An Amazon Redshift cluster (using reserved nodes) is experiencing intermittent CPU-heavy bursts from complex read queries while a team runs a deep audit. The cluster must continue to serve read and write queries at all times. Which option provides the required burst capacity in the MOST cost-effective way?

Enabling Concurrency Scaling for the Amazon Redshift cluster is the most cost-effective solution. Concurrency Scaling automatically adds temporary capacity to handle sudden increases in read query workload, ensuring consistent performance without manual intervention or over-provisioning. This temporary capacity is billed per second and is free for up to one hour per day per cluster, making it highly cost-effective for intermittent bursts. Provisioning an Amazon EMR cluster is an alternative for offloading complex tasks, but it introduces additional operational overhead and cost for a separate cluster, which might be overkill for intermittent bursts within Redshift. Classic resize involves downtime, which violates the requirement to serve queries at all times. Elastic resize also involves a brief period of read-only access and is generally used for more permanent scaling needs, not intermittent bursts.