9798245218601 - building generative ai systems on azure: cloud native architecture, model integration, and cost control for production applications de ming, alex (5 resultados)
- Tapa blanda
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 22,43
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
- Tapa blanda
Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 20,81
Envío por EUR 4,87Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
- Tapa blanda
- Impresión bajo demanda
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 21,40
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Generative AI is no longer experimental-it is becoming a core capability of modern cloud platforms. Building Generative AI Systems on Azure provides a practical, production-oriented guide to designing, deploying, and operating large-scale generative AI applications within Microsoft Azure.Thi…s book focuses on real engineering decisions: how to structure cloud-native architectures that incorporate large language models, how to integrate managed AI services into existing systems, and how to balance performance, security, and cost at scale. Rather than treating generative AI as an isolated feature, the book shows how it fits into enterprise-grade application lifecycles.You will learn how to provision and manage Azure-based AI resources, connect applications to model endpoints, and design end-to-end systems that support observability, governance, and compliance. Special attention is given to responsible AI practices, data boundaries, identity management, and secure integration with internal knowledge sources.This book is written for engineers and architects who need clear guidance on turning generative AI capabilities into reliable cloud services-not prototypes. Each chapter emphasizes architectural patterns, deployment strategies, and operational best practices that can be applied across real-world projects.Who this book is forCloud and backend developers building AI-enabled servicesSolution architects designing enterprise AI platformsTechnical leaders planning generative AI adoption on AzureEngineers responsible for security, cost management, and scalability This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Tapa blanda
- Impresión bajo demanda
Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 21,41
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. Print on Demand.
- Tapa blanda
- Impresión bajo demanda
Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 24,69
Envío por EUR 43,30Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Generative AI is no longer experimental-it is becoming a core capability of modern cloud platforms. Building Generative AI Systems on Azure provides a practical, production-oriented guide to designing, deploying, and operating large-scale generative AI applications within Microsoft Azure.Thi…s book focuses on real engineering decisions: how to structure cloud-native architectures that incorporate large language models, how to integrate managed AI services into existing systems, and how to balance performance, security, and cost at scale. Rather than treating generative AI as an isolated feature, the book shows how it fits into enterprise-grade application lifecycles.You will learn how to provision and manage Azure-based AI resources, connect applications to model endpoints, and design end-to-end systems that support observability, governance, and compliance. Special attention is given to responsible AI practices, data boundaries, identity management, and secure integration with internal knowledge sources.This book is written for engineers and architects who need clear guidance on turning generative AI capabilities into reliable cloud services-not prototypes. Each chapter emphasizes architectural patterns, deployment strategies, and operational best practices that can be applied across real-world projects.Who this book is forCloud and backend developers building AI-enabled servicesSolution architects designing enterprise AI platformsTechnical leaders planning generative AI adoption on AzureEngineers responsible for security, cost management, and scalability This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
