AZD For Beginners: A Structured Learning Journey

Automated Translations (Always Up-to-Date)

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Prefer to Clone Locally?

This repository includes 50+ language translations which significantly increases the download size. To clone without translations, use sparse checkout:

Bash / macOS / Linux:

git clone --filter=blob:none --sparse https://github.com/microsoft/AZD-for-beginners.git
cd AZD-for-beginners
git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'

CMD (Windows):

git clone --filter=blob:none --sparse https://github.com/microsoft/AZD-for-beginners.git
cd AZD-for-beginners
git sparse-checkout set --no-cone "/*" "!translations" "!translated_images"

This gives you everything you need to complete the course with a much faster download.

🆕 What's New in azd Today

📌 This course is validated against azd 1.27.1 (July 2026). Run azd version to check your build, and azd upgrade to get the latest.

Azure Developer CLI has grown beyond traditional web apps and APIs. Today, azd is the single tool for deploying any application to Azure—including AI-powered applications and intelligent agents.

Here's what that means for you:

• AI agents are now first-class azd workloads. You can initialize, deploy, and manage AI agent projects using the same azd init → azd up workflow you already know.
• A complete agent lifecycle from the CLI. The azure.ai.agents extension now covers the whole journey—azd ai agent init to scaffold, azd ai agent invoke to test (with response-timing output), azd ai agent eval generate and azd ai agent optimize to measure and improve quality, and azd ai agent delete to clean up.
• More AI building blocks. New preview extensions—azure.ai.skills and azure.ai.connections—let you manage reusable agent skills and Foundry connections directly with azd.
• Microsoft Foundry integration brings model deployment, agent hosting, and AI service configuration directly into the azd template ecosystem.
• Smoother day-to-day basics. Recent releases made azd init idempotent (safe to re-run), made azd auth login clear stale tokens automatically, and added a friendly azd tool first-run setup prompt.
• The core workflow hasn't changed. Whether you're deploying a todo app, a microservice, or a multi-agent AI solution, the commands are the same.

Note for Aspire users: Microsoft now refers to the product simply as Aspire (formerly ".NET Aspire"). azd's Aspire support is unchanged—only the name was updated.

If you've used azd before, AI support is a natural extension—not a separate tool or an advanced track. If you're starting fresh, you'll learn one workflow that works for everything.

🚀 What is Azure Developer CLI (azd)?

Azure Developer CLI (azd) is a developer-friendly command-line tool that makes it simple to deploy applications to Azure. Instead of manually creating and connecting dozens of Azure resources, you can deploy entire applications with a single command.

The Magic of azd up

# This single command does everything:
# ✅ Creates all Azure resources  
# ✅ Configures networking and security
# ✅ Builds your application code
# ✅ Deploys to Azure
# ✅ Gives you a working URL
azd up

That's it! No Azure Portal clicking, no complex ARM templates to learn first, no manual configuration - just working applications on Azure.

❓ Azure Developer CLI vs Azure CLI: What's the Difference?

This is the most common question beginners ask. Here's the simple answer:

Simple Analogy

• Azure CLI is like having all the tools to build a house - hammers, saws, nails. You can build anything, but you need to know construction.
• Azure Developer CLI is like hiring a contractor - you describe what you want, and they handle the building.

When to Use Each

They Work Together!

AZD uses Azure CLI under the hood. You can use both:

# Deploy your app with AZD
azd up

# Then fine-tune specific resources with Azure CLI
az webapp config set --name myapp --always-on true

🌟 Find Templates in Awesome AZD

Don't start from scratch! Awesome AZD is the community collection of ready-to-deploy templates:

Popular AI Templates from Awesome AZD

# RAG Chat with Microsoft Foundry Models + AI Search
azd init --template azure-search-openai-demo

# Quick AI Chat Application
azd init --template openai-chat-app-quickstart

# AI Agents with Foundry Agents
azd init --template get-started-with-ai-agents

🎯 Getting Started in 3 Steps

Before you start, make sure your machine is ready for the template you want to deploy:

Windows:

.\validate-setup.ps1

macOS / Linux:

bash ./validate-setup.sh

If any required check fails, fix that first and then continue with the quick start.

