AZD For Beginners: A Structured Learning Journey

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Prefer to Clone Locally?

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Bash / macOS / Linux:
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cd AZD-for-beginners
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git sparse-checkout set --no-cone "/*" "!translations" "!translated_images"
Dis go give you wetin you need to finish di course plus faster download.

🆕 Wetin New for azd Today

Azure Developer CLI don grow pass just normal web apps and APIs. Today, azd na di single tool wey fit deploy any application to Azure — including AI-powered applications and intelligent agents.

Wetin dis mean for you:

AI agents don turn first-class azd workloads. You fit initialize, deploy, and manage AI agent projects using the same azd init → azd up workflow wey you don sabi.
Microsoft Foundry integration don bring model deployment, agent hosting, and AI service configuration straight into di azd template ecosystem.
Di core workflow never change. Whether you dey deploy todo app, microservice, or multi-agent AI solution, di commands still be di same.

If you don use azd before, AI support na natural extension — no be separate tool or one advanced track. If you dey start fresh, you go learn one workflow wey dey work for everything.

🚀 Wetin be Azure Developer CLI (azd)?

Azure Developer CLI (azd) na developer-friendly command-line tool wey dey make am easy to deploy applications to Azure. Instead of you dey manually create and connect plenti Azure resources, you fit deploy complete applications with just one command.

Di Magic of `azd up`

# Dis one command dey do everytin:
# ✅ E go create all Azure resources
# ✅ E go arrange networking and security
# ✅ E go build your application code
# ✅ E go deploy am to Azure
# ✅ E go give you beta working URL
azd up

Na so e be! No need click for Azure Portal, no complex ARM templates to learn first, no manual configuration — just working applications for Azure.

❓ Azure Developer CLI vs Azure CLI: Wetin Different?

Na di question wey beginners dey ask pass. See di 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 na like get all di tools to build house - hammers, saws, nails. You fit build anything, but you gots sabi construction.
Azure Developer CLI na like hire contractor - you talk wetin you want, dem go handle di 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`

Dem Dey Work Together!

AZD dey use Azure CLI under di hood. You fit use both:

# Deploy your app wit AZD
azd up

# Den adjust specific resources wit Azure CLI
az webapp config set --name myapp --always-on true

🌟 Find Templates in Awesome AZD

No start from scratch! Awesome AZD na 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 Chát wit Microsoft Foundry Models + AI Search
azd init --template azure-search-openai-demo

# Quick AI Chát Applikeshn
azd init --template openai-chat-app-quickstart

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

🎯 How to Start: 3 Steps

Before you start, make sure your machine ready for the template you wan deploy:

Windows:

.\validate-setup.ps1

macOS / Linux:

bash ./validate-setup.sh

If any required check fail, fix am first before you 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

# Na Optional if you wan use Azure CLI commands direct for dis course
az login

# E dey required for AZD workflows
azd auth login

If you no sure which one you need, follow the full setup flow for Installation & Setup.

Step 3: Deploy Your First App

# Start from one template
azd init --template todo-nodejs-mongo

# Put for Azure (e go create everytin!)
azd up

🎉 Na so! Your app don dey live for Azure.

Clean Up (No Forget!)

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

📚 How to Use This Course

Dis course design for progressive learning — start where you comfortable and dey 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?

Dis repo get pass 50 language translations wey dey make di download big. If you wan clone without di 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'
Dis go give you wetin you need to finish di course plus faster download.

Course Overview

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

Why Dis Course Dey Important for Modern Developers

Based on Microsoft Foundry Discord community insights, 45% of developers wan use AZD for AI workloads but dem dey face challenges like:

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 finishing dis structured course, you go:

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 say you get di following things in place. Di installation steps wey dey later for dis guide dey assume say these basics don already handle.

Wan Azure subscription: You fit use one wey don dey for work or your own account, or create a free trial to start.
Permission to create Azure resources: For most exercises, make sure sey you get at least Contributor access for the subscription or resource group wey you dey target. Some chapters fit also assume say you fit create resource groups, managed identities, and RBAC assignments.
Wan GitHub account: Dis go help you to fork the repository, track your own changes, and use GitHub Codespaces for the workshop.
Template runtime prerequisites: Some templates need local tools like Node.js, Python, Java, or Docker. Run the setup validator before you start so you go fit catch missing tools early.
Basic terminal familiarity: You no need be expert, but you suppose sabi run commands like git clone, azd auth login, and azd up.

