NimbusX is a cloud resource optimization and auto-scaling simulator designed to mimic real-world cloud infrastructure behavior. It enables users to monitor system metrics, simulate dynamic workloads, and apply intelligent scaling strategies to optimize performance and cost.

Built using Java (Spring Boot) and React, NimbusX helps developers understand how modern cloud platforms handle auto-scaling, resource allocation, and cost optimization.

• 📊 Real-time CPU and memory monitoring (simulated workloads)
• ⚙️ Intelligent auto-scaling based on dynamic thresholds
• 💰 Cost optimization engine with resource usage insights
• 📈 Interactive dashboard with live metrics visualization
• 🕒 Historical data tracking and performance analysis
• 🧩 Modular architecture for open-source contributions

Backend

• Java (Spring Boot)
• Spring Web, Spring Data JPA
• Spring Scheduler
• WebSockets (STOMP)

Frontend

• React (Vite)
• Chart.js / Recharts

Database

• PostgreSQL

Optional

• Docker (for service simulation)
• Deployment: Render / Vercel / Supabase

Frontend (React Dashboard)
        ↓
Spring Boot Backend
        ↓
---------------------------------
| Metrics Engine (Simulation)   |
| Auto Scaling Engine           |
| Cost Optimization Engine      |
---------------------------------
        ↓
PostgreSQL Database

• Java 17+
• Node.js 18+
• PostgreSQL

cd backend
./mvnw spring-boot:run

cd frontend
npm install
npm run dev

• Create a PostgreSQL database
• Update credentials in application.properties

backend/
 ├── controller/
 ├── service/
 ├── scheduler/
 ├── model/
 ├── repository/
 ├── scaling/
 └── cost/

frontend/
 ├── components/
 ├── pages/
 ├── charts/
 └── services/

NimbusX is designed to be beginner-friendly and modular.

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

• good first issue → Beginner-friendly
• medium → Intermediate tasks
• advanced → Complex features

• Scaling algorithms (auto-scale logic)
• Metrics simulation improvements
• UI/UX enhancements
• Cost optimization strategies
• Real-time data handling

• Basic service & metrics simulation
• Auto-scaling engine implementation
• Cost optimization module
• Real-time dashboard (WebSockets)
• Advanced scaling strategies
• Predictive scaling (future scope)

Please follow respectful and collaborative practices while contributing.

This project is licensed under the MIT License.

Inspired by modern cloud platforms and auto-scaling systems used in real-world distributed architectures.

If you find this project useful, consider giving it a star ⭐ and contributing!