https://github.com/ericgitangu/uber-system-design
Analysis of Ubers System Design - For learning purposes
https://github.com/ericgitangu/uber-system-design
cicd iac k6 k8s qa qa-automation system-design terraform
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Analysis of Ubers System Design - For learning purposes
- Host: GitHub
- URL: https://github.com/ericgitangu/uber-system-design
- Owner: ericgitangu
- Created: 2025-06-15T10:33:30.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-06-15T13:05:54.000Z (10 months ago)
- Last Synced: 2025-07-28T17:14:21.105Z (8 months ago)
- Topics: cicd, iac, k6, k8s, qa, qa-automation, system-design, terraform
- Homepage: https://developer.ericgitangu.com
- Size: 65.4 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Enterprise System Architecture - Ride-Sharing Platform 🚗
[](LICENSE)
[](https://kubernetes.io/)
[](https://terraform.io/)
> A comprehensive, production-grade system architecture blueprint for ride-sharing platforms, demonstrating enterprise-scale infrastructure patterns, microservices design, and cloud-native technologies using Uber as a reference implementation.
## 📋 Table of Contents
- [Overview](#overview)
- [Architecture](#architecture)
- [Quick Start](#quick-start)
- [Infrastructure](#infrastructure)
- [Services](#services)
- [Development](#development)
- [Testing](#testing)
- [Deployment](#deployment)
- [Monitoring](#monitoring)
- [Security](#security)
- [Performance](#performance)
- [Disaster Recovery](#disaster-recovery)
- [Contributing](#contributing)
## 🏗️ Overview
This repository contains a complete implementation of an enterprise-grade system architecture for ride-sharing platforms, using Uber's design patterns as a reference case study. The architecture demonstrates modern cloud-native technologies, microservices patterns, and production-ready infrastructure suitable for high-scale platforms.
### Key Features
- 🚀 **Microservices Architecture**: Scalable, independent services
- ☁️ **Multi-Cloud Ready**: AWS, GCP, Oracle Cloud support
- 🔄 **Event-Driven**: Kafka-based real-time data processing
- 📊 **Big Data Analytics**: Hadoop, Spark, Hive integration
- 🔐 **Enterprise Security**: Zero-trust, encryption, compliance
- 📱 **Multi-Platform**: Web, mobile, admin interfaces
- 🎯 **Production-Ready**: Comprehensive monitoring, logging, alerting
- 🔧 **GitOps**: Infrastructure and application automation
### System Capabilities
- **Real-time Ride Matching**: Sub-second driver-rider pairing
- **Dynamic Pricing**: Surge pricing based on demand
- **Route Optimization**: ML-powered path planning
- **Payment Processing**: Multi-gateway payment support
- **Global Scale**: Multi-region deployment
- **High Availability**: 99.99% uptime SLA
## 🏛️ Architecture
### System Overview
```mermaid
graph TB
subgraph "Client Layer"
WEB[Web App]
MOBILE[Mobile Apps]
ADMIN[Admin Dashboard]
end
subgraph "API Gateway"
LB[Load Balancer]
API[API Gateway]
end
subgraph "Microservices"
USER[User Service]
DRIVER[Driver Service]
TRIP[Trip Service]
PAYMENT[Payment Service]
end
subgraph "Data Layer"
CACHE[Redis Cache]
DB[(PostgreSQL)]
NOSQL[(Cassandra)]
end
WEB --> LB
MOBILE --> LB
ADMIN --> LB
LB --> API
API --> USER
API --> DRIVER
API --> TRIP
API --> PAYMENT
USER --> CACHE
USER --> DB
TRIP --> NOSQL
```
### Technology Stack
| Component | Technology | Purpose | Language |
|-----------|------------|---------|----------|
| **Container Orchestration** | Kubernetes | Service deployment and scaling | YAML |
| **Service Mesh** | Istio | Inter-service communication | YAML |
| **API Gateway** | Kong/Envoy/Traefik | Request routing and rate limiting | Config |
| **Databases** | PostgreSQL, Cassandra, Redis | Data persistence and caching | SQL/CQL |
| **Message Streaming** | Apache Kafka | Event processing | Java/Scala |
| **Monitoring** | Prometheus + Grafana | Observability | PromQL |
| **Tracing** | Jaeger + OpenTelemetry | Distributed tracing | Multi-lang |
| **Logging** | ELK Stack | Log aggregation | Multi-lang |
| **CI/CD** | GitHub Actions + ArgoCD | Deployment automation | YAML |
