Web Performance Optimization & Lighthouse · 课时

将 Lighthouse 集成到持续集成和持续部署中

在持续集成和持续部署流水线中自动执行 Lighthouse 检查，及早发现性能退化。

第 3 / 4 课11 个步骤

将 Lighthouse 集成到持续集成和持续部署中 是 CoddyKit 上的免费 Web Performance Optimization & Lighthouse 课时。这是第 3 节课，共 4 节。你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。这是 Web Performance Optimization & Lighthouse 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Web Performance Optimization & Lighthouse 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

What is CI/CD?

CI/CD stands for Continuous Integration and Continuous Delivery/Deployment. It's a modern approach to software development that focuses on automating various stages of the software lifecycle.

Continuous Integration (CI): Developers frequently merge code into a central repository. Automated builds and tests run to detect issues early.
Continuous Delivery (CD): After CI, code is automatically prepared for release, ensuring it's always in a deployable state.
Continuous Deployment (CD): Takes CD a step further by automatically deploying every change to production, provided all tests pass.

CI/CD helps teams deliver updates faster and more reliably.

Why CI/CD for Performance?

Integrating performance checks into your CI/CD pipeline is crucial for maintaining a fast website. Here's why:

Catch Regressions Early: Automatically detect performance drops with every code change, before they reach users.
Consistent Feedback: Get objective performance scores on every build, ensuring teams stay aware of their impact.
Enforce Standards: Use performance budgets to fail builds if metrics fall below acceptable thresholds.
Save Time: Automate manual auditing, freeing up developer time.

Meet Lighthouse CI (LHCI)

While you can run Lighthouse manually, Lighthouse CI (LHCI) is a dedicated tool designed to make automated performance auditing in CI/CD pipelines easy and effective.

LHCI provides a set of tools to:

Collect Lighthouse reports across different branches and commits.
Assert performance budgets against these reports.
Display historical performance data.
Integrate with various CI providers like GitHub Actions, GitLab CI, and Jenkins.

LHCI: Collect & Assert

LHCI works through a command-line interface (CLI). You'll typically use two main commands:

lhci collect: Runs Lighthouse audits on specified URLs and collects the results.
lhci assert: Checks the collected results against predefined performance budgets and rules.

First, you usually install it globally or as a dev dependency:

npm install -g @lhci/cli

Configuring LHCI

LHCI uses a configuration file, often named lighthouserc.js or lighthouserc.json, to define how it should run. This file lives at the root of your project.

Here's a basic structure for lighthouserc.js, specifying where to run audits:

module.exports = {
  ci: {
    collect: {
      url: ['http://localhost:3000'],
      startServerCommand: 'npm run start',
      numberOfRuns: 3,
    },
    upload: {
      target: 'temporary-public-storage',
    },
  },
};

Enforcing Performance Budgets

A key feature of LHCI is enforcing performance budgets. These are thresholds for metrics (like score, total byte weight, or largest contentful paint) that your site must meet.

You define budgets in the assert section of your lighthouserc.js. If any budget is violated, LHCI can fail your CI build.

module.exports = {
  ci: {
    collect: { /* ... */ },
    assert: {
      assertions: {
        'performance-score': ['error', { minScore: 0.90 }],
        'first-contentful-paint': ['error', { maxNumericValue: 1500 }],
        'total-byte-weight': ['warn', { maxNumericValue: 1000000 }], // 1MB
      },
    },
    upload: { /* ... */ },
  },
};

LHCI with GitHub Actions

GitHub Actions is a popular CI/CD platform integrated directly into GitHub repositories. You can easily add LHCI to your GitHub Actions workflow.

You'll create a YAML file (e.g., .github/workflows/lighthouse.yml) that defines the steps to run LHCI when certain events occur, like a pull request or a push to the main branch.

This allows automated checks before merging code.

GitHub Actions Workflow Example

Here's a simplified GitHub Actions workflow that sets up Node.js, installs LHCI, starts a server (if needed), collects audits, and asserts against budgets.

This workflow runs on every pull request to the main branch.

name: Lighthouse CI
on: [pull_request]
jobs:
  lighthouse:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: actions/setup-node@v3
        with:
          node-version: 18
      - name: Install dependencies
        run: npm ci
      - name: Run Lighthouse CI
        run: npm install -g @lhci/cli && lhci collect && lhci assert

Reviewing CI/CD Results

After LHCI runs in your CI/CD pipeline, it provides output directly in the build log. If budgets are set, the build will pass or fail accordingly.

Passed: All performance budgets and assertions were met.
Failed: One or more budgets were exceeded, indicating a performance regression.

For more detailed historical data and trend analysis, you can configure LHCI to upload reports to an LHCI server (either self-hosted or a cloud service).

Quick Check

You've learned how Lighthouse CI helps automate performance checks. Which of the following are key benefits of integrating Lighthouse CI into your CI/CD pipeline?

在交互式课程中回答

Recap & Next Steps

Great job! In this lesson, we explored how to integrate Lighthouse into your CI/CD pipeline.

We understood the importance of automating performance checks to prevent regressions.
We learned about Lighthouse CI (LHCI) and its role in collecting audits and asserting budgets.
We saw examples of configuring LHCI and integrating it with GitHub Actions.

By automating performance, you ensure your web projects remain fast and user-friendly over time. Keep exploring how to fine-tune your CI/CD setup for optimal results!

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常见问题解答

「将 Lighthouse 集成到持续集成和持续部署中」课时是免费的吗？

是的 — 「将 Lighthouse 集成到持续集成和持续部署中」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Web Performance Optimization & Lighthouse 课程的其余内容，请升级到 CoddyKit PRO。 Web Performance Optimization & Lighthouse 课程共包含 4 节课。

「将 Lighthouse 集成到持续集成和持续部署中」这节课中我会学到什么？

在持续集成和持续部署流水线中自动执行 Lighthouse 检查，及早发现性能退化。你通过在浏览器中直接运行的动手代码来练习 Web Performance Optimization & Lighthouse，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Web Performance Optimization & Lighthouse 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Web Performance Optimization & Lighthouse 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。这是第 3 节课，共 4 节。

「将 Lighthouse 集成到持续集成和持续部署中」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 Web Performance Optimization & Lighthouse 课中编写并运行代码吗？

能。每节 Web Performance Optimization & Lighthouse 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

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