Data at Scale with DevOps

Welcome to the first chapter! In this book, you will learn the fundamentals of DevOps, its impact on the industry, and how to apply it to modern data persistence technologies.

When I first encountered the term DevOps years ago, I initially saw it as a way to grant development teams unrestricted access to production environments. This made me nervous, especially because there seemed to be a lack of clear accountability at that time, making the move toward DevOps appear risky.

At the time (around 2010), the roles of developers and operations were divided by a very strict line. Developers could gain read-only privileges, but that’s about it. What I did not see back then was that this was the first step in blurring the lines between development and operation teams. We already had many siloed teams pointing fingers at one another. This made the work slow, segmented, and frustrating. I was worried this would just increase complexity and cause an even greater challenge. Luckily, today’s world of DevOps is very different, and we can all improve it together even further!

There are no more dividing lines between the development and operations teams – they are one team with a common objective. This improves quality, speed, and agility! This also means that traditional roles such as database admin are changing as well. We now have site reliability engineers (SREs) or DevOps engineers who are experts at using databases and able to perform operational and development tasks alike. Blurring the line means you increase the responsibilities, and in a high-performing DevOps team, this means you are responsible for everything from end to end. Modern tooling and orchestration frameworks can help you do way more than ever before, but it’s a very different landscape than it was many years ago.

This book will introduce you to this amazing new world, walk you through the journey that leads us to this ever-changing world of DevOps today, and give some indications as to where we might go next.

By the end of this book, you will be able to not only demonstrate your theoretical knowledge but also design, build, and operate complex systems with a heavy focus on data persistence technologies.

DevOps and data persistence technologies have a love-hate relationship, which makes this topic even more interesting.

In this chapter, we will take a deep dive into the following topics:

• The modern data landscape
• Why speed matters
• Data management strategies
• The early days of DevOps
• SRE versus DevOps
• Engineering principles
• Objectives – SLOs/SLIs