| **Infrastructure** | Terraform | Infrastructure as Code | HCL |
| **Security** | HashiCorp Vault + OPA | Secrets & Policy | HCL/Rego |
## 🚀 Quick Start
### Prerequisites
- Docker & Docker Compose
- Kubernetes cluster (local or cloud)
- Terraform >= 1.5
- kubectl
- Helm >= 3.0
- Yarn >= 4.0
- Node.js >= 18
- Python >= 3.9
- Go >= 1.21
- Java >= 17
### Local Development Setup
1. **Clone the repository**
```bash
git clone https://github.com/ericgitangu/enterprise-system-architecture.git
cd enterprise-system-architecture
```
2. **Start local development environment**
```bash
# Start infrastructure services
docker-compose -f docker-compose.dev.yml up -d
# Install dependencies
yarn install # Node.js services
pip install -r requirements.txt # Python services
go mod download # Go services
mvn install # Java services
# Start development servers
yarn dev
```
3. **Verify setup**
```bash
# Check service health
curl http://localhost:8080/health
# Run tests
yarn test
```
### Cloud Deployment
1. **Configure cloud credentials**
```bash
# AWS
export AWS_ACCESS_KEY_ID=your-key
export AWS_SECRET_ACCESS_KEY=your-secret
export AWS_REGION=us-west-2
```
2. **Deploy infrastructure**
```bash
cd terraform/environments/production
terraform init
terraform plan
terraform apply
```
3. **Deploy applications**
```bash
# Connect to cluster
aws eks update-kubeconfig --name production-eks-cluster
# Deploy with ArgoCD
kubectl apply -f gitops/applications/
```
## 🏗️ Infrastructure
### Directory Structure
```
terraform/
├── modules/
│ ├── networking/ # VPC, subnets, security groups
│ ├── compute/ # EKS, EC2, Lambda
│ ├── data/ # RDS, ElastiCache, DocumentDB
│ ├── security/ # IAM, secrets, certificates
│ └── monitoring/ # CloudWatch, Prometheus
├── environments/
│ ├── dev/ # Development environment
│ ├── staging/ # Staging environment
│ └── production/ # Production environment
└── shared/ # Shared configurations
```
### Supported Environments
| Environment | Purpose | Resources | Auto-scaling |
|-------------|---------|-----------|--------------|
| **Development** | Feature development | Minimal | Manual |
| **Staging** | Testing & QA | Production-like | Limited |
| **Production** | Live traffic | Full scale | Auto |
## 🔧 Services
### Core Microservices
#### User Service (Go)
```yaml
Technology: Go + Gin + GORM
Database: PostgreSQL
Responsibilities:
- User registration and authentication
- Profile management
- Preferences and settings
API Endpoints:
- POST /api/users # Create user
- GET /api/users/{id} # Get user profile
- PUT /api/users/{id} # Update profile
- DELETE /api/users/{id} # Deactivate account
Testing:
- Unit: Testify + Gomock
- Integration: Go HTTP tests
- Load: K6 + Vegeta
```
#### Driver Service (Java)
```yaml
Technology: Spring Boot + JPA
Database: PostgreSQL + Redis
Responsibilities:
- Driver onboarding
- Document verification
- Availability tracking
- Performance metrics
API Endpoints:
- POST /api/drivers # Register driver
- GET /api/drivers/{id} # Get driver info
- PUT /api/drivers/{id}/status # Update availability
- GET /api/drivers/nearby # Find nearby drivers
Testing:
- Unit: JUnit 5 + Mockito
- Integration: TestContainers
- Performance: JMeter
```
#### Trip Service (Node.js)
```yaml
Technology: Node.js + Express + TypeScript
Database: Cassandra + Redis
Responsibilities:
- Trip lifecycle management
- Route optimization
- ETA calculations
- Trip history
API Endpoints:
- POST /api/trips # Request trip
- GET /api/trips/{id} # Get trip details
- PUT /api/trips/{id}/status # Update trip status
- GET /api/trips/history # Trip history
Testing:
- Unit: Jest + Supertest
- Integration: Jest + TestContainers
- E2E: Playwright
```
#### Payment Service (Python)
```yaml
Technology: FastAPI + SQLAlchemy + Celery
Database: PostgreSQL + Redis
Responsibilities:
- Payment processing
- Multiple payment methods
- Fraud detection
- Financial reporting
API Endpoints:
- POST /api/payments # Process payment
- GET /api/payments/{id} # Payment details
- POST /api/payments/refund # Refund payment
- GET /api/payments/methods # Payment methods
Testing:
- Unit: pytest + pytest-mock
- Integration: pytest + httpx
- Load: Locust
