DevOps for Databases
By :
DevOps for Databases
By:
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)
Preface
Part 1: Database DevOps
Free Chapter
Chapter 1: Data at Scale with DevOps
Chapter 2: Large-Scale Data-Persistent Systems
Chapter 3: DBAs in the World of DevOps
Part 2: Persisting Data in the Cloud
Chapter 4: Cloud Migration and Modern Data(base) Evolution
Chapter 5: RDBMS with DevOps
Chapter 6: Non-Relational DMSs with DevOps
Chapter 7: AI, ML, and Big Data
Part 3: The Right Tool for the Job
Chapter 8: Zero-Touch Operations
Chapter 9: Design and Implementation
Chapter 10: Database Automation
Part 4: Build and Operate
Chapter 11: End-to-End Ownership Model – a Theoretical Case Study
Chapter 12: Immutable and Idempotent Logic – A Theoretical Case Study
Chapter 13: Operators and Self-Healing Data Persistent Systems
Chapter 14: Bringing Them Together
Part 5: The Future of Data
Chapter 15: Specializing in Data
Chapter 16: The Exciting New World of Data
Index
Customer Reviews