# E-Commerce Platform Project

## Project Overview
**Project Name**: Aurora Commerce Platform  
**Duration**: 18 months  
**Team Size**: 12 developers  
**Status**: Production  

## Technology Stack
- **Backend**: Python (Django), PostgreSQL, Redis
- **Frontend**: React, TypeScript, Next.js
- **Infrastructure**: Docker, Kubernetes, AWS (EKS, RDS, ElastiCache)
- **CI/CD**: GitHub Actions, ArgoCD
- **Monitoring**: Prometheus, Grafana, ELK Stack

## Architecture
- Microservices architecture with 8 core services
- Event-driven communication using Apache Kafka
- API Gateway with rate limiting and authentication
- CDN for static assets (AWS CloudFront)
- Multi-region deployment for high availability

## Key Features Implemented
1. **User Management Service**
   - JWT-based authentication
   - Role-based access control (RBAC)
   - OAuth integration (Google, Facebook)

2. **Product Catalog Service**
   - Elasticsearch for product search
   - Image processing pipeline
   - Inventory management with real-time updates

3. **Order Processing Service**
   - Payment gateway integration (Stripe, PayPal)
   - Order state management
   - Fraud detection using ML models

4. **Recommendation Engine**
   - Collaborative filtering algorithms
   - Real-time recommendation API
   - A/B testing framework for recommendations

## Skills Required for Different Roles

### Backend Developer
- **Essential**: Python, Django, PostgreSQL, REST APIs
- **Intermediate**: Docker, Redis, Kafka, AWS services
- **Advanced**: Microservices patterns, Event sourcing, Performance optimization

### Frontend Developer
- **Essential**: React, TypeScript, HTML/CSS, JavaScript
- **Intermediate**: Next.js, State management (Redux), API integration
- **Advanced**: Performance optimization, SSR, Micro-frontends

### DevOps Engineer
- **Essential**: Docker, Kubernetes, AWS, CI/CD pipelines
- **Intermediate**: Infrastructure as Code (Terraform), Monitoring
- **Advanced**: Service mesh, Security hardening, Cost optimization

### Data Engineer
- **Essential**: Python, SQL, Kafka, Elasticsearch
- **Intermediate**: ETL pipelines, Data warehousing, Apache Spark
- **Advanced**: ML pipelines, Real-time analytics, Data governance

## Learning Paths Based on Project Needs

### New Backend Developer Onboarding (4 weeks)
1. **Week 1**: Python fundamentals, Django basics, PostgreSQL
2. **Week 2**: REST API development, Authentication systems
3. **Week 3**: Microservices concepts, Docker containerization
4. **Week 4**: AWS services integration, Testing strategies

### Frontend Developer Growth (6 weeks)
1. **Week 1-2**: React advanced patterns, TypeScript mastery
2. **Week 3-4**: Next.js SSR, Performance optimization
3. **Week 5-6**: State management, Testing, Deployment

### DevOps Transition Path (8 weeks)
1. **Week 1-2**: Containerization (Docker), Basic Kubernetes
2. **Week 3-4**: AWS services, Infrastructure as Code
3. **Week 5-6**: CI/CD pipelines, Monitoring setup
4. **Week 7-8**: Security, Performance tuning, Incident response

## Common Challenges and Solutions
- **Scalability**: Horizontal scaling with Kubernetes HPA
- **Data Consistency**: Event sourcing and CQRS patterns
- **Performance**: Caching strategies, Database optimization
- **Security**: OAuth 2.0, API rate limiting, Input validation

## Current Open Positions
- Senior Backend Developer (Python/Django)
- React Developer (TypeScript focus)
- DevOps Engineer (Kubernetes/AWS)
- Data Engineer (ML/Analytics focus)