AZD For Beginners: A Structured Learning Journey

Automated Translations (Always Up-to-Date)

🚀 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:

Feature	Azure CLI (`az`)	Azure Developer CLI (`azd`)
Purpose	Manage individual Azure resources	Deploy complete applications
Mindset	Infrastructure-focused	Application-focused
Example	`az webapp create --name myapp...`	`azd up`
Learning Curve	Must know Azure services	Just know your app
Best For	DevOps, Infrastructure	Developers, Prototyping

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

Scenario	Use This
"I want to deploy my web app quickly"	`azd up`
"I need to create just a storage account"	`az storage account create`
"I'm building a full AI application"	`azd init --template azure-search-openai-demo`
"I need to debug a specific Azure resource"	`az resource show`
"I want production-ready deployment in minutes"	`azd up --environment production`

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:

Resource	Description
🔗 Awesome AZD Gallery	Browse 200+ templates with one-click deploy
🔗 Submit a Template	Contribute your own template to the community
🔗 GitHub Repository	Star and explore the source

Popular AI Templates from Awesome AZD

# RAG Chat with Azure OpenAI + 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

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: Login to Azure

azd auth login

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:

Your Experience	Start Here
Brand new to Azure	Chapter 1: Foundation
Know Azure, new to AZD	Chapter 1: Foundation
Want to deploy AI apps	Chapter 2: AI-First Development
Want hands-on practice	🎓 Interactive Workshop - 3-4 hour guided lab
Need production patterns	Chapter 8: Production & Enterprise

Quick Setup

Fork This Repository:
Clone It: git clone https://github.com/YOUR-USERNAME/azd-for-beginners.git
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

🗺️ Course Map: Quick Navigation by Chapter

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

Chapter	Topic	Lessons	Duration	Complexity
Ch 1: Foundation	Getting Started	AZD Basics \| Installation \| First Project	30-45 min	⭐
Ch 2: AI Development	AI-First Apps	Foundry Integration \| AI Agents \| Model Deployment \| Workshop	1-2 hrs	⭐⭐
Ch 3: Configuration	Auth & Security	Configuration \| Auth & Security	45-60 min	⭐⭐
Ch 4: Infrastructure	IaC & Deployment	Deployment Guide \| Provisioning	1-1.5 hrs	⭐⭐⭐
Ch 5: Multi-Agent	AI Agent Solutions	Retail Scenario \| Coordination Patterns	2-3 hrs	⭐⭐⭐⭐
Ch 6: Pre-Deployment	Planning & Validation	Preflight Checks \| Capacity Planning \| SKU Selection \| App Insights	1 hr	⭐⭐
Ch 7: Troubleshooting	Debug & Fix	Common Issues \| Debugging \| AI Issues	1-1.5 hrs	⭐⭐
Ch 8: Production	Enterprise Patterns	Production Practices	2-3 hrs	⭐⭐⭐⭐
🎓 Workshop	Hands-On Lab	Introduction \| Selection \| Validation \| Deconstruction \| Configuration \| Customization \| Teardown \| Wrap-up	3-4 hrs	⭐⭐

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

✅ 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

🤖 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):

Azure OpenAI (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):

Azure OpenAI (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 Azure OpenAI for learning (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:

Module	Topic	What You'll Do	Duration
0. Introduction	Workshop Overview	Understand learning objectives, prerequisites, and workshop structure	15 min
1. Selection	Template Discovery	Explore AZD templates and select the right AI template for your scenario	20 min
2. Validation	Deploy & Verify	Deploy the template with `azd up` and validate infrastructure works	30 min
3. Deconstruction	Understand Structure	Use GitHub Copilot to explore template architecture, Bicep files, and code organization	30 min
4. Configuration	azure.yaml Deep Dive	Master `azure.yaml` configuration, lifecycle hooks, and environment variables	30 min
5. Customization	Make It Yours	Enable AI Search, tracing, evaluation, and customize for your scenario	45 min
6. Teardown	Clean Up	Safely deprovision resources with `azd down --purge`	15 min
7. Wrap-up	Next Steps	Review accomplishments, key concepts, and continue your learning journey	15 min

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 Azure OpenAI, Cognitive 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.

Template	Chapter	Complexity	Services	Type
Get started with AI chat	Chapter 2	⭐⭐	AzureOpenAI + Azure AI Model Inference API + Azure AI Search + Azure Container Apps + Application Insights	External
Get started with AI agents	Chapter 2	⭐⭐	Foundry Agents + AzureOpenAI + Azure AI Search + Azure Container Apps + Application Insights	External
Azure Search + OpenAI Demo	Chapter 2	⭐⭐	AzureOpenAI + Azure AI Search + App Service + Storage	External
OpenAI Chat App Quickstart	Chapter 2	⭐	AzureOpenAI + Container Apps + Application Insights	External
Agent OpenAI Python Prompty	Chapter 5	⭐⭐⭐	AzureOpenAI + Azure Functions + Prompty	External
Contoso Chat RAG	Chapter 8	⭐⭐⭐⭐	AzureOpenAI + AI Search + Cosmos DB + Container Apps	External
Retail Multi-Agent Solution	Chapter 5	⭐⭐⭐⭐	AzureOpenAI + AI Search + Storage + Container Apps + Cosmos DB	Local

