{"product_id":"9781806664238","title":"The Ultimate AI Guide for Linux Engineers : A Hands-On Guide to Agentic AI, LLMs, and Cloud-Native Automation for Linux Infrastructure Teams","description":"\u003cp\u003eLearn how to integrate AI into Linux environments with real-world automation, observability, and scalable deployment techniques for modern infrastructure teams\u003c\/p\u003e\n\n\u003cp\u003eKey Features\u003c\/p\u003e\n\n\u003cp\u003eApply AI to Linux, from core concepts to production-ready deployments at scale\n\u003cbr\u003eBuild intelligent automation using LLMs, RAG, and AI agents for monitoring, troubleshooting, and system administration\n\u003cbr\u003eDeploy secure, scalable AI workloads with Docker, Kubernetes, and cloud-native best practices\u003c\/p\u003e\n\n\u003cp\u003eBook DescriptionUnlock the power of artificial intelligence to transform Linux infrastructure and operations.\n\u003cbr\u003eThe Ultimate AI Guide for Linux Engineers is a practical, hands-on handbook for applying AI to real-world Linux systems. You will demystify AI, machine learning, and large language models (LLMs) in practice, prepare AI-ready Linux environments for CPU and GPU workloads, and work with containers and essential open-source frameworks such as PyTorch, Hugging Face Transformers, LangChain, and OpenVINO.\n\u003cbr\u003eMoving into real operational use cases, you will build AI agents and agentic workflows to automate system administration, integrate LLMs into monitoring and troubleshooting pipelines, and apply Retrieval-Augmented Generation (RAG) to query logs, documentation, and internal knowledge bases. You will also enhance observability and incident response with intelligent automation.\n\u003cbr\u003eFinally, you will learn how to deploy and scale AI services using Docker, Kubernetes, and cloud-native architectures, implement security and privacy guardrails, and design reliable AI-driven workflows for enterprise Linux environments.\n\u003cbr\u003eBy the end, you will have a practical framework to integrate AI into Linux workflows securely and at scale.What you will learn\u003c\/p\u003e\n\n\u003cp\u003eOptimize Linux kernels and GPUs for AI workloads\n\u003cbr\u003eOrchestrate LLM pipelines across distributed systems\n\u003cbr\u003eDesign agentic workflows for autonomous operations\n\u003cbr\u003eImplement RAG over logs and internal knowledge graphs\n\u003cbr\u003eEmbed AI into observability and incident triage\n\u003cbr\u003eDeploy scalable AI microservices on Kubernetes\n\u003cbr\u003eEnforce security, isolation, and model guardrails\u003c\/p\u003e\n\n\u003cp\u003eWho this book is forThis book is for Linux engineers, system administrators, DevOps professionals, SREs, and platform engineers who want to integrate AI into real-world infrastructure and operations. Prior hands-on experience with Linux, the command line, and basic system administration is expected. Some familiarity with containers (Docker), Kubernetes, and scripting (Bash or Python) would be helpful. Prior AI or machine learning knowledge is beneficial but not required, as core concepts are explained in practical Linux terms.\u003c\/p\u003e","brand":"Packt Publishing Limited","offers":[{"title":"Default Title","offer_id":48872051376363,"sku":"EB_CP0700_F05-01_SIMS","price":86.13,"currency_code":"SGD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0758\/4484\/5803\/files\/9781806664238-1.jpg?v=1785900889","url":"https:\/\/kinokuniya.com.sg\/ja\/products\/9781806664238","provider":"Books Kinokuniya Singapore","version":"1.0","type":"link"}