Category: RDS for MySQL

AWS today announced the general availability of AMD-based R8a and M8a database instances for Amazon Aurora and Amazon RDS, powered by 5th generation AMD EPYC processors. R8a is a memory-optimized instance family available on both Aurora and RDS. M8a is a general-purpose instance family available on RDS.

After a major or minor version upgrade on Amazon Aurora MySQL or Amazon RDS for MySQL, some queries regress because the optimizer’s cost models, defaults, and execution strategies change. This post walks through a diagnostic workflow that traces each regression to the specific version change behind it and applies the right fix.

In this post, you will learn how CRED built an automated orchestration framework around Amazon RDS blue/green deployments. The framework performs engine upgrades, instance scaling, storage optimization, and Change Data Capture (CDC) pipeline migration across their entire fleet. This approach achieved zero data loss incidents and zero production incidents.

In this post, we share the version currency timelines for Aurora and RDS open source engines. We also explain why timelines differ across engines and how you can use them to plan your upgrades.

This post is part of a two-part series on upgrading RDS for MySQL 8.0 to 8.4. Here, we cover the end of standard support timeline, extended support costs, upgrade methods, and key best practices. For a step-by-step implementation guide, see Best practices for upgrading RDS for MySQL 8.0 to 8.4 with prechecks, Blue/Green, and rollback.

In this post, you learn how to build a complete upgrade workflow for RDS for MySQL 8.0 to 8.4, covering pre-upgrade compatibility checks, Amazon RDS Blue/Green Deployments for minimal downtime, and a rollback strategy for added protection.

In this post, we show you how to optimize full-text search (FTS) performance in Amazon RDS for MySQL and Amazon Aurora MySQL-Compatible Edition through proper maintenance and monitoring. We discuss why FTS indexes require regular maintenance, common issues that can arise, and best practices for keeping your FTS-enabled databases running smoothly.

In this post, we walk you through building an automated storage scaling solution for Amazon RDS Multi-AZ clusters with two readable standbys. We use AWS Lambda to execute scaling logic, Amazon CloudWatch to detect and alarm on storage thresholds, and Amazon SNS to deliver timely notifications. This combination provides event-driven automation, native AWS integration, and operational visibility without requiring third-party tooling.

In this post, we demonstrate how to migrate from Cloud SQL for MySQL 8+ to Amazon RDS for MySQL 8+ or Amazon Aurora MySQL–Compatible using AWS DMS over an AWS Site-to-Site VPN. We cover preparing the source and target environments, exemplifying cross-cloud connectivity, and setting up DMS tasks.

Amazon RDS for MySQL and Amazon Aurora MySQL provide built-in audit logging capabilities, but customers might need to export and store these logs for long-term retention and analysis. Amazon S3 offers an ideal destination, providing durability, cost-effectiveness, and integration with various analytics tools. In this post, we explore two approaches for exporting MySQL audit logs to Amazon S3: either using batching with a native export to Amazon S3 or processing logs in real time with Amazon Data Firehose.