Autonomous Networks: Using AI to Advance Operations in Sp and Enterprise Domains
Autonomous Networks: Using AI to Advance Operations in SP and Enterprise Domains is a practical, forward-looking guide to the next generation of network operations--where AI, automation, observability, and closed-loop control enable networks to operate with greater speed, scale, and resilience while reducing manual intervention.
As enterprise and service provider environments become increasingly complex, traditional reactive operations can no longer keep pace. This book explains how autonomous networking combines model-driven telemetry, distributed tracing, AIOps, automation frameworks, MLOps, and IT service management integration to create intelligent systems capable of sensing conditions, making decisions, and executing actions in real time.
Written for network engineers, architects, operations teams, and technology leaders, this vendor-agnostic guide provides a clear roadmap for evolving from basic automation initiatives to fully autonomous network operations. Readers will learn how to implement AI-driven operational models across both enterprise and service provider environments while addressing security, governance, compliance, and organizational transformation.
Through real-world case studies, architectural patterns, and industry-aligned frameworks, the authors demonstrate how narrow AI, generative AI, closed-loop automation, and predictive analytics can improve network reliability, operational efficiency, and service assurance at scale.
Whether you are modernizing existing infrastructure or building next-generation intelligent networks, this book delivers actionable strategies for designing, operating, and securing autonomous networking environments in an increasingly AI-driven world.
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