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.