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If a database migration causes downtime, first determine whether cutover happened and which database has accepted the latest committed writes. If the original source is still authoritative, keep or return application traffic there while you investigate. If the target has accepted writes, do not simply switch the connection string or DNS back: reconcile or replicate those changes before routing clients to the source. Follow the runbook for your database engine, migration tool, and cloud provider before making production changes.
What to do first when a database migration interrupts service
- Classify the migration phase. Establish whether the failure occurred during the initial load, ongoing replication, traffic draining, cutover, or post-cutover operation. Note when downtime began, which applications are affected, what errors they report, and whether clients can currently read or write.
- Identify the authoritative database. Check which endpoint has accepted committed writes since cutover. Prevent accidental writes to both databases unless the system was deliberately built for conflict-safe active-active operation. The authority decision determines whether traffic can safely be reversed.
- Stabilize service without discarding data. If the source remains the live primary and the migration is incomplete, keep traffic on the source and use the migration tool’s documented pause, abort, or restart procedure. Google Cloud says an in-progress migration can be aborted and its target reset after the failure is resolved, while the operational source remains unaffected (Google Cloud migration failure and fallback guidance).
- Capture the current state. Record the migration job status, last consistent transfer or replication position, logs and errors, schema and data changes, database health, connection-pool and routing configuration, and backup status. Preserve evidence and take a safe backup or snapshot if the platform procedure allows it. A backup should not be treated as recoverable until restoration has been tested.
- Choose fix-forward or rollback deliberately. Use the incident decision owner and predefined rollback checkpoints. Fix-forward may be preferable when the target is largely healthy and its data can be corrected safely. If returning to the source, account for every committed target-side change.
- Synchronize before switching traffic. Freeze ingestion or writes when consistency requires it, complete the final sync or drain, and only then change application routing. AWS’s cutover guidance sequences ingestion freeze, final backup, data sync, routing changes, and testing (AWS cutover guidance).
- Validate and communicate. Test representative application behavior, read and write paths, data consistency, error rates, and relevant service objectives. Keep the source and recovery artifacts until the restored or target service is demonstrably stable.
How the safe response changes by migration phase
Failure before cutover
The source is normally still serving the application, so a failed migration can often be investigated, aborted, and retried after resetting the target. First confirm that application writes were not sent to the target; otherwise, resetting it could discard data (Google Cloud migration failure and fallback guidance).
Failure during cutover
Decide whether the source must be locked or ingestion frozen so that new transactions do not invalidate the final synchronization. Where possible, gracefully close connections, drain remaining changes, verify synchronization, and then route clients. A required freeze can extend downtime, so weigh consistency requirements against the permitted maintenance window (AWS cutover guidance; Google Cloud migration concepts, Part 1).
Failure after writes begin on the target
The former source may now be stale. Returning clients to it without moving or reconciling target-side writes can result in missing or inconsistent data. Depending on the systems and tested plan, recovery may use reverse migration or fail-forward replication, application dual writes with suitable semantics, or backup and restore. These approaches need advance planning and testing; dual writes can conflict unless the application is specifically designed to handle them (AWS cutover guidance; Google Cloud migration failure and fallback guidance).
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Choosing rollback or fix-forward
Make the choice against the incident’s agreed decision criteria, not just the apparent convenience of changing a route. Compare the outage window the business can tolerate with the actual state of the data and the recovery paths that have been tested.
- Whether the target accepted committed writes, and how much data would need to move or reconcile.
- Consistency and data-loss requirements, plus the source and target engines’ schema compatibility.
- Replication lag and the amount of remaining data to drain.
- Tested restore or reverse-replication time, alongside the permitted outage window.
- Whether the application supports connection changes or has safe, conflict-aware dual-write behavior.
A scheduled one-time dump/load can be simpler when a longer planned outage is acceptable. Continuous replication can reduce cutover work, but requires setup and operational control and brings source-load and replication-lag considerations (Google Cloud migration concepts, Part 1; Google Cloud Database Migration Service overview).
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Prepare a recovery path before the next cutover
- Rehearse the migration and recovery. Repeat the process in a representative environment, checking data coverage, transformation errors, throughput, estimated duration, and recovery behavior. Make schema creation repeatable and version controlled (Google Cloud migration failure and fallback guidance).
- Set decision criteria and ownership. Define success criteria and rollback triggers, name the decision maker, and document operational contacts. Test backup restoration outside production and estimate its duration before cutover (AWS cutover guidance).
- Watch replication progress. Monitor lag and the remaining change backlog so the team knows whether a final drain is feasible. Choose continuous replication or a one-time transfer based on the outage the business can accept and the setup and operational effort the approach requires (Google Cloud Database Migration Service overview; Google Cloud migration concepts, Part 1).
- Measure the interruption honestly. Google Cloud Architecture Center states that client-facing zero downtime is not achievable in a migration because clients have periods when they cannot process requests. Plan to minimize and measure that interval instead of promising it will not occur (Google Cloud migration concepts, Part 1).
- Keep a tested post-cutover fallback. Keeping the old database running is not enough if it no longer receives writes accepted by the target. The fallback must include a tested way to preserve or reconcile those changes (Google Cloud migration failure and fallback guidance).
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