Featured: Complete Learning Scenarios

Production-ready application templates mapped to learning chapters

Template	Learning Chapter	Complexity	Key Learning
openai-chat-app-quickstart	Chapter 2	⭐	Basic AI deployment patterns
azure-search-openai-demo	Chapter 2	⭐⭐	RAG implementation with Azure AI Search
ai-document-processing	Chapter 4	⭐⭐	Document Intelligence integration
agent-openai-python-prompty	Chapter 5	⭐⭐⭐	Agent framework and function calling
contoso-chat	Chapter 8	⭐⭐⭐	Enterprise AI orchestration
retail-multi-agent-solution	Chapter 5	⭐⭐⭐⭐	Multi-agent architecture with Customer and Inventory agents

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

🔧 Quick Troubleshooting Guide

Common issues beginners face and immediate solutions:

❌ "azd: command not found"

# 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

❌ "No subscription found" or "Subscription not set"

# 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

❌ "InsufficientQuota" or "Quota exceeded"

# 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"
}

❌ "azd up" fails halfway through

# 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

❌ "Authentication failed" or "Token expired"

# Re-authenticate
az logout
az login

azd auth logout
azd auth login

# Verify authentication
az account show

❌ "Resource already exists" or naming conflicts

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

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

❌ Template deployment taking too long

Normal wait times:

Simple web app: 5-10 minutes
App with database: 10-15 minutes
AI applications: 15-25 minutes (OpenAI provisioning is slow)

# Check progress
azd show

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

❌ "Permission denied" or "Forbidden"

# 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)

❌ Can't find deployed application URL

# 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:

Practical Exercise: Complete the chapter's hands-on deployment
Knowledge Check: Review the FAQ section for your chapter
Community Discussion: Share your experience in Azure Discord
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 →

Name		Name	Last commit message	Last commit date
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.vscode		.vscode
docs		docs
examples		examples
images		images
resources		resources
translated_images		translated_images
translations		translations
workshop		workshop
.gitignore		.gitignore
CODE_OF_CONDUCT.md		CODE_OF_CONDUCT.md
CONTRIBUTING.md		CONTRIBUTING.md
LICENSE		LICENSE
README.md		README.md
SECURITY.md		SECURITY.md
SUPPORT.md		SUPPORT.md
changelog.md		changelog.md
course-outline.md		course-outline.md
requirements-dev.txt		requirements-dev.txt

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microsoft/AZD-for-beginners

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AZD For Beginners: A Structured Learning Journey

Automated Translations (Always Up-to-Date)

🚀 What is Azure Developer CLI (azd)?

The Magic of azd up

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

Simple Analogy

When to Use Each

They Work Together!

🌟 Find Templates in Awesome AZD

Popular AI Templates from Awesome AZD

🎯 Getting Started in 3 Steps

Step 1: Install AZD (2 minutes)

Step 2: Login to Azure

Step 3: Deploy Your First App

Clean Up (Don't Forget!)

📚 How to Use This Course

Quick Setup

Course Overview

Why This Course is Essential for Modern Developers

Learning Objectives

🗺️ Course Map: Quick Navigation by Chapter

📚 Learning Chapters

🚀 Chapter 1: Foundation & Quick Start

What You'll Learn

Learning Resources

Practical Exercises

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

What You'll Learn

Learning Resources

Practical Exercises

💰 Cost Considerations for AI Deployments

⚙️ Chapter 3: Configuration & Authentication

What You'll Learn

Learning Resources

Practical Exercises

🏗️ Chapter 4: Infrastructure as Code & Deployment

What You'll Learn

Learning Resources

Practical Exercises

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

What You'll Learn

Learning Resources

Practical Exercises

🔍 Chapter 6: Pre-Deployment Validation & Planning

What You'll Learn

Learning Resources

Practical Exercises

🚨 Chapter 7: Troubleshooting & Debugging

What You'll Learn

Learning Resources

Practical Exercises

🏢 Chapter 8: Production & Enterprise Patterns

What You'll Learn

Learning Resources

Practical Exercises

🎓 Workshop Overview: Hands-On Learning Experience

Interactive Workshop Materials

🛠️ Workshop Features

📚 Workshop Module Structure

🚀 Getting Started with the Workshop

🎯 Workshop Learning Outcomes

📖 Workshop Resources

📖 Deep Dive: AZD Capabilities

AZD + Microsoft Foundry: Perfect for AI Deployments

🎯 Templates & Examples Library

Featured: Microsoft Foundry Templates

Featured: Complete Learning Scenarios

Learning by Example Type

Local Examples (Ready to Use)

Local Examples - Container Applications (Chapters 2-5)

External Examples - Simple Applications (Chapters 1-2)

External Examples - Database Integration (Chapter 3-4)

External Examples - Advanced Patterns (Chapters 4-8)

External Template Collections

The Magic of `azd up`

Packages