Category: Expert (400)

Configure AWS DMS change data capture (CDC) from a self-managed SQL Server source without granting sysadmin to the endpoint login. This least-privilege pattern uses certificate-signed wrapper procedures, granular permissions, and AWS Secrets Manager to meet separation-of-duties requirements while preserving full CDC functionality.

Amazon Aurora DSQL supports foreign key constraints, letting you enforce referential integrity directly in the database. This post covers defining foreign keys, immediate versus deferred enforcement, adding constraints to existing tables, and how optimistic concurrency control resolves conflicts in distributed workloads.

Learn how to use AWS DMS and a Db2 gateway server on Amazon EC2 to migrate and replicate data from an on-premises IBM Db2 database on z/OS to Amazon Aurora PostgreSQL. This post covers configuring the gateway, creating DMS resources, running a full load with periodic full-load refresh, and validating the migration.

In this post, we show you how to build a fully managed, event-driven change data capture (CDC) pipeline. It streams row-level changes from Amazon RDS for PostgreSQL or Amazon Aurora PostgreSQL to Amazon S3 in near real time. You deploy the entire pipeline with a single AWS CloudFormation template, and it can run in private subnets with no internet gateway without exposing resources to the public internet.

How Amazon Fire TV redesigned its Continue Watching watch-progress data model on Amazon DynamoDB with vertical partitioning and hash-prefixed sort keys for parallel reads, removing item-size limits, cutting write costs by 97%, and keeping reads under 50 milliseconds at any profile size.

Learn how to build a tiered alerting strategy for Amazon DocumentDB by organizing CloudWatch metrics into Critical, Warning, and Advisory tiers, diagnosing slow queries through three complementary lenses, and monitoring garbage collection health before it becomes a cluster-wide incident.

Learn how to build, train, and score a credit risk machine learning model entirely in SQL using Oracle Machine Learning for SQL (OML4SQL) on Amazon RDS for Oracle. The built-in AutoML feature selects the best algorithm automatically, with no data movement and no external machine learning platforms.

AWS DMS uses exponential backoff for recoverable errors, and default settings can let a change data capture (CDC) task retry silently for up to 30 minutes before failing. This post shows how to tune four recoverable-error settings so CDC tasks fail within minutes, and how to pair them with Amazon EventBridge and Amazon CloudWatch alerts.

In this post, we demonstrate a serverless approach to continuous forensic artifact collection for Amazon RDS and Amazon Aurora databases. By capturing point-in-time snapshots of database internals on a cadence and storing them in Amazon S3, you create a time-series record that AI tools can analyze in seconds. This turns what was hours of manual investigation into an instant conversation.

In this post, you learn how to use the sp_invoke_external_rest_endpoint stored procedure on Amazon RDS for SQL Server 2025 to call AWS services and external HTTPS endpoints directly from T-SQL.