Architecting Intelligent Agents in Azure: Building Agentic Systems with Python and the Microsoft Agent Framework (Paperback)
暫譯: 在 Azure 中架構智能代理：使用 Python 和 Microsoft 代理框架構建代理系統 (平裝本)
Narayn, Hari
- 出版商: Apress-滿千折百
- 出版日期: 2026-06-11
- 售價: $2,120
- 貴賓價: 9.5 折 $2,014
- 語言: 英文
- 頁數: 459
- 裝訂: Quality Paper - also called trade paper
- ISBN: 9798868824326
- ISBN-13: 9798868824326
-
相關分類:
AI Coding
海外代購書籍(需單獨結帳)
相關主題
商品描述
Architecting Intelligent Agents in Azure takes you from your first interaction with an AI agent to deploying a fully orchestrated, production-ready system that can reason, remember, collaborate, and act.
Using the Microsoft Agent Framework and Python, this book walks you through every engineering layer behind modern agentic systems, from grounding and memory to tools, semantic recall, and autonomous action.
Across the chapters, you'll build Thain, an Azure-native feedback agent that evolves into a multi-agent system with the ability to retrieve knowledge, coordinate tasks, and refine its performance.
With a balanced mix of architecture, hands-on code, and cloud patterns, you'll learn how Azure Cosmos DB, Azure AI Search, Azure Monitor, and serverless components come together to form intelligent, self-improving enterprise agents.
Whether you're an AI engineer, Azure developer, or solution architect, this book offers a practical, end-to-end guide to building agents that can reason, recall, collaborate, and grow over time.
What You Will Learn:
- Build a fully functioning agent using Python and the Microsoft Agent Framework Implement reasoning loops, short-term memory, and tool-based actions Add persistent memory using Azure Cosmos DB and semantic recall using Azure AI Search Create safe and governed agents with telemetry, observability, and policy enforcement Integrate external systems through tools for tickets, documents, notifications, and workflows Orchestrate collaborative multi-agent systems with shared memory Deploy agentic workloads using Azure Functions, CI/CD pipelines, and cloud-native architecture Optimize cost, scale, and performance for enterprise production environments
Who This Book Is For:
AI engineers and developers building real agentic systems and evaluating the Microsoft Agent Framework, vector search, and Azure AI services
Cloud and Azure engineers looking to integrate AI capabilities deeply into existing or new applications
Solution architects designing AI-native or AI-augmented enterprise platforms
Full-stack engineers transitioning into AI engineering and wanting an end-to-end practical pathway into agentic systems
商品描述(中文翻譯)
《在 Azure 中架構智能代理》將帶您從第一次與 AI 代理的互動開始，到部署一個完全編排、準備投入生產的系統，該系統能夠推理、記憶、協作和行動。
使用 Microsoft Agent Framework 和 Python，本書將引導您了解現代代理系統背後的每一個工程層面，從基礎和記憶到工具、語意回憶和自主行動。
在各章中，您將構建 Thain，一個 Azure 原生的反饋代理，該代理將演變為一個多代理系統，具備檢索知識、協調任務和提升性能的能力。
通過平衡的架構、實作代碼和雲端模式，您將學習如何將 Azure Cosmos DB、Azure AI Search、Azure Monitor 和無伺服器組件結合起來，形成智能、自我改善的企業代理。
無論您是 AI 工程師、Azure 開發人員還是解決方案架構師，本書都提供了一個實用的端到端指南，幫助您構建能夠推理、回憶、協作並隨時間增長的代理。
您將學到的內容：
- 使用 Python 和 Microsoft Agent Framework 構建一個完全運作的代理
- 實現推理循環、短期記憶和基於工具的行動
- 使用 Azure Cosmos DB 添加持久記憶，並使用 Azure AI Search 實現語意回憶
- 創建具有遙測、可觀察性和政策執行的安全和受管代理
- 通過票證、文件、通知和工作流程的工具整合外部系統
- 使用共享記憶編排協作的多代理系統
- 使用 Azure Functions、CI/CD 管道和雲原生架構部署代理工作負載
- 優化企業生產環境的成本、規模和性能
本書適合的讀者：
- 建立真實代理系統並評估 Microsoft Agent Framework、向量搜索和 Azure AI 服務的 AI 工程師和開發人員
- 希望將 AI 能力深度整合到現有或新應用中的雲端和 Azure 工程師
- 設計 AI 原生或 AI 增強企業平台的解決方案架構師
- 轉型為 AI 工程的全端工程師，並希望獲得進入代理系統的端到端實用途徑
作者簡介
Hari Narayn is an AI architect and full-stack engineer with over 15 years of experience designing and delivering enterprise-grade systems across the public and private sectors. Based in Melbourne, he currently works within the Victorian State Government, focusing on building intelligent, cloud-native solutions using Microsoft Azure, serverless architectures, .NET, and modern JavaScript and Python ecosystems.
Hari has led the design of durable, high-throughput systems using Azure Durable Functions, Cosmos DB, and AI Search. He has built intelligent agents that combine LLMs, semantic memory, and tool-driven automation. His recent focus is on multi-agent systems, vector search, Retrieval-Augmented Generation (RAG), and the Microsoft Agent Framework. He also works extensively with Azure AI services, serverless computing, and end-to-end engineering using Python, .NET, and cloud-native design principles.
He aims to connect architecture with practical engineering, supporting teams as they adopt AI responsibly and build systems that scale. He holds multiple industry certifications across Microsoft Azure and cloud architecture.
Hari is passionate about simplicity in engineering and enjoys mentoring developers exploring the AI and cloud space. He continues to contribute to the developer community through writing, sharing, and building practical, real-world AI systems.
作者簡介(中文翻譯)
Hari Narayn 是一位人工智慧架構師和全端工程師，擁有超過 15 年的經驗，專注於設計和交付公共及私營部門的企業級系統。他目前居住在墨爾本，並在維多利亞州政府工作，專注於使用 Microsoft Azure、無伺服器架構、.NET 以及現代 JavaScript 和 Python 生態系統來構建智能的雲原生解決方案。
Hari 主導設計了耐用的高吞吐量系統，使用 Azure Durable Functions、Cosmos DB 和 AI Search。他建立了結合大型語言模型（LLMs）、語義記憶和工具驅動自動化的智能代理。他最近的重點是多代理系統、向量搜索、檢索增強生成（Retrieval-Augmented Generation, RAG）以及 Microsoft Agent Framework。他還廣泛使用 Azure AI 服務、無伺服器計算，並使用 Python、.NET 和雲原生設計原則進行端到端工程。
他的目標是將架構與實際工程相連接，支持團隊負責任地採用人工智慧並構建可擴展的系統。他擁有多項 Microsoft Azure 和雲架構的行業認證。
Hari 對工程中的簡單性充滿熱情，並喜歡指導探索人工智慧和雲端領域的開發者。他持續通過寫作、分享和構建實用的現實世界人工智慧系統來貢獻開發者社群。
