# TODO - LiveDash Architecture Evolution & Improvements

## 🚀 CRITICAL PRIORITY - Architectural Refactoring

### Phase 1: Service Decomposition & Platform Management (Weeks 1-4)
- [x] **Create Platform Management Layer** (80% Complete)
  - [x] Add Organization/PlatformUser models to Prisma schema
  - [x] Implement super-admin authentication system (/platform/login)
  - [x] Build platform dashboard for Notso AI team (/platform/dashboard)
  - [x] Add company creation workflows
  - [x] Add basic platform API endpoints with tests
  - [x] Create stunning SaaS landing page with modern design
  - [ ] Add company editing/management workflows
  - [ ] Create company suspension/activation UI features
  - [ ] Add proper SEO metadata and OpenGraph tags
  - [ ] Add user management within companies from platform
  - [ ] Add AI model management UI
  - [ ] Add cost tracking/quotas UI

- [ ] **Extract Data Ingestion Service (Golang)**
  - [ ] Create new Golang service for CSV processing
  - [ ] Implement concurrent CSV downloading & parsing
  - [ ] Add transcript fetching with rate limiting
  - [ ] Set up Redis message queues (BullMQ/RabbitMQ)
  - [ ] Migrate lib/scheduler.ts and lib/csvFetcher.ts logic

- [ ] **Implement tRPC Infrastructure**
  - [ ] Add tRPC to existing Next.js app
  - [ ] Create type-safe API procedures for frontend
  - [ ] Implement inter-service communication protocols
  - [ ] Add proper error handling and validation

### Phase 2: AI Service Separation & Compliance (Weeks 5-8)
- [ ] **Extract AI Processing Service**
  - [ ] Separate lib/processingScheduler.ts into standalone service
  - [ ] Implement async AI processing with queues
  - [ ] Add per-company AI cost tracking and quotas
  - [ ] Create AI model management per company
  - [ ] Add retry logic and failure handling

- [ ] **GDPR & ISO 27001 Compliance Foundation**
  - [ ] Implement data isolation boundaries between services
  - [ ] Add audit logging for all data processing
  - [ ] Create data retention policies per company
  - [ ] Add consent management for data processing
  - [ ] Implement data export/deletion workflows (Right to be Forgotten)

### Phase 3: Performance & Monitoring (Weeks 9-12)
- [ ] **Monitoring & Observability**
  - [ ] Add distributed tracing across services (Jaeger/Zipkin)
  - [ ] Implement health checks for all services
  - [ ] Create cross-service metrics dashboard
  - [ ] Add alerting for service failures and SLA breaches
  - [ ] Monitor AI processing costs and quotas

- [ ] **Database Optimization**
  - [ ] Implement connection pooling per service
  - [ ] Add read replicas for dashboard queries
  - [ ] Create database sharding strategy for multi-tenancy
  - [ ] Optimize queries with proper indexing

## High Priority

### Testing & Quality Assurance
- [ ] Add comprehensive test coverage for API endpoints (currently minimal)
- [ ] Implement integration tests for the data processing pipeline
- [ ] Add unit tests for validation schemas and authentication logic
- [ ] Create E2E tests for critical user flows (registration, login, dashboard)

### Error Handling & Monitoring
- [ ] Implement global error boundaries for React components
- [ ] Add structured logging with correlation IDs for request tracing
- [ ] Set up error monitoring and alerting (e.g., Sentry integration)
- [ ] Add proper error pages for 404, 500, and other HTTP status codes

### Performance Optimization
- [ ] Implement database query optimization and indexing strategy
- [ ] Add caching layer for frequently accessed data (Redis/in-memory)
- [ ] Optimize React components with proper memoization
- [ ] Implement lazy loading for dashboard components and charts

## Medium Priority

### Security Enhancements
- [ ] Add CSRF protection for state-changing operations
- [ ] Implement session timeout and refresh token mechanism
- [ ] Add API rate limiting with Redis-backed storage (replace in-memory)
- [ ] Implement role-based access control (RBAC) for different user types
- [ ] Add audit logging for sensitive operations

### Code Quality & Maintenance
- [ ] Resolve remaining ESLint warnings and type issues
- [ ] Standardize chart library usage (currently mixing Chart.js and other libraries)
- [ ] Add proper TypeScript strict mode configuration
- [ ] Implement consistent API response formats across all endpoints