Step 1: Install AZD (2 minutes)

Windows:

winget install microsoft.azd

macOS:

brew tap azure/azd && brew install azd

Linux:

curl -fsSL https://aka.ms/install-azd.sh | bash

Step 2: Authenticate for AZD

# Optional if you plan to use Azure CLI commands directly in this course
az login

# Required for AZD workflows
azd auth login

If you are not sure which one you need, follow the full setup flow in Installation & Setup.

Step 3: Deploy Your First App

# Initialize from a template
azd init --template todo-nodejs-mongo

# Deploy to Azure (creates everything!)
azd up

🎉 That's it! Your app is now live on Azure.

Clean Up (Don't Forget!)

# Remove all resources when done experimenting
azd down --force --purge

📚 How to Use This Course

This course is designed for progressive learning - start where you're comfortable and work your way up:

Quick Setup

1. Fork This Repository:
2. Clone It: git clone https://github.com/YOUR-USERNAME/azd-for-beginners.git
3. Get Help: Azure Discord Community

Prefer to Clone Locally?

This repository includes 50+ language translations which significantly increases the download size. To clone without translations, use sparse checkout:

git clone --filter=blob:none --sparse https://github.com/microsoft/AZD-for-beginners.git
cd AZD-for-beginners
git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'

This gives you everything you need to complete the course with a much faster download.

Course Overview

Master Azure Developer CLI (azd) through structured chapters designed for progressive learning. Special focus on AI application deployment with Microsoft Foundry integration.

Why This Course is Essential for Modern Developers

Based on Microsoft Foundry Discord community insights, 45% of developers want to use AZD for AI workloads but encounter challenges with:

• Complex multi-service AI architectures
• Production AI deployment best practices
• Azure AI service integration and configuration
• Cost optimization for AI workloads
• Troubleshooting AI-specific deployment issues

Learning Objectives

By completing this structured course, you will:

• Master AZD Fundamentals: Core concepts, installation, and configuration
• Deploy AI Applications: Use AZD with Microsoft Foundry services
• Implement Infrastructure as Code: Manage Azure resources with Bicep templates
• Troubleshoot Deployments: Resolve common issues and debug problems
• Optimize for Production: Security, scaling, monitoring, and cost management
• Build Multi-Agent Solutions: Deploy complex AI architectures

Before You Start: Accounts, Access, and Assumptions

Before you begin Chapter 1, make sure you have the following in place. The installation steps later in this guide assume these basics are already handled.

• An Azure subscription: You can use an existing subscription from work or your own account, or create a free trial to get started.
• Permission to create Azure resources: For most exercises, you should have at least Contributor access on the target subscription or resource group. Some chapters may also assume you can create resource groups, managed identities, and RBAC assignments.
• A GitHub account: This is useful for forking the repository, tracking your own changes, and using GitHub Codespaces for the workshop.
• Template runtime prerequisites: Some templates need local tools such as Node.js, Python, Java, or Docker. Run the setup validator before starting so you catch missing tools early.
• Basic terminal familiarity: You do not need to be an expert, but you should be comfortable running commands such as git clone, azd auth login, and azd up.

Working in an enterprise subscription? If your Azure environment is managed by an administrator, confirm ahead of time that you can deploy resources in the subscription or resource group you plan to use. If not, ask for a sandbox subscription or Contributor access before you start.

New to Azure? Start with your own Azure trial or pay-as-you-go subscription at https://aka.ms/azurefreetrial so you can complete the exercises end to end without waiting on tenant-level approvals.

