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DevOps for Databases

You're reading from   DevOps for Databases A practical guide to applying DevOps best practices to data-persistent technologies

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781837637300
Length 446 pages
Edition 1st Edition
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Author (1):
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David Jambor David Jambor
Author Profile Icon David Jambor
David Jambor
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Table of Contents (24) Chapters Close

Preface 1. Part 1: Database DevOps
2. Chapter 1: Data at Scale with DevOps FREE CHAPTER 3. Chapter 2: Large-Scale Data-Persistent Systems 4. Chapter 3: DBAs in the World of DevOps 5. Part 2: Persisting Data in the Cloud
6. Chapter 4: Cloud Migration and Modern Data(base) Evolution 7. Chapter 5: RDBMS with DevOps 8. Chapter 6: Non-Relational DMSs with DevOps 9. Chapter 7: AI, ML, and Big Data 10. Part 3: The Right Tool for the Job
11. Chapter 8: Zero-Touch Operations 12. Chapter 9: Design and Implementation 13. Chapter 10: Database Automation 14. Part 4: Build and Operate
15. Chapter 11: End-to-End Ownership Model – a Theoretical Case Study 16. Chapter 12: Immutable and Idempotent Logic – A Theoretical Case Study 17. Chapter 13: Operators and Self-Healing Data Persistent Systems 18. Chapter 14: Bringing Them Together 19. Part 5: The Future of Data
20. Chapter 15: Specializing in Data 21. Chapter 16: The Exciting New World of Data 22. Index 23. Other Books You May Enjoy

Operators and Self-Healing Data Persistent Systems

This chapter aims to delve into the realm of operators and self-healing data persistent systems, with a particular focus on Kubernetes and containerization technologies. It provides an in-depth exploration of the concept of self-healing, elucidates its benefits and risks, and highlights the factors to consider when implementing self-healing mechanisms in different types of databases. By the end of this chapter, you will have gained a thorough understanding of how self-healing systems can enhance the reliability and resilience of data persistence in modern infrastructure.

Throughout this chapter, we will explore self-healing data persistent systems from various angles, including their definition, core principles, benefits, and risks. We will also discuss the specific factors that come into play when implementing self-healing mechanisms in different types of databases, with a focus on relational, NoSQL, NewSQL, and time-series databases...

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