● Covered by 1 source · 1 reportLow impact1 neutral
Google Finance Engineering automates Spanner dual-write migrations with Antigravity CLI
Key points
- Google Finance Engineering migrated to Spanner.
- Automated dual-write logic with Antigravity CLI.
- Reduced manual effort across 30+ DAOs.
- Maintained data parity during migration.
Migration to Spanner
Google's Finance Engineering team migrated its legacy data layer to Spanner, a globally distributed, strongly consistent, multi-model database. The migration required moving high-throughput production services without taking them offline, which presented a significant engineering challenge.
Dual-Write Challenge
Migrating financial systems requires dual-write implementations to ensure both the legacy datastore and Spanner receive identical writes simultaneously. Manually implementing dual-write logic across dozens of Data Access Objects (DAOs) is slow and prone to human error, potentially taking months of engineering time for over 30 DAOs.
Automated Solution with Antigravity CLI
To address the manual effort, the team built an automated refactoring pipeline powered by Antigravity CLI in headless mode. This automation accelerates the migration process and ensures strict data parity in staging environments before production deployment.
Migration Phases
The migration was structured into three phases: historical backfill, dual-write/dual-read implementation, and automated API verification with parity checking. Each DAO required a dedicated MutationConverter class, dual-write branch handling, rollback logic, and a suite of unit tests.
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Reporting from
Google's Finance Engineering team developed an automated refactoring pipeline using Antigravity CLI to migrate legacy data layers to Spanner. This automation addresses the challenge of manually rewriting dual-write logic across Data Access Objects (DAOs) for high-throughput production services, which is prone to error and time-consuming. The solution accelerates migration velocity while maintaining data parity during the transition.