pos-system/docs/en/skills/performance-optimization.md

---
name: performance-optimization
description: Performance optimization patterns for GoodGo microservices including database query optimization, memory leak detection, profiling, connection pooling, and caching strategies.
---

# Performance Optimization Patterns

## When to Use This Skill

Use this skill when:
- Optimizing database queries
- Detecting and fixing memory leaks
- Profiling application performance
- Optimizing connection pooling
- Improving caching strategies
- Identifying N+1 query problems

## Performance Optimization Workflow

The performance optimization process follows a systematic approach to identify, analyze, and resolve performance bottlenecks.

```mermaid
flowchart TD
    Start([Start Optimization]) --> Identify[Identify Performance Issue]
    Identify --> Monitor[Monitor Metrics]
    Monitor --> Profiling[Profile Application]
    Profiling --> Analyze[Analyze Results]
    Analyze --> IdentifyBottleneck{Identify Bottleneck}
    
    IdentifyBottleneck -->|Database| OptimizeDB[Optimize Queries]
    IdentifyBottleneck -->|Memory| OptimizeMem[Fix Memory Leaks]
    IdentifyBottleneck -->|Network| OptimizeNet[Optimize Connections]
    IdentifyBottleneck -->|Cache| OptimizeCache[Improve Caching]
    
    OptimizeDB --> Implement[Implement Optimization]
    OptimizeMem --> Implement
    OptimizeNet --> Implement
    OptimizeCache --> Implement
    
    Implement --> Test[Test Changes]
    Test --> Verify{Performance Improved?}
    Verify -->|Yes| Monitor
    Verify -->|No| Analyze
    Monitor --> Threshold{Meets Targets?}
    Threshold -->|Yes| Complete([Optimization Complete])
    Threshold -->|No| Profiling
```

## Query Optimization Flow

Database query optimization is a critical aspect of performance. This flow shows how to systematically optimize queries.

```mermaid
flowchart TD
    Start([Query Performance Issue]) --> Analyze[Analyze Query Performance]
    Analyze --> CheckIndexes[Check Indexes]
    CheckIndexes --> Explain[Run EXPLAIN ANALYZE]
    Explain --> IdentifyIssues{Identify Issues}
    
    IdentifyIssues -->|N+1 Queries| FixN1[Use Include/Join]
    IdentifyIssues -->|Missing Index| AddIndex[Add Database Index]
    IdentifyIssues -->|Slow Query| OptimizeQuery[Rewrite Query]
    IdentifyIssues -->|Unbounded| AddPagination[Add Pagination]
    
    FixN1 --> VerifyQuery[Verify Query Performance]
    AddIndex --> VerifyQuery
    OptimizeQuery --> VerifyQuery
    AddPagination --> VerifyQuery
    
    VerifyQuery --> TestQuery{Query Time < 50ms?}
    TestQuery -->|Yes| Complete([Optimization Complete])
    TestQuery -->|No| Analyze
    
    style FixN1 fill:#e1f5e1
    style AddIndex fill:#e1f5e1
    style OptimizeQuery fill:#e1f5e1
    style AddPagination fill:#e1f5e1
```

## Profiling Process

The profiling process helps identify performance bottlenecks through systematic data collection and analysis.

```mermaid
flowchart TD
    Start([Start Profiling]) --> Setup[Setup Profiling Tools]
    Setup --> ChooseTool{Choose Profiling Type}
    
    ChooseTool -->|CPU| CPUProf[CPU Profiling]
    ChooseTool -->|Memory| MemProf[Memory Profiling]
    ChooseTool -->|Database| DBProf[Database Query Profiling]
    
    CPUProf --> CollectCPU[Collect CPU Metrics]
    MemProf --> CollectMem[Collect Memory Metrics]
    DBProf --> CollectDB[Collect Query Metrics]
    
    CollectCPU --> Analyze[Analyze Profiling Data]
    CollectMem --> Analyze
    CollectDB --> Analyze
    
    Analyze --> IdentifyHotspots[Identify Hotspots]
    IdentifyHotspots --> Prioritize[Prioritize Issues]
    Prioritize --> Optimize[Optimize Critical Paths]
    Optimize --> ReProfile[Re-run Profiling]
    ReProfile --> Compare{Performance Improved?}
    Compare -->|Yes| Complete([Profiling Complete])
    Compare -->|No| IdentifyHotspots
    
    style CPUProf fill:#e3f2fd
    style MemProf fill:#e3f2fd
    style DBProf fill:#e3f2fd
```

## Key Patterns

### Database Query Optimization

```typescript
// Avoid N+1 queries
// Bad: Multiple queries
for (const user of users) {
  user.orders = await orderRepository.findByUserId(user.id);
}

// Good: Single query with join
const users = await userRepository.findAll({
  include: { orders: true },
});
```

### Memory Profiling

```typescript
// Monitor memory usage
const profiler = new MemoryProfiler();
profiler.start(); // Monitor every minute
```

### Batch Operations

```typescript
// Batch database operations
await batchOperations.batchCreate(items, 100); // Process 100 at a time
```

## Best Practices

1. Use indexes, avoid N+1 queries
2. Monitor memory usage, detect leaks
3. Cache frequently accessed data
4. Configure connection pools appropriately
5. Profile regularly to identify bottlenecks

## Resources

- [Caching Patterns](./caching-patterns.md)
- [Observability & Monitoring](./observability-monitoring.md)
- Skill Source: `.cursor/skills/performance-optimization/SKILL.md`