### Database & Schema
- [ ] Add database connection pooling configuration
- [ ] Implement proper database migrations for production deployment
- [ ] Add data retention policies for session data
- [ ] Consider database partitioning for large-scale data

### User Experience
- [ ] Add loading states and skeleton components throughout the application
- [ ] Implement proper form validation feedback and error messages
- [ ] Add pagination for large data sets in dashboard tables
- [ ] Implement real-time notifications for processing status updates

## Low Priority

### Documentation & Development
- [ ] Add API documentation (OpenAPI/Swagger)
- [ ] Create deployment guides for different environments
- [ ] Add contributing guidelines and code review checklist
- [ ] Implement development environment setup automation

### Feature Enhancements
- [ ] Add data export functionality (CSV, PDF reports)
- [ ] Implement dashboard customization and user preferences
- [ ] Add multi-language support (i18n)
- [ ] Create admin panel for system configuration

### Infrastructure & DevOps
- [ ] Add Docker configuration for containerized deployment
- [ ] Implement CI/CD pipeline with automated testing
- [ ] Add environment-specific configuration management
- [ ] Set up monitoring and health check endpoints

### Analytics & Insights
- [ ] Add more detailed analytics and reporting features
- [ ] Implement A/B testing framework for UI improvements
- [ ] Add user behavior tracking and analytics
- [ ] Create automated report generation and scheduling

## Completed ✅
- [x] Fix duplicate MetricCard components
- [x] Add input validation schema with Zod
- [x] Strengthen password requirements (12+ chars, complexity)
- [x] Fix schema drift - create missing migrations
- [x] Add rate limiting to authentication endpoints
- [x] Update README.md to use pnpm instead of npm
- [x] Implement platform authentication and basic dashboard
- [x] Add platform API endpoints for company management
- [x] Write tests for platform features (auth, dashboard, API)

## 📊 Test Coverage Status (< 30% Overall)

### ✅ Features WITH Tests:
- User Authentication (regular users)
- User Management UI & API
- Basic database connectivity
- Transcript Fetcher
- Input validation
- Environment configuration
- Format enums
- Accessibility features
- Keyboard navigation
- Platform authentication (NEW)
- Platform dashboard (NEW)
- Platform API endpoints (NEW)

### ❌ Features WITHOUT Tests (Critical Gaps):
- **Data Processing Pipeline** (0 tests)
  - CSV import scheduler
  - Import processor
  - Processing scheduler
  - AI processing functionality
  - Transcript parser
- **Most API Endpoints** (0 tests)
  - Dashboard endpoints
  - Session management
  - Admin endpoints
  - Password reset flow
- **Custom Server** (0 tests)
- **Dashboard Features** (0 tests)
  - Charts and visualizations
  - Session details
  - Company settings
- **AI Integration** (0 tests)
- **Real-time Features** (0 tests)
- **E2E Tests** (only examples exist)

## 🏛️ Architectural Decisions & Rationale

### Service Technology Choices
- **Dashboard Service**: Next.js + tRPC (existing, proven stack)
- **Data Ingestion Service**: Golang (high-performance CSV processing, concurrency)
- **AI Processing Service**: Node.js/Python (existing AI integrations, async processing)
- **Message Queue**: Redis + BullMQ (Node.js ecosystem compatibility)
- **Database**: PostgreSQL (existing, excellent for multi-tenancy)

### Why Golang for Data Ingestion?
- **Performance**: 10-100x faster CSV processing than Node.js
- **Concurrency**: Native goroutines for parallel transcript fetching
- **Memory Efficiency**: Lower memory footprint for large CSV files
- **Deployment**: Single binary deployment, excellent for containers
- **Team Growth**: Easy to hire Golang developers for data processing

### Migration Strategy
1. **Keep existing working system** while building new services
2. **Feature flagging** to gradually migrate companies to new processing
3. **Dual-write approach** during transition period
4. **Zero-downtime migration** with careful rollback plans

### Compliance Benefits
- **Data Isolation**: Each service has limited database access
- **Audit Trail**: All inter-service communication logged
- **Data Retention**: Automated per-company data lifecycle
- **Security Boundaries**: DMZ for ingestion, private network for processing

## Notes
- **CRITICAL**: Architectural refactoring must be priority #1 for scalability
- **Platform Management**: Notso AI needs self-service customer onboarding
- **Compliance First**: GDPR/ISO 27001 requirements drive service boundaries
- **Performance**: Current monolith blocks on CSV/AI processing
- **Technology Evolution**: Golang for data processing, tRPC for type safety