Production-ready Infrastructure as Code that empowers organizations to achieve more with edge AI solutions. Built by friendly geeks, for every team that needs edge solutions to achieve real production results.

• Platform Engineers building edge AI infrastructure at scale
• DevOps Teams deploying IoT and edge computing solutions
• Solution Architects designing hybrid cloud-edge systems
• Every organization that needs edge infrastructure solutions that actually deliver production results

Start here if you want to achieve rapid deployment with existing blueprints to Azure. Time: 30-60 minutes

Start here if you're combining components to achieve new deployment scenarios. Time: 2-4 hours

Start here if you're developing new components to help others achieve more. Time: 1-2 days setup

graph TD
    Start([Target: Edge AI Solutions])

    subgraph experience [Your Experience Level]
        Beginner[New to Edge AI<br/>Need to learn<br/>fundamentals]
        Intermediate[Some Experience<br/>Want to deploy<br/>quickly]
        Advanced[Expert Level<br/>Building custom<br/>solutions]
    end

    subgraph learning [Learning Platform]
        Foundation[Foundation Katas<br/>AI-Assisted Engineering<br/>15-45 min each]
        Skills[Core Skills<br/>Task Planning<br/>ADR Creation<br/>Prompt Engineering]
        Application[Applied Practice<br/>Edge Deployment Labs<br/>2-50+ hours]
    end

    subgraph deployment [Deployment Path]
        QuickDeploy[Quick Deploy<br/>Use existing<br/>blueprints<br/>30-60 minutes]
        CustomBuild[Custom Solutions<br/>Combine<br/>components<br/>2-4 hours]
        NewFeatures[Feature Development<br/>Create new<br/>components<br/>1-2 days]
    end

    subgraph outcomes [Outcomes]
        Production[Production Systems<br/>Reliable edge AI<br/>solutions]
        Expertise[Team Expertise<br/>AI-assisted<br/>engineering skills]
        Community[Community Impact<br/>Contributions &<br/>improvements]
    end

    Start --> Beginner
    Start --> Intermediate
    Start --> Advanced

    Beginner --> Foundation
    Foundation --> Skills
    Skills --> Application
    Application --> QuickDeploy

    Intermediate --> QuickDeploy
    Intermediate --> CustomBuild

    Advanced --> CustomBuild
    Advanced --> NewFeatures

    %% Learning enhances all paths
    Foundation -.-> QuickDeploy
    Skills -.-> CustomBuild
    Application -.-> NewFeatures

    QuickDeploy --> Production
    CustomBuild --> Production
    NewFeatures --> Production

    Application --> Expertise
    NewFeatures --> Community

    %% Enhanced color scheme for learning journey
    style Start fill:#e1f5fe,stroke:#01579b,stroke-width:3px
    style Beginner fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px
    style Intermediate fill:#fff3e0,stroke:#e65100,stroke-width:2px
    style Advanced fill:#e8f5e8,stroke:#2e7d32,stroke-width:2px
    style Foundation fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px
    style Skills fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px
    style Application fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px
    style QuickDeploy fill:#e8f5e8,stroke:#2e7d32,stroke-width:2px
    style CustomBuild fill:#fff3e0,stroke:#e65100,stroke-width:2px
    style NewFeatures fill:#fff3e0,stroke:#e65100,stroke-width:2px
    style Production fill:#cffafe,stroke:#059669,stroke-width:2px
    style Expertise fill:#cffafe,stroke:#059669,stroke-width:2px
    style Community fill:#cffafe,stroke:#059669,stroke-width:2px

📦 edge-ai/
├── 📋 blueprints/          # Ready-to-deploy solution templates
├── 📚 docs/                # Complete documentation and guides
├── 🏗️  src/                # Reusable infrastructure components
├── 🧪 tests/               # Testing and validation
├── 🤖 scripts/             # Automation and utilities
└── 🚢 deploy/              # CI/CD pipelines and automation

Modular, reusable building blocks:

• Cloud services (identity, data, messaging, observability)
• Edge platforms (Kubernetes, Azure IoT Operations)
• Application frameworks (AI inference, telemetry)

