Working out when a second copy is worth what it costs
Replication creates synchronized copies of data across zones, regions, or instances to improve availability, read performance, and disaster recovery readiness. On Google Cloud, you choose replication when you need to reduce read latency for geographically distributed users, offload read traffic from a primary database, or protect against regional failures, as opposed to backups which are for point-in-time recovery from data loss or corruption.
1 · Learn the must-know
- Cloud SQL read replicas offload read-only queries from the primary instance and can be promoted to a standalone primary during failover, but replication is asynchronous so some lag is possible.
- Cloud Spanner automatically replicates data synchronously across zones or regions depending on the chosen instance configuration (regional, multi-region), providing strong consistency and high availability without manual replica management.
- Replication is not a substitute for backups: replicated data reflects the same errors or deletions as the source almost immediately, so it does not protect against accidental data corruption or deletion the way backups/snapshots do.
- Cloud Storage dual-region and multi-region buckets replicate objects across locations for higher availability and lower latency to distributed users, while single-region buckets do not provide this geographic redundancy.
- Choose replication when the priority is high availability, disaster recovery across regions, or scaling read throughput; choose backup/export strategies when the priority is recoverability from logical data loss or long-term retention.
- Cross-region replication typically increases cost and, for asynchronous methods, introduces some replication lag, so it should be selected based on the required recovery point objective (RPO) and read-scaling needs rather than by default.
2 · Check your understanding
A retail company runs a Cloud SQL for MySQL instance that handles both transactional order processing and hourly analytics dashboards. As the dashboard queries have grown more complex, write latency for order processing has increased noticeably. The data team wants to isolate the analytics workload from the production write traffic without redesigning the application. What should they configure?
What you have tried across GCP ADP's objectives, not a readiness score.
Data Preparation and Ingestion~30% of the exam0 of 8 tried
Data Analysis and Presentation~27% of the exam0 of 12 tried
Data Pipeline Orchestration~18% of the exam0 of 9 tried
Data Management~25% of the exam0 of 12 tried
3 · Keep going
Ready for more? Take a weighted mock or try free practice questions.