An automotive telematics enterprise needs to migrate its platform to Google Cloud within a strict 10-day maintenance window. The existing environment consists of of historical vehicle sensor log archives stored on an on-premises NAS and a operational MySQL database. The enterprise has a dedicated network uplink allocated for migration traffic. The solution must ensure minimal downtime for the live transaction database while completing the bulk historical data transfer within the 10-day constraint. Which migration strategy should the cloud architect recommend?
- Order a Google Cloud Transfer Appliance to migrate the historical sensor logs, and use Database Migration Service (DMS) with continuous replication for the MySQL database.Answer
- BUse Storage Transfer Service over the connection to transfer the historical sensor logs, and use Database Migration Service (DMS) with continuous replication for the MySQL database.
- CProvision an HA VPN tunnel to increase network throughput for transferring the sensor logs via Storage Transfer Service, and export database dump files to Cloud Storage via Transfer Appliance.
- DMigrate the MySQL database to Cloud Spanner using Database Migration Service, and stream the sensor logs over the network using Storage Transfer Service.
Answer
Order a Google Cloud Transfer Appliance to migrate the historical sensor logs, and use Database Migration Service (DMS) with continuous replication for the MySQL database.
The optimal strategy pairs Transfer Appliance for the unstructured file archives with Database Migration Service (DMS) utilizing continuous CDC replication for the MySQL database. Transferring over a link requires approximately 370 days, making physical appliance shipping mandatory to achieve the 10-day deadline. Conversely, the database initial load requires approximately 16.6 hours over , allowing DMS to establish an online baseline and stream ongoing updates for a near-zero downtime cutover.
Step-by-Step Solution
Key Concept
Selecting between online network transfer mechanisms and offline physical transport appliances based on bandwidth calculations, dataset scale, and database cutover constraints.