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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
Concepts
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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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Toc

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

DBAs in the World of DevOps

In this chapter, we will take a closer look at the evolving role of Database Administrators (DBAs) in the changing landscape of technology and data management. We will begin by exploring what the “early days” of database management were like when the DBA was primarily a gatekeeper of structured data, responsible for backups, data integrity, and query optimization. While those days may feel nostalgic, make no mistake, the profession has undergone significant transformations.

We’ll then delve into how cloud computing and big data are set to revolutionize the expectations of a DBA. Cloud computing is used to unshackle databases from on-premises limitations, offering scalability and flexibility like never before. Big data will be used to expand the types and volumes of data that DBAs interact with. It will no longer just be about SQL queries; it will be about managing and making sense of a torrent of structured and unstructured data flowing...

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