🗺️ Course Map: Quick Navigation by Chapter

Each chapter has a dedicated README with learning objectives, quick starts, and exercises:

Total Course Duration: ~10-14 hours | Skill Progression: Beginner → Production-Ready

📚 Learning Chapters

Select your learning path based on experience level and goals

🚀 Chapter 1: Foundation & Quick Start

Prerequisites: Azure subscription, basic command line knowledge
Duration: 30-45 minutes
Complexity: ⭐

What You'll Learn

• Understanding Azure Developer CLI fundamentals
• Installing AZD on your platform
• Your first successful deployment

Learning Resources

• 🎯 Start Here: What is Azure Developer CLI?
• 📖 Theory: AZD Basics - Core concepts and terminology
• ⚙️ Setup: Installation & Setup - Platform-specific guides
• 🛠️ Hands-On: Your First Project - Step-by-step tutorial
• 📋 Quick Reference: Command Cheat Sheet

Practical Exercises

# Quick installation check
azd version

# Deploy your first application
azd init --template todo-nodejs-mongo
azd up

💡 Chapter Outcome: Successfully deploy a simple web application to Azure using AZD

✅ Success Validation:

# After completing Chapter 1, you should be able to:
azd version              # Shows installed version
azd init --template todo-nodejs-mongo  # Initializes project
azd up                  # Deploys to Azure
azd show                # Displays running app URL
# Application opens in browser and works
azd down --force --purge  # Cleans up resources

📊 Time Investment: 30-45 minutes
📈 Skill Level After: Can deploy basic applications independently 📈 Skill Level After: Can deploy basic applications independently

🤖 Chapter 2: AI-First Development (Recommended for AI Developers)

Prerequisites: Chapter 1 completed
Duration: 1-2 hours
Complexity: ⭐⭐

What You'll Learn

• Microsoft Foundry integration with AZD
• Deploying AI-powered applications
• Understanding AI service configurations

Learning Resources

• 🎯 Start Here: Microsoft Foundry Integration
• 🤖 AI Agents: AI Agents Guide - Deploy intelligent agents with AZD
• 📖 Patterns: AI Model Deployment - Deploy and manage AI models
• 🛠️ Workshop: AI Workshop Lab - Make your AI solutions AZD-ready
• 🎥 Interactive Guide: Workshop Materials - Browser-based learning with MkDocs * DevContainer Environment
• 📋 Templates: Microsoft Foundry Templates
• 📝 Examples: AZD Deployment Examples

Practical Exercises

# Deploy your first AI application
azd init --template azure-search-openai-demo
azd up

# Try additional AI templates
azd init --template openai-chat-app-quickstart
azd init --template agent-openai-python-prompty

💡 Chapter Outcome: Deploy and configure an AI-powered chat application with RAG capabilities

✅ Success Validation:

# After Chapter 2, you should be able to:
azd init --template azure-search-openai-demo
azd up
# Test the AI chat interface
# Ask questions and get AI-powered responses with sources
# Verify search integration works
azd monitor  # Check Application Insights shows telemetry
azd down --force --purge

📊 Time Investment: 1-2 hours
📈 Skill Level After: Can deploy and configure production-ready AI applications
💰 Cost Awareness: Understand $80-150/month dev costs, $300-3500/month production costs

💰 Cost Considerations for AI Deployments

Development Environment (Estimated $80-150/month):

• Microsoft Foundry Models (Pay-as-you-go): $0-50/month (based on token usage)
• AI Search (Basic tier): $75/month
• Container Apps (Consumption): $0-20/month
• Storage (Standard): $1-5/month

Production Environment (Estimated $300-3,500+/month):

• Microsoft Foundry Models (PTU for consistent performance): $3,000+/month OR Pay-as-go with high volume
• AI Search (Standard tier): $250/month
• Container Apps (Dedicated): $50-100/month
• Application Insights: $5-50/month
• Storage (Premium): $10-50/month

💡 Cost Optimization Tips:

• Use Free Tier Microsoft Foundry Models for learning (Azure OpenAI 50,000 tokens/month included)
• Run azd down to deallocate resources when not actively developing
• Start with consumption-based billing, upgrade to PTU only for production
• Use azd provision --preview to estimate costs before deployment
• Enable auto-scaling: pay only for actual usage

Cost Monitoring:

