![]() Additionally, you don’t need to worry about pausing and resuming (like you do with provisioned clusters) in order to optimize costs since you only pay for Serverless when queries are run. ![]() As it relates to concurrency, Redshift Serverless automatically adjusts resources and scales as needed based on workload activity and the cost control limits that you set as thresholds. The general guidance from AWS is that increasing your RPU base capacity will improve query performance. I’ll give you my perspective and first impression after recently taking Redshift Serverless for a hands-on spin.Ĭhanging your RPU base capacity - status is “Modifying.” This is an impactful option for everyone in the AWS data ecosystem and delivers a simple, fast, and operationally sustainable way to deliver data outcomes. In the case of Redshift Serverless, as a data analyst, data engineer, analytics engineer, data scientist or virtually any data professional, data products and data applications across multiple data workloads can be developed, built and run without the need or overhead to design, provision, and manage data warehouse clusters. Broadly speaking, a serverless-based approach to computing is considered cloud-native and eliminates the need for users of computing resources to get involved in provisioning and ongoing management of the compute infrastructure, effectively reducing infrastructure effort. I was excited to see this release since I had been mentioning this capability to clients in my previous consulting role since the public preview announcement last November. Amazon Redshift Serverless became generally available in July 2022.
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