This post explains how to integrate Amazon Aurora with Datadog for comprehensive monitoring of database health and performance. To start, you need to connect Datadog to CloudWatch, which involves setting up role delegation in AWS IAM, creating a new role for Datadog, and granting the Datadog role read-only access to your AWS services. Next, you integrate Datadog with Aurora's database engine by installing the Datadog Agent on an EC2 instance running the database, providing the Aurora instance endpoint, and tagging Aurora metrics with the DB instance identifier. Once set up, the Agent collects detailed metrics from the database instance, which can be unified under a single dashboard called "Amazon - RDS (Aurora)". This dashboard displays key metrics around query throughput, resource utilization, and replication lag, as well as database engine metrics from all instances configured via the MySQL integration. Additionally, enhanced monitoring for RDS instances running Aurora is available, providing more than 50 new CPU, memory, file system, and disk I/O metrics that can be collected on a per-instance basis as frequently as once per second. With Datadog's RDS Enhanced integration, you can monitor these high-resolution metrics in real-time and customize your dashboard to suit your needs.