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Hands-On Python for DevOps
Hands-On Python for DevOps

Hands-On Python for DevOps: Leverage Python's native libraries to streamline your workflow and save time with automation

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Hands-On Python for DevOps

Introducing DevOps Principles

Obey the principles without being bound by them.

– Bruce Lee

DevOps has numerous definitions, most of which are focused on culture and procedure. If you’ve gotten to the point where you have purchased this book as a part of your journey in the DevOps field, you have probably heard at least about 100 of these definitions. Since this is a book that focuses more on the hands-on, on-the-ground aspect of DevOps, we’ll keep those abstractions and definitions to a minimum, or rather, explain them through actions rather than words whenever possible.

However, since this is a DevOps book, I am obliged to take a shot at this:

DevOps is a series of principles and practices that aims to set a culture that supports the automation of repetitive work and continuous delivery of a product while integrating the software development and IT operation aspects of product delivery.

Not bad. It’s probably incomplete, but that’s...

Exploring automation

We’re going to start with why automation is needed in life in general and then we’ll move toward a more specific definition that relates to DevOps and other tech team activities. Automation is for the lazy, but many do not realize how hard you must work and how much you must study to truly be lazy. To achieve automation, it requires a mindset, an attitude, a frustration with present circumstances.

Automation and how it relates to the world

In Tim Ferris’s book The 4-Hour Workweek, he has an entire section dedicated to automating the workflow which emphasizes the fact that the principle of automation helps you clean up your life and remove or automate any unnecessary tasks or distractions. DevOps hopes to do something similar but in your professional life. Automation is the primary basis that frees up our time to do other things we want.

One of the things mankind has always tried to automate even further is transportation. We have evolved...

Understanding logging and monitoring

Switching to a more grounded topic, one of the driving principles of DevOps is logging and monitoring instances, endpoints, services, and whatever else you can track and trace. This is necessary because regardless of whatever you do, how clean your code is, or how good your server configuration is, something will fail, go wrong, or just inexplicably stop working altogether. This will happen. It’s a fact of life. It is in fact, Murphy’s law:

Anything that can go wrong will go wrong at the worst possible time.

Familiarizing yourself with this truth is important for a DevOps engineer. Once you have acknowledged it, then you can deal with it. Logging and monitoring come in because when something does go wrong, you need the appropriate data to respond to that event, sometimes automatically.

The rest of this section has been laid out in terms of logging, monitoring, and alerts. Each one of these aspects plays an important role in...

Incident and event response

I’m going to put Murphy’s Law here again because I cannot state this enough:

Anything that can go wrong will go wrong at the worst possible time.

Dealing with incident and event response involves either a lot of work or zero work. It depends on how prepared you are and how unique the incident or event is. Incident and event response covers a lot of ground from automation and cost control, to cybersecurity.

How a DevOps engineer responds to an event depends on a great number of things. In terms of dealing with clients and customers, a Service Level Objective (SLO) is used when a response is necessary. However, this is largely on production environments and requires the definition of a Service Level Indicator (SLI). It also involves the creation of an error budget to determine the right time to add new features and what the right time is to work on the maintenance of a system. Lower-priority development environments are used to stress...

Understanding high availability

I’m not going to state Murphy’s Law a third time, but understand that it applies here as well. Things will go wrong and they will fall apart. Never forget that. One of the reasons DevOps as a concept and culture became so popular was that its techniques delivered a highly available product with very little downtime, maintenance time, and vulnerability to app-breaking errors.

One of the reasons DevOps succeeds in its mission for high availability is the ability to understand failure, react to failure, and recover from failure. Here’s a famous quote from Werner Vogel, the CTO of Amazon:

Everything fails, all the time.

This is, in fact, the foundation of the best practice guides, tutorials, and documentation that AWS makes for DevOps operations, and it’s true. Sometimes, things fail because of a mistake that has been made. Sometimes, they fail because of circumstances that are completely out of our control, and sometimes...

