Step 10: Data Analytics and Statistics Service
- Created comprehensive statistics service with real-time metrics collection
- Implemented time-series data storage interface (InfluxDB compatible)
- Added data aggregation and analytics endpoints
- Integrated Redis caching for performance optimization
- Made Kafka connection optional for resilience
Step 11: Real-time Notification System
- Built multi-channel notification service (Email, SMS, Push, In-App)
- Implemented priority-based queue management with Redis
- Created template engine for dynamic notifications
- Added user preference management for personalized notifications
- Integrated WebSocket server for real-time updates
- Fixed pymongo/motor compatibility issues (motor 3.5.1)
Testing:
- Created comprehensive test suites for both services
- Added integration test script to verify cross-service communication
- All services passing health checks and functional tests
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
주요 기능:
- Statistics Service 마이크로서비스 구축
- 실시간 메트릭 수집 시스템 (Kafka 연동)
- 시계열 데이터베이스 인터페이스 구현
- 데이터 집계 및 분석 엔진
- 사용자/시스템/이벤트 분석 API
- WebSocket 기반 실시간 대시보드
- 알림 규칙 및 임계값 설정
- CSV 데이터 내보내기
구현된 컴포넌트:
- MetricsCollector: Kafka 이벤트 메트릭 수집
- DataAggregator: 시간별/일별 데이터 집계
- TimeSeriesDB: 시계열 데이터 저장 인터페이스
- WebSocketManager: 실시간 데이터 스트리밍
- Analytics APIs: 다양한 분석 엔드포인트
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
