AWS Database Blog

Starting today, you can use AI agents to orchestrate entire AWS DMS Schema Conversion (DMS SC) workflows through natural language. An AI agent manages the full lifecycle, including creating migration projects, browsing source metadata, converting schemas, generating assessment reports, and exporting results, all from a conversational prompt.

This post is the second in a two-part series on reducing replication lag for Amazon RDS for Oracle Read Replicas. In Part 1, we discussed redo compression and configuration options to optimize replica lag. In this post, we show you how to monitor replica lag using Amazon CloudWatch metrics and database views, identify common root causes through wait event analysis, and how to troubleshoot and resolve performance issues.

In part 1 (this post), we show you how to optimize lag for RDS for Oracle replicas using the redo compression feature. In part 2, we discuss various techniques to monitor, troubleshoot, and resolve replication lag for RDS for Oracle replicas.

In this post, you learn how to set up CDC-only reverse replication from Amazon Relational Database Service (Amazon RDS) for Db2 back to your on-premises AIX Db2 instance using AWS Database Migration Service (AWS DMS).

In this post, we demonstrate how to use the PostgreSQL 18 logical replication improvements on RDS for PostgreSQL: replicating STORED generated columns with the publish_generated_columns parameter, monitoring conflicts through the new counters in pg_stat_subscription_stats, verifying that parallel streaming is enabled by default, toggling two-phase commit on a running subscription, and configuring idle_replication_slot_timeout for automatic slot cleanup. These features are available on RDS for PostgreSQL 18.0 and later and Aurora PostgreSQL.

In this post, we show you how to deploy an automated pipeline that extracts PostgreSQL audit logs from CloudWatch Logs, converts them into structured comma-separated values (CSV) format, and stores them in Amazon S3 for long-term analysis. The solution processes log entries in near real time after generation.

In this post, we show how Dynata simplified database cost optimization and accelerated modernization to AWS Graviton processors by adopting Database Savings Plans. Rather than managing Reserved Instances across multiple database services, Dynata consolidated their cost commitment into a single, flexible pricing model. This reduced operational overhead by 70%, extended cost coverage to Amazon Aurora serverless, and lowered total cost of ownership as their infrastructure evolved.

In this post, we walk through how to use the Oracle Data Masking and Subsetting Pack with Amazon RDS for Oracle. We cover setting up Data Masking in Oracle Enterprise Manager (OEM) and automation options.

In this post, you will learn how CRED built an automated orchestration framework around Amazon RDS blue/green deployments. The framework performs engine upgrades, instance scaling, storage optimization, and Change Data Capture (CDC) pipeline migration across their entire fleet. This approach achieved zero data loss incidents and zero production incidents.

This post shows you how to set up centralized cross-account and cross-Region monitoring for Amazon Relational Database Service (Amazon RDS) and Amazon Aurora databases using Amazon CloudWatch Database Insights. Whether your databases are spread across two AWS accounts or ten, and across one Region or several, this walkthrough gives you a single monitoring account with visibility across your entire database fleet.