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Python for DevOps : learn ruthlessly effective automation

By: Contributor(s): Material type: TextTextPublication details: New Delhi : Shroff Publishers, ©2021Description: xx, 481 p. : ill. ; 24 cmISBN:
  • 9789352139583
Subject(s): DDC classification:
  • 005.133 23 GIF-P
LOC classification:
  • QA76.73.P98 G54 2020
Contents:
Python essentials for DevOps -- Automating files and the Filesystem -- Working with the command line -- Useful Linux utilities -- Package management -- Continuous integration and continuous deployment -- Monitoring and logging -- Pytest for DevOps -- Cloud computing -- Infrastructure as code -- Container technologies : Docker and Docker compose -- Container orchestration : Kubernetes -- Serverless technologies -- MLOps and machine learning engineering -- Data engineering -- DevOps war stories and interviews. 1. Python Essentials for DevOps 2. Automating Files and the Filesystem 3. Working with the Command Line 4. Useful Linux Utilities 5. Package Management 6. Continuous Integration and Continuous Deployment 7. Monitoring and Logging 8. Pytest for DevOps 9. Cloud Computing 10. Infrastructure as Code 11. Container Technologies: Docker and Docker Compose 12. Container Orchestration: Kubernetes 13. Serverless Technologies 14. MLOps and Machine learning Engineering 15. Data Engineering 16. DevOps War Stories and Interviews
Summary: "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."--
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
Books Books IIITD General Stacks Computer Science and Engineering 005.133 GIF-P (Browse shelf(Opens below)) Available 012186
Total holds: 0

Includes index.

Includes bibliographical references and index.

Python essentials for DevOps -- Automating files and the Filesystem -- Working with the command line -- Useful Linux utilities -- Package management -- Continuous integration and continuous deployment -- Monitoring and logging -- Pytest for DevOps -- Cloud computing -- Infrastructure as code -- Container technologies : Docker and Docker compose -- Container orchestration : Kubernetes -- Serverless technologies -- MLOps and machine learning engineering -- Data engineering -- DevOps war stories and interviews. 1. Python Essentials for DevOps 2. Automating Files and the Filesystem 3. Working with the Command Line 4. Useful Linux Utilities 5. Package Management 6. Continuous Integration and Continuous Deployment 7. Monitoring and Logging 8. Pytest for DevOps 9. Cloud Computing 10. Infrastructure as Code 11. Container Technologies: Docker and Docker Compose 12. Container Orchestration: Kubernetes 13. Serverless Technologies 14. MLOps and Machine learning Engineering 15. Data Engineering 16. DevOps War Stories and Interviews

"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."--

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