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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Stefan-Alexandru Manza, CCIE No. 15687, is a Distinguished Architect in the office of the CTO at Cisco Systems. In his current role, he focuses on strategic adoption of new technology trends such as observability, automation, and AI within Cisco and by Cisco’s key enterprise and SP customers.
Over the years Stefan has specialized in leading large and complex technology transformations with customers within the EMEA region, covering a diverse set of technical domains like licensed radio access, IP transport, private data center, and Mobile Packet Core. His efforts include ensuring the associated process and people skills evolutions are properly executed to ensure the successful adoption of the new technology.
Stefan has a PhD in systems engineering from The University Politehnica of Bucharest and an MBA from Vlerick Business School in Leuven; he also has completed postgraduate studies in big data and analytics at KU Leuven and has an active C-level presence at international forums such as Cisco Live, Mobile World Congress, and TM Forum DTW.
Josh Halley, CCIEx3 No. 11924, is a Principal Architect in the office of the CTO at Cisco Systems, where his current role focuses on domains related to up-and-coming and burgeoning new technology trends and innovation, engaging in large and complex strategic negotiations, and working with C-Levels to set technology strategy and direction within their organizations. Over the years Josh has worked in many differing roles at organizations, ranging from technology companies to banking and finance and management consulting.
Within Cisco, Josh has worked side by side with many of the company’s business units, product managers, and technical marketing engineers and has been directly involved in the creation and deployment of many new software features across multiple technology domains seen in Cisco’s products and portfolio today.
Today Josh maintains his focus on technology, driving innovation with customers in the field and actively participating in the creation of patents, whitepapers, and new product and service offerings for Cisco. Further to his work within Cisco, Josh is also an opensource software advocate coleading the Cloud Native Computing Foundation (CNCF) Artificial Intelligence Technical Community Group, and is one of the coauthors of the Cisco Virtual Kubelet CNCF project, providing him an opportunity to share his knowledge and expertise with the wider open-source community.
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Paperback. Condition: new. Paperback. Autonomous Networks: Using AI to Advance Operations in SP and Enterprise Domains is a practical, forward-looking guide to the next generation of network operationswhere 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780135473368
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Paperback. Condition: new. Paperback. Autonomous Networks: Using AI to Advance Operations in SP and Enterprise Domains is a practical, forward-looking guide to the next generation of network operationswhere 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9780135473368
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Paperback. Condition: new. Paperback. Autonomous Networks: Using AI to Advance Operations in SP and Enterprise Domains is a practical, forward-looking guide to the next generation of network operationswhere 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9780135473368
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