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portada AI-Powered DevOps Engineering: Practical AI Assistance for Reliable Operations
Type
Physical Book
Publisher
Author
Language
English
Pages
348
Format
Paperback
ISBN13
9798161560549

AI-Powered DevOps Engineering: Practical AI Assistance for Reliable Operations

Lourenço, João (Author) · Independently published · Paperback

AI-Powered DevOps Engineering: Practical AI Assistance for Reliable Operations - Lourenço, João

New Book Imported to South Africa
Delivery: 16 Nov - 20 Nov Shipping: 6 to 7 business days.
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Synopsis "AI-Powered DevOps Engineering: Practical AI Assistance for Reliable Operations"

AI assistance can help an engineer explain a failed deployment, review an infrastructure change, or search an operational runbook. Using that assistance responsibly requires a clear account of the evidence, the permissions involved, and the checks that must happen before a change reaches a service. AI-Powered DevOps Engineering gives working DevOps engineers, platform engineers, and SREs a practical method for building those checks into everyday work. João Lourenço takes the reader through language-model limitations, security and privacy, prompt and context design, and a reproducible environment for evaluating generated suggestions. The sixteen chapters then apply that method to Linux and Python automation, infrastructure as code, containers, delivery pipelines, observability, incident response, and reliability. Later chapters develop retrieval over operational knowledge, bounded agents with explicit tool permissions, and evaluations of quality, cost, and governance. A capstone brings these ideas together in a DevOps/SRE assistant. Worked examples and answered exercises show how to inspect assumptions, reject unsupported conclusions, and design independent tests. Ten laboratory worksheets use synthetic evidence and deterministic local checks; their companion code is supplied separately. The examples distinguish these local results from integrations that still need testing against live infrastructure and model providers. For readers already comfortable with source control, automation, and infrastructure, this book provides a disciplined foundation for adding AI assistance to engineering work while keeping operational decisions accountable.

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