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

Automated data discovery and cataloging – unveiling the hidden treasures in today’s data landscape

As the digital revolution rages on, data has risen to become the world’s most valuable resource, driving innovation, strategic decisions, and operational efficiencies. However, as data grows in volume, variety, and velocity, businesses grapple with a fundamental challenge – knowing what data they have and where it is stored. Enter automated data discovery and cataloging – a groundbreaking technological innovation that enables businesses to navigate the increasingly complex data landscape effectively.

Understanding data discovery and cataloging

Data discovery refers to the process of finding and understanding patterns and trends in data. In contrast, data cataloging involves creating a comprehensive inventory of data assets and providing details about their source, usage, relationships, and business context. Combined, data discovery and cataloging...