gh-adrianpuiu-specification-document-generator-architecture-skills/skills/specification-architect/assets/sample_outputs/example_research.md

Research Summary for Task Management System

Domain Analysis

• Industry: Productivity/Project Management Software
• Scale Requirements: 1,000+ concurrent users, 10,000+ tasks, real-time collaboration
• Key Challenges: Real-time updates, data consistency, user permission management, notification delivery

Architectural Approaches Considered

1. Microservices Architecture

   • Description: Decompose system into independent services for users, tasks, projects, notifications
   • Pros: Independent scaling, fault isolation, technology diversity, team autonomy
   • Cons: Operational complexity, network latency, distributed transactions, higher cost

2. Monolithic Architecture

   • Description: Single application with modular components within one deployable unit
   • Pros: Simpler deployment, easier debugging, lower operational overhead, better performance
   • Cons: Scalability limits, technology lock-in, deployment risks, team coordination challenges

3. Event-Driven Architecture with CQRS

   • Description: Command Query Responsibility Segregation with event sourcing
   • Pros: Excellent scalability, audit trails, real-time updates, loose coupling
   • Cons: High complexity, eventual consistency, steep learning curve, debugging challenges

Technology Stack Research

Backend Frameworks

• Node.js + Express: Excellent for real-time features, large ecosystem, fast development
• Python + FastAPI: Strong typing, async support, good for APIs, data science integration
• Java + Spring Boot: Enterprise-grade, mature ecosystem, strong consistency

Database Options

• PostgreSQL: ACID compliance, JSON support, reliability, good for complex queries
• MongoDB: Flexible schema, horizontal scaling, good for rapid development
• MySQL: Mature, widely used, good performance, familiar to most developers

Real-time Communication

• WebSockets: Direct communication, low latency, widely supported
• Server-Sent Events (SSE): Simpler than WebSockets, good for one-way updates
• Message Queues (Redis/RabbitMQ): Reliable delivery, scalable, decoupled

Recommended Technology Stack

• Architecture Pattern: Modular Monolith with Microservice Readiness

  • Start with monolith for speed and simplicity
  • Design modules to be easily extractable into microservices later
  • Use clear boundaries between functional areas

• Backend: Node.js + TypeScript + Express

  • TypeScript for type safety and better development experience
  • Express for mature, well-documented framework
  • Excellent ecosystem for real-time features (Socket.io)
  • Good performance for I/O-bound applications

• Database: PostgreSQL + Redis

  • PostgreSQL as primary database for ACID compliance and reliability
  • Redis for session management, caching, and real-time data
  • Both have excellent Node.js support

• Real-time Communication: Socket.io + Redis Adapter

  • Socket.io for WebSocket connections with fallback support
  • Redis adapter for multi-instance scaling
  • Proven solution for real-time collaboration

• Authentication: JWT + Refresh Tokens

  • JWT for stateless authentication
  • Refresh tokens for security and better user experience
  • Industry standard with good library support

• Infrastructure: Docker + AWS ECS/RDS

  • Docker for containerization and consistency
  • AWS ECS for managed container orchestration
  • AWS RDS for managed PostgreSQL with automatic backups

Research Sources

1. "Microservices vs Monolith: When to Choose Which" (Martin Fowler, 2024)

   • Key insight: Start with monolith, extract microservices when clear boundaries emerge
   • Most successful microservices implementations evolved from monoliths

2. "Real-time Web Application Architecture Best Practices" (InfoQ, 2024)

   • WebSocket scaling challenges and solutions
   • Redis adapter pattern for multi-instance deployments

3. "PostgreSQL vs MongoDB for Task Management Systems" (Database Journal, 2024)

   • PostgreSQL superior for complex queries and data consistency
   • JSON support provides flexibility when needed

4. "Node.js TypeScript Best Practices for Enterprise Applications" (Node.js Foundation, 2024)

   • Type safety significantly reduces runtime errors
   • Better development experience with IDE support

5. "Authentication Patterns for Modern Web Applications" (OWASP, 2024)

   • JWT + refresh token pattern recommended for SPA applications
   • Proper token storage and refresh strategies

Decision Rationale

Why Modular Monolith First:

• Team size (3-5 developers) doesn't warrant microservices complexity
• Faster time-to-market with simpler deployment and debugging
• Clear module boundaries will allow future extraction if needed
• Lower operational cost and complexity for initial launch

Why Node.js + TypeScript:

• Real-time features are first-class citizens in Node.js ecosystem
• TypeScript provides enterprise-grade type safety
• Large talent pool and extensive library ecosystem
• Excellent performance for our I/O-bound use case

Why PostgreSQL + Redis:

• Data consistency is critical for task management
• PostgreSQL handles complex queries and relationships well
• Redis provides excellent caching and real-time data capabilities
• Both technologies are mature, well-supported, and cost-effective

Why Socket.io for Real-time:

• Handles WebSocket connection management complexity
• Provides automatic fallback to other transport methods
• Redis adapter enables horizontal scaling
• Large community and proven track record

This technology stack balances development speed, operational simplicity, and future scalability while leveraging current best practices and well-established patterns.