382 lines
13 KiB
Markdown
382 lines
13 KiB
Markdown
# Ticket Scaling Microservice - Design Document
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## Table of Contents
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1. [Architecture Overview](#architecture-overview)
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2. [System Components](#system-components)
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3. [Scalability Strategies](#scalability-strategies)
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4. [Atomic Operations](#atomic-operations)
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5. [Fallback Mechanisms](#fallback-mechanisms)
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6. [Performance Optimizations](#performance-optimizations)
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7. [Monitoring & Observability](#monitoring--observability)
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8. [Security Considerations](#security-considerations)
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9. [Deployment Strategy](#deployment-strategy)
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10. [Future Enhancements](#future-enhancements)
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## Architecture Overview
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### High-Level Architecture
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```
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┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
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│ Load Balancer │ │ Prometheus │ │ Grafana │
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│ (Optional) │ │ Monitoring │ │ Dashboard │
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└─────────────────┘ └─────────────────┘ └─────────────────┘
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│ │ │
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│ │ │
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┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
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│ │ │ │ │ │
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│ Ticket Service │◄───┤ Redis │ │ In-Memory │
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│ (Node.js/ │ │ Primary Store │ │ Fallback Store │
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│ Express) │ │ │ │ │
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│ │ │ │ │ │
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└─────────────────┘ └─────────────────┘ └─────────────────┘
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│
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│
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┌─────────────────┐
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│ PDF Generator │
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│ (PDFKit) │
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└─────────────────┘
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```
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### Design Principles
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1. **High Availability**: Fallback mechanisms ensure service continuity
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2. **Atomic Operations**: Redis Lua scripts prevent race conditions
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3. **Horizontal Scalability**: Stateless design enables easy scaling
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4. **Observability**: Comprehensive logging and metrics
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5. **Performance**: Optimized for high-throughput scenarios
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## System Components
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### 1. Core Application (server.js)
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- **Technology**: Node.js with Express framework
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- **Responsibilities**:
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- HTTP request handling
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- Business logic orchestration
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- Error handling and logging
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- PDF generation coordination
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### 2. Redis Client (redis-client.js)
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- **Technology**: Redis with Lua scripting
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- **Responsibilities**:
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- Atomic ticket operations
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- Event metadata management
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- Connection health monitoring
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- Script execution
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### 3. Fallback Store (fallback-store.js)
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- **Technology**: In-memory JavaScript Map
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- **Responsibilities**:
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- Emergency ticket storage
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- Temporary operation continuity
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- Graceful degradation
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### 4. PDF Generator (pdf-generator.js)
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- **Technology**: PDFKit library
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- **Responsibilities**:
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- Professional ticket generation
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- File management
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- Cleanup operations
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### 5. Logging System (logger.js)
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- **Technology**: Winston logging framework
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- **Responsibilities**:
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- Structured logging
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- Request tracking
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- Error reporting
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- Performance metrics
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## Scalability Strategies
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### Horizontal Scaling
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```
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┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
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│ Instance 1 │ │ Instance 2 │ │ Instance N │
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│ Port: 3049 │ │ Port: 3050 │ │ Port: 305X │
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└─────────────────┘ └─────────────────┘ └─────────────────┘
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│ │ │
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└───────────────────────┼───────────────────────┘
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│
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┌─────────────────┐
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│ Shared Redis │
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│ Cluster │
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└─────────────────┘
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```
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**Key Features**:
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- Stateless application design
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- Shared Redis backend
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- Load balancer distribution
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- Independent scaling
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### Vertical Scaling
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- **CPU**: Multi-core utilization through Node.js cluster mode
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- **Memory**: Configurable heap sizes for high-throughput
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- **I/O**: Async operations prevent blocking
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### Database Scaling
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```
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┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
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│ Redis Master │ │ Redis Replica │ │ Redis Replica │
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│ (Read/Write) │───▶│ (Read Only) │ │ (Read Only) │
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└─────────────────┘ └─────────────────┘ └─────────────────┘
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```
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**Strategies**:
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- Redis clustering for horizontal scaling
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- Read replicas for metrics/stats queries
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- Sharding by event ID for massive scale
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## Atomic Operations
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### Lua Script Design
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Our core purchase operation uses a Redis Lua script to ensure atomicity:
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```lua
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-- Atomic ticket purchase script
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local ticketKey = KEYS[1] -- event:X:tickets
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local metaKey = KEYS[2] -- event:X:meta
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local globalKey = KEYS[3] -- global:stats
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-- Atomic operations:
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1. Check event exists
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2. Pop ticket from list
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3. Update sold count
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4. Update global stats
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5. Store purchase record
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```
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**Benefits**:
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- **Race Condition Prevention**: All operations execute atomically
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- **Consistency**: No partial state updates
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- **Performance**: Single round-trip to Redis
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- **Reliability**: All-or-nothing execution
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### Concurrency Handling
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- **Optimistic Locking**: Lua scripts handle concurrent access
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- **Queue Management**: Redis lists provide FIFO ticket distribution
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- **Connection Pooling**: Efficient Redis connection reuse
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## Fallback Mechanisms
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### Activation Triggers
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1. **Redis Connection Failure**: Network issues or Redis downtime
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2. **Script Execution Errors**: Lua script failures
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3. **Timeout Scenarios**: Slow Redis responses
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### Fallback Architecture
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```
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┌─────────────────┐
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│ Request Comes │
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└─────────────────┘
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│
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▼
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┌─────────────────┐ ┌─────────────────┐
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│ Try Redis │───▶│ Redis Success │
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│ Operation │ │ Return Result │
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└─────────────────┘ └─────────────────┘