# Check estimated monthly costs
azd provision --preview

# Monitor actual costs in Azure Portal
az consumption budget list --resource-group <your-rg>

⚙️ Chapter 3: Configuration & Authentication

Prerequisites: Chapter 1 completed
Duration: 45-60 minutes
Complexity: ⭐⭐

What You'll Learn

• Environment configuration and management
• Authentication and security best practices
• Resource naming and organization

Learning Resources

• 📖 Configuration: Configuration Guide - Environment setup
• 🔐 Security: Authentication patterns and managed identity - Authentication patterns
• 📝 Examples: Database App Example - AZD Database Examples

Practical Exercises

• Configure multiple environments (dev, staging, prod)
• Set up managed identity authentication
• Implement environment-specific configurations

💡 Chapter Outcome: Manage multiple environments with proper authentication and security

🏗️ Chapter 4: Infrastructure as Code & Deployment

Prerequisites: Chapters 1-3 completed
Duration: 1-1.5 hours
Complexity: ⭐⭐⭐

What You'll Learn

• Advanced deployment patterns
• Infrastructure as Code with Bicep
• Resource provisioning strategies

Learning Resources

• 📖 Deployment: Deployment Guide - Complete workflows
• 🏗️ Provisioning: Provisioning Resources - Azure resource management
• 📝 Examples: Container App Example - Containerized deployments

Practical Exercises

• Create custom Bicep templates
• Deploy multi-service applications
• Implement blue-green deployment strategies

💡 Chapter Outcome: Deploy complex multi-service applications using custom infrastructure templates

🎯 Chapter 5: Multi-Agent AI Solutions (Advanced)

Prerequisites: Chapters 1-2 completed
Duration: 2-3 hours
Complexity: ⭐⭐⭐⭐

What You'll Learn

• Multi-agent architecture patterns
• Agent orchestration and coordination
• Production-ready AI deployments

Learning Resources

• 🤖 Featured Project: Retail Multi-Agent Solution - Complete implementation
• 🛠️ ARM Templates: ARM Template Package - One-click deployment
• 📖 Architecture: Multi-agent coordination patterns - Patterns

Practical Exercises

# Deploy the complete retail multi-agent solution
cd examples/retail-multiagent-arm-template
./deploy.sh

# Explore agent configurations
az deployment group show --resource-group <rg-name> --name <deployment-name>

💡 Chapter Outcome: Deploy and manage a production-ready multi-agent AI solution with Customer and Inventory agents

🔍 Chapter 6: Pre-Deployment Validation & Planning

Prerequisites: Chapter 4 completed
Duration: 1 hour
Complexity: ⭐⭐

What You'll Learn

• Capacity planning and resource validation
• SKU selection strategies
• Pre-flight checks and automation

Learning Resources

• 📊 Planning: Capacity Planning - Resource validation
• 💰 Selection: SKU Selection - Cost-effective choices
• ✅ Validation: Pre-flight Checks - Automated scripts

Practical Exercises

• Run capacity validation scripts
• Optimize SKU selections for cost
• Implement automated pre-deployment checks

💡 Chapter Outcome: Validate and optimize deployments before execution

🚨 Chapter 7: Troubleshooting & Debugging

Prerequisites: Any deployment chapter completed
Duration: 1-1.5 hours
Complexity: ⭐⭐

What You'll Learn

• Systematic debugging approaches
• Common issues and solutions
• AI-specific troubleshooting

Learning Resources

• 🔧 Common Issues: Common Issues - FAQ and solutions
• 🕵️ Debugging: Debugging Guide - Step-by-step strategies
• 🤖 AI Issues: AI-Specific Troubleshooting - AI service problems

Practical Exercises

• Diagnose deployment failures
• Resolve authentication issues
• Debug AI service connectivity

💡 Chapter Outcome: Independently diagnose and resolve common deployment issues

🏢 Chapter 8: Production & Enterprise Patterns

Prerequisites: Chapters 1-4 completed
Duration: 2-3 hours
Complexity: ⭐⭐⭐⭐

What You'll Learn

• Production deployment strategies
• Enterprise security patterns
• Monitoring and cost optimization

