Medium1 markMultiple Choice
Domain 4.3: Migration StrategyMigrationSnowballData Transfer

AWS SAP-C02 · Question 16 · Domain 4.3: Migration Strategy

An organization is migrating a massive on-premises data warehouse to Amazon Redshift. The data volume is 500 TB. The on-premises internet connection is 1 Gbps, but only 200 Mbps can be allocated for the migration. The migration must be completed within 3 weeks. Which data transfer strategy is feasible and MOST cost-effective?

Answer options:

A.

Order multiple AWS Snowball Edge Storage Optimized devices. Copy the data locally, ship them to AWS, and import the data into Amazon S3. Use the COPY command to load data into Redshift.

B.

Use AWS DataSync to transfer the data directly to Amazon S3 over the internet connection. Load the data into Redshift.

C.

Establish a new 10 Gbps AWS Direct Connect dedicated connection. Use AWS Database Migration Service (DMS) to replicate the data to Redshift.

D.

Order an AWS Snowmobile to transfer the data directly to Amazon Redshift.

How to approach this question

Calculate the network transfer time (500TB @ 200Mbps = ~230 days). Since it exceeds 3 weeks, an offline transfer method is required.

Full Answer

A.Order multiple AWS Snowball Edge Storage Optimized devices. Copy the data locally, ship them to AWS, and import the data into Amazon S3. Use the COPY command to load data into Redshift.✓ Correct
Order multiple AWS Snowball Edge Storage Optimized devices. Copy the data locally, ship them to AWS, and import the data into Amazon S3. Use the COPY command to load data into Redshift.
To transfer 500 TB over a 200 Mbps link would take approximately 231 days. Because the deadline is 3 weeks, an offline migration strategy is mandatory. AWS Snowball Edge Storage Optimized devices hold 80 TB of usable capacity each. Ordering several devices allows parallel local copying, shipping, and loading into S3, easily meeting the 3-week deadline.

Common mistakes

Failing to do the mental math on transfer speeds and choosing an online method like DataSync.

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