AWS Compute Optimizer now provides recommendations for optimizing Amazon Relational Database Service (RDS) MySQL and PostgreSQL databases. These recommendations help identify under-provisioned, over-provisioned, and idle RDS instances, providing suggestions for optimal instance types and provisioned IOPS configurations to reduce costs and enhance performance. By leveraging these recommendations, users can streamline database resource configurations quickly and efficiently.
The recommendations include two parts: one for the DB instance and another for the DB instance storage. The DB instance recommendation offers insights into the status of the database and provides options for optimized, under-provisioned, or over-provisioned instances. Similarly, the storage recommendation suggests upgrades to storage type and provisioned IOPS configurations. By analyzing performance metrics such as CPU utilization, database connections, network performance, and storage metrics, Compute Optimizer assists users in making informed decisions regarding their RDS resources.
Companies like Wabtec have successfully optimized their RDS instances by implementing Compute Optimizer’s recommendations, resulting in significant cost savings and improved efficiency. The platform’s data-driven approach and cost savings forecast have enabled organizations to optimize their RDS workloads effectively, accelerating the adoption of next-generation instance types like AWS Graviton.
To access these recommendations, users need to enable Compute Optimizer, which requires at least 30 hours of metrics before generating suggestions for an RDS DB instance. Recommendations can be viewed in the Compute Optimizer Console or through the API, providing actionable insights for resizing instances, upgrading storage, and optimizing performance. Cost Optimization Center aggregates all savings opportunities, including RDS recommendations, allowing users to prioritize and implement changes to maximize cost-effectiveness.
Overall, AWS Compute Optimizer’s new recommendations empower users to detect inactive databases, optimize RDS instances, and storage usage, striking a balance between cost efficiency and performance. By utilizing these insights in the Cost Optimization Hub, organizations can assess potential savings across their RDS workloads and prioritize optimization strategies alongside other cost-saving opportunities within the organization. Through a data-driven approach and streamlined optimization processes, AWS Compute Optimizer enhances the efficiency and cost-effectiveness of managing RDS databases.
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https://aws.amazon.com/blogs/aws-cloud-financial-management/new-rightsizing-recommendations-for-amazon-rds-mysql-and-rds-postgresql-in-aws-compute-optimizer/