Learning Resources

• 🏭 Production: Production AI Best Practices - Enterprise patterns
• 📝 Examples: Microservices Example - Complex architectures
• 📊 Monitoring: Application Insights integration - Monitoring

Practical Exercises

• Implement enterprise security patterns
• Set up comprehensive monitoring
• Deploy to production with proper governance

💡 Chapter Outcome: Deploy enterprise-ready applications with full production capabilities

🎓 Workshop Overview: Hands-On Learning Experience

⚠️ WORKSHOP STATUS: Active Development
The workshop materials are currently being developed and refined. Core modules are functional, but some advanced sections are incomplete. We're actively working to complete all content. Track progress →

Interactive Workshop Materials

Comprehensive hands-on learning with browser-based tools and guided exercises

Our workshop materials provide a structured, interactive learning experience that complements the chapter-based curriculum above. The workshop is designed for both self-paced learning and instructor-led sessions.

🛠️ Workshop Features

• Browser-Based Interface: Complete MkDocs-powered workshop with search, copy, and theme features
• GitHub Codespaces Integration: One-click development environment setup
• Structured Learning Path: 8-module guided exercises (3-4 hours total)
• Progressive Methodology: Introduction → Selection → Validation → Deconstruction → Configuration → Customization → Teardown → Wrap-up
• Interactive DevContainer Environment: Pre-configured tools and dependencies

📚 Workshop Module Structure

The workshop follows an 8-module progressive methodology that takes you from discovery to deployment mastery:

Workshop Flow:

Introduction → Selection → Validation → Deconstruction → Configuration → Customization → Teardown → Wrap-up
     ↓            ↓           ↓              ↓               ↓              ↓            ↓           ↓
  Overview    Find the     Deploy &      Explore        Master         Customize     Clean up    Review &
             right        verify        code &        azure.yaml      for your      resources   next steps
             template                   structure                     scenario

🚀 Getting Started with the Workshop

# Option 1: GitHub Codespaces (Recommended)
# Click "Code" → "Create codespace on main" in the repository

# Option 2: Local Development
git clone https://github.com/microsoft/azd-for-beginners.git
cd azd-for-beginners/workshop
# Follow the setup instructions in workshop/README.md

🎯 Workshop Learning Outcomes

By completing the workshop, participants will:

• Deploy Production AI Applications: Use AZD with Microsoft Foundry services
• Master Multi-Agent Architectures: Implement coordinated AI agent solutions
• Implement Security Best Practices: Configure authentication and access control
• Optimize for Scale: Design cost-effective, performant deployments
• Troubleshoot Deployments: Resolve common issues independently

📖 Workshop Resources

• 🎥 Interactive Guide: Workshop Materials - Browser-based learning environment
• 📋 Module-by-Module Instructions:
  • 0. Introduction - Workshop overview and objectives
  • 1. Selection - Find and select AI templates
  • 2. Validation - Deploy and verify templates
  • 3. Deconstruction - Explore template architecture
  • 4. Configuration - Master azure.yaml
  • 5. Customization - Customize for your scenario
  • 6. Teardown - Clean up resources
  • 7. Wrap-up - Review and next steps
• 🛠️ AI Workshop Lab: AI Workshop Lab - AI-focused exercises
• 💡 Quick Start: Workshop Setup Guide - Environment configuration

Perfect for: Corporate training, university courses, self-paced learning, and developer bootcamps.

📖 Deep Dive: AZD Capabilities

Beyond the basics, AZD provides powerful features for production deployments:

• Template-based deployments - Use pre-built templates for common application patterns
• Infrastructure as Code - Manage Azure resources using Bicep or Terraform
• Integrated workflows - Seamlessly provision, deploy, and monitor applications
• Developer-friendly - Optimized for developer productivity and experience

AZD + Microsoft Foundry: Perfect for AI Deployments

Why AZD for AI Solutions? AZD addresses the top challenges AI developers face:

• AI-Ready Templates - Pre-configured templates for Microsoft Foundry Models, Azure AI Services, and ML workloads
• Secure AI Deployments - Built-in security patterns for AI services, API keys, and model endpoints
• Production AI Patterns - Best practices for scalable, cost-effective AI application deployments
• End-to-End AI Workflows - From model development to production deployment with proper monitoring
• Cost Optimization - Smart resource allocation and scaling strategies for AI workloads
• Microsoft Foundry Integration - Seamless connection to Microsoft Foundry model catalog and endpoints

🎯 Templates & Examples Library

Featured: Microsoft Foundry Templates

Start here if you're deploying AI applications!

