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Architecture Overview

This document provides a comprehensive overview of the Cyber Training Platform's architecture.

System Architecture

High-Level Overview

┌─────────────────┐     ┌──────────────┐     ┌─────────────────┐
│    Frontend     │────▶│    Backend   │────▶│    Database     │
│    (React)      │     │   (FastAPI)  │     │  (PostgreSQL)   │
└─────────────────┘     └──────────────┘     └─────────────────┘
                              │
                              │
                        ┌─────▼─────┐
                        │ VirtualBox │
                        │    API    │
                        └───────────┘

The platform is built on a modern, scalable architecture with four main components:

  1. Frontend: React-based SPA with TypeScript
  2. Backend: FastAPI application
  3. Database: PostgreSQL for data persistence
  4. VM Management: VirtualBox API integration

Component Details

1. Frontend Architecture

frontend/
├── src/
│   ├── components/       # Reusable UI components
│   ├── pages/           # Route-based page components
│   ├── hooks/           # Custom React hooks
│   ├── services/        # API integration
│   ├── store/           # State management
│   └── utils/           # Helper functions
└── public/              # Static assets

Key Features:

  • React with TypeScript for type safety
  • Redux for state management
  • React Router for navigation
  • Material-UI for consistent styling
  • WebSocket integration for real-time updates

2. Backend Architecture

backend/
├── app/
│   ├── api/            # REST endpoints
│   ├── core/           # Core business logic
│   ├── models/         # Database models
│   ├── services/       # External service integration
│   └── utils/          # Helper functions
└── tests/              # Test suite

Key Features:

  • FastAPI for high-performance async operations
  • SQLAlchemy for ORM
  • Pydantic for data validation
  • JWT-based authentication
  • Role-based access control

3. Database Schema

-- Core Tables
users
├── id          (PK)
├── username
├── email
└── role

labs
├── id          (PK)
├── name
├── user_id     (FK → users.id)
├── status
└── created_at

vms
├── id          (PK)
├── lab_id      (FK → labs.id)
├── name
└── status

-- Association Tables
lab_templates
├── id          (PK)
├── name
└── config

user_labs
├── user_id     (FK → users.id)
└── lab_id      (FK → labs.id)

4. VM Management System

┌────────────────┐     ┌───────────────┐
│   VM Manager   │────▶│   VirtualBox  │
└────────────────┘     └───────────────┘
        │
        │
┌───────▼────────┐
│  VM Templates  │
└────────────────┘

Features:

  • Isolated network environments
  • Resource management
  • Snapshot capabilities
  • Template management

Security Architecture

Authentication Flow

┌──────────┐     ┌──────────┐     ┌──────────┐
│  Client  │────▶│   JWT    │────▶│ Resource │
└──────────┘     └──────────┘     └──────────┘
  1. User authentication via JWT
  2. Role-based access control
  3. Resource isolation
  4. Network security

Network Security

┌────────────┐     ┌─────────────┐     ┌──────────┐
│ Public Net │────▶│   Firewall  │────▶│ Lab Net  │
└────────────┘     └─────────────┘     └──────────┘
  • Isolated lab networks
  • Firewall rules
  • VPN access (optional)
  • HTTPS enforcement

Scalability

Horizontal Scaling

┌─────────────┐
│ Load        │
│ Balancer    │
└─────────────┘
      │
    ┌─┴─┐
┌───┴─┐ ├───┐
│ App │ │App │
└─────┘ └───┘
  • Container-based deployment
  • Load balancing
  • Database replication
  • Caching strategy

Resource Management

  • Dynamic resource allocation
  • Auto-scaling capabilities
  • Resource quotas
  • Performance monitoring

Data Flow

Request Flow

Client Request
     │
     ▼
Load Balancer
     │
     ▼
API Gateway
     │
     ▼
Authentication
     │
     ▼
Business Logic
     │
     ▼
Database/VM

WebSocket Flow

Client
  │
  ▼
WebSocket Server
  │
  ▼
Event Handler
  │
  ▼
VM Status Updates

Monitoring and Logging

System Monitoring

  • Prometheus metrics
  • Grafana dashboards
  • Resource utilization
  • Performance metrics

Logging

  • Centralized logging
  • Error tracking
  • Audit trails
  • Performance monitoring

Deployment Architecture

Production Environment

┌─────────────┐     ┌─────────────┐
│   CI/CD     │────▶│  Production │
└─────────────┘     └─────────────┘
                          │
                    ┌─────┴─────┐
                    │  Staging  │
                    └───────────┘
  • Containerized deployment
  • Blue-green deployment
  • Automated testing
  • Rolling updates

High Availability

  • Multiple availability zones
  • Database replication
  • Failover mechanisms
  • Backup strategies

Integration Points

External Services

  • Authentication providers
  • Storage services
  • Monitoring services
  • Backup services

APIs

  • REST API
  • WebSocket API
  • VirtualBox API
  • Management API

Future Considerations

Planned Improvements

  1. Microservices architecture
  2. Kubernetes orchestration
  3. Enhanced monitoring
  4. AI-powered assistance

Scalability Roadmap

  1. Multi-region support
  2. Enhanced caching
  3. Improved resource management
  4. Advanced analytics

Technical Decisions

Technology Choices

  1. Frontend: React + TypeScript

    • Type safety
    • Component reusability
    • Rich ecosystem

  2. Backend: FastAPI

    • Async support
    • High performance
    • OpenAPI documentation

  3. Database: PostgreSQL

    • ACID compliance
    • Rich feature set
    • Reliability

  4. VM Management: VirtualBox

    • Open source
    • Rich API
    • Cross-platform support

Conclusion

This architecture is designed to be:

  • Scalable
  • Maintainable
  • Secure
  • Performance-oriented

The modular design allows for future improvements and modifications while maintaining system stability and security.