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