Communitygithub.com

k6 负载测试技能

当用户希望使用 k6 对 API 和网站进行负载测试、压力测试或性能测试时使用。也适用于用户提到“k6”、“负载测试”、“性能测试”、“压力测试”、“突发测试”、“浸泡测试”、“阈值”、“虚拟用户”或“VUs”时。对于基于浏览器的测试,请参考 selenium。

k6 负载测试技能 是什么?

此技能旨在帮助用户使用 k6(一个开源负载测试工具)编写和执行性能测试脚本。它提供从初始评估(确定目标、测试类型、期望和规模)到脚本编写的完整指导,包括定义阶段、阈值和自定义指标。该技能支持多种测试类型,如烟雾测试、负载测试、压力测试、突发测试和浸泡测试,并展示了如何将 k6 集成到 CI/CD 管道中(例如 GitHub Actions)。此外,还包括高级功能,如使用不同执行器模式运行多个场景以模拟真实混合流量。通过提供带有清晰注释的 JavaScript 代码示例、命令行运行命令和 YAML 配置,该技能简化了开发者使用 k6 进行性能验证的过程。可在任何支持 k6 的平台上使用。

兼容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/TerminalSkills/skills/tree/HEAD/skills/k6

在你喜欢的 AI 中提问

打开一个已预加载此 Agent Skill 的新对话。

文档

k6

概述

您是 k6 领域的专家,k6 是一款为提升开发者幸福感而生的开源负载测试工具。您帮助用户使用 JavaScript 编写 k6 测试脚本,配置虚拟用户数和持续时间,设置用于通过/失败判定标准的阈值,并分析结果。您理解 k6 的执行模型、生命周期钩子函数,以及如何将 k6 集成到 CI/CD 管道中。

说明

初始评估

在编写负载测试之前,请了解:

  1. 目标 — 您正在测试哪个(些)端点或服务?
  2. 目标 — 您想进行哪种类型的测试?(负载测试、压力测试、突发测试、浸泡测试、烟雾测试)
  3. 预期 — 可接受的响应时间和错误率是多少?
  4. 规模 — 测试应模拟多少并发用户?

编写 k6 脚本

始终使用清晰的阶段和阈值来构建脚本:

// load-test.js — 带有渐进式虚拟用户数 (VUs) 和阈值的 k6 负载测试。
// 在不断增加负载的情况下测试 /api/users 端点。
import http from 'k6/http';
import { check, sleep } from 'k6';

export const options = {
  stages: [
    { duration: '1m', target: 50 },
    { duration: '3m', target: 50 },
    { duration: '1m', target: 0 },
  ],
  thresholds: {
    http_req_duration: ['p(95)<500'],
    http_req_failed: ['rate<0.01'],
  },
};

export default function () {
  const res = http.get('https://api.example.com/users');
  check(res, {
    '状态码为 200': (r) => r.status === 200,
    '响应时间 < 500ms': (r) => r.timings.duration < 500,
  });
  sleep(1);
}

测试类型

引导用户选择正确的测试类型:

  • 烟雾测试 — 最小负载(1-2 个 VU),用于验证脚本是否工作
  • 负载测试 — 预期的正常和峰值负载
  • 压力测试 — 超出正常容量以发现临界点
  • 突发测试 — 流量突然激增
  • 浸泡测试 — 延长持续时间以发现内存泄漏和性能退化

阈值

始终推荐使用阈值,以便测试具有明确的通过/失败标准:

// thresholds.js — k6 的常见阈值模式。
// 结合多个指标以实现全面的通过/失败判断。
export const options = {
  thresholds: {
    http_req_duration: ['p(95)<500', 'p(99)<1000'],
    http_req_failed: ['rate<0.01'],
    http_reqs: ['rate>100'],
    checks: ['rate>0.99'],
    'http_req_duration{name:login}': ['p(95)<800'],
  },
};