```
### Service Communication
```mermaid
graph LR
A[API Gateway] --> B[User Service - Go]
A --> C[Driver Service - Java]
A --> D[Trip Service - Node.js]
A --> E[Payment Service - Python]
D --> F[Kafka: Trip Events]
E --> F
B --> F
C --> F
F --> G[Analytics Pipeline - Spark/Scala]
F --> H[Notification Service - Go]
F --> I[ML Pipeline - Python]
```
## 💻 Development
### Development Workflow
1. **Feature Development**
```bash
# Create feature branch
git checkout -b feature/user-verification
# Install dependencies per language
yarn install # Node.js/TypeScript
go mod tidy # Go
pip install -r requirements.txt # Python
mvn install # Java
# Make changes and test
yarn test # Node.js
go test ./... # Go
pytest # Python
mvn test # Java
# Commit and push
git commit -m "feat: add user verification"
git push origin feature/user-verification
```
2. **Code Quality Checks**
```bash
# Node.js/TypeScript
yarn lint # ESLint
yarn format # Prettier
yarn type-check # TypeScript
# Go
golangci-lint run # Linting
go fmt ./... # Formatting
go vet ./... # Static analysis
# Python
flake8 . # Linting
black . # Formatting
mypy . # Type checking
bandit -r . # Security analysis
# Java
mvn spotbugs:check # Static analysis
mvn pmd:check # Code quality
```
### Code Standards
| Language | Framework | Style Guide | Testing | Documentation |
|----------|-----------|-------------|---------|---------------|
| **TypeScript/Node.js** | Express/Fastify | ESLint + Prettier | Jest + Supertest | TSDoc |
| **Go** | Gin/Echo | gofmt + golangci-lint | Testify + Gomock | godoc |
| **Python** | FastAPI/Django | Black + flake8 | pytest + pytest-mock | Sphinx |
| **Java** | Spring Boot | Google Java Style | JUnit 5 + Mockito | Javadoc |
### Environment Variables
```bash
# Application (Language Agnostic)
ENVIRONMENT=development
LOG_LEVEL=debug
SERVICE_NAME=user-service
SERVICE_VERSION=1.0.0
# Database
DATABASE_URL=postgresql://user:pass@localhost:5432/rideshare_dev
REDIS_URL=redis://localhost:6379
CASSANDRA_HOSTS=localhost:9042
# Message Streaming
KAFKA_BROKERS=localhost:9092
KAFKA_TOPIC_PREFIX=rideshare
# Observability
JAEGER_ENDPOINT=http://localhost:14268/api/traces
PROMETHEUS_ENDPOINT=http://localhost:9090
# Security
JWT_SECRET=your-jwt-secret
VAULT_ADDR=http://localhost:8200
VAULT_TOKEN=your-vault-token
```
## 🧪 Testing
### Testing Strategy
```
Testing Pyramid (Multi-Language):
├── Unit Tests (70%) # Fast, isolated component tests
├── Integration Tests (20%) # Service interaction tests
├── Contract Tests (5%) # API contract validation
├── E2E Tests (3%) # Full user journey tests
└── Performance Tests (2%) # Load and stress tests
```
### Testing Tools by Language
#### Node.js/TypeScript Testing
```bash
# Unit testing with Jest
yarn test:unit # All unit tests
yarn test:unit:watch # Watch mode
yarn test:unit:coverage # With coverage report
# Integration testing
yarn test:integration # Database and API integration
# E2E testing with Playwright
yarn test:e2e # All E2E tests
# Performance testing
yarn test:performance # Load testing with K6
```
#### Go Testing
```bash
# Unit testing
go test ./... # All packages
go test -race ./... # Race condition detection
go test -cover ./... # Coverage analysis
# Integration testing
go test -tags=integration ./... # Integration tests
# Benchmark testing
go test -bench=. ./... # Benchmark tests
```
#### Python Testing
```bash
# Unit testing with pytest
pytest tests/unit/ # Unit tests
pytest tests/unit/ --cov=src # With coverage
# Integration testing
pytest tests/integration/ # Integration tests
# Performance testing
pytest tests/performance/ --benchmark-only
```
#### Java Testing
```bash
# Maven testing
mvn test # Unit tests
mvn integration-test # Integration tests
mvn verify # All tests + verification
# Coverage with JaCoCo
mvn jacoco:prepare-agent test jacoco:report
```
### Performance Testing
#### Load Testing (Expected Performance Verification)
```bash
# K6 Load Testing - Verify system handles expected traffic
k6 run --vus 100 --duration 30m tests/performance/load-testing/main.js
