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DevOps for Databases
DevOps for Databases

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

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DevOps for Databases

Data at Scale with DevOps

Welcome to the first chapter! In this book, you will learn the fundamentals of DevOps, its impact on the industry, and how to apply it to modern data persistence technologies.

When I first encountered the term DevOps years ago, I initially saw it as a way to grant development teams unrestricted access to production environments. This made me nervous, especially because there seemed to be a lack of clear accountability at that time, making the move toward DevOps appear risky.

At the time (around 2010), the roles of developers and operations were divided by a very strict line. Developers could gain read-only privileges, but that’s about it. What I did not see back then was that this was the first step in blurring the lines between development and operation teams. We already had many siloed teams pointing fingers at one another. This made the work slow, segmented, and frustrating. I was worried this would just increase complexity and cause an even greater challenge. Luckily, today’s world of DevOps is very different, and we can all improve it together even further!

There are no more dividing lines between the development and operations teams – they are one team with a common objective. This improves quality, speed, and agility! This also means that traditional roles such as database admin are changing as well. We now have site reliability engineers (SREs) or DevOps engineers who are experts at using databases and able to perform operational and development tasks alike. Blurring the line means you increase the responsibilities, and in a high-performing DevOps team, this means you are responsible for everything from end to end. Modern tooling and orchestration frameworks can help you do way more than ever before, but it’s a very different landscape than it was many years ago.

This book will introduce you to this amazing new world, walk you through the journey that leads us to this ever-changing world of DevOps today, and give some indications as to where we might go next.

By the end of this book, you will be able to not only demonstrate your theoretical knowledge but also design, build, and operate complex systems with a heavy focus on data persistence technologies.

DevOps and data persistence technologies have a love-hate relationship, which makes this topic even more interesting.

In this chapter, we will take a deep dive into the following topics:

  • The modern data landscape
  • Why speed matters
  • Data management strategies
  • The early days of DevOps
  • SRE versus DevOps
  • Engineering principles
  • Objectives – SLOs/SLIs

The modern data landscape

Have you ever wondered how much data we generate every single day? Or the effort required to store and access your data on demand? What about the infrastructure or the services required to make all of this happen? Not to mention the engineering effort put in to make all of this happen. If you have, you are in the right place. These questions inspired me to dive deep into the realms of DevOps and SRE and inspired the creation of this book.

Technology impacts almost every aspect of our lives. We are more connected than ever, with access to more information and services than we even realize. It’s not just our computers, phones, or tablets that are connected to the internet, but our cars, cameras, watches, televisions, speakers, and more. The more digital native we become, the bigger our digital footprint grows.

A digital footprint, also known as a digital shadow, is a collection of data that represents an individual’s interactions and activities across digital platforms and the internet. This data can be categorized as either passive, where it’s generated without direct interaction – such as browsing history – or active, resulting from deliberate online actions such as social media posts or emails. Your digital footprint serves as an online record of your digital presence, and it can have lasting implications for your privacy and reputation.

As of 2022, researchers estimate that out of 8 billion people (the world’s population as of 2022), approximately 5 billion utilize the internet daily. Compared to the 2 billion that was measured in 2012, this is a 250% increase over 10 years. This is an incredible increase. See the following figure for reference:

Figure 1.1 – Daily internet users (in billions)

Figure 1.1 – Daily internet users (in billions)

Each person who has a digital presence generates digital footprints in two ways.

The first is actively. When you browse a website, upload a picture, send an email, or make a video call, you generate data that will be utilized and stored for some time. The other, less obvious way is passive data generation. If you, like me, utilize digital services with push notifications on or have GPS enabled on your phone with a timeline, for example, you are generating data every minute of the day – even if you do not use these services actively. Prime examples can be any Internet of Things (IoT) devices, something such as an internet-enabled security camera – even if you are not actively using it, it’s still generating data and constantly uploading it to your service provider for safekeeping. IoT devices are the secondary source of data generators right after us active internet surfers. Researchers estimate that approximately 13 billion IoT devices are being connected and in daily use as of 2022, with the expectation that this figure will become close to 30 billion by the end of 2030. See the following figure for reference:

Figure 1.2 – Connected IoT devices (in the billions)

Figure 1.2 – Connected IoT devices (in the billions)

Combining the 5 billion active internet users with the 13 billion connected IoT devices, it is easy to guess that our combined digital footprint must be ginormous. Yet trying to guess the exact number is much harder than you might think. Give it a try.

As of 2023, it is estimated that we generate approximately 3.5 exabytes of data every single day. This is about 1 exabyte more than what was estimated in 2021. To help visualize how much data we are talking about, let me try to put this into perspective. Let’s say you have a notebook (or one of the latest phones) with 1 TB of storage capacity. If you were to use this 1 TB storage to store all this information, it would be full in less than 0.025 seconds. An alternative way to think about it is that we can fill 3,670,016 devices with 1 TB storage within 24 hours.

How do we generate data today?

Well, for starters, we collectively send approximately 333.2 billion emails per day. This means that more than 3.5 million emails are sent per second. We also make over 0.5 billion hours of video calls, stream more than 200 million hours of media content, and share more than 5 billion videos and photos every single day.

