Performance Optimisation Skill

Tooling Notes

This skill should only use read-only commands and avoid modifying files.

Workflow

Copy this checklist and use it to track your progress through the performance optimisation process:

Performance Optimisation Checklist

• Measure Baseline Performance
  • Use profiling tools to gather performance metrics.
  • Identify slow functions, database queries, and network requests.
• Identify Bottlenecks
  • Analyse profiling data to pinpoint performance issues.
  • Prioritise issues based on impact and ease of resolution.
• Implement Optimisations
  • Optimise algorithms and data structures.
  • Improve database query efficiency.
  • Reduce network latency and payload sizes.
  • Implement caching strategies where appropriate.
• Validate Improvements
  • Re-measure performance after optimisations.
  • Ensure that optimisations have led to measurable improvements.
• Document Changes
  • Update documentation to reflect performance changes.
  • Provide explanations for significant optimisations.

Profiling Commands

Node.js profiling

node --prof app.js node --prof-process isolate-0x*.log > processed.txt

Python profiling

python -m cProfile -o profile.out app.py snakeviz profile.out

Database query analysis (PostgreSQL example)

EXPLAIN ANALYZE SELECT * FROM your_table WHERE condition;

Web performance analysis

lighthouse https://yourwebsite.com --output html --output-path report.html

Common Bottlenecks and Ways to Fix Them

• Inefficient Algorithms: Replace with more efficient algorithms or data structures.

• Database Query Performance: Optimize queries, add indexes, or denormalize data.

• Network Latency: Minimize requests, use CDNs, and compress payloads.

• Unnecessary Computations: Cache results of expensive operations.

• Memory Leaks: Identify and fix memory leaks to improve performance over time.