data-migration

Data Migration

The Law

EVERY MIGRATION NEEDS A ROLLBACK.
A migration without a rollback plan is a one-way door.
Before you open it, know how to close it.

When to Use

Use this skill before:

• Any ALTER TABLE in production
• Any column rename, type change, or removal
• Any large UPDATE or DELETE (more than 1000 rows)
• Any index creation on a large table
• Any data backfill or transformation script

The Migration Process

Step 1: Classify the Migration

Type	Risk	Strategy
Additive (new table, new nullable column)	Low	Single deploy
Non-breaking change (add index, add constraint)	Low–Medium	Verify impact first
Column rename or type change	High	Multi-phase deploy
Column or table removal	High	Multi-phase deploy
Large data backfill (>100k rows)	Medium	Batched, off-peak
Destructive (DROP TABLE, DELETE)	Critical	Backup + explicit approval

Step 2: Write the Migration Plan

Save to docs/migrations/YYYY-MM-DD-description.md:

# Migration: [Title]

## Summary
[What changes and why]

## Risk Level
[Low / Medium / High / Critical]

## Migration Steps

### UP (apply)
\```sql
-- Step 1: Add new column (nullable — safe, no lock)
ALTER TABLE orders ADD COLUMN discount_amount NUMERIC(10,2);

-- Step 2: Backfill (batched — see script)
-- Run: scripts/migrations/backfill-discount.sql

-- Step 3: Add NOT NULL constraint after backfill
ALTER TABLE orders ALTER COLUMN discount_amount SET NOT NULL;
\```

### DOWN (rollback)
\```sql
ALTER TABLE orders DROP COLUMN IF EXISTS discount_amount;
\```

## Rollback Plan
[How to revert if something goes wrong — step by step]

## Estimated Duration
[How long will the migration take? Any locking risk?]

## Verification
- [ ] Row count before: SELECT COUNT(*) FROM orders;
- [ ] Row count after matches
- [ ] Sample rows spot-checked: SELECT * FROM orders LIMIT 10;
- [ ] Application queries tested against migrated schema
- [ ] No errors in application logs after deploy

Step 3: Zero-Downtime Patterns

Column rename — never rename directly; multi-phase:

Phase 1: Add new column (old and new both exist)
Phase 2: Deploy app that writes to BOTH columns, reads from old
Phase 3: Backfill new column from old
Phase 4: Deploy app that writes to BOTH, reads from new
Phase 5: Drop old column

Type change — same multi-phase approach; never ALTER COLUMN TYPE on large tables in production directly.

Index creation on large table — always CREATE INDEX CONCURRENTLY:

-- [INVALID] — takes full table lock
CREATE INDEX idx_orders_user ON orders(user_id);

-- [VALID] — non-blocking on PostgreSQL
CREATE INDEX CONCURRENTLY idx_orders_user ON orders(user_id);

Large backfill — never in one transaction; batch it:

-- Process in batches of 1000 rows until done
DO $$
DECLARE
  batch_size INT := 1000;
  rows_updated INT;
BEGIN
  LOOP
    UPDATE orders
    SET discount_amount = 0
    WHERE discount_amount IS NULL
    LIMIT batch_size;

    GET DIAGNOSTICS rows_updated = ROW_COUNT;
    EXIT WHEN rows_updated = 0;
    PERFORM pg_sleep(0.1);  -- yield between batches
  END LOOP;
END $$;

Step 4: Pre-Migration Checklist

Before executing in production:

• [ ] Migration tested in staging with production-sized dataset
• [ ] DOWN migration tested — rollback actually works
• [ ] Row counts recorded (before state documented)
• [ ] Backup taken or verified recent backup exists
• [ ] Maintenance window announced if locking is expected
• [ ] Application can tolerate both old and new schema simultaneously (for multi-phase migrations)
• [ ] Monitoring alerts active during migration

Step 5: Execute

# Dry run first (PostgreSQL)
psql $DATABASE_URL --dry-run -f migration.sql

# Real run with timing
psql $DATABASE_URL -f migration.sql --echo-all

# Check for locks during execution
SELECT pid, query, state, wait_event_type, wait_event
FROM pg_stat_activity
WHERE state != 'idle';

Step 6: Verify

-- Row count matches expectations
SELECT COUNT(*) FROM affected_table;

-- Sample spot-check
SELECT * FROM affected_table LIMIT 20;

-- No NULL where NOT NULL expected
SELECT COUNT(*) FROM affected_table WHERE new_column IS NULL;

-- No application errors in logs for 10 minutes post-migration

Rollback Decision Tree

Migration complete?
  └── No errors in monitoring for 10 minutes? → DONE
  └── Errors found?
      ├── Can app tolerate the error state? → Fix forward (hotfix)
      └── Cannot tolerate? → ROLLBACK IMMEDIATELY
          ├── Run DOWN migration
          ├── Verify application recovers
          └── Document in post-mortem

Hard Rules

• Never DROP a column in the same deploy as the last code that reads it — always separate by at least one deploy
• Never run destructive migrations (DROP TABLE, DELETE) without an explicit human approval step — not just a code review
• Never skip the DOWN migration — "we can recreate it" is not a rollback strategy
• Never migrate in peak traffic hours — schedule for the lowest-traffic window