You dey work for enterprise subscription? If administrator dey manage your Azure environment, make you confirm beforehand sey you fit deploy resources for the subscription or resource group wey you wan use. If no, ask for 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 go fit finish the exercises end-to-end without waiting for tenant-level approvals.

🗺️ Course Map: Quick Navigation by Chapter

Each chapter get im own README wey get 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

Choose your learning path based on your experience level and goals

🚀 Chapter 1: Foundation & Quick Start

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

Wetin You Go Learn

Understand Azure Developer CLI basics
How to install AZD for your platform
How to make 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 check make sure say installation dey okay
azd version

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

💡 Chapter Outcome: You go fit deploy small web application to Azure using AZD

✅ Success Validation:

# After you don finish Chapter 1, you go fit:
azd version              # Dey show di installed version
azd init --template todo-nodejs-mongo  # Dey initialize di project
azd up                  # Dey deploy go Azure
azd show                # Dey show di running app URL
# Di application go open for browser and e go work
azd down --force --purge  # Dey clean up resources

📊 Time Investment: 30-45 minutes
📈 Skill Level After: Fit deploy basic applications by yourself 📈 Skill Level After: Fit deploy basic applications by yourself

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

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

Wetin You Go Learn

Microsoft Foundry integration with AZD
How to deploy AI-powered applications
Understand AI service configurations

Learning Resources

🎯 Start Here: Microsoft Foundry Integration
🤖 AI Agents: AI Agents Guide - How to deploy intelligent agents with AZD
📖 Patterns: AI Model Deployment - How to 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

# Put your first AI app live
azd init --template azure-search-openai-demo
azd up

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

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

✅ Success Validation:

# After Chapter 2, you go fit:
azd init --template azure-search-openai-demo
azd up
# Try the AI chat interface
# Ask question dem, then AI go give you answer wey get source
# Confirm say search integration dey work
azd monitor  # Check say Application Insights dey show telemetry
azd down --force --purge

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

💰 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 you no dey actively develop
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 wetin you use

Cost Monitoring:

# Check di estimated cost wey go dey every month
azd provision --preview

# Dey monitor di real costs inside Azure Portal
az consumption budget list --resource-group <your-rg>

⚙️ Chapter 3: Configuration & Authentication

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

Wetin You Go Learn

How to manage environment configuration
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 correct authentication and security

🏗️ Chapter 4: Infrastructure as Code & Deployment

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

Wetin You Go 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: ⭐⭐⭐⭐

Wetin You Go 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 di full retail solution wey get many agents
cd examples/retail-multiagent-arm-template
./deploy.sh

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

💡 Chapter Outcome: Deploy and manage 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: ⭐⭐

Wetin You Go Learn

Plan capacity and check resources
Ways to choose SKU dem
Checks wey you go run before deployment and automation

Resources wey You Go Use

📊 Planning: Capacity Planning - Check resources
💰 Selection: SKU Selection - Choices wey cost-effective
✅ Validation: Pre-flight Checks - Automated scripts

Practical Exercises

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

💡 Chapter Outcome: Check and make deployments better before you run dem

🚨 Chapter 7: Troubleshooting & Debugging

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

Wetin You Go Learn

Step-by-step debugging approaches
Common problems and how to solve dem
Troubleshooting wey concern AI

Resources wey You Go Use

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

Practical Exercises

Diagnose deployment failures
Resolve authentication issues
Debug AI service connectivity

💡 Chapter Outcome: Fit diagnose and fix common deployment issues by yourself

🏢 Chapter 8: Production & Enterprise Patterns

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

Wetin You Go Learn

Strategies for production deployment
Enterprise-level security patterns
Monitoring and cost-saving optimization

Resources wey You Go Use

🏭 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 apps wey ready for enterprise with full production capabilities

🎓 Workshop Overview: Hands-On Learning Experience

⚠️ WORKSHOP STATUS: Active Development
The workshop materials dem still dey under development and refinement. Core modules dey work, but some advanced sections never finish. We dey actively work to finish everything. See progress →

Interactive Workshop Materials

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

Our workshop materials dey provide structured, interactive learning wey go complement di chapter-based curriculum wey dey top. Di workshop design fit for self-paced learning or instructor-led sessions.

