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performance_engineering

Profile CPU, memory, and I/O bottlenecks and optimize application responsiveness.

43|11|Updated Dec 27, 2025
Search Tags:#performance#scalability#optimization#profiling#latency#load testing#k6
One-click install
npx skills add https://github.com/vuralserhat86/antigravity-agentic-skills --skill performance-engineering-vuralserhat86
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: performance_engineering
Source: https://github.com/vuralserhat86/antigravity-agentic-skills/tree/main/skills/performance_engineering
Command: npx skills add https://github.com/vuralserhat86/antigravity-agentic-skills --skill performance-engineering-vuralserhat86

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses system performance issues by providing tools and strategies for load testing, profiling, and optimization, ensuring applications are responsive, scalable, and cost-effective.

Core Features & Use Cases

  • Load Testing: Simulate user traffic to validate system capacity and identify breaking points using tools like k6 and Locust.
  • Profiling: Pinpoint performance bottlenecks (CPU, memory, I/O) in applications using tools like py-spy, pprof, and Chrome DevTools.
  • Optimization Strategies: Implement techniques such as caching, database query optimization, and frontend performance improvements (Core Web Vitals).
  • Use Case: When an e-commerce website experiences slow loading times during peak shopping seasons, this Skill can be used to conduct load tests, profile the application to find the bottleneck (e.g., slow database queries), and then apply optimizations like database indexing and caching to improve response times.

Quick Start

Use the performance_engineering skill to run a load test against 'https://api.example.com/products' using k6 with 20 virtual users for 30 seconds.

Frequently Asked Questions about performance_engineering

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find application performance bottlenecks using profiling?▼

Profiling pinpoints application performance bottlenecks by analyzing CPU, memory, and I/O usage with tools like py-spy, pprof, and Chrome DevTools to isolate slow code paths. This process identifies exactly where optimization efforts should focus.

What's the best way to load test an API for peak traffic capacity?▼

Load testing validates API capacity by simulating concurrent user traffic with tools like k6 and Locust to identify breaking points. This establishes performance baselines, detects regressions, and supports accurate capacity planning.

Why does my system slow down under heavy user load?▼

Systems slow under heavy load due to CPU, memory, or I/O bottlenecks that limit scalability. Conducting load tests and profiling application resource usage identifies these constraints so you can apply targeted optimizations like query indexing.

How do I establish performance SLOs for my application?▼

Establish performance SLOs by running load tests to determine system capacity, profiling to identify bottlenecks, and applying optimizations to meet responsiveness targets. This validates system behavior under expected traffic and detects regressions.

Can I use k6 and Locust together for load testing?▼

Yes, k6 and Locust can be used for load testing to simulate virtual user traffic and validate system capacity. Both tools help identify breaking points and establish performance baselines for capacity planning and regression detection.

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