Category: Advanced (300)

In this post, we walk through the steps to set up the custom migration assistant agent and migrate a PostgreSQL database to Aurora DSQL. We demonstrate how to use natural language prompts to analyze database schemas, generate compatibility reports, apply converted schemas, and manage data replication through AWS DMS. As of this writing, AWS DMS does not support Aurora DSQL as target endpoint. To address this, our solution uses Amazon Simple Storage Service (Amazon S3) and AWS Lambda functions as a bridge to load data into Aurora DSQL.

In this post, we review the options for changing the AWS KMS key on your Amazon RDS database instances and on your Amazon RDS and Aurora clusters. We start with the most common approach, which is the snapshot method, and then we include additional options to consider when performing this change on production instances and clusters that can mitigate downtime. Each of the approaches mentioned in this post can be used for cross-account or cross-Region sharing of the instance’s data while migrating it to a new AWS KMS key.

In this post, I show you how to connect Lambda functions to Aurora PostgreSQL using Amazon RDS Proxy. We cover how to configure AWS Secrets Manager, set up RDS Proxy, and create a C# Lambda function with secure credential caching. I provide a GitHub repository which contains a YAML-format AWS CloudFormation template to provision the key components demonstrated, a C# sample function. I also walk through the Lambda function deployment step by step.

Using a movie streaming reference architecture, this post shows how to implement and sync operational, analytical, and search JSON workloads across AWS services. This pattern provides a scalable blueprint for any use case requiring multi-modal JSON data capabilities.

In this post, we demonstrate how to create custom Amazon RDS for SQL Server CloudWatch metrics. You accomplish this by using SQL Server Agent jobs and CloudWatch Logs integration. We walk through an example of monitoring table size within a SQL Server database however, this approach works for various other metrics. You can adapt this approach to track row counts, database size, job counts, user sessions, or other metrics.

In this post, we show how logical replication with fine-grained filtering works in PostgreSQL, when to use it, and how to implement it using a realistic healthcare compliance scenario. Whether you’re running Amazon RDS for PostgreSQL, Amazon Aurora PostgreSQL, or a self-managed PostgreSQL database on an Amazon EC2 instance, the approach is the same.

Amazon Aurora DSQL now supports PostgreSQL-compatible identity columns and sequence objects, so developers can generate unique integer identifiers with configurable performance characteristics optimized for distributed workloads. In distributed database environments, generating unique, sequential identifiers is a fundamental challenge: coordinating across multiple nodes creates performance bottlenecks, especially under high concurrency workloads. In this post, we show you how to create and manage identity columns for auto-incrementing IDs, selecting between identity columns and standalone sequence objects, and improving cache settings while choosing between UUIDs and integer sequences for your workload requirements.

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.