# Objectives:
# - Validate performance under expected load (100-500 concurrent users)
# - Verify SLA compliance (p95 < 1.5s, p99 < 3s)
# - Confirm system stability over extended periods
```
#### Stress Testing (Breaking Point Analysis)
```bash
# K6 Stress Testing - Find system limits
k6 run tests/performance/stress-testing/stress.js
# Objectives:
# - Determine maximum system capacity (breaking point)
# - Observe system behavior under extreme load
# - Validate graceful degradation mechanisms
```
#### Chaos Engineering
```bash
# Chaos Monkey for Kubernetes
kubectl apply -f tests/chaos/chaos-monkey-deployment.yml
# Custom chaos testing scenarios:
yarn test:chaos:network # Network partition simulation
yarn test:chaos:cpu # CPU exhaustion scenarios
yarn test:chaos:memory # Memory pressure testing
```
## 🚀 Deployment
### CI/CD Pipeline
```yaml
Stages:
1. Code Quality # Linting, formatting, security
2. Testing # Unit, integration, security tests
3. Build # Docker image creation
4. Deploy to Staging # Automated deployment
5. E2E Testing # Full system validation
6. Deploy to Prod # Manual approval required
7. Smoke Tests # Production health checks
```
### Deployment Strategies
#### Blue-Green Deployment
```bash
# Deploy new version (green)
kubectl set image deployment/user-service user-service=new-image:v2.0.0
# Verify deployment
kubectl rollout status deployment/user-service
# Switch traffic (if successful)
kubectl patch service user-service -p '{"spec":{"selector":{"version":"v2.0.0"}}}'
```
#### Canary Deployment
```yaml
# 10% traffic to new version
apiVersion: argoproj.io/v1alpha1
kind: Rollout
spec:
strategy:
canary:
steps:
- setWeight: 10
- pause: {duration: 10m}
- setWeight: 50
- pause: {duration: 10m}
- setWeight: 100
```
### GitOps Workflow
```mermaid
graph LR
A[Code Push] --> B[CI Pipeline]
B --> C[Build & Test]
C --> D[Update Manifests]
D --> E[ArgoCD Sync]
E --> F[Deploy to K8s]
F --> G[Health Checks]
```
## 📊 Monitoring & Observability
### Comprehensive Observability Stack
| Component | Tool | Purpose | Language Support |
|-----------|------|---------|------------------|
| **Metrics** | Prometheus + Grafana | Time-series metrics | All |
| **Tracing** | Jaeger + OpenTelemetry | Distributed tracing | All |
| **Logging** | ELK Stack + Fluentd | Log aggregation | All |
| **APM** | Datadog/New Relic | Application performance | All |
| **Uptime** | Pingdom/Uptime Robot | Synthetic monitoring | HTTP/API |
### Performance Targets & SLAs
| Metric | Target | Monitoring | Alerting Threshold |
|--------|--------|------------|-------------------|
| **API Response Time (p95)** | < 500ms | Prometheus + Grafana | > 750ms |
| **API Response Time (p99)** | < 1.5s | Distributed tracing | > 2s |
| **Database Query Time (p95)** | < 100ms | PostgreSQL metrics | > 200ms |
| **Cache Hit Ratio** | > 85% | Redis metrics | < 75% |
| **Throughput** | > 10,000 RPS | Load balancer metrics | < 8,000 RPS |
| **Error Rate** | < 0.1% | Application logs | > 0.5% |
| **Availability** | 99.99% | Synthetic monitoring | < 99.9% |
### Application-Level Observability
```yaml
Custom Business Metrics:
├── Ride requests per minute: Counter
├── Driver utilization rate: Gauge
├── Payment success rate: Histogram
├── User session duration: Summary
└── Revenue per ride: Custom metric
SLA/SLI Monitoring:
├── API latency percentiles (p50, p95, p99)
├── Error rate budgets (99.9% availability)
├── Throughput measurements (requests/second)
└── Dependency availability tracking
```
### Health Checks and Synthetic Monitoring
#### Universal Health Check Pattern
```yaml
endpoints:
- path: /health
method: GET
response:
status: 200
content-type: application/json
schema:
type: object
properties:
status:
type: string
enum: ["healthy", "degraded", "unhealthy"]
timestamp: { type: string, format: date-time }
version: { type: string }
checks:
type: object
properties:
database: { type: object }
cache: { type: object }
external_apis: { type: array }
uptime_seconds: { type: number }
```
## 🔐 Security
### Security Framework
```yaml
Security Layers:
1. Network Security # VPC, Security Groups, NACLs
2. Identity & Access # IAM, RBAC, MFA
3. Application Security # Authentication, Authorization
