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GCP Professional Cloud Architect Practice Question

Your team is migrating 50 TB of transactional data from an on-premises MySQL database to Cloud Spanner by using a Dataflow pipeline. Before cut-over, auditors require evidence that every source table's row count and column-level checksums are identical in the target system. You need an automated, scalable solution that can read from both databases and output a summary report highlighting any mismatches. Which Google-supported approach should you recommend?

  • Create Cloud Monitoring uptime checks with a custom metric that queries each table's row count and triggers an alert on mismatch.

  • Run the open-source Data Validation Tool as a Dataflow job to compare row counts and column aggregates between MySQL and Cloud Spanner.

  • Enable Datastream schema drift detection and export the alert logs to Cloud Logging for post-migration analysis.

  • Use Cloud SQL Insights to collect query statistics from both environments and manually compare the results.

GCP Professional Cloud Architect
Analyzing and optimizing technical and business processes
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