Azure Local Unleashed: Modernizing hybrid infrastructure with cloud-consistent management and governance (English Edition)
暫譯: Azure Local 解放：以雲端一致的管理與治理現代化混合基礎設施 (英文版)

Hybrid and edge computing have become essential for organizations that need cloud innovation with local control, compliance, resilience, low latency, and data sovereignty. Azure Local, together with Azure Arc, extends the Azure operating model to data centers, remote sites, and edge environments, enabling consistent management, security, and governance wherever workloads run.

This book provides a comprehensive introduction to designing, deploying, and operating Azure Local as part of a modern hybrid strategy. It starts with adaptive cloud foundations, then explores sovereignty and compliance, and the key decisions for installation and configuration. Readers will learn how Azure Local supports virtual machines, Kubernetes, AVD and modern applications, and how Azure Arc simplifies operations through unified management, patching, security, policy, monitoring, and reporting.

By the end of this book, IT leaders, architects, platform engineers, and cloud professionals will be able to evaluate when Azure Local is the right choice, design sustainable hybrid architectures, and operate distributed environments with confidence and control.

WHAT YOU WILL LEARN

● Understand Azure Local for hybrid and edge scenarios.

● Plan hardware, networking, storage, and deployment requirements.

● Deploy and configure Azure Local using practical guidance.

● Run VMs, Kubernetes, AVD, and AI workloads locally.

● Manage distributed environments consistently with Azure Arc.

● Explore edge AI and future hybrid cloud strategies.

WHO THIS BOOK IS FOR

This book is for IT leaders, cloud architects, infrastructure architects, platform engineers, system administrators, consultants, and technology decision-makers who design, deploy, or manage hybrid and edge environments. It is also valuable for professionals evaluating Azure Local, Azure Arc, cloud governance, modernization strategies, and distributed workload placement.