Category: RDS for MySQL

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.

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.

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.

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.

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 […]

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.

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 […]

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.

Careem powers rides, deliveries, and payments across the Middle East, North Africa and South Asia. As Careem grew, so did its data infrastructure challenges. Their monolithic 270 TB Amazon RDS for MySQL database consisting of one writer and five read replicas— experienced performance issues due to increased storage utilization, slow queries, high replica lag, and increased Amazon RDS cost. In this post, we provide a step-by-step breakdown of how Careem successfully implemented a phased data purging strategy, improving DB performance while addressing key technical challenges.

In this post, we discuss how to migrate MySQL very large databases (VLDBs) from a self-managed MySQL database to Amazon Aurora MySQL-Compatible Edition using the MyDumper and MyLoader tools.