InfraBlocks is a modern drag-and-drop infrastructure design platform that lets you visually create, configure, and deploy cloud resources across AWS, GCP, and Azure. With an AI agent called Rex, automated Terraform generation, and real-time deployment capabilities, it simplifies cloud infrastructure management for everyone by removing technical barriers and making powerful tools accessible to all. Whether you’re a beginner exploring cloud services or an experienced developer seeking faster workflows, InfraBlocks provides an intuitive, visual way to build and launch infrastructure without needing deep certifications or complex configuration steps.

• Drag & Drop Interface: Intuitive canvas for building cloud architectures
• Multi-Cloud Support: AWS, Google Cloud Platform, and Microsoft Azure
• Service Catalog: Pre-configured cloud services with icons and templates
• Connection Validation: Smart connection suggestions and validation
• Real-time Configuration: Live editing of resource configurations

• Natural Language Processing: Describe your infrastructure needs in plain English
• Intelligent Suggestions: AI recommends optimal architectures and connections
• Automated Creation: Generate infrastructure from conversations
• Best Practices: Built-in guidance for security and performance

• Terraform Generation: Automatic conversion to production-ready Terraform
• Multi-File Output: Organized main.tf, variables.tf, outputs.tf, and providers.tf
• Configuration Management: Visual configuration panels with validation
• Version Control Ready: Export clean, maintainable infrastructure code

• One-Click Deployment: Direct deployment to cloud providers
• Real-time Status: Live deployment progress and status monitoring
• Credential Management: Secure storage and validation of cloud credentials
• Project Organization: Multi-project workspace with version history

• Frontend: Next.js 14, React 18, TypeScript
• UI Components: Radix UI, Tailwind CSS, Lucide Icons
• Canvas: React Flow (XY Flow) for visual editing
• AI Integration: OpenAI GPT for intelligent assistance
• State Management: Zustand for global state
• Validation: Zod for schema validation
• Infrastructure: Terraform generation and deployment
• Cloud SDKs: AWS, GCP, and Azure APIs

• Node.js 18+ and npm/yarn
• Cloud provider accounts (AWS, GCP, or Azure)
• OpenAI API key (for AI features)

# Clone the repository
git clone https://github.com/yourusername/CodeBlocks.git
cd CodeBlocks

# Install dependencies
npm install

# Set up environment variables
cp .env.example .env.local
# Edit .env.local with your API keys

# Start the development server
npm run dev

# OpenAI Configuration (for AI features)
OPENAI_API_KEY=your_openai_api_key_here

# Optional: Custom API endpoints
NEXT_PUBLIC_API_URL=http://localhost:3000

• Click "Create Project" on the dashboard
• Choose your cloud provider (AWS, GCP, or Azure)
• Name your project and add a description

• Drag & Drop: Drag services from the sidebar to the canvas
• Connect Services: Click and drag between service handles to create connections
• Configure Resources: Double-click any service to open its configuration panel
• Use AI Assistant: Click the brain icon to get AI-powered suggestions

• View auto-generated Terraform in the right panel
• Switch between main.tf, variables.tf, outputs.tf, and providers.tf
• Download individual files or complete Terraform package

• Set up cloud credentials in Settings
• Click the play button to deploy directly to your cloud provider
• Monitor deployment progress in real-time

• Ask for Help: "Create a web application with database and load balancer"
• Get Recommendations: AI suggests optimal service configurations
• Auto-Generate: Convert conversations into visual infrastructure
• Best Practices: Receive guidance on security and performance

• Compute: EC2, Lambda, Auto Scaling Groups
• Storage: S3, EBS, EFS
• Database: RDS, DynamoDB
• Networking: VPC, ALB, API Gateway
• Messaging: SQS, SNS
• Security: IAM, Security Groups

• Compute: Compute Engine, Cloud Functions
• Storage: Cloud Storage, Persistent Disks
• Database: Cloud SQL, Firestore
• Networking: VPC, Load Balancers

• Compute: Virtual Machines, Azure Functions
• Storage: Blob Storage, Managed Disks
• Database: Azure SQL, Cosmos DB
• Networking: Virtual Network, Application Gateway

The AI assistant understands natural language requests:

"Create a web application architecture"
"Add a database to my current setup"
"Set up monitoring for my services"
"What's the best way to scale this architecture?"
"Generate a CI/CD pipeline"
"Review my architecture for security best practices"

├── app/                    # Next.js app directory
│   ├── api/               # API routes
│   ├── layout.tsx         # Root layout
│   └── page.tsx           # Home page
├── components/            # React components
│   ├── agent-chat.tsx     # AI assistant chat
│   ├── cloud-service-node.tsx # Visual service nodes
│   ├── dashboard.tsx      # Main dashboard
│   ├── infrastructure-canvas.tsx # Visual editor
│   ├── terraform-generator.ts # Terraform code generation
│   └── ui/               # UI components
├── lib/                   # Utility libraries
│   ├── api-service.ts     # Cloud API integrations
│   ├── config-loader.ts   # Service configurations
│   ├── credential-manager.ts # Secure credential storage
│   ├── infrastructure-manager.ts # Canvas state management
│   └── openai-agent.ts    # AI integration
├── types/                 # TypeScript type definitions
└── public/               # Static assets
    └── aws/              # Cloud service icons
    └── gcp/
    └── azure/

1. AWS: Configure access keys in Settings → Cloud Credentials
2. GCP: Set up service account JSON credentials
3. Azure: Configure subscription and service principal credentials

Add new services by creating configuration files in /lib/services/:

{
  "id": "new-service",
  "name": "New Service",
  "icon": "/path/to/icon.svg",
  "category": "Compute",
  "description": "Service description",
  "terraformType": "resource_type",
  "configSchema": {
    "instance_type": {
      "type": "select",
      "label": "Instance Type",
      "options": ["t3.micro", "t3.small", "t3.medium"]
    }
  }
}

# Run unit tests
npm test

# Run integration tests
npm run test:integration

# Run end-to-end tests
npm run test:e2e

# Build the application
npm run build

# Start production server
npm start

# Build Docker image
docker build -t infrablocks .

# Run container
docker run -p 3000:3000 -e OPENAI_API_KEY=your_key infrablocks

We welcome contributions! Please see our Contributing Guide for details.

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Make your changes and add tests
4. Commit your changes: git commit -m 'Add amazing feature'
5. Push to the branch: git push origin feature/amazing-feature
6. Open a Pull Request

• We use ESLint and Prettier for code formatting
• Run npm run lint to check code style
• Run npm run format to auto-format code

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

• 📧 Email: support@infrablocks.dev
• 💬 Discord: Join our community
• 🐛 Issues: GitHub Issues
• 📖 Docs: Documentation

• Multi-region deployment support
• Infrastructure cost estimation
• Team collaboration features
• Custom service templates
• Integration with GitOps workflows
• Infrastructure testing and validation
• Kubernetes support
• Infrastructure drift detection

• React Flow for the amazing visual editing experience
• Radix UI for accessible UI components
• OpenAI for AI capabilities
• Terraform for infrastructure as code
• All the amazing open-source contributors

Built with ❤️ by the InfraBlocks team

Transform your cloud infrastructure with visual design and AI assistance