So, yes, that’s a lot of us armed with many devices (on average, one active internet user had about 2.6 IoT devices in 2022) generating an unbelievable amount of data every single day. But the challenge does not stop at the amount of data alone. The speed and reliability of interacting with it are just as important as, if not more important than, the storage itself. Have you ever searched for one of your photos to show someone, but it was slow and took forever to find, so you gave up? We have all been there, but can you remember just how much time after doing this that you decided to abandon your search?

As technology advances, we gain quicker access to information and multitask more efficiently, which may be contributing to a gradual decline in our attention spans. Research shows that in 2000, the average attention span was 12 seconds. Since then, significant technological milestones have occurred: the advent of the iPhone, YouTube, various generations of mobile networks, Wikipedia, and Spotify, to name a few. Internet speed has also soared, moving from an average of 127 kilobits per second in 2000 to 4.4 Mbps by 2010, and hitting an average of 50.8 Mbps by 2020 – with some areas experiencing speeds well over 200 Mbps today.

As the digital landscape accelerates, so do our expectations, resulting in further erosion of our attention spans. By 2015, that 12-second average had fallen to just 8.25 seconds and dropped slightly below 8 seconds by 2022.

Why speed matters

If you consider your attention span the full amount of time you would consider spending to complete a simple task, such as showing photos or videos to a friend, this means searching for it is just a small percentage of your total time. Let’s say you are using a type of cloud service to search for your photo or video. What would you consider to be an acceptable amount of time between you hitting search and receiving your content?

I still remember the time when “buffering” was a given thing, but if you see something similar today, you would find it unacceptable. According to multiple studies, the ideal load time for “average content,” such as photos or videos, is somewhere between 1 and 2 seconds. 53% of mobile site visits are abandoned if pages take longer than three seconds to load. A further two-second delay in load time results in abandonment rates of up to 87%.

This shows us that storing our data is not enough – making it accessible reliably and with blazing speed is not only nice to have but an absolute necessity in today’s world.

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Key benefits

  • 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

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.

Who is this book 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.

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

Product Details

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Publication date : Dec 29, 2023
Length: 446 pages
Edition : 1st
Language : English
ISBN-13 : 9781837637300
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Product Details

Publication date : Dec 29, 2023
Length: 446 pages
Edition : 1st
Language : English
ISBN-13 : 9781837637300
Vendor :
Couchbase Inc
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Tools :

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Table of Contents

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

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Sangita Mahala Jan 11, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I highly recommend this book to anyone interested in the intersection of DevOps and database management. It's an insightful, informative, and essential read for anyone involved in building, managing, or utilizing data-persistent systems.
Amazon Verified review Amazon
Gabor Gerencser Feb 05, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
DevOps for Databases book presents an invaluable resource for professionals engaged in database management within contemporary DevOps/SRE frameworks. This comprehensive tome adeptly blends practical insights with theoretical underpinnings, offering a well-rounded understanding of the subject matter. Drawing from extensive real-world experience and best practices, it meticulously explores various facets of database management, ranging from fundamental concepts to advanced AI applications, encompassing both relational and non-relational databases. With illustrative examples, the book delves into essential tooling, self-healing mechanisms, and a plethora of other compelling topics. I wholeheartedly recommend this publication to individuals at all career levels, as it serves as a catalyst for enhancing one's proficiency in database management
Amazon Verified review Amazon
Michael Cade May 05, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I received my copy of the book at the turn of the new year and took to it in some of my spare time, my specific interest was obviously around databases but how in 2024 we should consider the database, a stateful workload when it comes to automation, orchestration and code. I thought the book kicked off nicely with the brief overview but not going to deep into the over arching devops mindset, principles and process.The ability to cover the concepts I throughout and make the book engaging is the key metric for me and why it has to be a 5 star rating.If you are easily distracted like me, the best way to attack this book and similar is to set aside some time each day or week to get through a chapter or 10 pages. This will help with that concentration. NAs the author of 90DaysOfDevOps, I was also intrigued to how this could be used to spread the use cases to the community. In 2023 there was a section on Databases where we cover the fundamentals but this book gave me a much bigger insight into the next level of databases and how we can really bring that level of automation and control to our mission critical data.It has also given me an idea regarding DevOps for Data Management which would include data protection, recovery, security, intelligence and mobility when it comes to databases but also other data services we find in our environments today.I have always found that Pakt books and mostly authors provide a great human touch and perspective to the subject matter being covered.
Amazon Verified review Amazon
Sandor Szabo Jan 07, 2024
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I have bought this book as a means to get more information about how DevOps practices can be applied for everyday use in a corporate environment mostly concerning Databases, but also touching best practices, security, team build-out and much more.I was very happy with the content! It's a well built, step-by-step explanation of different steps, procedures, practices backed up with lots of demonstrable content as well. I especially loved the code segments that I could use effortlessly by slightly changing it to fit my needs to try out new settings or demonstrate for my team how the new capabilities work.An overwhelming amount of information - in a good way! - yet still so clearly being guided through the book. It's a must have and I encourage everyone to read it over and over again to discover all the important bits and pieces of how DevOps can (and should) be applied in practice!
Amazon Verified review Amazon
David Jambor Dec 30, 2023
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Amazon Verified review Amazon
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