4. Data Protection # Encryption, Key Management
5. Monitoring & Audit # Security logs, Compliance
```
### Zero Trust Architecture
```yaml
Zero Trust Principles:
├── Network Segmentation
│ ├── Micro-segmentation with Istio service mesh
│ ├── Network policies for pod-to-pod communication
│ ├── Private subnets for all backend services
│ └── WAF and DDoS protection at ingress
├── Identity Verification
│ ├── Multi-factor authentication for all users
│ ├── Certificate-based service authentication
│ ├── Short-lived tokens with automatic rotation
│ └── Continuous identity validation
├── Device Security
│ ├── Device registration and compliance checking
│ ├── Mobile application certificate pinning
│ ├── Jailbreak/root detection
│ └── Remote device management capabilities
└── Data Classification
├── PII data encryption at rest and in transit
├── Data loss prevention (DLP) policies
├── Geographic data residency compliance
└── Automated data discovery and classification
```
### Security Implementation
#### Authentication & Authorization (Go Example)
```go
type Claims struct {
UserID string `json:"user_id"`
Email string `json:"email"`
Roles []string `json:"roles"`
Scope []string `json:"scope"`
SessionID string `json:"session_id"`
jwt.RegisteredClaims
}
// Role-Based Access Control
var RoleDefinitions = map[string]Role{
"rider": {
Name: "rider",
Permissions: []Permission{
{Resource: "trips", Action: "create", Scope: "own"},
{Resource: "trips", Action: "read", Scope: "own"},
{Resource: "payments", Action: "create", Scope: "own"},
},
},
"driver": {
Name: "driver",
Permissions: []Permission{
{Resource: "trips", Action: "read", Scope: "assigned"},
{Resource: "trips", Action: "update", Scope: "assigned"},
{Resource: "earnings", Action: "read", Scope: "own"},
},
},
"admin": {
Name: "admin",
Permissions: []Permission{
{Resource: "*", Action: "*", Scope: "*"},
},
},
}
```
#### Data Encryption (TypeScript Example)
```typescript
class DataEncryption {
private readonly algorithm = 'aes-256-gcm';
encryptPII(data: string, additionalData?: string): EncryptionResult {
const iv = crypto.randomBytes(16);
const cipher = crypto.createCipher(this.algorithm, key, iv);
if (additionalData) {
cipher.setAAD(Buffer.from(additionalData));
}
let encrypted = cipher.update(data, 'utf8', 'hex');
encrypted += cipher.final('hex');
const authTag = cipher.getAuthTag();
return {
encrypted,
iv: iv.toString('hex'),
authTag: authTag.toString('hex'),
keyId: 'current'
};
}
}
```
### Security Scanning Pipeline
```yaml
security-pipeline:
dependency-scanning:
- npm audit (Node.js)
- safety check (Python)
- nancy (Go)
- OWASP Dependency Check (Java)
container-scanning:
- Trivy image scan
- Docker Scout CVE scan
static-code-analysis:
- CodeQL Analysis
- SonarQube Scan
- Semgrep SAST
infrastructure-scanning:
- Checkov (Terraform)
- kube-score (Kubernetes)
- Terrascan (IaC)
```
### Compliance Implementation
#### GDPR Compliance
```python
class GDPRCompliance:
async def handle_data_subject_request(self, request_type: str, user_id: str):
if request_type == "access":
return await self.export_user_data(user_id)
elif request_type == "deletion":
return await self.delete_user_data(user_id)
elif request_type == "rectification":
return await self.update_user_data(user_id)
elif request_type == "portability":
return await self.export_portable_data(user_id)
```
#### PCI DSS Compliance
```python
class PCIDSSCompliance:
def tokenize_card_data(self, card_number: str, user_id: str) -> str:
# Generate secure token
token = self.generate_secure_token()
# Store mapping in secure vault (not in application database)
self.vault.store_card_mapping(token, card_number, user_id)
return token
```
## ⚡ Performance
### Performance Engineering Framework
```yaml
Performance Strategy:
├── Application Performance
│ ├── Code optimization and profiling
│ ├── Algorithm efficiency improvements
│ ├── Memory management and GC tuning
│ └── Asynchronous processing patterns
├── Database Performance
│ ├── Query optimization and indexing
│ ├── Connection pooling and caching
│ ├── Read replicas and sharding
│ └── Automated performance monitoring
