Architect production-grade multi-agent AI solutions in Azure

  • Learning Path
  • 4 Modules

At a glance

Production-grade multi-agent AI solutions require a deep understanding of agentic architectures, orchestration patterns, and communication strategies. This learning path will guide you through the essential concepts and best practices for building scalable and maintainable multi-agent systems in Azure.

Prerequisites

  • Completion of AI-103 "Develop AI agents on Azure" or equivalent hands-on experience building and deploying agents
  • Working experience with Microsoft Foundry Agent Service and Microsoft Agent Framework
  • Familiarity with foundational multi-agent orchestration patterns (sequential, concurrent, group chat, handoff)
  • Basic knowledge of the A2A protocol and how to connect to a remote agent
  • Python programming proficiency, including async patterns and REST API consumption

Modules in this learning path

Design stateful agentic loops with Microsoft Foundry Agent Service

Design stateful agentic loops for production AI systems. Implement run-status handling and context accumulation, configure agent reflection and planning cycles, architect session state persistence, build fork-based session patterns, and migrate Agents v1 workloads to the Agents v2 Responses API.

Implement advanced multi-agent orchestration patterns in Microsoft Foundry

Implement advanced multi-agent orchestration patterns in Microsoft Foundry. Design hub-and-spoke architectures, implement parallel agent spawning with synchronization and partial failure recovery, configure hierarchical supervisor patterns, and evaluate trade-offs across Semantic Kernel, LangGraph, AutoGen, and CrewAI.

Apply task decomposition and agent collaboration strategies in Microsoft Foundry

Apply advanced task decomposition strategies in Microsoft Foundry multi-agent systems. Design prompt chaining workflows for complex reasoning, implement LLM-driven adaptive decomposition with meta-agent planners, configure agent handoff protocols for context-preserving transitions, and balance decomposition granularity against coordination overhead.

Design enterprise-scale agent communication with A2A in Azure

Design enterprise-scale agent communication architectures using the A2A protocol in Azure. Implement agent discovery registries with capability-based routing, design shared state management using Azure Cosmos DB and Azure Managed Redis, configure context isolation for multitenant deployments, and build conflict detection and resolution mechanisms for collaborative agent networks.

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