2.5 KiB
2.5 KiB
Performance Considerations Checklist
Use this checklist to assess performance implications of code examples and recommendations.
Algorithm Efficiency
- Algorithm complexity appropriate (avoid O(n²) where O(n) possible)
- Data structures chosen appropriately
- Unnecessary iterations avoided
- Early termination conditions used where applicable
- Recursive vs iterative approaches considered
Database Performance
- N+1 query problem avoided
- Appropriate use of indexes mentioned
- Query optimization demonstrated
- Lazy loading vs eager loading discussed
- Database connection pooling recommended
- Pagination implemented for large datasets
Caching
- Caching strategies mentioned where beneficial
- Cache invalidation discussed
- Appropriate cache levels considered (application, database, CDN)
- Memory vs speed tradeoffs explained
Memory Management
- No obvious memory leaks
- Large data structures handled appropriately
- Memory usage patterns reasonable
- Object pooling or reuse considered where relevant
- Garbage collection implications discussed
Network Performance
- API calls minimized
- Batch operations used where appropriate
- Compression mentioned for large payloads
- Async operations used for I/O
- Connection reuse demonstrated
Scalability
- Solutions scale to production workloads
- Resource constraints considered
- Horizontal scaling implications discussed
- Stateless design patterns where appropriate
- Load distribution strategies mentioned
Optimization Balance
- Premature optimization avoided
- Clarity prioritized over micro-optimizations
- Performance tradeoffs explained
- When to optimize discussed (profiling first)
- Educational clarity maintained
Profiling & Monitoring
- Profiling tools mentioned where relevant
- Performance testing approaches suggested
- Monitoring best practices referenced
- Bottleneck identification techniques shown
- Benchmarking guidance provided
Resource Usage
- File handles closed properly
- Database connections released
- Thread/process management appropriate
- Timeouts configured
- Rate limiting considered for APIs
Production Considerations
- Development vs production differences noted
- Logging performance impact discussed
- Debug mode disabled in production examples
- Production-ready patterns demonstrated
- Performance SLAs considered