🛠️ Workshop Features

Browser-Based Interface: Complete MkDocs-powered workshop wey get search, copy, and theme features
GitHub Codespaces Integration: One-click setup for development environment
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

Di workshop follow an 8-module progressive methodology wey go carry you from discovery reach deployment mastery:

Module	Topic	Wetin You Go 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

🚀 How to Start the Workshop

# Option 1: GitHub Codespaces (We dey recommend am)
# Click "Code" → "Create codespace on main" for di repository

# Option 2: Local Development (Work for your komputa)
git clone https://github.com/microsoft/azd-for-beginners.git
cd azd-for-beginners/workshop
# Follow di setup instructions wey dey for workshop/README.md

🎯 Wetin You Go Gain from the Workshop

By finishing the workshop, participants go:

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 - Exercises wey focus on AI
💡 Quick Start: Workshop Setup Guide - Environment configuration

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

📖 Deep Dive: AZD Capabilities

Pass di basics, AZD get 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 tackle di main challenges wey AI developers dey face:

AI-Ready Templates - Pre-configured templates for Microsoft Foundry Models, 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 dey deploy AI applications!

Note: These templates dey show different AI patterns. Some be external Azure Samples, others na 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 wey map 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

How You Go Learn by Example

📌 Local vs. External Examples:
Local Examples (inside 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)

Complete container deployment examples for 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 start:

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 - Patterns wey dem dey use to connect database
Functions + Cosmos DB - Data workflow wey no need server

External Examples - Advanced Patterns (Chapters 4-8)

Java Microservices - Architectures wey get many services
Container Apps Jobs - Processing wey dey run for background
Enterprise ML Pipeline - ML patterns wey ready for production

External Template Collections

Official AZD Template Gallery - Collection wey dem choose well of official and community templates
Azure Developer CLI Templates - Microsoft Learn documentation for templates
Examples Directory - Local learning examples wey get detailed explanations

📚 Learning Resources & References

Quick References

Command Cheat Sheet - Important azd commands wey dem arrange by chapter
Glossary - Words and meanings for Azure and azd
FAQ - Common questions wey dem arrange by learning chapter
Study Guide - Wide set of practice exercises

Hands-On Workshops

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

External Learning Resources

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. Fit install dem for GitHub Copilot, Cursor, Claude Code, or any agent wey support am:
```
npx skills add microsoft/github-copilot-for-azure
```

🔧 Quick Troubleshooting Guide

Common problems wey beginners dey face and quick solutions:

❌ "azd: command not found"

# First make you install AZD
# Windows (PowerShell):
winget install microsoft.azd

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

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

# Make sure say e don install
azd version

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

# Show di subscriptions wey dey available
az account list --output table

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

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

# Check am
az account show

❌ "InsufficientQuota" or "Quota exceeded"

# Try use another Azure region
azd env set AZURE_LOCATION "westus2"
azd up

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

❌ "azd up" fails halfway through

# Option 1: Clear am, try again
azd down --force --purge
azd up

# Option 2: Just fix di infrastructure
azd provision

# Option 3: Check di detailed status
azd show

# Option 4: Check di logs for Azure Monitor
azd monitor --logs

❌ "Authentication failed" or "Token expired"

# Make you sign in again for AZD
azd auth logout
azd auth login

# If you want: refresh di Azure CLI too if you dey run az commands
az logout
az login

# Make sure say you don sign in
az account show

❌ "Resource already exists" or naming conflicts

# AZD dey generate unique names, but if e get conflict:
azd down --force --purge

# Den try again wit fresh environment
azd env new dev-v2
azd up

❌ Template deployment dey take too long

Normal time wey e dey take:

Simple web app: 5-10 minutes
App wey get database: 10-15 minutes
AI apps: 15-25 minutes (OpenAI provisioning dey slow)

# Check how e dey go
azd show

# If you dey stuck pass 30 minutes, check Azure Portal:
azd monitor --overview
# Find di deployments wey fail

❌ "Permission denied" or "Forbidden"

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

# You suppose get at least "Contributor" role
# Tell your Azure admin make em give you:
# - Contributor (so e fit manage resources)
# - User Access Administrator (so e fit assign roles)