Complete solution templates:

• Single-node edge deployments
• Multi-node cluster setups
• Cloud-only configurations
• Minimal proof-of-concept setups

Everything you need to know:

• Getting started guides for different roles
• Architecture decisions and design patterns
• Contributing guidelines and development workflow

Prerequisites: Docker, VS Code, and GitHub Copilot (seriously, this repo is optimized for AI-assisted development)

# Clone and open in VS Code
git clone https://github.com/Microsoft/edge-ai.git
cd edge-ai
code .

# When prompted, "Reopen in Container"
# Everything gets installed automatically 🎉

Alternative: Manual setup instructions (for the brave)

Note on Telemetry: If you wish to opt-out of sending telemetry data to Microsoft when deploying Azure resources with Terraform, you can set the environment variable ARM_DISABLE_TERRAFORM_PARTNER_ID=true before running any terraform commands.

• Actually works in production - empowering real deployments
• Modular design - enabling teams to build custom solutions that meet business needs
• AI-assisted development - optimized for GitHub Copilot to accelerate every engineer's productivity
• Multiple IaC frameworks - Terraform & Bicep
• Comprehensive testing - because empowering reliable edge infrastructure deployments is our mission

Share our AI instructions, chatmodes, and prompts across your projects with a simple dev container setup:

Step 1: Clone both repositories into the same workspace

git clone https://github.com/Microsoft/edge-ai.git
git clone https://github.com/<your-organization>/<your-project>.git  # Replace with your own repository URL

Step 2: Add mount to your project's devcontainer.json

{
  "mounts": [
    "source=${localWorkspaceFolder}/../edge-ai,target=/workspaces/edge-ai,type=bind,consistency=cached"
  ]
}

Step 3: Update your project's .vscode/settings.json

{
  "chat.modeFilesLocations": {
    ".github/chatmodes": true,
    "../edge-ai/.github/chatmodes": true
  },
  "chat.instructionsFilesLocations": {
    ".github/instructions": true,
    "../edge-ai/.github/instructions": true
  },
  "chat.promptFilesLocations": {
    ".github/prompts": true,
    "../edge-ai/.github/prompts": true
  }
}

Result: Rebuild your dev container and gain instant access to:

• ✅ Task researcher and task planner modes
• ✅ AI-assisted engineering workflows
• ✅ Coding standards and conventions
• ✅ Always up-to-date - no file copying needed

💡 Perfect for teams wanting to adopt AI-assisted development patterns without duplicating files across repositories.

Empower your team to achieve proficiency in AI-assisted, hyper-velocity engineering through hands-on training labs and focused practice exercises (Katas).

This Learning Platform combines AI assistance with practical engineering challenges, empowering every engineer to achieve more and ensuring that learning translates directly into real-world engineering capabilities and better contributions to Edge-AI.

The Learning Platform provides challenge-based learning for edge-to-cloud AI systems:

• 🥋 Katas - Focused 15-45 minute practice exercises
• 🧪 Training Labs - Comprehensive 2-8 hour hands-on experiences (Coming Soon)
• 🤖 AI Coaching - Built-in coaching prompts for discovery-based learning

One-click training mode - launch documentation with automatic navigation to Learning Platform:

npm run docs

This command automatically:

• ✅ Builds the documentation
• ✅ Starts the local server
• ✅ Opens your browser directly to the documentation site
• ✅ Navigate to the Learning section to access all learning paths and resources

We ❤️ contributions! Whether you're fixing typos or adding new components:

1. Read our Contributing Guide
2. Check out open issues
3. Join the discussion

Microsoft encourages customers to review its Responsible AI Standard when developing AI-enabled systems to ensure ethical, safe, and inclusive AI practices. Learn more at Microsoft's Responsible AI.

This project is licensed under the MIT License.

Security: See SECURITY.md for security policy and reporting vulnerabilities.

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.

🤖 Crafted with precision by ✨Copilot following brilliant human instruction, then carefully refined by our team of discerning human reviewers.