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

name, description

name	description
performance-optimization	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.

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.

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.

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

// 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

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

Batch Operations

// 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
• Observability & Monitoring
• Skill Source: .cursor/skills/performance-optimization/SKILL.md