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Hands-On Python for DevOps

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

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781835081167
Length 220 pages
Edition 1st Edition
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Author (1):
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Ankur Roy Ankur Roy
Author Profile Icon Ankur Roy
Ankur Roy
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Table of Contents (19) Chapters Close

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 18. Other Books You May Enjoy

Advanced monitoring tools

The purpose behind monitoring has always been to make sure that the things you said were working are still working. And it is often the case that they won’t be. It could be your fault or not; the concept of fault gets in the way of solving the problem. The proper monitoring of your workloads provides the path to more easily solving your problems.

The simplest workloads can be monitored and the reactions to the information received can be automated so that you don’t even have to be involved most of the time when it comes to dealing with something going wrong. In more complex workloads, it is still important to keep up monitoring for faster reaction times to any situation, as well as to get more information on the situation in real time.

Often, your solution, as it gets more complex, starts using more tools. More tools and services means the requirement for more monitoring and also more complex monitoring. If your monitoring comes from multiple...

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