Python for DevOps
by Chacko, Varghese;
English | 2025 | ISBN: 9365895391 | 648 pages | True EPUB | 6 MB
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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Links are Interchangeable - Single Extraction
rogress from Python fundamentals to advanced conceptsConstruct robust data pipelines and analytics projectsGain practical experience with real-world datasetsLearn data engineering with AWS and cloud technologiesExplore machine learning and AI applications in Python
