AWS Certified Data Engineer Associate DEA-C01 Practice Question

A retail analytics team runs a 4-node Amazon Redshift cluster that generally supports 20 business-intelligence users but occasionally experiences 10-minute spikes during flash-sales when more than 200 ad-hoc queries run concurrently. Management wants to meet the existing query-response SLA during these spikes while keeping ongoing compute costs as low as possible and avoiding manual cluster resize operations. Which solution meets these requirements?

Enable Concurrency Scaling on the Amazon Redshift cluster so transient capacity is added automatically and billed only for seconds used.
Create materialized views for the most expensive queries and automatically refresh them every 5 minutes.
Use elastic resize to double the node count during peak periods and schedule a resize back after each sale.
Migrate the cluster to RA3 nodes with Redshift Managed Storage and keep the current node count.

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Answer Description

Concurrency Scaling attaches transient clusters only when query volumes exceed the baseline concurrency, then shuts them down automatically. These additional clusters are billed per-second, so the company pays for extra compute only during the short flash-sale windows. Elastic resize keeps the added nodes online for the entire billing hour (or longer if not manually reversed), increasing steady-state cost. Migrating to RA3 nodes lowers storage cost but does not address short-lived concurrency spikes. Materialized views can improve latency for specific queries but do nothing to add execution slots, so they will not satisfy the large surge of simultaneous queries.

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