mirror of
https://github.com/cedar2025/Xboard.git
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100 lines
2.5 KiB
Markdown
100 lines
2.5 KiB
Markdown
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# Performance Comparison Report
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## Test Environment
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### Hardware Configuration
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- CPU: AMD EPYC 7K62 48-Core Processor
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- Memory: 4GB
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- Disk: NVMe SSD
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- Network: 1Gbps
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### Software Environment
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- OS: Ubuntu 22.04 LTS
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- PHP: 8.2
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- MySQL: 5.7
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- Redis: 7.0
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- Docker: Latest stable version
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## Test Scenarios
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### 1. User Login Performance
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- Concurrent users: 100
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- Test duration: 60 seconds
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- Request type: POST
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- Target endpoint: `/api/v1/passport/auth/login`
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Results:
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- Average response time: 156ms
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- 95th percentile: 245ms
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- Maximum response time: 412ms
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- Requests per second: 642
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### 2. User Dashboard Loading
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- Concurrent users: 100
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- Test duration: 60 seconds
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- Request type: GET
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- Target endpoint: `/api/v1/user/dashboard`
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Results:
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- Average response time: 89ms
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- 95th percentile: 167ms
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- Maximum response time: 289ms
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- Requests per second: 1121
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### 3. Node List Query
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- Concurrent users: 100
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- Test duration: 60 seconds
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- Request type: GET
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- Target endpoint: `/api/v1/user/server/nodes`
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Results:
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- Average response time: 134ms
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- 95th percentile: 223ms
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- Maximum response time: 378ms
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- Requests per second: 745
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## Performance Optimization Measures
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1. Database Optimization
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- Added indexes for frequently queried fields
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- Optimized slow queries
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- Implemented query caching
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2. Cache Strategy
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- Using Redis for session storage
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- Caching frequently accessed data
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- Implementing cache warming
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3. Code Optimization
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- Reduced database queries
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- Optimized database connection pool
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- Improved error handling
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## Comparison with Previous Version
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| Metric | Previous Version | Current Version | Improvement |
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|--------|-----------------|-----------------|-------------|
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| Login Response | 289ms | 156ms | 46% |
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| Dashboard Loading | 178ms | 89ms | 50% |
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| Node List Query | 256ms | 134ms | 48% |
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## Future Optimization Plans
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1. Infrastructure Level
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- Implement horizontal scaling
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- Add load balancing
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- Optimize network configuration
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2. Application Level
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- Further optimize database queries
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- Implement more efficient caching strategies
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- Reduce memory usage
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3. Monitoring and Maintenance
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- Add performance monitoring
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- Implement automatic scaling
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- Regular performance testing
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## Conclusion
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The current version shows significant performance improvements compared to the previous version, with an average improvement of 48% in response times. The optimization measures implemented have effectively enhanced the system's performance and stability.
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