In Season 4, Episode 43, Karl and Jon are joined by Senior Technical Account Manager at AWS, Loïc Fournier, to discuss optimizing Amazon RDS and Amazon Aurora database costs and performance with AWS Compute Optimizer, the introduction of AWS pricing capabilities in Amazon Q Developer, serverless databases and their use cases, a comparison of different storage types for databases (GP2, GP3, IO1, IO2), and AWS Q’s capabilities in providing cost insights and pricing information—before joking about using a complicated CAPTCHA to stall users for 15 seconds while their serverless database spun up.

02:39 - Optimizing Amazon RDS and Amazon Aurora database costs and performance with AWS Compute Optimizer 

This article discusses how AWS Compute Optimizer now provides recommendations for optimizing RDS and Aurora databases. The tool uses machine learning to analyze metrics and provide suggestions for instance types, including Graviton options. It categorizes databases as optimized, not optimized, or idle. The feature is currently available for MySQL and PostgreSQL engines. The tool focuses on performance optimization first, with cost savings as a secondary benefit.

31:47 -Introducing AWS pricing capabilities in Amazon Q developer 

This article introduces new pricing capabilities in Amazon Q, allowing users to ask natural language questions about AWS pricing and receive instant cost insights. Users can inquire about cost comparisons between services, optimal regions for deployments based on pricing, and get accurate, up-to-date pricing information directly from AWS APIs. This feature aims to simplify the process of estimating costs for various AWS architectures and workloads, making it easier for architects and developers to provide quick pricing estimates to businesses.