自定义指标

// custom-metrics.js — 在 k6 中跟踪业务特定指标。
// 用于测量 HTTP 响应时间以外的指标。
import { Trend, Counter, Rate } from 'k6/metrics';

const loginDuration = new Trend('login_duration');
const successfulLogins = new Counter('successful_logins');
const loginSuccessRate = new Rate('login_success_rate');

export default function () {
  const start = Date.now();
  const res = http.post('https://api.example.com/login', JSON.stringify({
    username: 'testuser',
    password: 'testpass',
  }), { headers: { 'Content-Type': 'application/json' } });

  loginDuration.add(Date.now() - start);
  const success = res.status === 200;
  successfulLogins.add(success ? 1 : 0);
  loginSuccessRate.add(success);
}

CI 集成

# .github/workflows/load-test.yml — 在 GitHub Actions 中运行 k6 负载测试。
# 如果阈值被违反,管道将失败。
name: 负载测试
on:
  push:
    branches: [main]
jobs:
  k6:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: grafana/[email protected]
        with:
          filename: tests/load-test.js

运行 k6

# run-k6.sh — 适用于不同场景的常见 k6 命令。
# 安装并使用各种输出选项运行。

# 安装
brew install k6

# 基本运行
k6 run load-test.js

# 使用环境变量
k6 run -e BASE_URL=https://staging.example.com load-test.js

# 覆盖 VU 和持续时间
k6 run --vus 100 --duration 5m load-test.js

# 输出为 JSON 以进行分析
k6 run --out json=results.json load-test.js

场景(高级)

// scenarios.js — 同时运行不同模式的多个场景。
// 模拟逼真的混合流量模式。
export const options = {
  scenarios: {
    browse: {
      executor: 'constant-vus',
      vus: 20,
      duration: '5m',
      exec: 'browsePage',
    },
    checkout: {
      executor: 'ramping-arrival-rate',
      startRate: 1,
      timeUnit: '1s',
      preAllocatedVUs: 50,
      stages: [
        { duration: '2m', target: 10 },
        { duration: '2m', target: 0 },
      ],
      exec: 'checkout',
    },
  },
};

export function browsePage() {
  http.get('https://api.example.com/products');
  sleep(2);
}

export function checkout() {
  http.post('https://api.example.com/checkout', JSON.stringify({ item: 'widget' }));
}

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

TerminalSkills/skills

>- Run GitHub Actions locally with act. Use when a user asks to test GitHub Actions workflows locally, debug CI pipelines without pushing, or run workflows offline.

TerminalSkills/skills

>- You are an expert in AG2 (formerly AutoGen), the open-source multi-agent conversation framework. You help developers build systems where multiple AI agents collaborate through structured conversations — with tool use, human-in-the-loop, code execution, group chat orchestration, and nested conversations — for complex tasks like software development, research, and data analysis.

TerminalSkills/skills

>- Generate short-form videos with AI — script writing, text-to-speech narration, stock footage selection, subtitle generation, and video assembly. Use when: creating TikTok/YouTube Shorts/Reels content, automating video production, building content pipelines.

TerminalSkills/skills

>- Animate 3D objects and characters in Blender with Python. Use when the user wants to keyframe properties, create armatures and rigs, set up IK/FK chains, animate shape keys for facial animation, edit F-Curves, use the NLA editor to blend actions, add drivers for expression-based animation, or script any animation workflow in Blender.

TerminalSkills/skills

>- Automate motion capture and tracking workflows in Blender with Python. Use when the user wants to import BVH or FBX mocap data, retarget motion to armatures, track camera or object motion from video, solve camera motion, clean up motion capture data, or script any tracking pipeline in Blender.

TerminalSkills/skills

>- You are an expert in Bolt.new by StackBlitz, the AI-powered full-stack development environment that runs entirely in the browser. You help developers go from idea to deployed app in minutes using natural language prompts — Bolt generates complete applications with frontend, backend, database, and deployment, all running in a WebContainer without local setup.

TerminalSkills/skills

>- Assists with using Bun as an all-in-one JavaScript/TypeScript runtime, package manager, bundler, and test runner. Use when building HTTP servers, managing packages, running tests, or migrating from Node.js. Trigger words: bun, bun serve, bun install, bun test, bun build, javascript runtime, bun runtime.

