Book Image

DevOps for Databases

By : David Jambor
Book Image

DevOps for Databases

By: David Jambor

Overview of this book

In today's rapidly evolving world of DevOps, traditional silos are a thing of the past. Database administrators are no longer the only experts; site reliability engineers (SREs) and DevOps engineers are database experts as well. This blurring of the lines has led to increased responsibilities, making members of high-performing DevOps teams responsible for end-to-end ownership. This book helps you master DevOps for databases, making it a must-have resource for achieving success in the ever-changing world of DevOps. You’ll begin by exploring real-world examples of DevOps implementation and its significance in modern data-persistent technologies, before progressing into the various types of database technologies and recognizing their strengths, weaknesses, and commonalities. As you advance, the chapters will teach you about design, implementation, testing, and operations using practical examples, as well as common design patterns, combining them with tooling, technology, and strategies for different types of data-persistent technologies. You’ll also learn how to create complex end-to-end implementation, deployment, and cloud infrastructure strategies defined as code. By the end of this book, you’ll be equipped with the knowledge and tools to design, build, and operate complex systems efficiently.
Table of Contents (24 chapters)
1
Part 1: Database DevOps
5
Part 2: Persisting Data in the Cloud
7
Chapter 5: RDBMS with DevOps
10
Part 3: The Right Tool for the Job
14
Part 4: Build and Operate
19
Part 5: The Future of Data

Summary

I consider myself lucky, having been able to experience first-hand such an amazing change in the world of Data and DevOps in such a short period of time. The last 14-15 years were nothing but extraordinary, filled with ambiguity, opportunity, and pure passion for innovation.

In 2009, the term “DevOps” was only just emerging, and its principles were far from widespread adoption. Traditional software development was marked by silos, where developers and operations teams worked separately. This disjointed approach often led to significant bottlenecks in the software delivery process, causing delays and conflicts.

Data systems at this time were largely monolithic and on-premises. Relational databases were the norm, and NoSQL databases were just beginning to gain traction. The management of these systems was largely manual, and they were often treated as separate entities from the applications they supported.

CI/CD practices were not as widely accepted or...