Agentic Architectures on Azure
Autor Ricardo Cataldien Limba Engleză Paperback – 31 oct 2026
Using a hands-on, progressive approach, you'll build a multi-agent retail system from scratch-starting with a single agent on Azure Container Apps and evolving into a full event-driven architecture powered by Azure OpenAI, Azure AI Foundry, and the Microsoft Agent Framework. You'll learn how to design agent boundaries, enable synchronous and asynchronous communication, and orchestrate intelligent workflows using modern Azure services, with working code and infrastructure templates throughout.
The book also covers what it takes to run these systems in production, including secure zero-trust architectures, CI/CD pipelines, observability, and cost control. By the end, you'll have a clear blueprint for designing, deploying, and managing scalable, enterprise-grade agentic systems on Azure.
What You Will Learn:
- Design multi-agent architectures using Azure Container Apps, AKS, and Azure AI Foundry
- Implement synchronous agent communication with MCP servers hosted on Azure Container Apps
- Build event-driven agent workflows using Azure Service Bus, Event Hubs, and Event Grid
- Deploy agent infrastructure using Bicep templates and the Azure Developer CLI (azd)
- Operate multi-agent systems with Azure Monitor, Application Insights, and Cost Management
Who This Book Is For:
Azure Solution Architects designing AI-enhanced enterprise systems and back-end engineers on Azure
Preț: 251.28 lei
Preț vechi: 314.10 lei
-20% Nou
Carte disponibilă
Livrare economică 30 noiembrie-14 decembrie
Specificații
Pagini: 252
Ilustrații: XXIV, 252 p. 37 illus.
Dimensiuni: 178 x 254 x 16 mm
Greutate: 0.53 kg
Ediția:First Edition
Editura: APRESS L.P.
Colecția Apress
Notă biografică
Ricardo Cataldi is a software engineer, AI practitioner, author, and educator focused on production-grade AI systems, cloud architecture, and applied artificial intelligence. With a master's degree in Applied Economics (UFRGS) and graduate studies in Mathematics (USP), he brings rigorous analytical foundations to enterprise AI delivery. During his time at Microsoft, Ricardo delivered AI solutions for customers in banking, education, retail, and telecommunications. He owns delivery from discovery to production, industrializing machine-learning engineering pipelines and building multi-agent workflows with reliability and governance controls. Ricardo has taught Machine Learning Engineering at FIAP. His published research on traceability and trust has accumulated more than 100 citations, and his Azure Samples contributions-Holiday Peak Hub, Tutor, and Tayra-demonstrate production-grade AI patterns.