Delving into infrastructure as a code

Finally, in a book about Python, we get to a section about code. So far, I’ve given you a lot of information about what needs to be accomplished but to accomplish the things we want especially in this book, we must have a method, a tool, a weapon, i.e., code.

Now the word “code” scares a lot of people in the tech industry, even developers. It’s weird being afraid of the thing that is under everything you work with. But that’s the reality sometimes. If you, dear reader, are such a person, first off, it’s a brave thing to purchase this book, and secondly, all you are doing is denying yourself the opportunity to solve all the problems you have in the world. Seriously.

Now, the reason is that code is the weapon of choice in almost every situation. It is the solution to all your automation problems, monitoring problems, response problems, contract problems, and maybe other problems that you may have that...

Summary

The concept of DevOps is exciting, vast, and has room to get creative. It is a discipline where the world is essentially at your command. Effective DevOps requires effective structure and adaptation of that structure to a challenge as we learned in our Exploring automation section.

But remember, anything that can go wrong will go wrong, so plan for success but prepare for the fact that failure is a common occurrence. In such cases of failure – as we learned in the sections about monitoring and event response – the ability to recover is what matters, and the speed of that recovery also matters quite often. If an incident to be recovered from is new, it must be reported and understood so that such incidents can be mitigated in the future.

And lastly, as we covered in Delving into infrastructure as a code, code is your friend. Be nice to your friends and play with them. You’ll learn how to in this book.

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Key benefits

  • Integrate Python into DevOps for streamlined workflows, task automation, and improved collaboration
  • Combine the principles of Python and DevOps into a unified approach for problem solving
  • Learn about Python’s role in Infrastructure as Code (IaC), MLOps, networking, and other domains
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

Python stands out as a powerhouse in DevOps, boasting unparalleled libraries and support, which makes it the preferred programming language for problem solvers worldwide. This book will help you understand the true flexibility of Python, demonstrating how it can be integrated into incredibly useful DevOps workflows and workloads, through practical examples. You'll start by understanding the symbiotic relation between Python and DevOps philosophies and then explore the applications of Python for provisioning and manipulating VMs and other cloud resources to facilitate DevOps activities. With illustrated examples, you’ll become familiar with automating DevOps tasks and learn where and how Python can be used to enhance CI/CD pipelines. Further, the book highlights Python’s role in the Infrastructure as Code (IaC) process development, including its connections with tools like Ansible, SaltStack, and Terraform. The concluding chapters cover advanced concepts such as MLOps, DataOps, and Python’s integration with generative AI, offering a glimpse into the areas of monitoring, logging, Kubernetes, and more. By the end of this book, you’ll know how to leverage Python in your DevOps-based workloads to make your life easier and save time.

Who is this book for?

This book is for IT professionals venturing into DevOps, particularly programmers seeking to apply their existing programming knowledge to excel in this field. For DevOps professionals without a coding background, this book serves as a resource to enhance their understanding of development practices and communicate more effectively with developers. Solutions architects, programmers, and anyone regularly working with DevOps solutions and Python will also benefit from this hands-on guide.

What you will learn

  • Implement DevOps practices and principles using Python
  • Enhance your DevOps workloads with Python
  • Create Python-based DevOps solutions to improve your workload efficiency
  • Understand DevOps objectives and the mindset needed to achieve them
  • Use Python to automate DevOps tasks and increase productivity
  • Explore the concepts of DevSecOps, MLOps, DataOps, and more
  • Use Python for containerized workloads in Docker and Kubernetes

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 15, 2024
Length: 220 pages
Edition : 1st
Language : English
ISBN-13 : 9781835081495
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Product Details

Publication date : Mar 15, 2024
Length: 220 pages
Edition : 1st
Language : English
ISBN-13 : 9781835081495
Languages :
Concepts :

