feat: add ms transaction and ms antifraud

[Martin161195]

🚀 Feature: Transaction Service with Anti-Fraud Integration via Kafka

📋 Summary

Implements a complete transaction management microservice with real-time anti-fraud validation using event-driven architecture and hexagonal design pattern.

🎯 What's New

• Transaction Service microservice with RESTful API
• Anti-Fraud integration via Apache Kafka for asynchronous validation
• Hexagonal Architecture ensuring clean domain logic and infrastructure decoupling
• Event-driven communication between services using Kafka topics
• PostgreSQL persistence with JPA/Hibernate and connection pooling
• Transaction status management: PENDING → APPROVED/REJECTED

🏗️ Architecture Highlights

• Domain Layer: Pure business logic with value objects and entities
• Application Layer: Use cases implementation (Create, Get, Update transactions)
• Infrastructure Layer: REST controllers, Kafka producers/consumers, PostgreSQL adapters
• Kafka Topics:
  • transaction.created - Published by Transaction Service
  • transaction.approved/rejected - Consumed from Anti-Fraud Service

🔧 Technical Stack

• Java 17 + Spring Boot
• Apache Kafka
• PostgreSQL
• Maven (dependency management)
• Docker & Docker Compose (containerization)

📦 Key Components

Transaction Service

• CreateTransactionUseCase - Creates transactions with PENDING status
• UpdateTransactionStatusUseCase - Updates status based on anti-fraud response
• KafkaEventPublisher - Publishes transaction events
• KafkaTransactionConsumer - Consumes fraud evaluation results

Configuration

• Kafka Producer: idempotent, acks=all, compression enabled
• Kafka Consumer: manual commit, 3 concurrent threads
• Database: HikariCP connection pool

📝 API Endpoints

• POST /api/v1/transactions - Create new transaction
• GET /api/v1/transactions/{id} - Retrieve transaction by ID

🔄 Transaction Flow

1. Client creates transaction via REST API
2. Transaction saved with status PENDING
3. Event published to Kafka (transaction.created)
4. Anti-Fraud Service evaluates (async)
5. Result received via Kafka (approved or rejected)
6. Transaction status updated accordingly

📚 Documentation

• Complete README with architecture diagrams
• Scaffolding structure documented
• API examples with curl commands

✅ Checklist

• Hexagonal architecture implemented
• REST API endpoints working
• Kafka producer configured
• Kafka consumer configured
• PostgreSQL integration
• Logging configured
• README documentation
• Unit tests completed
• Integration tests completed

🚦 How to Test

# Start infrastructure
docker-compose up -d postgres kafka zookeeper

# Run application
mvn spring-boot:run -Dspring.profiles.active=dev

# Create transaction
curl -X POST http://localhost:8080/api/v1/transactions \
  -H "Content-Type: application/json" \
  -d '{
    "accountExternalIdDebit": "550e8400-e29b-41d4-a716-446655440000",
    "accountExternalIdCredit": "6ba7b810-9dad-11d1-80b4-00c04fd430c8",
    "transferTypeId": 1,
    "value": 500.00
  }'