🍞 BakeWise - Multi-Service Architecture

Welcome to BakeWise, an advanced AI-powered platform for bakery management and optimization. This project implements a microservices architecture with multiple interconnected services to provide comprehensive bakery management solutions.

🚀 Quick Start

Prerequisites

• Docker Desktop with Kubernetes enabled
• Docker Compose
• Node.js (for frontend development)

Running the Application

1. Clone the repository:

   git clone <repository-url>
   cd bakery-ia
   

2. Set up environment variables:

   cp .env.example .env
   # Edit .env with your specific configuration
   

3. Run with Docker Compose:

   docker-compose up --build
   

4. Or run with Kubernetes (Docker Desktop):

   # Enable Kubernetes in Docker Desktop
   # Run the setup script
   ./scripts/setup-kubernetes-dev.sh
   

🏗️ Architecture Overview

The project follows a microservices architecture with the following main components:

• Frontend: React-based dashboard for user interaction
• Gateway: API gateway handling authentication and routing
• Services: Multiple microservices handling different business domains
• Infrastructure: Redis, RabbitMQ, PostgreSQL databases

🐳 Kubernetes Infrastructure

🛠️ Services

The project includes multiple services:

• Auth Service: Authentication and authorization
• Tenant Service: Multi-tenancy management
• Sales Service: Sales processing
• External Service: Integration with external systems
• Training Service: AI model training
• Forecasting Service: Demand forecasting
• Notification Service: Notifications and alerts
• Inventory Service: Inventory management
• Recipes Service: Recipe management
• Suppliers Service: Supplier management
• POS Service: Point of sale
• Orders Service: Order management
• Production Service: Production planning
• Alert Processor: Background alert processing

📊 Monitoring

The system includes comprehensive monitoring with:

• Prometheus for metrics collection
• Grafana for visualization
• ELK stack for logging (planned)

🚀 Production Deployment

For production deployment on clouding.io with Kubernetes:

1. Set up your clouding.io Kubernetes cluster
2. Update image references to your container registry
3. Configure production-specific values
4. Deploy using the production kustomization:

   kubectl apply -k infrastructure/environments/prod/k8s-manifests
   

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

📄 License

This project is licensed under the MIT License.