Devops in Python: Infrastructure as Python

Devops in Python: Infrastructure as Python

作者: Zadka Moshe
出版社: Apress
出版在: 2019-06-04
ISBN-13: 9781484244326
ISBN-10: 148424432X
裝訂格式: Quality Paper - also called trade paper
總頁數: 110 頁





內容描述


Explore and apply best practices for efficient application deployment. This book draws upon author Moshe Zadka's years of Dev Ops experience and focuses on the parts of Python, and the Python ecosystem, that are relevant for DevOps engineers.
You'll start by writing command-line scripts and automating simple DevOps-style tasks. You'll then move on to more advanced cases, like using Jupyter as an auditable remote-control panel, and writing Ansible and Salt extensions. This work also covers how to use the AWS API to manage cloud infrastructure, and how to manage Python programs and environments on remote machines.
Python was invented as a systems management language for distributed operating systems, which makes it an ideal tool for DevOps. ​Assuming a basic understanding of Python concepts, this book is perfect for engineers who want to move from operations/system administration into coding.
 
What You'll Learn

Use third party packages and create new packages
Create operating system management and automation code in Python
Write testable code, and testing best practices
Work with REST APIs for web clients

Who This Book Is For
Junior or intermediate sysadmin who has picked up some bash and Python basics.


作者介紹


Moshe Zadka has been part of the open source community since 1995 and has been involved with DevOps since before the term became mainstream. One of two collaborators in the Facebook bootcamp Python class, he made his first core Python contributions in 1998, and is a founding member of the Twisted open source project. He has also given tutorials and talks at several recent PyCon conferences and contributed to Expert Twisted (Apress, 2019).
 
 
 
 
 
ted at "Production Engineers," which is what Facebook calls DevOps. Moshe has been part of the open source community since 1995, made his first core Python contributions in 1998 and is a founding member of the Twisted open source project. He has given tutorials or talks at several recent PyCon conferences and contributed to Expert Twisted (Apress, 2019)
 
 
ted at "Production Engineers," which is what Facebook calls DevOps. Moshe has been part of the open source community since 1995, made his first core Python contributions in 1998 and is a founding member of the Twisted open source project. He has given tutorials or talks at several recent PyCon conferences and contributed to Expert Twisted (Apress, 2019)
 
ted at "Production Engineers," which is what Facebook calls DevOps. Moshe has been part of the open source community since 1995, made his first core Python contributions in 1998 and is a founding member of the Twisted open source project. He has given tutorials or talks at several recent PyCon conferences and contributed to Expert Twisted (Apress, 2019)
 
ted at "Production Engineers," which is what Facebook calls DevOps. Moshe has been part of the open source community since 1995, made his first core Python contributions in 1998 and is a founding member of the Twisted open source project. He has given tutorials or talks at several recent PyCon conferences and contributed to Expert Twisted (Apress, 2019)
 
ted at "Production Engineers," which is what Facebook calls DevOps. Moshe has been part of the open source community since 1995, made his first core Python contributions in 1998 and is a founding member of the Twisted open source project. He has given tutorials or talks at several recent PyCon conferences and contributed to Expert Twisted (Apress, 2019)
 
ted at "Production Engineers," which is what Facebook calls DevOps. Moshe has been part of the open source community since 1995, made his first core Python contributions in 1998 and is a founding member of the Twisted open source project. He has given tutorials or talks at several recent PyCon conferences and contributed to Expert Twisted (Apress, 2019)




相關書籍

機器學習即服務:將 Python 機器學習創意快速轉變為雲端 Web 應用程序 (Monetizing Machine Learning: Quickly Turn Python ML Ideas into Web Applications on the Serverless Cloud)

作者 (美)曼紐爾·阿米納特吉(Manuel Amunategui) (美)邁赫迪·洛佩伊(Mehdi Roopaei)

2019-06-04

深度學習之美 : AI時代的數據處理與最佳實踐

作者 張玉宏

2019-06-04

Hands-On Meta Learning with Python: Meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow (Paperback)

作者 Sudharsan Ravichandiran

2019-06-04