🔧 Automating Databases for Modern DevOps Practices: A Guide to Common Patterns and Anti-Patterns for Database Automation Techniques

Editor's Note: The following is an article written for and published in DZone's 2024 Trend Report, Database Systems: Modernization for Data-Driven Architectures.

As companies increasingly depend on data for decision making, operational improvements, and enhanced customer experiences, the manual management of large and complex databases becomes a daunting task, as shown in Figure 1. Database automation offers a solution by simplifying operations, reducing errors, and enhancing efficiency. Automation can handle tasks such as provisioning, scaling, and backups, allowing IT teams to focus on other initiatives. Some common techniques include scripting and scheduling, configuration management tools, Infrastructure as Code (IaC), automated testing, and more.