data-migration-expert

Preventing production data corruption during database migration requires validating up and down behavior, using scoped updates with batching, implementing dual write strategies, and documenting explicit rollback procedures.

Post-deploy verification queries, metrics, and alerts detect anomalies immediately after a database migration by observing production data directly, confirming that ID changes, enum updates, and value transformations completed successfully.

When your pull request changes IDs, migrates data across columns, or transforms live enum values, you need a verification plan that includes explicit production data SQL queries, scoped updates, and documented rollback procedures to prevent corruption.

A dual-write strategy prevents data corruption during migrations by writing data to both the old and new schema simultaneously, allowing you to verify mapping correctness and maintain a rollback path before fully switching over.

You need rollback procedures for SQL backfill scripts whenever your code transforms live values, changes IDs, or updates enums, ensuring you can immediately revert scoped updates if post-deploy observability queries detect data anomalies.