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Table of Contents

18 Chapters
Part 1: Introduction to DevOps and role of Python in DevOps Chevron down icon Chevron up icon
Chapter 1: Introducing DevOps Principles Chevron down icon Chevron up icon
Chapter 2: Talking about Python Chevron down icon Chevron up icon
Chapter 3: The Simplest Ways to Start Using DevOps in Python Immediately Chevron down icon Chevron up icon
Chapter 4: Provisioning Resources Chevron down icon Chevron up icon
Part 2: Sample Implementations of Python in DevOps Chevron down icon Chevron up icon
Chapter 5: Manipulating Resources Chevron down icon Chevron up icon
Chapter 6: Security and DevSecOps with Python Chevron down icon Chevron up icon
Chapter 7: Automating Tasks Chevron down icon Chevron up icon
Chapter 8: Understanding Event-Driven Architecture Chevron down icon Chevron up icon
Chapter 9: Using Python for CI/CD Pipelines Chevron down icon Chevron up icon
Part 3: Let’s Go Further, Let’s Build Bigger Chevron down icon Chevron up icon
Chapter 10: Common DevOps Use Cases in Some of the Biggest Companies in the World Chevron down icon Chevron up icon
Chapter 11: MLOps and DataOps Chevron down icon Chevron up icon
Chapter 12: How Python Integrates with IaC Concepts Chevron down icon Chevron up icon
Chapter 13: The Tools to Take Your DevOps to the Next Level Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

