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DevOps for Databases

DevOps for Databases

By : David Jambor
5 (7)
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DevOps for Databases

DevOps for Databases

5 (7)
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)
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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

Hey, are you tired of all the buzzwords I’ve just used in this chapter? Shall we recap what we were saying in this chapter, and more or less in this book? Let’s take a quick tour!

Part 1 dived into the world of data – you know, all the things that keep our information secure and accessible? Right now, we’re talking about things such as NoSQL and in-memory databases. But looking forward, imagine automated data management and even quantum databases! It sounds complex, but with the right skills and an eagerness to learn, we can keep up with these changes.

Part 2 dived into AI/ML DevOps. This is where AI meets development and operations. Pretty cool, huh? Imagine automated pipelines and continuous integration, all working seamlessly. The future here is even more automation and collaboration, but also being mindful of ethics and explainability. It’s all about aligning tech with our core values.

In Part 3, we learned all about SRE. Ever...

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DevOps for Databases
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