Category: Advanced (300)

In this post, you learn how to build a real-time AI movie recommendation system by streaming live data changes from Amazon Keyspaces to Amazon S3 vector storage. The post shows how to use Keyspaces change data capture streams to capture database modifications, convert them into vector embeddings using Amazon Bedrock, and store them in S3 Vector indexes for similarity searches that give AI applications access to fresh data within milliseconds.

Amazon DocumentDB 8.0 brings in support for MongoDB 8.0 API driver compatibility while maintaining support for applications built using MongoDB API versions 6.0 and 7.0. This post explores the new features in Amazon DocumentDB 8.0 and demonstrates how they improve performance and cost efficiency.

In this post, you learn how to implement conversational operations for Oracle E-Business Suite (Oracle EBS) on AWS by connecting Kiro CLI with your monitoring infrastructure through the MCP. We walk through the technical architecture that enables natural language queries to retrieve CloudWatch metrics, analyze logs, and execute operational commands.

In this post, I introduce a framework for managing atomicity, consistency, isolation, and durability (ACID) compliant transactions in Amazon DynamoDB using C#, featuring support for nested transactions. This capability allows you to implement sophisticated logic with finer control over data consistency and error handling within your .NET applications. With this nested transaction framework, you can isolate issues, allow for partial rollbacks, and build maintainable, modular workflows on top of the built-in transactional capabilities of DynamoDB.

In this post, you will learn how to build a serverless monitoring solution sending detailed alerts whenever Amazon RDS parameter groups are modified, including which databases are affected and whether a restart is required.

As AWS continues to evolve its services to better align with customer needs and modern workloads, we’re excited to introduce a new export functionality for Amazon SimpleDB . By using this feature, you can export domain data to Amazon S3 in JSON format, unlocking new opportunities for long-term storage, and migration to purpose-built databases. The export generates a complete JSON representation of Amazon SimpleDB data. In this post, we walk you through how to use the new export functionality, highlight best practices, and share monitoring functionality to help you make the most of it.

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.

In this post, you’ll learn how to deploy a serverless solution using AWS CloudFormation that automatically adjusts RDS maintenance and backup windows for DST transitions.

In this post, we demonstrate how to configure IAM database authentication in AWS Database Migration Service (AWS DMS). You’ll also learn the structured troubleshooting approach you follow to address the errors when configuring IAM database authentication with AWS DMS

In this post, we show you how to migrate spatial (geospatial) data from self-managed PostgreSQL, Amazon RDS for PostgreSQL, or Amazon Aurora PostgreSQL-Compatible Edition to Amazon RDS for PostgreSQL or Amazon Aurora PostgreSQL using AWS DMS. Spatial data is useful for applications such as mapping, routing, asset tracking, and geographic visualization. We walk through setting up your environment, configuring AWS DMS, and validating the successful migration of spatial datasets.