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Zorluk: ZorDesigning Migration Plans and Data Transfer Strategies

An automotive telematics enterprise needs to migrate its platform to Google Cloud within a strict 10-day maintenance window. The existing environment consists of 800 TB800\text{ TB} of historical vehicle sensor log archives stored on an on-premises NAS and a 1.5 TB1.5\text{ TB} operational MySQL database. The enterprise has a dedicated 200 Mbps200\text{ Mbps} 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?

  1. Order a Google Cloud Transfer Appliance to migrate the 800 TB800\text{ TB} historical sensor logs, and use Database Migration Service (DMS) with continuous replication for the 1.5 TB1.5\text{ TB} MySQL database.Cevap
  2. B
    Use Storage Transfer Service over the 200 Mbps200\text{ Mbps} connection to transfer the 800 TB800\text{ TB} historical sensor logs, and use Database Migration Service (DMS) with continuous replication for the 1.5 TB1.5\text{ TB} MySQL database.
  3. C
    Provision an HA VPN tunnel to increase network throughput for transferring the 800 TB800\text{ TB} sensor logs via Storage Transfer Service, and export database dump files to Cloud Storage via Transfer Appliance.
  4. D
    Migrate the 1.5 TB1.5\text{ TB} MySQL database to Cloud Spanner using Database Migration Service, and stream the 800 TB800\text{ TB} sensor logs over the network using Storage Transfer Service.

Cevap

Order a Google Cloud Transfer Appliance to migrate the 800 TB800\text{ TB} historical sensor logs, and use Database Migration Service (DMS) with continuous replication for the 1.5 TB1.5\text{ TB} MySQL database.
The optimal strategy pairs Transfer Appliance for the 800 TB800\text{ TB} unstructured file archives with Database Migration Service (DMS) utilizing continuous CDC replication for the 1.5 TB1.5\text{ TB} MySQL database. Transferring 800 TB800\text{ TB} over a 200 Mbps200\text{ Mbps} link requires approximately 370 days, making physical appliance shipping mandatory to achieve the 10-day deadline. Conversely, the 1.5 TB1.5\text{ TB} database initial load requires approximately 16.6 hours over 200 Mbps200\text{ Mbps}, allowing DMS to establish an online baseline and stream ongoing updates for a near-zero downtime cutover.

Adım Adım Çözüm

1
Calculate data transfer time for the unstructured historical dataset over the available network uplink.
800 TB=6.4×1015 bits800\text{ TB} = 6.4 \times 10^{15}\text{ bits}. At 200 Mbps200\text{ Mbps} (2×108 bps2 \times 10^8\text{ bps}), transfer duration is 6.4×10152×108=32,000,000 seconds370 days\frac{6.4 \times 10^{15}}{2 \times 10^8} = 32,000,000\text{ seconds} \approx 370\text{ days}. Online network transfer is impossible within 10 days.
Large dataset scale (800 TB800\text{ TB}) under constrained bandwidth (200 Mbps200\text{ Mbps}) mandates an offline physical transfer appliance.
2
Evaluate network transfer feasibility for the 1.5 TB1.5\text{ TB} relational database.
1.5 TB=1.2×1013 bits1.5\text{ TB} = 1.2 \times 10^{13}\text{ bits}. At 200 Mbps200\text{ Mbps}, initial bulk copy takes 1.2×10132×108=60,000 seconds16.6 hours\frac{1.2 \times 10^{13}}{2 \times 10^8} = 60,000\text{ seconds} \approx 16.6\text{ hours}, which fits comfortably within the timeline.
The initial snapshot can load over the network in less than a day, followed by continuous Change Data Capture (CDC) replication.
3
Synthesize the optimal hybrid migration plan.
Ship an offline Transfer Appliance for the 800 TB800\text{ TB} file archives while running Database Migration Service with CDC for the 1.5 TB1.5\text{ TB} MySQL database.
This strategy satisfies both the 10-day total window constraint and the minimal downtime requirement for the live transactional workload.

Anahtar Kavram

Selecting between online network transfer mechanisms and offline physical transport appliances based on bandwidth calculations, dataset scale, and database cutover constraints.
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