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

Product type Paperback

Published in Mar 2024

Publisher Packt

ISBN-13 9781835081167

Length 220 pages

Edition 1st Edition

Languages

Python

Tools

Combine

Concepts

DevOps

Author (1):

Ankur Roy

View More author details

Table of Contents (19) Chapters

Preface

1. Part 1: Introduction to DevOps and role of Python in DevOps

2. Chapter 1: Introducing DevOps Principles FREE CHAPTER

3. Chapter 2: Talking about Python

4. Chapter 3: The Simplest Ways to Start Using DevOps in Python Immediately

5. Chapter 4: Provisioning Resources

6. Part 2: Sample Implementations of Python in DevOps

7. Chapter 5: Manipulating Resources

8. Chapter 6: Security and DevSecOps with Python

9. Chapter 7: Automating Tasks

10. Chapter 8: Understanding Event-Driven Architecture

11. Chapter 9: Using Python for CI/CD Pipelines

12. Part 3: Let’s Go Further, Let’s Build Bigger

13. Chapter 10: Common DevOps Use Cases in Some of the Biggest Companies in the World

14. Chapter 11: MLOps and DataOps

15. Chapter 12: How Python Integrates with IaC Concepts

16. Chapter 13: The Tools to Take Your DevOps to the Next Level

17. Index

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What Python offers DevOps

In the previous section, we focused on the principles of Python. Now, we are going to look into what following those principles offers DevOps as a practice and DevOps engineers in general. The principles behind DevOps and Python are more similar than they are different. They both share an emphasis on flexibility, automation, and conciseness. This makes Python and DevOps a perfect pairing in the field of DevOps. Even for DevOps professionals who may not have the sharpest coding skills, Python is easy to pick up, easy to use, and can be integrated with practically every tool and platform because almost all these platforms have native support and libraries in Python.

I previously stated that the reason that Python is so pervasive in DevOps is that it handles data that resides between curly brackets ({}) better than almost any other language. The offerings of Python for DevOps are numerous and will be covered in further detail in future chapters. Right now...