Linux Systems Architecture in the AI Era: Engineering the Linux Operating System from Filesystem and Kernel Fundamentals to Cloud Infrastructure
Format:
Kindle
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0.76 kg
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Amazon
USA
- Modern infrastructure runs on Linux — and increasingly, it runs with AI assistance.From cloud-native platforms and container orchestration systems to production clusters and intelligent automation pipelines, Linux remains the deterministic substrate of modern computing. Yet many engineers learn Linux as a collection of commands rather than as a coherent architectural system.Linux Systems Architecture in the AI Era reframes Linux as it truly is: a layered, enforceable, observable, and governable system architecture. This book connects kernel-level mechanics to cloud-scale infrastructure and shows how classical operating system principles make safe AI-assisted operations possible.You will move from core primitives — processes, memory management, scheduling, filesystems, networking, and privilege enforcement — into modern operational models such as immutability, infrastructure as code, structured observability, disciplined troubleshooting, and bounded AI agents.What You Will LearnHow Linux kernel primitives create deterministic control over compute, storage, and networkingWhy mutable systems drift — and how immutable design improves reliabilityHow to separate configuration intent from runtime state for operational clarityHow logging, monitoring, and structured observability enable disciplined troubleshootingWhy human-only operations fail at scale — and how automation must be governedHow to integrate AI as a diagnostic and automation assistant without surrendering controlHow to design bounded AI agents with least privilege, auditability, and rollback safetyHow to evolve from Linux user to operator to systems architectWhat This Book IsAn architectural guide to understanding Linux as a systems foundationA bridge between kernel fundamentals and cloud-scale infrastructureA disciplined approach to automation, reproducibility, and governanceA practical framework for integrating AI as a diagnostic and automation assistantA progression from user → operator → architect in modern Linux environmentsWhat This Book Is NotNot a beginner Linux command referenceNot a distribution-specific tutorialNot a DevOps tools crash courseNot an AI hype book detached from operational realityNot a collection of shortcuts without architectural reasoningWho This Book Is ForInfrastructure engineers and DevOps practitionersSite Reliability Engineers (SREs)Cloud and platform architectsSecurity-focused systems engineersTechnical leaders designing scalable Linux-based systemsExperienced practitioners ready to move beyond command fluencyIf you already understand basic Linux usage and want to reason about systems at scale — this book is for you.Who This Book May Not Be ForReaders looking for step-by-step beginner tutorialsThose seeking distribution-specific installation guidesReaders wanting quick command cheatsheets without architectural depthAs AI tools begin generating scripts, correlating logs, and proposing remediation actions, engineering discipline becomes more important — not less. This book demonstrates how to integrate AI into Linux-based workflows while preserving privilege boundaries, auditability, reproducibility, and deterministic rollback.If you want to design scalable Linux infrastructure, govern automation safely, and integrate AI without surrendering architectural control, this book provides the structured foundation required to lead in the intelligent era.
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