence: 0.90
  • Set a short lock_timeout and statement_timeout at the top of each migration. Confidence: 0.85
  • Run large backfills as batched background jobs, not inside the migration itself. Confidence: 0.90
  • Keep one logical change per migration so failures are easy to read and retry. Confidence: 0.80
  • Name migration files with a UTC timestamp prefix and a short verb phrase like 20261017_add_orders_status. Confidence: 0.75
  • Prefer forward-only migrations and fix mistakes with a new migration instead of relying on down scripts. Confidence: 0.70
  • Run migrations as a separate deploy step before the new application code starts. Confidence: 0.85
  • Test every migration in CI against a fresh database and against a copy of production-sized data. Confidence: 0.80
  • Add foreign keys and check constraints as NOT VALID first, then validate them in a separate step. Confidence: 0.80
  • Rename columns and tables only through a view or dual-write period, never in a single step. Confidence: 0.75
  • Store the applied migration history in the database and fail the deploy if it has drifted. Confidence: 0.85
  • Review migrations as carefully as application code, with the generated SQL visible in the pull request. Confidence: 0.90
  • Keep seed and fixture data out of schema migrations. Confidence: 0.80

Use Cases

Imported from source sync; refine manually if needed

Reference Output

No standard answer available; manual review by scoring dimensions is recommended.

Scoring Rubric

Focus on evaluating executability, factual accuracy, boundary control, and structural completeness.

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