AWS Database Blog

Category: RDS for MySQL

Architecture Diagram: AWS architecture diagram showing RDS Multi-AZ DB Cluster connected to CloudWatch Alarm, which triggers a Lambda Function to scale storage. The alarm also sends notifications to Amazon SNS. The components are arranged in a workflow with connecting arrows, displayed within a blue-bordered region box.

Automatically scale storage for Amazon RDS Multi-AZ DB clusters using AWS Lambda

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.

Migrate Cloud SQL for MySQL to Amazon Aurora and Amazon RDS for MySQL Using AWS DMS

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.

Overview of solution 1

Automate the export of Amazon RDS for MySQL or Amazon Aurora MySQL audit logs to Amazon S3 with batching or near real-time processing

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.

Monitoring multithreaded replication in Amazon RDS for MySQL, Amazon RDS for MariaDB, and Aurora MySQL

In this post, we discuss methods to effectively monitor parallel replication performance and tune its related parameters for Amazon Aurora MySQL and Amazon Relational Database Service for MySQL and MariaDB.

Overview and best practices of multithreaded replication in Amazon RDS for MySQL, Amazon RDS for MariaDB, and Amazon Aurora MySQL

In this first post, we dive into the world of MySQL replication, with a special focus on parallel replication techniques. We start with a quick overview of how MySQL replication works, then explore the intricacies of multithreaded replication. We discuss key configuration options and best practices for optimization.

Performance optimization strategies for MySQL on Amazon RDS

In this post, we share infrastructure-level optimizations, RDS-specific performance features, and database design patterns to help improve MySQL performance on Amazon RDS. We focus on practical configurations and monitoring techniques that complement existing parameter tuning documentation, helping you make informed decisions for your specific workload requirements.

Dynamic view-based data masking in Amazon RDS and Amazon Aurora MySQL

Data masking is an important technique in cybersecurity, allowing organizations to safeguard personally identifiable information (PII) and other confidential data, while maintaining its utility for development, testing, and analytics purposes. Data masking involves replacing original sensitive data with false, yet realistic information. This process helps ensure that the masked version preserves the format and characteristics […]

Scaling transaction peaks: Juspay’s approach using Amazon ElastiCache

Juspay powers global enterprises by streamlining payment process orchestration, enhancing security, reducing fraud, and providing seamless customer experiences. In this post, we walk you through how Juspay transformed their payment processing architecture to handle transaction peaks. Using Amazon ElastiCache and Amazon RDS for MySQL, Juspay built a system that processes 7.6 million transactions per hour during peak events, achieves sub-millisecond latency, and reduces infrastructure costs by 80% compared to their previous solution.

Simplify data integration using zero-ETL from Amazon RDS to Amazon Redshift

Organizations rely on real-time analytics to gain insights into their core business drivers, enhance operational efficiency, and maintain a competitive edge. Traditionally, this has involved the use of complex extract, transform, and load (ETL) pipelines. ETL is the process of combining, cleaning, and normalizing data from different sources to prepare it for analytics, AI, and […]

Implement row-level security in Amazon Aurora MySQL and Amazon RDS for MySQL

Row-level security (RLS) is a security mechanism that enhances data protection in scalable applications by controlling access at the individual row level. It enables organizations to implement fine-grained access controls based on user attributes, so users can only view and modify data they’re authorized to access. This post focuses on implementing a cost-effective custom RLS solution using native MySQL features, making it suitable for a wide range of use cases without requiring additional software dependencies. This solution is applicable for both Amazon Relational Database Service (Amazon RDS) for MySQL and Amazon Aurora MySQL-Compatible Edition, providing flexibility for users of either service.