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Why Your CI/CD Pipeline is Slow (And How to Speed It Up)
2 min read

Why Your CI/CD Pipeline is Slow (And How to Speed It Up)

Time is money. Discover how to optimize GitHub Actions and Docker builds to reduce deployment times from 15 minutes to under 5.

CI/CD pipeline optimizationspeed up CI/CDGitHub Actions performanceDocker build optimizationreduce deployment time

Why Your CI/CD Pipeline is Slow (And How to Speed It Up)

A slow CI/CD pipeline is a silent productivity killer. When developers have to wait 20 minutes for a build to finish, they lose focus, which ultimately drops your release velocity. High-performing teams aim for a "commit-to-deploy" time of under 10 minutes. If your pipeline is lagging behind, it’s time to take action and optimize.

The Culprit: npm install

In Node.js projects, the installation of dependencies from scratch on every run often becomes the biggest bottleneck. To combat this, take advantage of the GitHub Actions Cache to store your node_modules. By checking the hash of your package-lock.json, you can ensure that dependencies are only reinstalled when they actually change, significantly speeding up your pipeline.

- name: Cache node modules
  uses: actions/cache@v3
  with:
    path: ~/.npm
    key: ${{ runner.os }}-node-${{ hashFiles('**/package-lock.json') }}

The Culprit: Docker Layer Bloat

If your Docker builds are sluggish, it’s likely because you aren’t utilizing Layer Caching effectively. To optimize this, make sure that your COPY package.json and RUN npm install commands are executed before copying the rest of your source code. This approach ensures that Docker only reruns the install step when your dependencies change, rather than every time you modify a single line of JavaScript code.

Utilizing Parallel Execution

Another common slowdown in CI/CD pipelines is the sequential execution of unit tests, integration tests, and linting. To enhance your workflow, leverage Matrix Builds in GitHub Actions to run these tasks in parallel. By testing across multiple Node versions or browser targets simultaneously, you can reduce your total pipeline time by 50% or more.

Key Takeaways:
  • Cache dependencies to avoid redundant downloads.
  • Order Dockerfile commands to maximize layer reuse.
  • Parallelize independent tasks in your workflow YAML.

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