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docs/PERFORMANCE_OPTIMIZATION.md
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# Performance Optimization Guide
**Date**: 2025-01-27
**Purpose**: Guide for optimizing performance across integrated system
**Status**: Complete
---
## Overview
This guide provides strategies and best practices for optimizing performance across the integrated workspace.
---
## Application Performance
### Code Optimization
#### TypeScript/JavaScript
- Use efficient algorithms
- Minimize object creation
- Cache expensive computations
- Use lazy loading
#### Database Queries
- Use indexes
- Avoid N+1 queries
- Use connection pooling
- Optimize joins
#### API Performance
- Implement caching
- Use compression
- Minimize payload size
- Batch requests
### Caching Strategies
#### Application Cache
```typescript
// In-memory cache
const cache = new Map();
function getCached(key: string) {
if (cache.has(key)) {
return cache.get(key);
}
const value = computeExpensive();
cache.set(key, value);
return value;
}
```
#### Redis Cache
```typescript
import { Redis } from 'ioredis';
const redis = new Redis();
async function getCached(key: string) {
const cached = await redis.get(key);
if (cached) return JSON.parse(cached);
const value = await computeExpensive();
await redis.setex(key, 3600, JSON.stringify(value));
return value;
}
```
---
## Infrastructure Performance
### Resource Optimization
#### Right-Sizing
- Monitor actual usage
- Adjust resources based on metrics
- Use auto-scaling
- Optimize for cost
#### Load Balancing
- Distribute traffic evenly
- Health check optimization
- Session affinity when needed
- Geographic distribution
### Database Performance
#### Connection Pooling
```typescript
const pool = new Pool({
max: 20,
min: 5,
idleTimeoutMillis: 30000,
connectionTimeoutMillis: 2000,
});
```
#### Query Optimization
- Use prepared statements
- Index frequently queried fields
- Analyze slow queries
- Use query caching
---
## Monitoring & Profiling
### Application Metrics
Track:
- Response times (p50, p95, p99)
- Throughput (requests/second)
- Error rates
- Resource usage (CPU, memory)
### Profiling Tools
#### Node.js
- `clinic.js` - Performance profiling
- `0x` - Flamegraph generation
- `autocannon` - Load testing
#### Database
- `EXPLAIN ANALYZE` - Query analysis
- Slow query logs
- Connection pool metrics
---
## Optimization Checklist
### Code Level
- [ ] Profile before optimizing
- [ ] Identify bottlenecks
- [ ] Optimize hot paths
- [ ] Use efficient algorithms
- [ ] Minimize allocations
### Infrastructure Level
- [ ] Right-size resources
- [ ] Enable caching
- [ ] Optimize database
- [ ] Use CDN for static assets
- [ ] Implement load balancing
### Monitoring Level
- [ ] Set up performance monitoring
- [ ] Track key metrics
- [ ] Set up alerts
- [ ] Regular performance reviews
- [ ] Continuous optimization
---
## Performance Targets
### Application
- **API Response Time**: < 200ms (p95)
- **Page Load Time**: < 2 seconds
- **Database Query Time**: < 100ms (p95)
- **Cache Hit Rate**: > 80%
### Infrastructure
- **CPU Usage**: < 70% average
- **Memory Usage**: < 80% average
- **Network Latency**: < 50ms
- **Disk I/O**: Optimized
---
**Last Updated**: 2025-01-27