❌ No fit find deployed application URL

# Make e show all service endpoints
azd show

# Or open di Azure Portal
azd monitor

# Check di specific service
azd env get-values
# Find di *_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 how you dey progress for 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 you don finish each chapter, make you verify wetin you don learn by:

Practical Exercise: Do the chapter hands-on deployment
Knowledge Check: Review the FAQ section for your chapter
Community Discussion: Share your experience for Azure Discord
Next Chapter: Move go the next complexity level

Course Completion Benefits

When you don finish all chapters, you go get:

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 wan use AZD for AI workloads
Main wahalas: Multi-service deployments, credential management, production readiness
Wetin dem dey request pass: AI-specific templates, troubleshooting guides, best practices

Join our community make you fit:

Share your AZD + AI experiences and get help
See early previews of new AI templates
Help add to AI deployment best practices
Fit influence future AI + AZD feature development

Contributing to the Course

We dey happy when people contribute! Abeg read our Contributing Guide for details on:

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

📄 Course Information

License

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

Related Microsoft Learning Resources

Our team dey produce other complete learning courses:

LangChain

Azure / Edge / MCP / Agents

Generative AI Series

Core Learning

Copilot Series

🗺️ How to waka di Course

🚀 You ready to start learn?

Pipul wey dey start: Start wit Chapter 1: Foundation & Quick Start
Developers wey dey do AI: Jump go Chapter 2: AI-First Development
Developers wey don get experience: Begin wit Chapter 3: Configuration & Authentication

Wetin next: Start Chapter 1 - AZD Basics →

Disclaimer: Dis dokument don translate wit AI translation service Co-op Translator. Even tho we dey try make am correct, abeg sabi say automatic translations fit get errors or inaccuracies. Di original dokument for im native language na di authoritative source. If na critical information, make person wey sabi do professional human translation do am. We no go liable for any misunderstanding or misinterpretation wey fit come from di use of dis translation.

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AZD For Beginners: A Structured Learning Journey

Automated Translations (Always Up-to-Date)

🆕 Wetin New for azd Today

🚀 Wetin be Azure Developer CLI (azd)?

Di Magic of azd up

❓ Azure Developer CLI vs Azure CLI: Wetin Different?

Simple Analogy

When to Use Each

Dem Dey Work Together!

🌟 Find Templates in Awesome AZD

Popular AI Templates from Awesome AZD

🎯 How to Start: 3 Steps

Step 1: Install AZD (2 minutes)

Step 2: Authenticate for AZD

Step 3: Deploy Your First App

Clean Up (No Forget!)

📚 How to Use This Course

Quick Setup

Course Overview

Why Dis Course Dey Important for Modern Developers

Learning Objectives

Before You Start: Accounts, Access, and Assumptions

🗺️ Course Map: Quick Navigation by Chapter

📚 Learning Chapters

🚀 Chapter 1: Foundation & Quick Start

Wetin You Go Learn

Learning Resources

Practical Exercises

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

Wetin You Go Learn

Learning Resources

Practical Exercises

💰 Cost Considerations for AI Deployments

⚙️ Chapter 3: Configuration & Authentication

Wetin You Go Learn

Learning Resources

Practical Exercises

🏗️ Chapter 4: Infrastructure as Code & Deployment

Wetin You Go Learn

Learning Resources

Practical Exercises

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

Wetin You Go Learn

Learning Resources

Practical Exercises

🔍 Chapter 6: Pre-Deployment Validation & Planning

Wetin You Go Learn

Resources wey You Go Use

Practical Exercises

🚨 Chapter 7: Troubleshooting & Debugging

Wetin You Go Learn

Resources wey You Go Use

Practical Exercises

🏢 Chapter 8: Production & Enterprise Patterns

Wetin You Go Learn

Resources wey You Go Use

Practical Exercises

🎓 Workshop Overview: Hands-On Learning Experience

Interactive Workshop Materials

🛠️ Workshop Features

📚 Workshop Module Structure

🚀 How to Start the Workshop

🎯 Wetin You Go Gain from the Workshop

📖 Workshop Resources

📖 Deep Dive: AZD Capabilities

AZD + Microsoft Foundry: Perfect for AI Deployments

🎯 Templates & Examples Library

Featured: Microsoft Foundry Templates

Featured: Complete Learning Scenarios

How You Go Learn by Example

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)

Di Magic of `azd up`