Starting today, AWS Compute Optimizer delivers new recommendations for Amazon Relational Database Service (RDS) MySQL and PostgreSQL databases. These recommendations help you detect idle RDS instances and identify the optimal instance types and provisioned IOPS settings for your existing RDS DB instances, so you can reduce costs for idle and over-provisioned RDS DB instances or increase the performance of under-provisioned workloads.
Amazon RDS, a managed service, allows you to set up, operate, and scale a relational database, while automating time-consuming database admin tasks, such as hardware provisioning, patching, and backups. While you can easily scale up your RDS database instances to handle varying business needs, it’s also important to optimize your cost as you scale. You can take advantage of RDS Reserved Instances pricing and leverage RI purchase recommendations in AWS Cost Explorer. You can also turn off RDS DB instances that are not being used, avoid over-provisioning for your applications, and upgrade to the latest generation instances for better price-performance.
However, getting the insights to help you optimize can be time-consuming. You need to dedicate engineering resources specialized in databases to analyze the cost and performance or iteratively adjust resources to achieve the optimal configuration. With these new recommendations in AWS Compute Optimizer, you can identify opportunities to optimize your database resource configurations faster.
Introducing Rightsizing Recommendations for Amazon RDS
A recommendation for Amazon RDS MySQL and RDS PostgreSQL databases includes two parts. First, you will see a recommendation for the DB instance, and second, you will see a recommendation for the DB instance storage.
The DB instance part of the recommendation tells you whether Compute Optimizer thinks the database might be idle. Then it gives you up to two instance recommendation options (one x86 and one Graviton) based on whether Compute Optimizer finds the database to be optimized, under-provisioned, or over-provisioned. You can then compare options with the current DB instance to understand the cost and specification differences. Similarly, in the storage tab, you will find a recommendation for the storage type (such as upgrades to gp3 from gp2) and provisioned IOPS for io1 storage volumes.
Wabtec has been able to reinvigorate our RDS optimization initiatives by leveraging the insights and recommendations provided by AWS Compute Optimizer for RDS, which has streamlined engineers’ ability to analyze and act upon RDS optimization opportunities. With single-click access to data, we quickly optimized 40% of the pilot group. This data-driven approach has accelerated a comprehensive roadmap for adopting AWS Graviton instances, which was backed by Compute Optimizer cost savings forecasting.
David Poulliott
Director, Cloud & Application Architecture | Tech Services | Wabtec Corporation
To generate these recommendations, Compute Optimizer analyzes metrics from Amazon CloudWatch such as CPU utilization, database connections, network throughput, and storage IOPS and throughput. If you have Amazon RDS Performance Insights enabled, Compute Optimizer also uses additional metrics such as database load (DBLoad) to provide more accurate recommendations.