├── Infrastructure Performance
│ ├── Auto-scaling policies
│ ├── Load balancing and traffic distribution
│ ├── CDN and edge computing optimization
│ └── Network latency reduction
└── Monitoring & Optimization
├── Real-time performance metrics
├── Performance regression detection
├── Capacity planning and forecasting
└── Continuous performance testing
```
### Performance Optimization Examples
#### Go Service Performance
```go
// Memory pool for frequent allocations
var requestPool = sync.Pool{
New: func() interface{} {
return &RequestContext{
Data: make(map[string]interface{}, 10),
}
},
}
// Optimized middleware with object pooling
func PerformanceMiddleware() gin.HandlerFunc {
return gin.HandlerFunc(func(c *gin.Context) {
// Get context from pool
reqCtx := requestPool.Get().(*RequestContext)
defer func() {
reqCtx.Reset()
requestPool.Put(reqCtx)
}()
c.Next()
})
}
// Connection pool optimization
func OptimizeDatabasePool(db *sql.DB) {
db.SetMaxOpenConns(100) // Maximum active connections
db.SetMaxIdleConns(25) // Keep 25 idle connections
db.SetConnMaxLifetime(5 * time.Minute)
}
```
#### Node.js Cluster Setup
```typescript
// Cluster setup for multi-core utilization
export function setupCluster(): void {
const numCPUs = os.cpus().length;
if (cluster.isMaster) {
console.log(`Master ${process.pid} is running`);
// Fork workers
for (let i = 0; i < numCPUs; i++) {
cluster.fork();
}
cluster.on('exit', (worker) => {
console.log(`Worker ${worker.process.pid} died`);
cluster.fork();
});
} else {
// Worker processes
startServer();
}
}
```
## 🔄 Disaster Recovery
### Disaster Recovery Strategy
```yaml
DR Components:
├── Backup Strategy
│ ├── Automated daily database backups
│ ├── Point-in-time recovery capabilities
│ ├── Cross-region backup replication
│ └── Application state snapshots
├── High Availability
│ ├── Multi-region deployment
│ ├── Auto-failover mechanisms
│ ├── Load balancer health checks
│ └── Database clustering
├── Recovery Procedures
│ ├── RTO: 4 hours (Recovery Time Objective)
│ ├── RPO: 1 hour (Recovery Point Objective)
│ ├── Automated failover scripts
│ └── Manual recovery runbooks
└── Testing & Validation
├── Monthly DR testing
├── Chaos engineering
├── Backup restoration testing
└── Business continuity exercises
```
### Multi-Region Setup
```yaml
# terraform/multi-region.tf
provider "aws" {
alias = "primary"
region = "us-west-2"
}
provider "aws" {
alias = "secondary"
region = "us-east-1"
}
# Primary region resources
module "primary_infrastructure" {
source = "./modules/infrastructure"
providers = {
aws = aws.primary
}
region = "us-west-2"
environment = "production"
}
# Secondary region resources
module "secondary_infrastructure" {
source = "./modules/infrastructure"
providers = {
aws = aws.secondary
}
region = "us-east-1"
environment = "production-dr"
}
```
## 🤝 Contributing
### Development Process
1. **Fork the repository**
2. **Create a feature branch**: `git checkout -b feature/amazing-feature`
3. **Follow coding standards** for each language
4. **Write comprehensive tests**
5. **Run security scans**: `yarn security-scan`
6. **Update documentation** if needed
7. **Submit a pull request**
### Code Review Guidelines
- **Security**: All PRs must pass security scans
- **Testing**: Minimum 80% code coverage required
- **Performance**: No performance regressions allowed
- **Documentation**: Update relevant docs for new features
### Release Process
1. **Version bumping**: Follow semantic versioning
2. **Changelog updates**: Document all changes
3. **Security review**: Additional security review for major releases
4. **Staging deployment**: Test in staging environment
5. **Production rollout**: Gradual canary deployment
---
## 📚 Additional Resources
- [API Documentation](docs/api.md)
- [Deployment Guide](docs/deployment.md)
- [Security Best Practices](docs/security.md)
- [Performance Tuning Guide](docs/performance.md)
- [Troubleshooting Guide](docs/troubleshooting.md)
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
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**Built with ❤️ for enterprise-scale ride-sharing platforms**