First establish whether cutover happened and which database has accepted the latest committed writes. If the original database is still authoritative, keep or restore traffic there while you investigate. If the new database has accepted writes, do not simply point clients back: reconcile those changes or use a tested reverse-replication or fail-forward plan. Then synchronize data, route clients deliberately, and validate service before declaring recovery.
Database engines, migration tools, and cloud platforms have different recovery procedures. Follow the runbooks for your specific environment before issuing production commands.
First, determine where the migration failed
Classify the current phase before changing traffic or data: initial load, ongoing replication, write or connection draining, cutover, or operation after cutover. Record when downtime began, which applications are affected, what errors users see, and whether each application can read or write.
The key question is not only whether cutover was announced; it is whether the target database has accepted committed application writes. Confirm this from database and application evidence, including the migration job’s state and the endpoints clients actually used. If both databases received writes, stop accidental concurrent writes unless the system was explicitly designed to resolve active-active conflicts.
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Choose the safe recovery path
Failure before cutover
If the source is still serving as the live primary and no application writes reached the target, keep traffic on the source while investigating the migration. A failed target load can often be aborted, the target reset, and the migration retried without changing the live source. Use the migration tool’s documented pause, abort, and restart steps; do not assume this path is safe until you confirm the target did not receive application writes. Google Cloud describes this approach for in-progress migrations in its database migration failure and fallback guidance.
Failure during cutover
Prevent new writes from making the final synchronization inconsistent. Depending on the system, this may mean freezing ingestion, locking writes on the source, or gracefully draining application connections. Complete the final change sync, verify the databases are synchronized to the required point, and only then route clients to the intended database. A freeze can extend the interruption, so account for it in the maintenance window and consistency requirements. AWS’s cutover guidance describes an order that includes freezing ingestion, a final backup, data synchronization, routing changes, and testing.
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Failure after the target accepted writes
The original source may now be stale. Sending clients back to it without accounting for target-side commits can lose or hide data. Preserve the target state and choose a recovery method that brings those writes into the database that will serve traffic:
- Fix forward: repair the target-side migration or application issue if the target is recoverable and data can be corrected safely.
- Reverse replication or fail forward: move target-side changes back toward the source using a tested process that fits the engines and schemas.
- Backup and restore: restore to a point and destination that preserve required transactions, after confirming the procedure and expected recovery time.
- Application dual writes: consider only if the application was designed to handle partial failures, retries, and conflicting writes. Enabling dual writes as an improvised recovery step can create divergence.
Google Cloud and AWS both treat rollback after cutover as a data and synchronization problem, not merely a routing change: see Google Cloud’s fallback guidance and AWS’s cutover guidance.
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Stabilize and recover without losing evidence
- Appoint the decision owner. Use the incident’s rollback criteria and escalation path to decide whether to fix forward or return to the source. If those criteria are unclear, make the authority and data-consistency decision explicit before switching.
- Capture the current state. Record migration-job status, the last consistent transfer or replication position, logs and errors, schema or data changes, database health, routing and connection-pool settings, and backup status.
- Preserve recoverable data. Where the platform procedure permits, take a safe snapshot or backup before resetting, restoring, or changing replication. A backup is not a proven recovery path until its restoration has been tested.
- Stop writes that undermine consistency. Freeze ingestion or writes when required by the selected recovery path. Confirm which database remains authoritative and prevent clients from unintentionally writing to both.
- Synchronize before routing. Complete the final sync, reverse movement, or restore needed for the chosen destination. Check the relevant replication position or remaining backlog rather than assuming the databases match.
- Change routing deliberately. Apply the documented application, proxy, or endpoint change, and manage existing connections so clients do not continue using stale destinations.
- Validate and communicate. Test representative reads and writes, data consistency, application behavior, error rates, and relevant service objectives. Keep the source and recovery artifacts available until the serving system is demonstrably stable.
Decide between fix-forward and rollback
Use the incident’s predefined rollback triggers and decision owner when available. Otherwise compare the recovery options against the conditions that actually determine risk and time:
- The outage window the business can tolerate.
- Whether the target accepted writes, and whether those writes can be moved or reconciled.
- Required consistency and acceptable data loss, if any.
- Source and target engines, schema compatibility, and transformation behavior.
- Replication lag and the amount of change still waiting to be applied.
- Tested reverse-replication or restore duration.
- Whether applications can safely handle endpoint changes or dual-write behavior.
A healthy target with a repairable defect may favor fixing forward. Returning to the source may be appropriate when the target cannot be stabilized, but only after accounting for target-side commits. The decision should be based on data safety and a rehearsed recovery path, not on the apparent simplicity of changing a connection string.
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Prepare the next cutover to reduce downtime
Rehearse the migration and its failure paths
Run the migration repeatedly outside production. Check data coverage, transformation errors, throughput, duration estimates, and what happens when a step fails. Keep schema creation repeatable and version controlled. Rehearse the rollback or fail-forward path as a data operation, not just a traffic switch.
Set criteria, contacts, and restore expectations
Define measurable success criteria, rollback triggers, a named decision maker, and operational contacts before cutover. Test backup restoration in a non-production environment and estimate how long the restore takes. A backup that cannot meet the recovery window is not an adequate fallback for that window.
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Choose a migration method that fits the outage window
A one-time dump and load can be simpler when the business accepts a longer planned outage. Continuous replication can reduce the work left at cutover, but requires setup and operational oversight of source load and replication lag. Google Cloud’s Database Migration Service overview describes the service, while its migration concepts and principles discuss cutover considerations.
Measure the interruption honestly
Do not promise literal zero downtime for client requests. Google Cloud Architecture Center states, “In a migration, achieving truly zero downtime for clients is impossible; there are times when clients cannot process requests.” The practical goal is to minimize and measure that interval, then design application behavior and operational procedures around it.
Keep a real fallback after cutover
Leaving the old database powered on is not enough if it no longer receives writes. A rapid fallback requires a tested way to preserve and synchronize target-side changes, along with a deliberate routing procedure. Use the specific engine, migration-tool, and cloud-provider runbooks for the recovery steps; no single production command is safe across unspecified platforms.
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