Your company wants to migrate their 10-TB on-premises database export into Cloud Storage. You want to minimize the time it takes to complete this activity, the overall cost, and database load. The…

Question

Options

• ADevelop a Dataflow job to read data directly from the database and write it into Cloud Storage.
• BUse the Data Transfer appliance to perform an offline migration.
• CUse a commercial partner ETL solution to extract the data from the on-premises database and
• DCompress the data and upload it with gsutil -m to enable multi-threaded copy.

• A
  11% (4)
• B
  3% (1)
• C
  16% (6)
• D
  70% (26)

Explanation

Compressing the data reduces transfer size, and gsutil -m parallelizes the upload across multiple threads - together, these maximize throughput over the 1 Gbps link and complete the migration fastest at lowest cost. Crucially, the question specifies a database export (already a flat file), so no live database connection is needed, satisfying the "minimize database load" requirement with zero additional queries.

Why the distractors fail:

• A (Dataflow): Reads directly from the live database, increasing its load - violating one of the three stated goals. It also adds unnecessary pipeline complexity and cost.
• B (Data Transfer Appliance): Physical appliance shipping takes days or weeks of turnaround. At 1 Gbps, 10 TB transfers in roughly 22 hours over the network - far faster than waiting for hardware logistics.
• C (Commercial ETL): Third-party tools add licensing cost and typically also connect to the live database, both of which conflict with the cost-minimization and load-minimization goals.

Memory tip: When you see "database export" + "1 Gbps bandwidth" + "minimize cost/time/load," the data is already off the database - your only job is moving a file fast and cheap. gsutil -m with compression is the Google-native answer whenever network bandwidth makes online transfer practical (rule of thumb: use the Transfer Appliance only when the network transfer would take weeks, not hours).

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