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
Not a good book for DevOps. Covers very little and at the end you feel incomplete.
Amazon Verified review
Thomas M.Apr 04, 2024
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
Shanthababu PandianMar 26, 2024
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
Mr S PaynterMar 25, 2024
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
Ashar NeyazMar 24, 2024
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.
Krishnendu Roy is an associate professor of computer science at Valdosta State University. Prior to joining VSU, Krishnendu completed his PhD. and M.S. in computer engineering at Louisiana State University, Baton Rouge, LA in 2009 and 2005, respectively. As an MIT App Inventor Master Trainer, Krishnendu taught computing using App Inventor in summer camps for middle and high school students and in CS0 courses at his university. He has conducted in-person App Inventor workshops for teachers, including Google CS4HS and the University of Massachusetts at Boston's BATEC Summer Institute. He has also organized online App Inventor workshops for teachers who were involved in AAUW's Tech Trek camps and mentored national winning teams of Verizon's Innovative App Challenge.
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