Category: Intermediate (200)

The new aws_dynamodb_global_secondary_index resource treats each GSI as an independent resource with its own lifecycle management. You can use this feature to make capacity adjustments for GSI and tables outside of Terraform. In this post, I demonstrate how to use Terraform’s new aws_dynamodb_global_secondary_index resource to manage GSI drift selectively. I walk you through the limitations of current approaches and guide you through implementing the solution.

In this post, we show how you can use graph algorithms to analyze the results of AWS Entity Resolution and related transactions for the CNP use case. We use several AWS services, including Neptune Analytics, AWS Entity Resolution, Amazon SageMaker notebooks, and Amazon S3.

Today, we’re announcing multi-account global tables for Amazon DynamoDB, which let you replicate DynamoDB table data across multiple AWS accounts and AWS Regions. This feature adds account-level isolation to global tables, so you can replicate DynamoDB table data across multiple AWS accounts and Regions for stronger isolation and resiliency. In this post, we show you how to create and configure a multi-account global table, and introduce use cases highlighting the value of using this feature.

In this post, we talk about the benefits of caching in generative AI applications. We also elaborated on a few implementation strategies that can help you create and maintain an effective cache for your application.

Amazon Keyspaces now supports the pre-warming feature to provide you with proactive throughput management. With pre-warming, you can set minimum warm throughput values that your table can handle instantly, avoiding the cold start delays that occur during dynamic partition splits. In this post, we discuss the Amazon Keyspaces pre-warming feature capabilities and demonstrate how it can enhance your throughput performance.

In 2023, Tradeshift migrated one of its core PostgreSQL databases from self-managed Amazon Elastic Compute Cloud (Amazon EC2) instances to Amazon Relational Database Service (Amazon RDS) for PostgreSQL. The decision followed mounting operational risks and performance limits that made the existing setup increasingly unsustainable. Tradeshift needed a managed solution that could reduce downtime risk, improve observability, and simplify ongoing operations. Amazon RDS met those requirements. In this post, we explain why we migrated to Amazon RDS, how we executed the migration, and highlight the invaluable benefits it delivered in terms of safety, flexibility, and audit compliance.

AWS Organizations now supports an upgrade rollout policy, a new capability that provides a streamlined solution for managing automatic minor version upgrades across your database fleet. This feature supports Amazon Aurora MySQL-Compatible Edition and Amazon Aurora PostgreSQL-Compatible Edition and Amazon RDS database engines MySQL, PostgreSQL, MariaDB, SQL Server, Oracle, and Db2. It eliminates the operational overhead of coordinating upgrades across hundreds of resources and accounts while validating changes in less critical environments before reaching production. In this post, we explore how upgrade rollout policy works, its key benefits, and how you can use it to implement a systematic approach to database maintenance across your organization.

Amazon Relational Database Service (Amazon RDS) for SQL Server now offers the Optimize CPU feature, which enabled control over vCPU allocation through core count modification setting. SQL Server licensing costs can consume a significant portion of your database budget, especially when you’re paying for vCPUs that aren’t fully utilized. This post demonstrates how to implement the Optimize CPU feature to potentially reduce licensing costs while maintaining performance for both new and existing Amazon RDS instances, along with performance benchmarking results and cost implications.

As a global leader in the online travel industry, Booking.com continuously works to improve the travel experience for its users. Latency is a key factor in achieving this—nobody likes waiting for their search results to be returned. In this post, we share how Booking.com designed a well-architected Amazon ElastiCache-based feature platform, achieving ultra-low latency and high throughput, to ensure the best possible user experience.

In this post, we show you how to create and deploy SQL Server Developer Edition on Amazon RDS.