Summary

DevOps presents challenges; introduce data and those challenges intensify. This book aims to explore that intricate landscape.

Consider this: immutable objects and IaC with declarative orchestration frameworks often yield secure, dependable, and repeatable results. But what happens when you must manage entities that resist immutability? Think about databases or message queues that house data that can’t be replicated easily. These technologies are integral to production but demand unique attention.

Picture this: a Formula 1 car swaps out an entire tire assembly in mere seconds during a pit stop. Similarly, with immutable objects such as load balancers, a quick destroy-and-recreate action often solves issues. It’s convenient and rapid, but try applying this quick-swap approach to databases and you risk data corruption. You must exercise caution when dealing with mutable, data-persistent technologies.

Fast forward to recent years, and you’ll find attempts to facilitate database automation via custom resource definitions (CRDs) or operators. However, such methods have proven costly and complex, shifting the trend toward managed services. Yet, for many, outsourcing data operations isn’t the ideal solution, given the priority of data security.

Navigating DevOps and SRE best practices reveals the looming complexities in managing data-centric technologies. Despite the valuable automation tools at our disposal, maintaining the highest DevOps standards while capitalizing on this automation is anything but straightforward. We’ll delve into these challenges and potential solutions in the chapters to come.