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Infrastructure Overview

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System Architecture

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Core Infrastructure Philosophy

1. Cloud-Native Design: Leveraging managed services and serverless architectures where appropriate
2. Infrastructure as Code: All infrastructure defined and version-controlled
3. Security by Design: Security integrated at all levels of the stack
4. Observability First: Comprehensive monitoring, logging, and alerting
5. Developer Experience: Infrastructure that enables rapid, confident development

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System Architecture Diagram

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Deployment Environments

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Environment Structure

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Deployment Process

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Cloud Infrastructure

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Primary Providers

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Key AWS Services

• Lambda: Serverless computing for backend services
• ECS/Fargate: Container orchestration for stateful services
• S3: Object storage for assets and backups
• CloudFront: Content delivery network
• RDS: Managed PostgreSQL (secondary to Supabase)
• ElastiCache: Redis caching layer
• SQS/SNS: Messaging and event handling
• CloudWatch: Monitoring and alerting
• IAM: Identity and access management

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Database Infrastructure

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Primary Data Stores

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Data Flow Architecture

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CI/CD Pipeline

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GitHub Actions Workflows

• PR Validation: Test and lint code on pull requests
• Preview Deployments: Deploy feature branches to preview environments
• Dependency Updates: Automated dependency management
• Production Deployments: Staged deployment to production
• Infrastructure Changes: Terraform workflow for infrastructure updates

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Deployment Automation

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Security Infrastructure

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Security Layers

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Authentication Infrastructure

• Supabase Auth: Primary authentication provider
• JWT tokens: For API authorization
• Row-Level Security: For data access control
• Secret Management: AWS Secrets Manager and GitHub Secrets
• API Keys: For service-to-service communication

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Monitoring and Observability

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Monitoring Stack

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Logging Strategy

• Centralized Logging: All logs collected in a central system
• Structured Logging: JSON-formatted logs with consistent fields
• Log Levels: Appropriate detail based on environment
• Retention Policy: Compliance-aligned log retention
• Log Analysis: Real-time parsing and alerting

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Disaster Recovery

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Backup Strategy

• Database Backups: Automated daily backups with point-in-time recovery
• Code and Configuration: Version-controlled in Git
• Infrastructure Definition: Terraform state and configuration
• Asset Storage: Redundant storage with cross-region replication

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Recovery Processes

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Infrastructure as Code

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Terraform Management

• Modular Architecture: Reusable Terraform modules
• Environment Separation: Dev/staging/prod environment configuration
• State Management: Remote state with locking
• Change Workflow: Plan, review, apply process
• Integration with CI/CD: Automated infrastructure updates

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Resource Provisioning

# Example Terraform configuration structure
module "networking" {
  source = "./modules/networking"
  environment = var.environment
  # Additional configuration
}

module "database" {
  source = "./modules/database"
  environment = var.environment
  depends_on = [module.networking]
  # Additional configuration
}

module "application" {
  source = "./modules/application"
  environment = var.environment
  database_endpoint = module.database.endpoint
  # Additional configuration
}

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Scaling Strategy

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Horizontal Scaling

• Auto-scaling Groups: For variable workload services
• Serverless Scaling: Lambda and Vercel functions
• Database Connection Pooling: Efficient resource utilization
• Read Replicas: For read-heavy database workloads

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Performance Optimization

• CDN Caching: Edge caching for static assets
• Application Caching: Redis for frequent data access
• Query Optimization: Database indexing and query tuning
• Asset Optimization: Image and media processing pipelines

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Cost Management

• Resource Tagging: Consistent tagging for cost allocation
• Scheduled Scaling: Reducing resources during low-traffic periods
• Serverless Preference: Pay-per-use over always-on where appropriate
• Storage Tiering: Moving infrequently accessed data to lower-cost storage
• Reserved Instances: For predictable workloads
• Cost Anomaly Detection: Alerts for unexpected spending

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Implementation Resources