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    DevOps for Databases: A practical guide to applying DevOps best practices to data-persistent technologies

    Posted By: TiranaDok
    DevOps for Databases: A practical guide to applying DevOps best practices to data-persistent technologies

    DevOps for Databases: A practical guide to applying DevOps best practices to data-persistent technologies by David Jambor
    English | December 29, 2023 | ISBN: 183763789X | 765 pages | EPUB | 5.15 Mb

    Implement, automate, build, operate, and optimize databases and other data-persistent technologies efficiently by leveraging the right set of DevOps best practices
    Key Features
    • Implement core operational capabilities via automated pipelines, including testing and rollbacks
    • Create infrastructure, deploy software, test execution, and monitor operations using the as-code strategy
    • Automate common implementation patterns for databases with declarative orchestration frameworks
    • Purchase of the print or Kindle book includes a free PDF eBook
    Book Description
    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.
    What you will learn
    • Apply DevOps best practices to data-persistent technologies
    • Get to grips with architectural-level design and implementation
    • Explore the modern data journey and data modeling with database technology
    • Master the operation of large-scale systems with zero-touch automation
    • Achieve speed, resilience, security, and operability at different scales
    • Design DevOps teams with end-to-end ownership models
    Who this book is for
    This book is for newcomers as well as seasoned SREs, DevOps engineers, and system engineers who are interested in large-scale systems with a heavy focus on data-persistent technologies. Database administrators looking to level up in the world of DevOps will also find this book helpful. Experience with cloud Infrastructure, basic development, and operations will help you get the most out of this book.
    Table of Contents
    • Implementing DevOps in Real Life
    • Large scale Data Persistent Systems
    • DBAs in the world of DevOps - The increased responsibility of a DevOps DBA
    • Data(base) evolution / Modern cloud-migration
    • Relational Databases … through the eyes of a DevOps DBA
    • Non-Relational Databases … through the eyes of a DevOps DBA
    • Big Data, AI and ML … through the eyes of a DevOps DBA
    • What good looks like - Zero touch operations
    • Design and Implementation - The role of the DevOps DBA through design to production
    • Database Automation
    • End to end ownership model
    • Immutable and Idempotent logic
    • Operators and Self-Healing systems - Advanced DevOps DBA automation
    • Bring them together
    • (The past) - Specialising in Data - The author's a personal experience and evolution into DevOps and Database DevOps
    (N.B. Please use the Look Inside option to see further chapters)