1.1 - Introduction to Microsoft Foundry

Welcome to Day 1! Today we begin our journey by exploring Microsoft Foundry, the foundation for building enterprise-grade AI applications on Azure.

What You’ll Learn

What Microsoft Foundry is and why it matters for AI development
Key components and capabilities of the Foundry platform
How Foundry simplifies the AI application development lifecycle
Integration points between Foundry and Azure Developer CLI

Resources

Before diving in, review these essential resources:

📘 Microsoft Foundry Overview - Official Microsoft documentation introducing Foundry
📘 Azure AI Services - Understanding the broader Azure AI ecosystem
🎥 Microsoft Build 2025: Foundry Announcement - Watch the official announcement and demos

Understanding Microsoft Foundry

Microsoft Foundry is a comprehensive platform that brings together AI services, tools, and infrastructure to accelerate AI application development. Think of it as your AI development workspace that provides:

Pre-built AI Models: Access to state-of-the-art language models, vision models, and specialized AI services
Development Tools: Integrated environments for prompt engineering, model fine-tuning, and evaluation
Infrastructure Management: Simplified deployment and scaling of AI workloads
Enterprise Security: Built-in security, compliance, and governance features

Why Foundry Matters

Traditional AI development requires stitching together multiple services, managing complex infrastructure, and navigating fragmented tools. Foundry consolidates these elements into a cohesive platform, allowing you to:

Focus on building features rather than managing infrastructure
Accelerate time-to-market with pre-configured templates
Ensure enterprise-grade security and compliance from day one
Scale applications efficiently as your needs grow

Key Components

1. AI Model Catalog

Access a curated collection of models including:

OpenAI models (GPT-4, GPT-3.5)
Open-source models (Llama, Mistral)
Specialized Azure AI services

2. Development Workspace

An integrated environment providing:

Prompt engineering playground
Model comparison tools
Evaluation frameworks
Dataset management

3. Deployment Platform

Simplified deployment through:

One-click deployment options
Auto-scaling infrastructure
Monitoring and observability
Cost optimization tools

4. Governance Framework

Enterprise controls including:

Content filtering
Usage tracking
Access management
Compliance reporting

Foundry + Azure Developer CLI

Throughout this course, you’ll see how Azure Developer CLI (AZD) templates integrate with Foundry to provide:

Infrastructure as Code: Bicep/Terraform templates that provision Foundry resources
Configuration Management: Environment variables and settings for Foundry services
Local Development: Tools to test Foundry integrations locally before deployment
CI/CD Integration: Automated pipelines for deploying Foundry-based applications

Your First Foundry Exploration

While we won’t deploy anything today, familiarize yourself with the Foundry portal:

Navigate to Azure AI Foundry
Explore the model catalog
Review sample applications
Check out the documentation and quickstarts

Ask Copilot

Deepen your understanding by asking GitHub Copilot:

“What are the main differences between using Azure OpenAI Service directly versus through Microsoft Foundry?”
“How does Microsoft Foundry help with responsible AI practices and content filtering?”
“What types of AI applications are best suited for building on Microsoft Foundry?”

Next: Day 2 - Enterprise Retail AI Scenario

Ready to see how Foundry applies to a real-world scenario? Tomorrow we’ll explore an enterprise retail AI application.