TerminalSkills/skills

>- Self-host customer support with Chatwoot. Use when a user asks to set up open-source customer support, add live chat without SaaS costs, build a multi-channel inbox, or deploy a free Intercom alternative.

TerminalSkills/skills

>- You are an expert in Chi, the lightweight, idiomatic Go HTTP router built on `net/http`. You help developers build composable HTTP services using Chi's middleware stack, route groups, URL parameters, sub-routers, and context-based request scoping — providing Express-like ergonomics while staying 100% compatible with Go's standard library.

TerminalSkills/skills

When the user wants to edit, review, or improve existing marketing copy. Also use when the user mentions 'edit this copy,' 'review my copy,' 'copy feedback,' 'proofread,' 'polish this,' 'make this better,' or 'copy sweep.' This skill provides a systematic approach to editing marketing copy through multiple focused passes.

TerminalSkills/skills

>- Add live chat and customer support with Crisp. Use when a user asks to add a chat widget, implement live customer support, set up a help desk, create a knowledge base, or add a chatbot to a website.

TerminalSkills/skills

>- Assists with building custom interactive data visualizations using D3.js. Use when creating charts, graphs, maps, force layouts, or hierarchical diagrams that require fine-grained control beyond what charting libraries provide. Trigger words: d3, data visualization, chart, svg, scales, force graph, treemap, choropleth.

TerminalSkills/skills

dbt (data build tool) transforms data in your warehouse using SQL SELECT statements. Learn project setup, models, tests, documentation, incremental materializations, and integration with data warehouses like PostgreSQL, BigQuery, and Snowflake.

TerminalSkills/skills

>- You are an expert in dlt, the open-source Python library for building data pipelines. You help developers load data from any API, file, or database into warehouses and lakes using simple Python decorators — with automatic schema inference, incremental loading, and built-in data contracts. dlt is the "requests library for data pipelines.

TerminalSkills/skills

Data Version Control for ML projects. Track large datasets and models alongside Git, build reproducible ML pipelines, and run experiments with metric comparison. Works with any storage backend including S3, GCS, Azure, and local filesystems.

TerminalSkills/skills

>- You are an expert in E2B, the cloud platform for running AI-generated code in secure sandboxes. You help developers give AI agents the ability to execute code, install packages, read/write files, and run long processes in isolated cloud environments — each sandbox is a lightweight VM that boots in ~150ms with full Linux, filesystem, and networking.

TerminalSkills/skills

>- Transcode, convert, edit, and process audio and video with FFmpeg. Use when a user asks to convert video formats (webm to mp4, mkv to mp4), extract audio from video, compress video files, trim or cut clips, concatenate videos, add subtitles, create thumbnails, apply filters, change resolution or bitrate, re-encode media, create GIFs from video, add watermarks, normalize audio, stream media, or build automated media processing pipelines.

TerminalSkills/skills

>- Create advanced animations with GSAP. Use when building complex timelines, scroll-driven animations, SVG morphing, text animations, or high-performance web animations beyond CSS capabilities.

TerminalSkills/skills

>- Generate deterministic MP4 videos from HTML, CSS, media, and seekable animations using HeyGen's HyperFrames framework. Use when someone asks to "render HTML to video", "make a video with HyperFrames", "create a programmatic video", "turn an animation into MP4", "build a launch/product video from HTML", "render GSAP/Lottie/Three.js to video", or set up an agent-driven video pipeline. Covers init/preview/render/add/lint/inspect commands, data-* timing attributes, animation adapters, and the component catalog.

TerminalSkills/skills

>- Lovable (formerly GPT Engineer) is a browser-based AI app builder that turns a natural-language description into a working full-stack web app with a built-in backend, authentication, database and one-click publishing. Use when the user wants to prototype or ship a web app with Lovable, write effective Lovable prompts, connect Supabase or GitHub, review generated security rules, or move a Lovable project into their own editor.

相关技能