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sukul Oct 27, 2024
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
Not a good book for DevOps. Covers very little and at the end you feel incomplete.
Amazon Verified review Amazon
Thomas M. Apr 04, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I've found this book to be an essential guide for IT professionals looking to leverage Python's capabilities in DevOps. The book provides a comprehensive and practical approach to integrating Python into DevOps workflows. I’ve read other resources on the topic and, IMO, Roy’s book is unparalleled in terms of its holistic view of DevOps philosophies along with its modern approach to using Python for DevOps.The book begins by explaining the symbiotic relationship between Python and DevOps philosophies, setting a solid foundation for understanding the role of Python in streamlining DevOps processes. This helped me understand the ‘why’ behind architectural decisions later in the book, such as provisioning and manipulating cloud resources, automating DevOps tasks, and enhancing CI/CD pipelines – all of which are super practical and aligned with modern best practices I’ve seen in the field.One of the strengths of this book is its focus on practical examples and real-world scenarios. Roy provides step-by-step instructions and code snippets, making it easy for readers to apply the concepts discussed in the book to their own work. The book covers advanced topics such as DevSecOps, MLOps, DataOps, and Python's integration with generative AI, offering a glimpse into the cutting-edge applications of DevOps. Roy is definitely at the frontier of the field and his command of the topic comes through.The author has done an excellent job in presenting complex concepts in a clear and concise manner. The book is well-organized and easy to navigate, with each chapter building upon the previous one. While the topics are pretty technical, the writing style tends to be super engaging and informative, making it a pleasure to read.IMO Hands On Python for DevOps is a great read for folks looking to enhance their DevOps skills with modern practices. Highly recommended!
Amazon Verified review Amazon
Shanthababu Pandian Mar 26, 2024
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
The book consists of three parts and thirteen chapters as sub-folders. The Author’s statement, “Leverage Python's native libraries to streamline your workflow and save time with automation”, is perfectly reflected in the book without any questions.Part 1:Introducing DevOps Principles: The book introduces DevOps Principles, talks about Python, and connects both technologies in the simplest ways, starting with API calls and networking with classic examples.The Provisioning Resources chapter is a major breakthrough in this book. Here, the Author discusses Python SDKs, giving a detailed walkthrough of Creating an AWS EC2 instance with Python’s boto3 library, Autoscaling, Docker, and Kubernetes administration with crystal-clear steps and required screenshots.Part 2: Sample Implementations of Python in DevOps: I would say this is a core part of this book. The Author covers sample implementations of common DevOps use cases using Python. The book also covers how to Manipulate Resources—event-based resource adjustment and edge location-based resource sharing—and how to Analyze data—live and historical data.We know that Security and DevSecOps play vital roles in the industry. The Author briefly notes this part with Python, such as securing API keys and passwords, extracting and obfuscating PII details, and monitoring and responding to incidents using Python in the AWS environment. He also discusses the process of validating and verifying container images with Binary Authorization.Automating tasks is a significant task in DevOps, so the Author has shared his thoughts on this topic, including server maintenance, container creation, and a playbook using Google Forms. Following my favourite topic, event-driven architecture, the Author’s experience is excellently reflected in this specific chapter, which includes Kafka with Python and Exploring loosely coupled architecture.Another important activity in CI/CD Pipelines in DevOps is that the Author provides excellent content for readers right from the origins and philosophy of CI/CD and Python CI/CD essentials—automating a primary task and Performing rollback are significant milestones in this book.Part 3: Let’s Go Further, Let’s Build Bigger: The Author brings the DevOps and Python skills and knowledge to the next level in this part with common DevOps use cases in some of the biggest companies worldwide: AWS use cases—Samsung electronics, Azure Use Cases—Intertech, and Google Cloud use cases—MLB and AFL.One step further, how do MLOps and DataOps differ from regular DevOps, with DataOps' use case—from JSON concatenation—and MLOps' use case—overclocking a GPU?As we know, IaC is growing rapidly. The Author details how Python integrates with IaC concepts, including automation and customization with Python’s salt library, how Ansible works, and the Python code behind it.The particular chapter “The Tools to Take Your DevOps to the Next Level” is magic with advanced automation tools - AWS Step Functions, Advanced monitoring tools – Grafana, and How to work on advanced event response strategies.Overall … I can give 4.5/5.0 for this. Indeed, the author's extraordinary effort is much appreciated.-Shanthababu PandianAI and Data Architect | Scrum Master | National and International Speaker | Blogger | Author
Amazon Verified review Amazon
Mr S Paynter Mar 25, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
"Python for DevOps" is an indispensable guide that seamlessly integrates the power of Python into the world of DevOps, revolutionizing workflows, automating tasks, and fostering improved collaboration. With its comprehensive approach, this book expertly combines the principles of Python programming with the core tenets of DevOps philosophy, making it a must-have resource for both seasoned professionals and newcomers alike.One of the key strengths of this book is its practical approach, offering readers a hands-on journey through the symbiotic relationship between Python and DevOps. From provisioning and manipulating cloud resources to automating tasks and enhancing CI/CD pipelines, each concept is illustrated with clear examples, ensuring a thorough understanding of how Python can be leveraged to optimize DevOps workflows.The book doesn't just stop at basic automation tasks; it delves into advanced topics such as DevSecOps, MLOps, and DataOps, showcasing Python's versatility across various domains. Whether you're interested in Infrastructure as Code (IaC) development or exploring Python's integration with containerized workloads in Docker and Kubernetes, this book covers it all, providing valuable insights and practical techniques to elevate your DevOps game.What sets this book apart is its accessibility. While it caters to IT professionals venturing into DevOps, it also serves as a valuable resource for programmers looking to apply their coding expertise in the DevOps realm. Even for DevOps professionals without a coding background, this book offers a bridge to understanding development practices and fostering effective communication with developers.
Amazon Verified review Amazon
Ashar Neyaz Mar 24, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book is an excellent resource if you're an IT professional wanting to use Python in DevOps processes. It is helpful for both programmers and DevOps specialists because it covers essential subjects like automation, CI/CD pipelines, and security. The information is simple and provides valuable insights into contemporary DevOps principles. It's an excellent tool for improving Python-based DevOps abilities. The book is understandable to novices and seasoned experts through its step-by-step methodology and practical examples. This book is fantastic for incorporating Python into DevOps for effective local and cloud systems orchestration.
Amazon Verified review Amazon
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