adhit-r / adhit-r/niyama-policy-as-code
🚀 Performance & Scalability
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- HTML
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Descrição
## Performance and Scalability Improvements
### High Priority
- [ ] Implement database query optimization
- [ ] Add caching layer (Redis) for frequently accessed data
- [ ] Optimize frontend bundle size and loading performance
- [ ] Implement API rate limiting and throttling
- [ ] Add database connection pooling
### Medium Priority
- [ ] Implement horizontal scaling for backend services
- [ ] Add CDN for static assets
- [ ] Create performance monitoring and alerting
- [ ] Implement lazy loading for large datasets
- [ ] Add database indexing optimization
### Low Priority
- [ ] Implement microservices architecture
- [ ] Add auto-scaling capabilities
- [ ] Create performance benchmarking suite
- [ ] Implement distributed caching
- [ ] Add load balancing optimization
## Performance Targets
- Frontend load time: < 2 seconds
- API response time: < 200ms (95th percentile)
- Database query time: < 100ms
- Support for 10,000+ concurrent users
- 99.9% uptime SLA
## Monitoring Requirements
- Application performance monitoring (APM)
- Database performance metrics
- API response time tracking
- Error rate monitoring
- Resource utilization tracking
Guia de contribuição
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Direção de pesquisa
The issue names no files, tests, or entry points and combines many independent performance goals. Start by narrowing the work to one target, such as Redis caching or frontend loading, then identify the affected entry points and baseline metrics. Done should be demonstrated against the stated response-time, load-time, scalability, or monitoring target.
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Avaliação
- Stack de tecnologia
- html, redis
- Domínio
- api, backend, databases, frontend, infrastructure, observability, performance
- Tipo de issue
- Funcionalidade
- Dificuldade
- 5/5
- Tempo estimado
- Mais de uma semana
- Status de atividade
- Estagnada
- Clareza
- Precisa de esclarecimento
- Facilidade para iniciantes
- 10/100