Python for Devops: Learn Ruthlessly Effective Automation

by Noah Gift, Kennedy Behrman, Alfredo Deza

Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today's most useful DevOps tools, including Docker, Kubernetes, and Terraform.

Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you'll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to "get stuff done" in Python? This is your guide.


Python foundations, including a brief introduction to the language
How to automate text, write command-line tools, and automate the filesystem
Linux utilities, package management, build systems, monitoring and instrumentation, and automated testing
Cloud computing, infrastructure as code, Kubernetes, and serverless
Machine learning operations and data engineering from a DevOps perspective
Building, deploying, and operationalizing a machine learning project

Genres: Programming, Technology, Computer Science, Coding, Software, Nonfiction, Technical

506 pages, Paperback

Published December 31, 2019

About the author

Noah Gift is lecturer and consultant at UC Davis Graduate School of Management in the MSBA program, Northwestern's Master of Data Science program, and UC Berkeley Data Science program. He is also the founder of Pragmatic AI Labs. At Pragmatic AI Labs he provides consulting and training on Machine Learning and AI, and also develops AI SaaS products. At UC Davis, he is teaching graduate machine learning and consulting on Machine Learning and Cloud Architecture for students and faculty. He has published close to 100 technical publications including two books on subjects ranging from Pragmatic AI: An Introduction to Cloud-Based Machine Learning, First Edition to DevOps. He is also a certified AWS Solutions Architect and has an MBA from UC Davis, a M.S. in Computer Information Systems from Cal State Los Angeles, and a B.S. in Nutritional Science from Cal Poly San Luis Obispo. Professionally, Noah has approximately 20 years’ experience programming in Python and is a member of the Python Software Foundation. He has worked in roles ranging from CTO, General Manager, Consulting CTO and Cloud Architect. This experience has been with a wide variety of companies including ABC, Caltech, Sony Imageworks, Disney Feature Animation, Weta Digital, AT&T, Turner Studios and Linden Lab. In the last ten years, he has been responsible for shipping many new products at multiple companies that generated millions of dollars of revenue and had global scale. Currently he is consulting startups and other companies, on Machine Learning, Cloud Architecture and CTO level consulting via Pragmatic AI Labs

Reviews

[Nickolai · Rating 3 out of 5]

В книге есть парочку хороших идей, но, в целом, она достаточно неудачная. Я повелся на многообещающее оглавление, однако автор надергал в каждую из глав весьма пестрый набор не всегда связанных между собой данных и привел не самые удачные примеры кода. Некоторые предлагаемые им модули, на первый взгляд, хороши, но при более детальном изучении замечаешь, что эти проекты почти не развиваются и не имеют большой поддержки. Поэтому советовать их для использования в производстве как-то не совсем целесообразно.