Develop Multi-Agent Solutions in Azure – AI-500 Study Guide
This domain accounts for 33% of the AI-500 exam and is the most heavily weighted domain. It assesses your hands-on proficiency in building agentic systems using Microsoft frameworks, advanced context management, multi-agent RAG, Model Context Protocol (MCP) tool integration, and resilient orchestration patterns.
Orchestration Frameworks in Azure
The AI-500 exam tests your knowledge of the major frameworks supported in Azure AI:
1. Microsoft Agent Framework & Semantic Kernel
- Semantic Kernel (SK): Microsoft's lightweight enterprise SDK (available in C#, Python, Java). Core components:
- Kernel: Coordinates AI models, memory, and plugins.
- Plugins & Native Functions: Strongly typed code callable as tools using function-calling annotations (
@kernel_function). - Agent Framework / Agent Groups: Native abstractions for chat completion agents, assistant agents, and collaborative multi-agent groups with termination strategies (
TerminationStrategy).
- Auto-Invocation / Function Calling: Semantic Kernel inspects model tool calls, dynamically executes native plugins, and feeds structured results back into the model loop automatically.
2. LangGraph & Graph-Based Multi-Agent Workflows
- Models multi-agent systems as state graphs consisting of:
- Nodes: Agents or tool functions that transform state.
- Edges: Conditional routing functions (e.g., if model called a tool $\rightarrow$ route to tool node; if finished $\rightarrow$ route to supervisor).
- State Channels: Strongly typed Pydantic or TypedDict schemas that accumulate updates.
- Checkpointers: Persists graph state to Cosmos DB or PostgreSQL, enabling durable execution and human-in-the-loop pause/resume.
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