DEA-C01 Practice Question 36: Redshift Datashare Workload Isolation
AWS Certified Data Engineer – Associate (DEA-C01) · Test 4 · question 6 of 10
A single Amazon Redshift RA3 provisioned cluster serves two workloads. Between 00:00 and 05:00 a heavy ETL load runs; during the same hours, BI dashboards used by an overseas office slow to a crawl. The BI team wants compute it can size and pay for separately, but the numbers it reports must reflect committed ETL results immediately; a nightly copy into a second warehouse has already been rejected as too stale and too duplicative.
Which solution meets these requirements?
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Answer:
Data sharing lets you "securely share access to live data across Amazon Redshift clusters, workgroups, AWS accounts, and AWS Regions without manually moving or copying the data." The documentation names this exact pattern as a primary use case: "Use a central extract, transform, and load (ETL) cluster that shares data with multiple business intelligence (BI) or analytic clusters. This approach provides read workload isolation and chargeback for individual workloads. You can size and scale your individual workload compute according to the workload-specific requirements of price and performance." Freshness is covered too: "the data is live and available to all warehouses as soon as a write transaction is committed", with transactional consistency across producer and consumer.
Option A adds capacity but not isolation. Concurrency scaling helps with queued concurrent queries, yet the BI queries still run on the same warehouse competing with ETL for the same resources, and there is no separate compute to size or charge back.
Option C is the rejected nightly copy in a different wrapper. The restored cluster is a point-in-time copy, so it is stale from the moment it exists, it duplicates the entire dataset's storage, and the restore itself has to be operated every day.
Option D also produces a copy, with the added cost that the BI team changes query engine and loses the ability to join to anything still resident in Redshift. Data is only as fresh as the last UNLOAD.
Reference: Data sharing in Amazon Redshift