Performance Audit Command

Audit application performance metrics

Instructions

Conduct a comprehensive performance audit following these steps:

1. Technology Stack Analysis

   • Identify the primary language, framework, and runtime environment
   • Review build tools and optimization configurations
   • Check for performance monitoring tools already in place

2. Code Performance Analysis

   • Identify inefficient algorithms and data structures
   • Look for nested loops and O(n²) operations
   • Check for unnecessary computations and redundant operations
   • Review memory allocation patterns and potential leaks

3. Database Performance

   • Analyze database queries for efficiency
   • Check for missing indexes and slow queries
   • Review connection pooling and database configuration
   • Identify N+1 query problems and excessive database calls

4. Frontend Performance (if applicable)

   • Analyze bundle size and chunk optimization
   • Check for unused code and dependencies
   • Review image optimization and lazy loading
   • Examine render performance and re-render cycles
   • Check for memory leaks in UI components

5. Network Performance

   • Review API call patterns and caching strategies
   • Check for unnecessary network requests
   • Analyze payload sizes and compression
   • Examine CDN usage and static asset optimization

6. Asynchronous Operations

   • Review async/await usage and promise handling
   • Check for blocking operations and race conditions
   • Analyze task queuing and background processing
   • Identify opportunities for parallel execution

7. Memory Usage

   • Check for memory leaks and excessive memory consumption
   • Review garbage collection patterns
   • Analyze object lifecycle and cleanup
   • Identify large objects and unnecessary data retention

8. Build & Deployment Performance

   • Analyze build times and optimization opportunities
   • Review dependency bundling and tree shaking
   • Check for development vs production optimizations
   • Examine deployment pipeline efficiency

9. Performance Monitoring

   • Check existing performance metrics and monitoring
   • Identify key performance indicators (KPIs) to track
   • Review alerting and performance thresholds
   • Suggest performance testing strategies

10. Benchmarking & Profiling

    • Run performance profiling tools appropriate for the stack
    • Create benchmarks for critical code paths
    • Measure before and after optimization impact
    • Document performance baselines

11. Optimization Recommendations

    • Prioritize optimizations by impact and effort
    • Provide specific code examples and alternatives
    • Suggest architectural improvements for scalability
    • Recommend appropriate performance tools and libraries

Include specific file paths, line numbers, and measurable metrics where possible. Focus on high-impact, low-effort optimizations first.