Amazon Redshift Serverless now makes AI-driven scaling and optimization the default for all new workgroups. AI-driven scaling uses machine learning to predict compute needs and automatically adjust resources before queries queue, delivering better price-performance without manual tuning. This release also expands support to workloads with a Base RPU range of 8–512 RPU, up from the previous 32–512 RPU, reducing the entry cost for AI-driven scaling. With AI-driven scaling and optimization, Amazon Redshift monitors your workload patterns and automatically adjusts compute resources based on query complexity, data volume, and expected data scan size. You can use the price-performance slider to choose whether to prioritize cost, performance, or a balance of both. Amazon Redshift also applies additional optimizations, including automatic materialized views and automatic table design optimization, to meet your selected target. To configure price-performance targets, use the AWS Management Console or Amazon Redshift API operations. You can also modify the target after you create the workgroup. Amazon Redshift Serverless AI-driven scaling and optimization is available in all AWS Regions where Amazon Redshift Serverless is available. For more information, see Amazon Redshift Serverless product page  and AI-driven scaling and optimization documentation .