Completed File Management Service with S3-compatible object storage:
Infrastructure:
- Added MinIO for S3-compatible object storage (port 9000/9001)
- Integrated with MongoDB for metadata management
- Configured Docker volumes for persistent storage
File Service Features:
- Multi-file upload support with deduplication
- Automatic thumbnail generation for images (multiple sizes)
- File metadata management with search and filtering
- Presigned URLs for secure direct uploads/downloads
- Public/private file access control
- Large file upload support with chunking
- File type detection and categorization
API Endpoints:
- File upload (single and multiple)
- File retrieval with metadata
- Thumbnail generation and caching
- Storage statistics and analytics
- Bucket management
- Batch operations support
Technical Improvements:
- Fixed Pydantic v2.5 compatibility (regex -> pattern)
- Optimized thumbnail caching strategy
- Implemented file hash-based deduplication
Testing:
- All services health checks passing
- MinIO and file service fully operational
- Ready for production use
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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
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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
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Co-Authored-By: Claude <noreply@anthropic.com>
주요 기능:
- Kafka 이벤트 컨슈머 및 프로듀서 통합
- 지수 백오프 재시도 메커니즘 구현
- Dead Letter Queue (DLQ) 설정
- 이벤트 스키마 레지스트리 (Pydantic v2 호환)
- Console 서비스에 이벤트 관리 API 추가
- 실시간 이벤트 통계 및 모니터링
- 엔드-투-엔드 테스트 스크립트
구현된 이벤트 타입:
- USER_CREATED, USER_UPDATED, USER_DELETED
- OAUTH_APP_CREATED, OAUTH_TOKEN_ISSUED
- IMAGE_UPLOADED, IMAGE_PROCESSED
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- Updated PLAN.md to reflect Step 8 completion
- Added OAuth service to current services list
- Renumbered subsequent steps
- Updated PROGRESS.md with Step 8 details and outcomes
- Added new service ports and problem resolutions
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- OAuth 2.0 서비스 구현
* Authorization Code, Client Credentials, Refresh Token 플로우 지원
* 애플리케이션 등록 및 관리 기능
* 토큰 introspection 및 revocation
* SSO 설정 지원 (Google, GitHub, SAML)
* 실용적인 스코프 시스템 (user, app, org, api 관리)
- 사용자 프로필 기능 확장
* 프로필 사진 및 썸네일 필드 추가
* bio, location, website 등 추가 프로필 정보
* 이메일 인증 및 계정 활성화 상태 관리
* UserPublicResponse 모델 추가
- OAuth 스코프 관리
* picture 스코프 추가 (프로필 사진 접근 제어)
* 카테고리별 스코프 정리 (기본 인증, 사용자 데이터, 앱 관리, 조직, API)
* 스코프별 승인 필요 여부 설정
- 인프라 개선
* Users 서비스 포트 매핑 추가 (8001)
* OAuth 서비스 Docker 구성 (포트 8003)
* Kafka 이벤트 통합 (USER_CREATED, USER_UPDATED, USER_DELETED)
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- Kafka 및 Zookeeper 컨테이너 추가
- 공유 Kafka 라이브러리 생성 (Producer/Consumer)
- 이벤트 타입 정의 및 이벤트 모델 구현
- Users 서비스에 이벤트 발행 기능 추가 (USER_CREATED, USER_UPDATED, USER_DELETED)
- PROGRESS.md 및 PLAN.md 문서 생성
- aiokafka 통합 완료
- Integrated image-service from site00 as second microservice
- Maintained proxy and caching functionality
- Added Images service to docker-compose
- Configured Console API Gateway routing to Images
- Updated environment variables in .env
- Successfully tested image proxy endpoints
Services now running:
- Console (API Gateway)
- Users Service
- Images Service (proxy & cache)
- MongoDB & Redis
Next: Kafka event system implementation
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- Implemented JWT authentication in Console backend
- Added .env file for environment variable management
- Updated docker-compose to use .env variables
- Created authentication endpoints (login/logout/me)
- Added protected route middleware
- Created ARCHITECTURE.md with Kafka as main messaging platform
- Defined Kafka for both events and task queues
- Redis dedicated for caching and session management
Test credentials:
- admin/admin123
- user/user123
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- Created React application with TypeScript and Material-UI
- Implemented dashboard with service health monitoring
- Added Services and Users management pages
- Configured Nginx as reverse proxy to backend
- Successfully integrated frontend with Console backend
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- Added MongoDB and Redis containers to docker-compose
- Integrated Users service with MongoDB using Beanie ODM
- Replaced in-memory storage with persistent MongoDB
- Added proper data models with email validation
- Verified data persistence with MongoDB ObjectIDs
Services running:
- MongoDB: Port 27017 (with health checks)
- Redis: Port 6379 (with health checks)
- Users service: Connected to MongoDB
- Console: API Gateway routing working
Test: Users now stored in MongoDB with persistence
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- Created Users service with full CRUD operations
- Updated Console to act as API Gateway for Users service
- Implemented service-to-service communication
- Added service health monitoring in Console
- Docker Compose now manages both services
Services running:
- Console (API Gateway): http://localhost:8011
- Users service: Internal network only
Test endpoints:
- Status: curl http://localhost:8011/api/status
- Users: curl http://localhost:8011/api/users/users🤖 Generated with Claude Code
Co-Authored-By: Claude <noreply@anthropic.com>
- Created docker-compose.yml with Console backend service
- Implemented Console backend with FastAPI (port 8011)
- Added health check and status endpoints
- Set up Docker-only development principle
- Console service successfully running as API Gateway foundation
Test with:
- curl http://localhost:8011/health
- curl http://localhost:8011/api/status🤖 Generated with Claude Code
Co-Authored-By: Claude <noreply@anthropic.com>
- Created CLAUDE.md with architecture guidelines and context recovery guide
- Created docs/PLAN.md with progressive implementation strategy
- Created docs/PROGRESS.md for checkpoint tracking
- Added .gitignore for Python, Node, Docker environments
- Established API Gateway pattern with Console as orchestrator
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Co-Authored-By: Claude <noreply@anthropic.com>
