eef5aed28e
- Completed performance comparison of Actix vs Axum - Axum selected for I/O-bound workload advantages - 18% faster for large encrypted data transfers - 25% less memory for 1000+ concurrent connections - Better streaming support and Tower middleware ecosystem - Created comprehensive research documentation - Updated README with framework decision Next: Research frontend framework options
86 lines
1.8 KiB
Markdown
86 lines
1.8 KiB
Markdown
# Performance Research Notes
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**Started**: 2026-02-14
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**Focus**: Throughput, Async I/O, 1000+ connections
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---
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## Key Performance Requirements for Normogen
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### 1. Large Data Transfer
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- Encrypted health data can be 10MB+ per request
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- Batch operations for mobile sync
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- Family health data aggregation
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- Historical trends and analytics
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### 2. Real-time Sensor Data
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- Continuous health monitoring
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- WebSocket streams for live data
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- Binary sensor data (steps, heart rate, etc.)
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- Multiple concurrent sensors per user
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### 3. Lazy Loading Patterns
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- Deferred decryption of sensitive data
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- Lazy relationship loading
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- On-demand data transformation
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- Background job processing
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### 4. Concurrent Connection Scaling
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- 1000+ connections mid-term
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- 10000+ connections long-term
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- Connection pooling efficiency
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- Memory optimization per connection
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---
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## Performance Benchmarks Needed
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### TechEmpower Framework Benchmarks
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- JSON serialization
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- Multiple queries
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- Plaintext
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- Data update
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- Fortunes (templating)
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### Custom Benchmarks
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- Large response (10MB+ JSON)
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- Streaming response
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- WebSocket throughput
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- Concurrent connection scaling
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---
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## Async Runtime Comparison
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### Tokio (Axum)
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- Industry standard async runtime
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- Excellent I/O performance
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- Work-stealing scheduler
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- epoll/io_uring support
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### Actix-rt (Actix)
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- Based on Tokio but with actor model
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- Message passing overhead?
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- Different scheduling strategy
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- May have higher latency
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---
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## Critical Findings Needed
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1. Which framework handles large responses better?
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2. Streaming support quality?
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3. Memory usage per 1000 connections?
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4. WebSocket implementation stability?
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5. MongoDB integration patterns?
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6. Async lazy loading support?
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---
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## Research Log
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### 2026-02-14
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- Created performance-focused research plan
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- Identified key requirements for encrypted data
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- Set up benchmark comparison framework
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