Python for DevOps: Master automation, CI/CD pipelines, and containerization with Python DevOps strategies (English Edition)

· BPB Publications
Ebook
648
Pages

About this ebook

DESCRIPTION 

Python has emerged as a powerhouse for DevOps, enabling efficient automation across various stages of software development and deployment. This book bridges the gap between Python programming and DevOps practices, providing a practical guide for automating infrastructure, workflows, and processes, empowering you to streamline your development lifecycle.  


This book begins with foundational Python concepts and their application in Linux system administration and data handling. Progressing through command line tool development using argparse and Click, package management with pip, Pipenv, and Docker, you will explore automating cloud infrastructure with AWS, GCP, Azure, and Kubernetes. The book covers configuration management with Ansible, Chef, and Puppet, and CI/CD pipelines using Jenkins, GitLab, and GitHub. You will also learn monitoring with Prometheus, Grafana, and OpenTelemetry, MLOps with Kubeflow and MLflow, serverless architecture using AWS Lambda, Azure Functions and Google Cloud Functions, and security automation with DevSecOps practices. The real-world project in this book will ensure the practical application of your learning. 


By mastering the techniques within this guide, you will gain the expertise to automate complex DevOps workflows with Python, enhancing your productivity and ensuring robust and scalable deployments, making you a highly competent DevOps professional.


WHAT YOU WILL LEARN

● Automate DevOps tasks using Python for efficiency and scalability.

● Implement infrastructure as code (IaC) with Python, Terraform, and Ansible.

● Orchestrate containers with Python, Docker, Kubernetes, and Helm charts.

● Manage cloud infrastructure on AWS, Azure, and GCP using Python.

● Enhance security, monitoring, and compliance with Python automation tools.

● Monitor with Prometheus/Grafana/OpenTelemetry, implement MLOps using Kubeflow/MLflow, and deploy serverless architecture.

● Apply real-world project skills, and integrate diverse DevOps automations using Python.

● Ensure robust code quality, apply design patterns, secure secrets, and scale script optimization.


WHO THIS BOOK IS FOR

This book is for DevOps engineers, system administrators, software developers, students, and IT professionals seeking to automate infrastructure, deployments, and cloud management using Python. Familiarity with Python, Linux commands, and  DevOps concepts is beneficial, but the book is designed to provide guidance to all.


TABLE OF CONTENTS

1. Introduction to Python and DevOps

2. Python for Linux System Administration

3. Automating Text and Data with Python

4. Building and Automating Command-line Tools

5. Package Management and Environment Isolation

6. Automating System Administration Tasks

7. Networking and Cloud Automation

8. Container Orchestration with Kubernetes

9.  Configuration Management Automation

10. Continuous Integration and Continuous Deployment

11. Monitoring, Instrumentation, and Logging

12. Implementing MLOps

13. Serverless Architecture with Python

14. Security Automation and Compliance

15. Best Practices and Patterns in Automating with Python

16. Deploying a Blog in Microservices Architecture



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About the author

Varghese Chacko, an experienced technology leader, has a proven track record of leading transformational and innovative solutions across industries. In his current role as director of technology at Nuvento Inc, he spearheads the transformation of customer accounts from proof-of-concept experiments to long-term strategic partnerships, overseeing many development teams and the complete life cycle of the software delivery process. Varghese also has previous experience serving as a key executive at well-respected organizations, including Atemon, Nuventure, Hubspire, and CyberSurfers, where he has continuously pushed for innovative technology solutions while fostering business growth.


Varghese is a current DBA candidate in emerging technologies, with a focus on the study of generative AI, at Golden Gate University, San Francisco, California, USA. Academically, he is currently dedicated to leveraging artificial  intelligence (AI), retrieval-augmented generation (RAG), and generative AI (GenAI) to disrupt businesses and software development. Always looking to adopt the latest development tools and practices, Varghese regularly explores solutions on using AI with automation, DevOps, and other software delivery pipelines.


He was also on the Board of Studies of the Sahrdaya College of Engineering and Technology (Autonomous), Thrissur, Kerala as industry representative, helping to shape the academic syllabus structured around industry needs, alongside his corporate commitments. He draws on both this learning and his professional experience in his LinkedIn newsletter, also JotLore, where he tracks new trends and ideas in information technology.


He holds an MCA degree from Mahatma Gandhi University and a BSc in Physics from the University of Kerala, which has laid the groundwork for a strong career.


Expert in AI, GenAI, Python, DevOps, Linux administration, and Agile practices, Varghese strives to remain the thought leader in software development, automation, and emerging technologies. He is a technology enthusiast, who blogs on the side, mentors young professionals, and keeps his nose to the ground on the path of innovation.

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