Note: These templates demonstrate various AI patterns. Some are external Azure Samples, others are local implementations.

Featured: Complete Learning Scenarios

Production-ready application templates mapped to learning chapters

Learning by Example Type

📌 Local vs. External Examples:
Local Examples (in this repo) = Ready to use immediately
External Examples (Azure Samples) = Clone from linked repositories

Local Examples (Ready to Use)

• Retail Multi-Agent Solution - Complete production-ready implementation with ARM templates
  • Multi-agent architecture (Customer + Inventory agents)
  • Comprehensive monitoring and evaluation
  • One-click deployment via ARM template

Local Examples - Container Applications (Chapters 2-5)

Comprehensive container deployment examples in this repository:

• Container App Examples - Complete guide to containerized deployments
  • Simple Flask API - Basic REST API with scale-to-zero
  • Microservices Architecture - Production-ready multi-service deployment
  • Quick Start, Production, and Advanced deployment patterns
  • Monitoring, security, and cost optimization guidance

External Examples - Simple Applications (Chapters 1-2)

Clone these Azure Samples repositories to get started:

• Simple Web App - Node.js + MongoDB - Basic deployment patterns
• Static Website - React SPA - Static content deployment
• Container App - Python Flask - REST API deployment

External Examples - Database Integration (Chapter 3-4)

• Database App - C# + SQL - Database connectivity patterns
• Functions + Cosmos DB - Serverless data workflow

External Examples - Advanced Patterns (Chapters 4-8)

• Java Microservices - Multi-service architectures
• Container Apps Jobs - Background processing
• Enterprise ML Pipeline - Production-ready ML patterns

External Template Collections

• Official AZD Template Gallery - Curated collection of official and community templates
• Azure Developer CLI Templates - Microsoft Learn template documentation
• Examples Directory - Local learning examples with detailed explanations

📚 Learning Resources & References

Quick References

• Command Cheat Sheet - Essential azd commands organized by chapter
• Glossary - Azure and azd terminology
• FAQ - Common questions organized by learning chapter
• Study Guide - Comprehensive practice exercises

Hands-On Workshops

• AI Workshop Lab - Make your AI solutions AZD-deployable (2-3 hours)
• Interactive Workshop - 8-module guided exercises with MkDocs and GitHub Codespaces
  • Follows: Introduction → Selection → Validation → Deconstruction → Configuration → Customization → Teardown → Wrap-up

External Learning Resources

• Azure Developer CLI Documentation
• Azure Architecture Center
• Azure Pricing Calculator
• Azure Status

AI Agent Skills for Your Editor

• Microsoft Azure Skills on skills.sh - 37 open agent skills for Azure AI, Foundry, deployment, diagnostics, cost optimization, and more. Install them in GitHub Copilot, Cursor, Claude Code, or any supported agent:

  npx skills add microsoft/github-copilot-for-azure
  

🔧 Quick Troubleshooting Guide

Common issues beginners face and immediate solutions:

