Welcome to SGIVU
SGIVU is a cloud-native vehicle inventory management SaaS platform designed for automotive dealerships and vehicle sales businesses. Built on a modern microservices architecture, SGIVU provides comprehensive tools for managing vehicles, clients, purchases, sales, and leveraging machine learning for intelligent business insights.What is SGIVU?
SGIVU (Sistema de Gestión de Inventario de Vehículos Unidos) is an enterprise-grade platform that centralizes all aspects of vehicle inventory operations:- Vehicle Management: Complete catalog management for cars and motorcycles with advanced search, status tracking, and image management via AWS S3
- Client Management: Unified management of individual and corporate clients with detailed profiles and transaction history
- Purchase & Sales Contracts: End-to-end contract lifecycle management with reporting capabilities (PDF, Excel, CSV)
- User & Role Management: Granular permission system with OAuth 2.1/OIDC authentication
- Machine Learning: Predictive analytics for demand forecasting and business intelligence
- Multi-tenant Ready: Designed for scalability with centralized configuration and service discovery
Who is SGIVU For?
Auto Dealerships
Manage inventory across multiple locations with real-time tracking and intelligent demand forecasting
Vehicle Sales Businesses
Streamline purchase and sales operations with automated contract generation and reporting
Fleet Managers
Track vehicle status, maintenance schedules, and optimize fleet utilization
Enterprise Organizations
Scale operations with microservices architecture and centralized authentication
Key Capabilities
Authentication & Security
- OAuth 2.1 / OpenID Connect implementation with JWT tokens
- BFF (Backend for Frontend) pattern via API Gateway
- Granular role-based access control with custom permissions
- Session management with Redis for horizontal scalability
- Service-to-service authentication for internal communication
Architecture Highlights
SGIVU follows cloud-native best practices with:
- Spring Boot 4.0.1 & Java 21 for backend services
- Angular 21 for the frontend SPA
- FastAPI & Python 3.12 for ML services
- PostgreSQL for data persistence
- Redis for session storage
- Docker & Docker Compose for containerization
Observability
- Health checks via Spring Boot Actuator
- Distributed tracing with Zipkin
- Metrics collection with Micrometer
- Centralized logging for troubleshooting
Technology Stack
Frontend:- Angular 21, TypeScript
- Bootstrap 5, Chart.js
- RxJS for reactive programming
- Spring Boot 4.0.1, Spring Cloud
- Spring Security (OAuth2/OIDC)
- Spring Data JPA
- Flyway (database migrations)
- FastAPI, Uvicorn
- scikit-learn, XGBoost
- pandas, numpy
- Docker, Docker Compose
- Nginx reverse proxy
- AWS (S3, EC2/ECS/EKS, RDS, ALB)
- Redis 7
- Spring Boot Actuator
- Micrometer, Zipkin
- Health checks & metrics
Quick Start
Access the Application
- Frontend: http://localhost:4200
- API Gateway: http://localhost:8080
- Auth Server: http://localhost:9000
- Service Discovery: http://localhost:8761
- ML Service: http://localhost:8000
The development environment uses Docker Compose with mounted volumes for hot-reloading during development.
Main Endpoints
| Service | Port | Endpoint | Description |
|---|---|---|---|
| Frontend | 4200 | http://localhost:4200 | Angular SPA |
| Gateway | 8080 | http://localhost:8080 | API Gateway (BFF) |
| Auth | 9000 | http://localhost:9000 | OAuth2/OIDC Server |
| Config | 8888 | http://localhost:8888 | Centralized Configuration |
| Discovery | 8761 | http://localhost:8761 | Eureka Service Registry |
| ML | 8000 | http://localhost:8000 | Machine Learning API |
| Zipkin | 9411 | http://localhost:9411 | Distributed Tracing (optional) |
Next Steps
Architecture
Dive deep into the microservices architecture and communication patterns
Features
Explore comprehensive feature documentation