mirror of
https://github.com/SamyRai/turash.git
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000eab4740
Repository Structure:
- Move files from cluttered root directory into organized structure
- Create archive/ for archived data and scraper results
- Create bugulma/ for the complete application (frontend + backend)
- Create data/ for sample datasets and reference materials
- Create docs/ for comprehensive documentation structure
- Create scripts/ for utility scripts and API tools
Backend Implementation:
- Implement 3 missing backend endpoints identified in gap analysis:
* GET /api/v1/organizations/{id}/matching/direct - Direct symbiosis matches
* GET /api/v1/users/me/organizations - User organizations
* POST /api/v1/proposals/{id}/status - Update proposal status
- Add complete proposal domain model, repository, and service layers
- Create database migration for proposals table
- Fix CLI server command registration issue
API Documentation:
- Add comprehensive proposals.md API documentation
- Update README.md with Users and Proposals API sections
- Document all request/response formats, error codes, and business rules
Code Quality:
- Follow existing Go backend architecture patterns
- Add proper error handling and validation
- Match frontend expected response schemas
- Maintain clean separation of concerns (handler -> service -> repository)
59 lines
2.0 KiB
Markdown
59 lines
2.0 KiB
Markdown
## 15. Monitoring & Observability
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**Recommendation**: Comprehensive observability from day one.
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### Metrics to Track
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**Business Metrics** (Daily/Monthly Dashboard):
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- **Active businesses**: 500+ (Year 1), 2,000+ (Year 2), 5,000+ (Year 3)
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- **Sites & resource flows**: 85% data completion rate target
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- **Match rate**: 60% conversion from suggested to implemented matches
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- **Average savings**: €25,000 per implemented connection
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- **Platform adoption**: 15-20% free-to-paid conversion rate
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**Technical Metrics** (Real-time Monitoring):
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- **API response times**: p50 <500ms, p95 <2s, p99 <5s
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- **Graph query performance**: <1s for 95% of queries
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- **Match computation latency**: <30s for complex optimizations
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- **Error rates**: <1% API errors, <0.1% critical errors
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- **Database connection pool**: 70-90% utilization target
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- **Cache hit rates**: >85% Redis hit rate, >95% application cache
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- **Uptime**: >99.5% availability target
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**Domain-Specific Metrics**:
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- **Matching accuracy**: >90% user satisfaction with match quality
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- **Economic calculation precision**: ±€100 accuracy on savings estimates
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- **Geospatial accuracy**: <100m error on location-based matching
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- **Real-time updates**: <5s delay for new resource notifications
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### Alerting
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**Critical Alerts**:
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- API error rate > 1%
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- Database connection failures
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- Match computation failures
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- Cache unavailable
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**Warning Alerts**:
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- High latency (p95 > 2s)
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- Low cache hit rate (< 70%)
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- Disk space low
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**Tools**:
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- **Prometheus**: Metrics collection
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- **Grafana**: Visualization and dashboards
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- **AlertManager**: Alert routing and notification
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- **Loki or ELK**: Logging (Elasticsearch, Logstash, Kibana)
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- **Jaeger or Zipkin**: Distributed tracing
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- **Sentry**: Error tracking
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### Observability Tools
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- **Metrics**: Prometheus + Grafana
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- **Logging**: Loki or ELK stack
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- **Tracing**: Jaeger or Zipkin for distributed tracing
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- **APM**: Sentry for error tracking
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- **OpenTelemetry**: `go.opentelemetry.io/otel` for instrumentation
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---
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