Amazon Redshift Serverless launched AI-driven scaling and optimization, which scales compute based on data volume, query complexity, and price-performance targets, enabling proactive scaling for better performance and cost optimization.

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<p>The article discusses how Amazon Redshift Serverless utilizes a new AI-driven scaling and optimization feature to automatically scale compute resources based on factors like data volume, query complexity, and expected data scan, to meet desired price-performance targets.</p>
<p>Specifically, the article covers:</p>
<ul>
<li>Overview of the AI-driven scaling and optimization feature with a price-performance slider</li>
<li>Use case 1: Scaling compute based on query complexity for a long-running complex query</li>
<li>Use case 2: Scaling compute based on data volume for a data ingestion job with increased volume</li>
<li>Use case 3: Scaling compute for data lake queries scanning large datasets from Amazon S3</li>
<li>Considerations for choosing the desired price-performance target with the slider</li>
<li>Monitoring the scaled compute capacity</li>
</ul>
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