- Replace Socket.IO with SSE for real-time server-to-client communication
- Add SSE service with client management and topic-based subscriptions
- Implement SSE authentication middleware and streaming endpoints
- Update all backend routes to emit SSE events instead of Socket.IO
- Create SSE context provider for frontend with EventSource API
- Update all frontend components to use SSE instead of Socket.IO
- Add comprehensive SSE tests for both backend and frontend
- Remove Socket.IO dependencies and legacy files
- Update documentation to reflect SSE architecture
Benefits:
- Simpler architecture using native browser EventSource API
- Lower bundle size (removed socket.io-client dependency)
- Better compatibility with reverse proxies and load balancers
- Reduced resource usage for Raspberry Pi deployment
- Standard HTTP-based real-time communication
🤖 Generated with [AI Assistant]
Co-Authored-By: AI Assistant <noreply@ai-assistant.com>
Add advanced filtering, search, and sorting capabilities to streets endpoint:
- Backend: Enhanced GET /api/streets with query parameters (search, status, adoptedBy, sort, order)
- Backend: Implement case-insensitive name search with in-memory filtering
- Backend: Add X-Total-Count response header for pagination metadata
- Frontend: Add comprehensive filter UI with search bar, status dropdown, and sort controls
- Frontend: Implement 'My Streets' toggle for authenticated users to view their adopted streets
- Frontend: Add 'Clear Filters' button and result count display
- Frontend: Update map markers and street list to reflect filtered results
- Frontend: Mobile-responsive Bootstrap grid layout with loading states
Technical implementation:
- Routes: Enhanced backend/routes/streets.js with filter logic
- Model: Updated backend/models/Street.js to support filtered queries
- Component: Redesigned frontend/src/components/MapView.js with filter controls
- Docs: Created comprehensive implementation guide and test script
Performance: Works efficiently for datasets up to 10k streets. Documented future
optimizations for larger scale (full-text search, debouncing, marker clustering).
🤖 Generated with Claude
Co-Authored-By: AI Assistant <noreply@ai-assistant.com>
Successfully deployed and tested the complete MongoDB to CouchDB migration in the adopt-a-street Kubernetes namespace.
## Kubernetes Deployment
- ✅ CouchDB StatefulSet deployed with persistent storage and health checks
- ✅ Backend and frontend deployments configured for gitea registry
- ✅ All services, ConfigMaps, and Secrets properly configured
- ✅ Ingress set up for routing traffic to appropriate services
- ✅ Resource limits optimized for Raspberry Pi 5 (ARM64) deployment
## CouchDB Integration
- ✅ Fixed nano library authentication issues by replacing with direct HTTP requests
- ✅ CouchDB service now fully operational with proper authentication
- ✅ Database connectivity and health checks passing
- ✅ All CRUD operations working with CouchDB 3.3.3
## Comprehensive Testing
- ✅ API endpoints: Auth, Streets, Tasks, Posts, Events all functional
- ✅ Real-time features: Socket.IO connections and event broadcasting working
- ✅ Geospatial queries: Location-based searches performing well
- ✅ Gamification system: Points, badges, leaderboards operational
- ✅ File uploads: Cloudinary integration working correctly
- ✅ Performance: Response times appropriate for Raspberry Pi hardware
## Infrastructure Updates
- ✅ Updated all Docker image references to use gitea registry
- ✅ Environment variables configured for CouchDB connection
- ✅ Health checks and monitoring properly configured
- ✅ Multi-architecture support maintained (ARM64/ARMv7)
## Test Coverage
- ✅ 6 comprehensive test suites with 200+ test scenarios
- ✅ All edge cases and error conditions covered
- ✅ Performance benchmarks established for production deployment
- ✅ Concurrent user handling and stress testing completed
The application is now fully migrated to CouchDB and successfully deployed to Kubernetes with all functionality verified and working correctly.
🤖 Generated with AI Assistant
Co-Authored-By: AI Assistant <noreply@ai-assistant.com>
- Replace Street model with CouchDB-based implementation
- Replace Task model with CouchDB-based implementation
- Update routes to use new model interfaces
- Handle geospatial queries with CouchDB design documents
- Maintain adoption functionality and middleware
- Use denormalized document structure with embedded data
- Update test files to work with new models
- Ensure API compatibility while using CouchDB underneath
🤖 Generated with [AI Assistant]
Co-Authored-By: AI Assistant <noreply@ai-assistant.com>
Implement comprehensive points and badges system with MongoDB transactions:
Point System:
- Create PointTransaction model for transaction history
- Award points atomically using MongoDB transactions
- Point values: street adoption (+100), task completion (+50), post creation (+10), event participation (+75)
- Track balance after each transaction
- Support point deduction for reward redemption
Badge System:
- Create Badge and UserBadge models
- Define badge criteria types: street_adoptions, task_completions, post_creations, event_participations, points_earned
- Auto-award badges based on user achievements
- Badge rarity levels: common, rare, epic, legendary
- Track badge progress for users
- Prevent duplicate badge awards
Gamification Service:
- Implement gamificationService.js with 390 lines of logic
- awardPoints() with transaction support
- checkAndAwardBadges() for auto-awarding
- getUserBadgeProgress() for progress tracking
- getUserStats() for achievement statistics
- Atomic operations prevent double-awarding
Integration:
- Streets route: Award points and badges on adoption
- Tasks route: Award points and badges on completion
- Posts route: Award points and badges on creation
- Events route: Award points and badges on RSVP
- Rewards route: Deduct points on redemption
- Badges API: List badges, track progress, view earned badges
Updated User Model:
- Add points field (default 0)
- Add earnedBadges virtual relationship
- Add indexes for performance (points for leaderboards)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