# Install AZD first
# Windows (PowerShell):
winget install microsoft.azd

# macOS:
brew tap azure/azd && brew install azd

# Linux:
curl -fsSL https://aka.ms/install-azd.sh | bash

# Verify installation
azd version

# List available subscriptions
az account list --output table

# Set default subscription
az account set --subscription "<subscription-id-or-name>"

# Set for AZD environment
azd env set AZURE_SUBSCRIPTION_ID "<subscription-id>"

# Verify
az account show

# Try different Azure region
azd env set AZURE_LOCATION "westus2"
azd up

# Or use smaller SKUs in development
# Edit infra/main.parameters.json:
{
  "sku": "B1"  // Instead of "P1V2"
}

# Option 1: Clean and retry
azd down --force --purge
azd up

# Option 2: Just fix infrastructure
azd provision

# Option 3: Check detailed status
azd show

# Option 4: Check logs in Azure Monitor
azd monitor --logs

# Re-authenticate for AZD
azd auth logout
azd auth login

# Optional: refresh Azure CLI too if you are running az commands
az logout
az login

# Verify authentication
az account show

# AZD generates unique names, but if conflict:
azd down --force --purge

# Then retry with fresh environment
azd env new dev-v2
azd up

# Check progress
azd show

# If stuck >30 minutes, check Azure Portal:
azd monitor --overview
# Look for failed deployments

# Check your Azure role
az role assignment list --assignee $(az account show --query user.name -o tsv)

# You need at least "Contributor" role
# Ask your Azure admin to grant:
# - Contributor (for resources)
# - User Access Administrator (for role assignments)

# Show all service endpoints
azd show

# Or open Azure Portal
azd monitor

# Check specific service
azd env get-values
# Look for *_URL variables

📚 Full Troubleshooting Resources

• Common Issues Guide: Detailed Solutions
• AI-Specific Issues: AI Troubleshooting
• Debugging Guide: Step-by-step Debugging
• Get Help: Azure Discord #azure-developer-cli

🎓 Course Completion & Certification

Progress Tracking

Track your learning progress through each chapter:

• Chapter 1: Foundation & Quick Start ✅
• Chapter 2: AI-First Development ✅
• Chapter 3: Configuration & Authentication ✅
• Chapter 4: Infrastructure as Code & Deployment ✅
• Chapter 5: Multi-Agent AI Solutions ✅
• Chapter 6: Pre-Deployment Validation & Planning ✅
• Chapter 7: Troubleshooting & Debugging ✅
• Chapter 8: Production & Enterprise Patterns ✅

Learning Verification

After completing each chapter, verify your knowledge by:

1. Practical Exercise: Complete the chapter's hands-on deployment
2. Knowledge Check: Review the FAQ section for your chapter
3. Community Discussion: Share your experience in Azure Discord
4. Next Chapter: Move to the next complexity level

Course Completion Benefits

Upon completing all chapters, you will have:

• Production Experience: Deployed real AI applications to Azure
• Professional Skills: Enterprise-ready deployment capabilities
• Community Recognition: Active member of Azure developer community
• Career Advancement: In-demand AZD and AI deployment expertise

🤝 Community & Support

Get Help & Support

• Technical Issues: Report bugs and request features
• Learning Questions: Microsoft Azure Discord Community and
• AI-Specific Help: Join the
• Documentation: Official Azure Developer CLI documentation

Community Insights from Microsoft Foundry Discord

Recent Poll Results from #Azure Channel:

• 45% of developers want to use AZD for AI workloads
• Top challenges: Multi-service deployments, credential management, production readiness
• Most requested: AI-specific templates, troubleshooting guides, best practices

Join our community to:

• Share your AZD + AI experiences and get help
• Access early previews of new AI templates
• Contribute to AI deployment best practices
• Influence future AI + AZD feature development

Contributing to the Course

We welcome contributions! Please read our Contributing Guide for details on:

• Content Improvements: Enhance existing chapters and examples
• New Examples: Add real-world scenarios and templates
• Translation: Help maintain multi-language support
• Bug Reports: Improve accuracy and clarity
• Community Standards: Follow our inclusive community guidelines

📄 Course Information

License

This project is licensed under the MIT License - see the LICENSE file for details.

Related Microsoft Learning Resources

Our team produces other comprehensive learning courses:

LangChain

Azure / Edge / MCP / Agents

Generative AI Series

Core Learning

Copilot Series

🗺️ Course Navigation

🚀 Ready to Start Learning?

Beginners: Start with Chapter 1: Foundation & Quick Start
AI Developers: Jump to Chapter 2: AI-First Development
Experienced Developers: Begin with Chapter 3: Configuration & Authentication

Next Steps: Begin Chapter 1 - AZD Basics →