Platform Architecture

Overview

Portfolio OS is built on a modern monorepo architecture that enables code sharing, independent deployment, and rapid development velocity. This document explains the architectural decisions, technical foundation, and infrastructure design that makes the platform reliable, scalable, and maintainable.

Technology Foundation

Next.js 15 with App Router

The platform uses Next.js 15, representing the current state-of-the-art in React development. This choice demonstrates several important capabilities:

TypeScript End-to-End

TypeScript coverage spans from database queries through API routes to frontend components. This isn't just type checking for catching bugs - it's using types as documentation and enabling powerful refactoring capabilities.

Benefits:

• Fewer Bugs: Null reference errors caught at compile time
• Better IDE Support: Accurate autocomplete and error highlighting
• Self-Documenting: Types serve as inline documentation
• Confident Refactoring: Type errors flag all affected code

Monorepo Structure

The codebase is organized as a monorepo using Turborepo, allowing multiple applications to share code efficiently while maintaining clean boundaries.

Repository Organization

Application Responsibilities

Benefits of Monorepo Architecture

Database Architecture

PostgreSQL with Prisma ORM

The platform uses PostgreSQL for several strategic reasons:

Schema Design

Articles Table

model Article {
  id          String   @id @default(cuid())
  title       String
  slug        String   @unique
  content     String   @db.Text
  excerpt     String?
  published   Boolean  @default(false)
  publishedAt DateTime?
  createdAt   DateTime @default(now())
  updatedAt   DateTime @updatedAt
  authorId    String
  author      User     @relation(fields: [authorId], references: [id])
  tags        Tag[]
  views       Int      @default(0)
}

This schema supports:

• Unique slugs for URLs
• Draft/published workflow
• Author relationships
• Tag associations
• View counting
• Automatic timestamp management

Bookings Table

model Booking {
  id              String   @id @default(cuid())
  name            String
  email           String
  date            DateTime
  duration        Int      @default(30)
  timezone        String
  notes           String?
  status          String   @default("confirmed")
  googleEventId   String?
  googleMeetLink  String?
  confirmationSent Boolean @default(false)
  createdAt       DateTime @default(now())
  updatedAt       DateTime @updatedAt
}

This schema tracks:

• Booking details and contact info
• Timezone for accurate display
• Google Calendar event association
• Meet link for convenience
• Email confirmation status
• Audit trail with timestamps

Performance Optimization

Indexes: Strategic indexes on frequently queried columns:

@@index([slug])
@@index([published, publishedAt])
@@index([authorId])
@@index([email, date])

API Architecture

RESTful Endpoints

The platform exposes REST APIs following standard conventions:

Endpoint Structure:

/api/articles           GET: List    POST: Create
/api/articles/[id]      GET: Get     PUT: Update    DELETE: Delete
/api/auth/session       GET: Check auth status
/api/chatbot/stream     POST: Stream chatbot response
/api/schedule/available POST: Get available slots
/api/schedule/book      POST: Create booking

{
  "data": {
    "id": "abc123",
    "title": "Platform Architecture",
    "publishedAt": "2024-11-08T12:00:00Z"
  },
  "meta": {
    "timestamp": "2024-11-08T14:30:00Z"
  }
}

GraphQL Endpoint

GraphQL provides flexible querying for complex data requirements:

query GetArticle($slug: String!) {
  article(slug: $slug) {
    id
    title
    content
    publishedAt
    author {
      name
      avatar
      bio
    }
    tags {
      name
      slug
    }
  }
}

Deployment Architecture

Vercel Platform

Deployment Pipeline

Performance Optimization

Frontend Performance

Caching Strategy

Monitoring & Observability

Error Tracking (Sentry)

Captures:

• Frontend errors with component stack traces
• Backend API errors with request context
• Performance transaction tracing
• User session replays (privacy-safe)

Performance Monitoring

Vercel Analytics tracks:

• Core Web Vitals (LCP, FID, CLS, TTFB)
• Page load times
• API response times
• Build and deployment metrics

Segmentation:

• By device type (desktop/mobile/tablet)
• By geography (user location)
• By page/route
• Over time (trends)

Security Architecture

Authentication & Authorization

Security Headers

{
  "Content-Security-Policy": "default-src 'self'",
  "X-Frame-Options": "DENY",
  "X-Content-Type-Options": "nosniff",
  "Referrer-Policy": "strict-origin-when-cross-origin",
  "Permissions-Policy": "geolocation=(), microphone=()"
}

These headers prevent common attacks like clickjacking, MIME sniffing, and unauthorized API access.

Scalability Considerations

Horizontal Scaling

Database Scaling: PostgreSQL supports read replicas for scaling read-heavy workloads. Write traffic handled by primary, reads distributed across replicas.

Cost Scaling

Variable costs scale linearly with usage:

• Vercel: Function invocations and bandwidth
• Database: Storage and compute hours
• OpenAI: API tokens consumed
• Email: Messages sent

Conclusion

The platform architecture demonstrates understanding of modern web development practices while making pragmatic choices that balance simplicity with scalability. The monorepo structure enables rapid development without sacrificing code quality. The technology stack is production-proven while remaining at the cutting edge. The deployment architecture ensures reliability and performance globally.

This represents the kind of architectural thinking that translates directly to professional software development: making informed decisions, balancing tradeoffs, and building systems that solve today's problems while remaining flexible for tomorrow's requirements.

Related Documentation