Performance Optimizer

Performance Optimization

Overview

Use this skill to analyze and improve the performance of the codebase. Focus on measurable improvements, not premature optimization.

Workflow

1. Measure First:

   • Never optimize without a baseline.
   • Use profiling tools or simple timing logs to identify bottlenecks.
   • "What gets measured, gets managed."

2. Analyze and Hypothesize:

   • Identify the root cause: CPU, Memory, I/O, or Network?
   • Look for common culprits: N+1 queries, unoptimized loops, large payload sizes, unnecessary re-renders (frontend).

3. Optimize:

   • Algorithmic: Improve Big-O complexity (e.g., O(n^2) -> O(n)).
   • Caching: Implement caching strategies (in-memory, Redis, HTTP caching).
   • Database: Add indexes, optimize queries, use batching.
   • Frontend: Lazy loading, memoization, code splitting, asset optimization.

4. Verify:

   • Run the measurements again.
   • Confirm the improvement.
   • Ensure no regression in functionality.

Techniques & Patterns

• Database: Explain Analyze, Indexing, Connection Pooling.
• Backend: Async processing, Caching layers, Load balancing.
• Frontend: Virtualization for long lists, Debouncing/Throttling events.

Output

• Create a brief report of findings and improvements.
• Update code with optimized solution.