Python for Devops: Learn Ruthlessly Effective Automation Paperback
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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.
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What Stands Out
Product Details
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Pub date | 2019-12-31 |
| Pages | 503 |
| Reading level | Professional and Scholarly |
| Subgenre | Computers |
| Edition | 1st Edition |
| Publisher | O'Reilly Media |
| Original languages | English |
| Language | English |
| Edu focus | Technology |
| Is collectible | N |
| Binding type | Perfect Binding |
| Assembled product height | 9.17 in (23.3 cm) |
| Assembled product weight | 1.76 lb (800 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
-
Aspiring DevOps Engineers
Ideal for those starting a career in DevOps, providing essential automation skills with Python.
-
Experienced Developers
Great for software developers looking to expand their skillset into DevOps and automation practices.
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IT Operations Teams
Useful for IT professionals wanting to improve efficiency through automation and effective scripting techniques.
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Complete Beginners
Not suitable for absolute beginners with no prior programming or DevOps knowledge, as it may overwhelm them.
Product Description
Python for Devops: Learn Ruthlessly Effective Automation Paperback
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Noah Gift; Kennedy Behrman; Alfredo Deza All Books Editorial Review
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Pros
- Clear and concise explanations
- Practical examples for real-world use
- Focus on automation techniques
- Well-structured learning approach
- Suitable for all skill levels
Cons
- Some advanced topics may need additional resources.
Product Price History
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Features & Benefits
- Learn to use Python for everyday Linux systems administration.
- Master today's most useful DevOps tools: Docker, Kubernetes, and Terraform.
- Discover effective automation techniques for various tasks.
- Gain insights into cloud computing and infrastructure as code.
- Understand machine learning operations from a DevOps perspective.
- Develop skills in monitoring, load-testing, and operationalizing software.
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