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Answer: Cloud Storage using a scheduled task and gsutil via Cloud Interconnect
The question focuses on migrating ongoing data backup and disaster recovery solutions as the first step, with production migration to follow. Option B (Cloud Storage using a scheduled task and gsutil via Cloud Interconnect) is optimal because Cloud Storage provides scalable, durable object storage ideal for backups, and gsutil with scheduled tasks automates data transfer efficiently. Cloud Interconnect ensures stable, high-throughput connectivity for large data transfers. Community consensus strongly supports B (79% of votes), citing Google's documentation on disaster recovery scenarios for on-premises environments. Options A (BigQuery) and D (Cloud Datastore) are unsuitable as they are analytical and NoSQL databases, not backup solutions. Option C (Compute Engine VMs) is less suitable for initial backup/DR migration; it's better for full application migration in later phases, as noted in community comments about moving compute first being incorrect without specific RTO/RPO requirements.
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An organization is migrating its infrastructure from on-premises to Google Cloud Platform (GCP). The initial phase involves migrating its ongoing data backup and disaster recovery solutions, with the production environment to follow. A stable network connection between on-premises and GCP is being established.
Which GCP solution should be used for this scenario?
A
BigQuery using a data pipeline job with continuous updates via Cloud VPN
B
Cloud Storage using a scheduled task and gsutil via Cloud Interconnect
C
Compute Engines Virtual Machines using Persistent Disk via Cloud Interconnect
D
Cloud Datastore using regularly scheduled batch upload jobs via Cloud VPN
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