Optimize multi-agent performance and cost in Microsoft Foundry

  • Module
  • 7 Units
Advanced
AI Engineer
Solution Architect
Azure
Microsoft Foundry

Optimize multi-agent performance and cost in Microsoft Foundry. Design model routing strategies across agent ecosystems, implement multi-level caching architectures, optimize token usage and context management across agent chains, and systematically analyze quality-cost-latency trade-offs.

Learning objectives

By the end of this module, you're able to:

  • Design model routing strategies that assign optimal model tiers to agents based on task complexity
  • Implement multi-level caching architectures that reduce redundant computation across agent interactions
  • Optimize token usage and context management to reduce cost across multi-agent chains without sacrificing quality
  • Analyze and balance quality-cost-latency trade-offs systematically at the multi-agent system level

Prerequisites

Before starting this module, you should have:

  • Experience building multi-agent systems with Microsoft Foundry Agent Service
  • Familiarity with Azure Cache for Redis caching patterns
  • Understanding of token usage and cost monitoring in Microsoft Foundry
  • Experience with OpenTelemetry instrumentation for performance measurement
  • Proficiency in Python

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