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.

• Introduction xxiiiChapter 1 Network Autonomy 1Introduction 1State of Network Automation Today 2Industry Frameworks and Trends 27Challenges in Achieving Autonomy 39People and Processes 45System Integrations 53Summary and Future Considerations 58Chapter 2 Regulations Impact on Autonomous Networks 59Introduction 59Short History of Data Privacy 59Overview of EU Digital Regulations 72The State of AI Regulation in the Rest of the World 80How Companies React to Existing AI and Data Regulation 88Regulation Impact on Data and AI Projects and Mitigation Measures 96Summary and Future Considerations 109References 110Chapter 3 Observability and Data Sources 115Introduction 115Network Data Sources 117Model-Driven Telemetry 131Observability and Tracing Principles 135Audit Trails in Autonomous Networks 147Collecting and Correlating Disparate Traces 150Network Observability Architecture Patterns 154Observability Use Cases 156Summary and Future Considerations 165References 165Chapter 4 Conventional and Task-Specific AI/ML Models Usage for Autonomous Networks 167Introduction 167Short History of Artificial Intelligence 168Machine Learning Overview 172Semi-Supervised Learning 184Unsupervised Learning 186Reinforcement Learning 191Deep Learning and Neural Networks 196Model Evaluation, Validation, and Monitoring Metrics 206Summary and Future Considerations 219References 220Chapter 5 Generative AI in the Context of Autonomous Networks 221Introduction 221Agentic Workflows 252Federated Learning 264Infrastructure for xLMs 268Networking Use Cases 276Summary and Future Considerations 279References 280Chapter 6 Automated Execution and Testing 281Introduction 281Industry Automation Frameworks and Standards 284Automation Tools 287Cisco Virtual Kubelet 314Network Test Automation 315Domain vs. Cross-Domain Automation Architecture 334Network Automation Use Cases 337Summary and Future Considerations 343References 343Chapter 7 Closed-Loop Command and Control 345Introduction to Closed-Loop Systems 345Evolution of Network Operations 351Core Concepts of Closed-Loop Network Operations 360Closed-Loop Operations Architectural Framework 371High-Value Use Cases in Autonomous Network Operations 384Challenges and Limitations in Implementing Closed-Loop Operations 395Closed-Loop Future Evolution 397Summary and Future Considerations 398References 399Chapter 8 Communication Service Provider Autonomous Network Vision 401Background and Industry Context 401End-to-End Autonomous Network Architecture 411Typical Use-Case Deployment for Level 3+ 428Typical Use Case Deployment for Level 4+ 435Business Benefits 449Summary and Future Considerations 455References 455Chapter 9 Enterprise Domain Vision 459Introduction 459The Function of Today’s Networks 464Usage Ratios for Artificial Intelligence Methods 466Security Considerations 467End-to-End Autonomous Network Evolution Roadmap 484Alignment with Core Business Applications 489Planning and Deployment 494Integration with Existing Systems 495Technical Challenges 499Summary and Future Considerations 506References 507Chapter 10 Autonomous Network Considerations—Organizational Change 509Short History of Network Operations 509Core Network Operation Concepts and Frameworks 516Typical Network Operations Center Setup for CSP 540Typical NOC Setup for an IT Enterprise 548Organizational Culture Shift 553Key Skills Required for AN-Based Operations 560Summary and Future Considerations 572References 573  TOC, 9780135473368, 7/13/26