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│
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▼ (On Failure)
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┌─────────────────┐ ┌─────────────────┐
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│ Activate │───▶│ In-Memory │
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│ Fallback Store │ │ Operation │
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└─────────────────┘ └─────────────────┘
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```
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### Fallback Store Improvements
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- **Automatic Seeding**: Fallback store is seeded during server startup and when activated
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- **Data Synchronization**: Automatic attempt to sync with Redis data when activated
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- **Manual Seeding**: Admin endpoint to manually populate fallback store from Redis
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- **Resilient Operation**: Continues functioning even when Redis is completely unavailable
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### Fallback Limitations
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- **Non-Persistent**: Data lost on restart (mitigated by automatic reseeding)
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- **Single Instance**: No cross-instance synchronization
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- **Capacity Limited**: Memory constraints
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- **Warning Logs**: Clear indication of degraded mode
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## Performance Optimizations
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### Application Level
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1. **Async Operations**: Non-blocking I/O throughout
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2. **Connection Pooling**: Reuse Redis connections
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3. **Batch Operations**: Bulk ticket seeding
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4. **Caching**: Event metadata caching
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### Redis Optimizations
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1. **Lua Scripts**: Reduced network round-trips
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2. **Pipeline Operations**: Batch commands
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3. **Memory Management**: Efficient data structures
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4. **Persistence**: AOF for durability
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### PDF Generation
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1. **Async Generation**: Non-blocking PDF creation
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2. **Stream Processing**: Memory-efficient file handling
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3. **Cleanup Jobs**: Automatic old file removal
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4. **Error Isolation**: PDF failures don't affect purchases
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## Monitoring & Observability
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### Metrics Collection
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```json
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{
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"global": {
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"totalEvents": 5,
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"totalTickets": 50000,
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"totalSold": 1250
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},
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"events": [
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{
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"eventId": "1",
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"soldTickets": 250,
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"remainingTickets": 9750
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}
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],
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"system": {
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"usingFallback": false,
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"redisConnected": true,
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"uptime": 3600,
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"memoryUsage": {...}
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},
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"pdf": {
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"totalTickets": 1250,
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"totalSizeMB": "15.6"
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}
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}
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```
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### Logging Strategy
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- **Structured Logging**: JSON format for parsing
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- **Request Tracking**: Unique IDs for tracing
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- **Performance Metrics**: Response times and throughput
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- **Error Categorization**: Different log levels
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### Health Checks
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- **Application Health**: `/health` endpoint
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- **Redis Connectivity**: Connection status
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- **Fallback Status**: Degraded mode indication
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- **Resource Usage**: Memory and CPU monitoring
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## Security Considerations
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### Input Validation
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- **Event ID Validation**: Numeric constraints with range checking
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- **Purchase ID Validation**: UUID format validation
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- **Request Rate Limiting**: Multi-tier DDoS protection
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- **Parameter Sanitization**: Injection prevention
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- **Request Size Limits**: Prevents large payload attacks
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### Container Security
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- **Non-Root User**: Principle of least privilege
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- **Minimal Base Image**: Alpine Linux for smaller attack surface
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- **Health Checks**: Container monitoring
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### Data Protection
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- **No Sensitive Data**: Tickets are identifiers only
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- **Audit Logging**: Purchase tracking
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- **Secure Defaults**: Production-ready configuration
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### Security Headers & Middleware
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- **Helmet.js**: Comprehensive security headers
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- **Content Security Policy**: XSS prevention
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- **HSTS**: HTTPS enforcement
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- **Frame Guard**: Clickjacking protection
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- **Security Logging**: Suspicious request monitoring
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## Deployment Strategy
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### Development Environment
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```bash
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# Local development
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npm install
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npm run docker:up # Start Redis
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npm run seed # Seed events
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npm run dev # Start with nodemon
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```
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### Production Environment
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```bash
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# Docker deployment
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docker-compose up -d # Core services
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docker-compose --profile monitoring up # With monitoring
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```
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### Container Orchestration
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- **Docker Compose**: Local and small deployments
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- **Kubernetes**: Large-scale deployments
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- **Health Checks**: Automatic restart on failure
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- **Resource Limits**: CPU and memory constraints
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## Future Enhancements
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### Performance Improvements
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1. **Redis Clustering**: Horizontal database scaling
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2. **CDN Integration**: PDF delivery optimization
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3. **Caching Layer**: Application-level caching
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4. **Connection Optimization**: Advanced pooling
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### Feature Additions
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1. **QR Code Generation**: Enhanced ticket security
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2. **Email Integration**: Automatic ticket delivery
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3. **Payment Processing**: Complete purchase flow
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4. **Event Management**: Dynamic event creation
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### Monitoring Enhancements
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1. **Distributed Tracing**: Request flow tracking
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2. **Custom Dashboards**: Business metrics visualization
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3. **Alerting**: Proactive issue detection
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4. **Performance Profiling**: Bottleneck identification
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### Security Hardening
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1. **Authentication**: API key management
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2. **Rate Limiting**: Advanced throttling
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3. **Encryption**: Data in transit protection
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4. **Audit Trails**: Comprehensive logging
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## Conclusion
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This design provides a robust, scalable foundation for high-volume ticket sales with the following key strengths:
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- **Atomic Operations**: Guaranteed consistency under load
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- **High Availability**: Graceful degradation capabilities
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- **Observability**: Comprehensive monitoring and logging
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- **Scalability**: Horizontal and vertical scaling support
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- **Performance**: Optimized for high-throughput scenarios
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The architecture successfully handles the challenge requirements of processing thousands of concurrent requests while maintaining data integrity and system reliability.
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