Are you aiming to enhance the speed and efficiency of your GitLab pipeline? If optimizing time and boosting productivity are priorities for you, this article is tailored to your needs. Here, we present 16 actionable tips to fine-tune your GitLab CI/CD pipelines and expedite your development workflow.

GitLab CI

Introduction

Optimizing your CI/CD pipelines is crucial for maintaining a competitive edge in software development. This article will delve into various aspects of pipeline optimization that apply broadly, focusing on improvements that can make a tangible difference in your workflow. While specific tools such as NPM, PNPM, Yarn, Maven, or Gradle can be further optimized, this discussion will keep to broader strategies.

Assuming you’re familiar with foundational practices, let’s explore ways to enhance the efficiency of your GitLab CI pipelines.

 

CI YAML Optimizations

1. Parallelize Large Jobs

For extensive test suites or complex tasks, leveraging parallelization can drastically reduce the overall pipeline time. GitLab allows for job parallelization through the parallel keyword, enabling the division of work into multiple jobs that execute concurrently.

For example, you can split a test suite into three parallel jobs as follows:

tests-in-parallel:
  parallel: 3
  script:
    - bundle
    - bundle exec rspec_booster --job $CI_NODE_INDEX/$CI_NODE_TOTAL

This configuration allows tests to run simultaneously across three jobs, significantly cutting down the time needed to complete the test suite.

2. Opt for Small Linux Distributions

Selecting smaller Linux distributions for your Docker images can enhance pipeline performance. For instance, Alpine Linux is a lightweight alternative that results in smaller image sizes compared to more extensive distributions like Ubuntu or Debian.

image: alpine:latest

Utilizing a compact base image such as Alpine not only reduces the time required for image pulls but also accelerates the job execution time.

3. Optimize Caching Strategies

A robust caching strategy is essential for achieving speed in your pipelines. Consider configuring a shared runner cache when aiming for efficiency, and partition your cache when appropriate. Utilize cache:key or cache🔑files to share caches across multiple pipelines and establish suitable pull/push policies.

cache:
  key: ${CI_COMMIT_REF_SLUG}
  paths:
    - .npm

This setup reuses the cache based on the commit reference slug, optimizing the caching process for different pipeline runs on the same branch.

4. Conditional Cache Uploads

To maximize caching efficiency, share the cache between multiple pipelines when feasible and avoid unnecessary cache rebuilds. Before proceeding with pipeline steps, verify the cache’s presence and validity.

before_script:
  - if [ -f cache.tar.gz ]; then tar -xzf cache.tar.gz; fi
after_script:
  - tar -czf cache.tar.gz .npm

In this example, the script checks if a cache file exists before extracting it and updates the cache only when it’s necessary.

5. Limit Artifact Downloads

By default, GitLab retrieves all artifacts from preceding jobs at the start of a job. To minimize overhead, specify artifacts using the dependencies keyword to download only what is essential.

test:
  stage: test
  script:
    - npm test
  artifacts:
    paths:
      - test-results/

This ensures only the necessary test results are saved as artifacts, cutting down on the volume of data transferred between jobs.

6. Implement Targeted Rules

Reduce unnecessary job executions by establishing specific rules for when a pipeline should be triggered. Utilize the workflow:rules and rules keywords to minimize the load on your runners.

workflow:
  rules:
    - if: $CI_COMMIT_BRANCH == "main"

This rule restricts the pipeline’s execution to commits on the main branch, thus avoiding unnecessary runs for other branches.

7. Strategically Define Stages

Merging stages where feasible and utilizing the needs keyword can help bypass traditional job ordering constraints for better execution efficiency.

build:
  stage: build
  script:
    - npm run build
test:
  stage: test
  needs: ["build"]
  script:
    - npm test

In this configuration, the test job will commence as soon as the build job is complete, regardless of the status of other jobs within the same stage.

8. Enable Interruptible Pipelines

By setting the interruptible keyword to true, jobs can automatically halt for outdated pipelines, thereby conserving resources on your runners.

stages:
  - test
test:
  script:
    - sleep 30
  interruptible: true

This configuration allows the test job to be interrupted if a new pipeline is initiated, freeing up resources for new jobs.

9. Automatic Job Retries

To handle transient issues without manual intervention, set up automatic job retries using the retry keyword.

test:
  script:
    - npm test
  retry:
    max: 2
    when:
      - runner_system_failure
      - stuck_or_timeout_failure

This setup allows the test job to retry up to two times if it encounters specific failures like runner system issues or timeouts.

 

Project Configuration Optimizations

10. Unified Cache for Protected Branches

By default, GitLab maintains separate caches for protected and non-protected branches. Disabling this feature enables all branches to share the same cache, enhancing caching efficiency.

11. Utilize Fast-Forward Merges

Employ fast-forward merges to bring changes from one branch into another without necessitating Docker image rebuilds, thus improving pipeline performance.

12. Establish Push Rules

Implement push rules to control pipeline creation, ensuring that they are triggered only when necessary. This reduces unnecessary load on your runners.

 

Runner Configuration Optimizations

13. Cache Docker Builds

Utilizing Docker layer caching can significantly enhance build times. By pulling a similar image prior to starting the build, you can speed up the process. Consider alternatives like Kaniko, Buildah, or Img for faster builds.

services:
  - docker:19.03.12
variables:
  DOCKER_TLS_CERTDIR: "/certs"
build:
  stage: build
  script:
    - docker build --cache-from my-image:latest -t my-image:latest .

This example shows how to use Docker’s layer caching to improve the build process.

14. Optimize Image Pull Policy

Set the “if-not-present” Docker image pull policy at the runner level to download images only when they are not already available, saving both time and bandwidth.

variables:
  DOCKER_IMAGE: "my-image:latest"
job:
  script:
    - docker pull $DOCKER_IMAGE || true
    - docker run $DOCKER_IMAGE

This configuration ensures that the Docker image is pulled only when necessary, avoiding redundant downloads.

15. Enhance Compression for Caches and Artifacts

To improve performance, utilize FastZip for compression and fine-tune its settings. Adjust variables like FF_USE_FASTZIP, ARTIFACT_COMPRESSION_LEVEL, and CACHE_COMPRESSION_LEVEL for optimal performance.

variables:
  FF_USE_FASTZIP: "true"
  ARTIFACT_COMPRESSION_LEVEL: "fastest"
  CACHE_COMPRESSION_LEVEL: "fastest"

These settings configure the compression for artifacts and caches, ensuring they are processed quickly.

16. Properly Size Runners and Maximize Parallel Jobs

Ensure your runners are appropriately sized and that the maximum number of concurrent jobs is optimally set. This enhances the performance and efficiency of your GitLab CI/CD pipelines.

runners:
  limit: 10

Setting a limit on concurrent jobs helps to distribute the load effectively across your runners, ensuring optimal performance.

 

Conclusion

By implementing these strategies for faster GitLab CI/CD pipelines, you can significantly enhance your productivity. Reducing pipeline execution time not only improves efficiency but also accelerates the overall software development process.

While these optimizations can greatly enhance speed, it’s crucial to maintain a balance between performance and the readability and maintainability of your pipelines. Keeping complexity at bay ensures that your CI/CD processes remain manageable and transparent.

References