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Network Programmability with YANG: The Structure of Network Automation with YANG, NETCONF, RESTCONF, and gNMI

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Название: Network Programmability with YANG: The Structure of Network Automation with YANG, NETCONF, RESTCONF, and gNMI
Автор: Benoit Claise, Joe Clarke, Jan Lindblad
Издательство: Addison-Wesley Professional
Год: 2019
Формат: EPUB
Страниц: 304
Размер: 42 Mb
Язык: English

Today, networks must evolve and scale faster than ever. You can’t manage everything by hand anymore: You need to automate relentlessly. YANG, along with the NETCONF, RESTCONF, or gRPC/gNMI protocols, is the most practical solution, but most implementers have had to learn by trial and error. Now, Network Programmability with YANG gives you complete and reliable guidance for unlocking the full power of network automation using model-driven APIs and protocols.

Authored by three YANG pioneers, this plain-spoken book guides you through successfully applying software practices based on YANG data models. The authors focus on the network operations layer, emphasizing model-driven APIs, and underlying transports.

Whether you’re a network operator, DevOps engineer, software developer, orchestration engineer, NMS/OSS architect, service engineer, or manager, this guide can help you dramatically improve value, agility, and manageability throughout your network.

Discover the value of implementing YANG and Data Model-Driven Management in your network
Explore the layers and components of a complete working solution
Build a business case where value increases as your solution grows
Drill down into transport protocols: NETCONF, RESTCONF, and gNMI/gRPC
See how telemetry can establish a valuable automated feedback loop
Find data models you can build on, and evaluate models with similar functionality
Understand models, metadata, and tools from several viewpoints: architect, operator, module author, and application developer
Walk through a complete automation journey: business case, service model, service implementation, device integration, and operation
Leverage the authors’ experience to design successful YANG models and avoid pitfalls



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