Optimizing Slow GitLab Self-Hosted Runners: Causes and Solutions

GitLab runners are essential for automating CI/CD pipelines, but many developers face slow performance with their self-hosted runners. This article explores the common reasons for these slowdowns and how you can optimize your GitLab runner for faster, more efficient execution.

1. Insufficient Hardware Resources

One of the main causes for slow GitLab runners is inadequate hardware. When a CI/CD task demands high CPU, RAM, or disk space, insufficient resources can severely impact performance. To address this, you should consider upgrading your hardware or provisioning stronger resources. Increasing CPU limits and memory allocation helps runners handle more simultaneous tasks, which can lead to faster job completion times.

Example: Upgrading a runner with minimal resources:

Before:

Copied![[runners]]
 name = "Minimal Runner"
 url = "https://gitlab.example.com/"
 token = "your-token"
 executor = "shell"
 limit = 1
[[runners]]
 name = "Minimal Runner"
 url = "https://gitlab.example.com/"
 token = "your-token"
 executor = "shell"
 limit = 1

After:

Copied![[runners]]
 name = "Optimized Runner"
 url = "https://gitlab.example.com/"
 token = "your-token"
 executor = "shell"
 limit = 4
 [runners.machine]
   IdleCount = 2
   MachineDriver = "digitalocean"
   MachineName = "gitlab-runner-%s"
   MachineOptions = [
     "digitalocean-access-token=your-do-token",
     "digitalocean-size=s-2vcpu-4gb"
   ]
[[runners]]
 name = "Optimized Runner"
 url = "https://gitlab.example.com/"
 token = "your-token"
 executor = "shell"
 limit = 4
 [runners.machine]
   IdleCount = 2
   MachineDriver = "digitalocean"
   MachineName = "gitlab-runner-%s"
   MachineOptions = [
     "digitalocean-access-token=your-do-token",
     "digitalocean-size=s-2vcpu-4gb"
   ]

This adjustment helps runners handle more tasks concurrently and increases overall speed.

2. Network Bottlenecks

Slow network speeds can delay CI/CD tasks such as downloading dependencies or uploading artifacts. A stable and fast internet connection is crucial for GitLab runners to perform optimally. If your network infrastructure is struggling, consider investing in a dedicated line for your CI/CD operations or using tools like aria2 for parallel downloads, which speeds up the process by splitting the download into multiple parts​.

Example of Network Optimization:

Before:

Copied!curl -O https://example.com/largefile.zip
curl -O https://example.com/largefile.zip

After:

Copied!aria2c -x 16 https://example.com/largefile.zip
aria2c -x 16 https://example.com/largefile.zip

3. Misconfigurations

Improper runner configuration is another common issue. Incorrectly set environment variables, suboptimal cache settings, or inefficient Git strategies can negatively impact runner performance. Ensure you use the right caching strategies and variable settings for your needs.

Example of optimizing configurations:

Before:

Copied!variables:
 GIT_STRATEGY: fetch
 GIT_SUBMODULE_STRATEGY: recursive
variables:
 GIT_STRATEGY: fetch
 GIT_SUBMODULE_STRATEGY: recursive

After:

Copied!variables:
 GIT_STRATEGY: clone
 GIT_SUBMODULE_STRATEGY: none
cache:
 key: "$CI_COMMIT_REF_SLUG"
 paths:
   - node_modules/
variables:
 GIT_STRATEGY: clone
 GIT_SUBMODULE_STRATEGY: none
cache:
 key: "$CI_COMMIT_REF_SLUG"
 paths:
   - node_modules/

This configuration reduces build time by optimizing the caching and Git fetch strategies.

4. Inefficient Build Scripts

Overly complex or inefficient build scripts can also lead to slower CI/CD pipelines. Refactoring scripts to remove unnecessary steps, such as avoiding excessive sleep commands or switching to npm ci (which is faster and more reliable for CI environments), can drastically improve performance.

Example of an optimized build script:

Before:

Copied!echo "Starting build..."
sleep 10
npm install
npm run build
echo "Starting build..."
sleep 10
npm install
npm run build

After:

Copied!echo "Starting build..."
npm ci
npm run build
echo "Starting build..."
npm ci
npm run build

5. Parallelizing Tasks

A sequential execution of tasks can slow down the overall pipeline. By enabling parallelization, multiple tasks can run simultaneously, making full use of available resources and reducing the time to completion.

Example of parallelizing jobs:

Before:

Copied!stages:
  - build
  - test
  - deploy
stages:
  - build
  - test
  - deploy

After:

Copied!stages:
  - build
  - test
  - deploy
build:
  stage: build
  script:
    - ./build.sh
unit_test:
  stage: test
  script:
    - ./unit_test.sh
integration_test:
  stage: test
  script:
    - ./integration_test.sh
deploy:
  stage: deploy
  script:
    - ./deploy.sh
stages:
  - build
  - test
  - deploy
build:
  stage: build
  script:
    - ./build.sh
unit_test:
  stage: test
  script:
    - ./unit_test.sh
integration_test:
  stage: test
  script:
    - ./integration_test.sh
deploy:
  stage: deploy
  script:
    - ./deploy.sh

Running tests in parallel can significantly speed up the pipeline by maximizing the use of your runner’s available resources​.

6. Using Cloud-Hosted Runners

For teams looking to avoid the hassle of managing physical resources, cloud-hosted runners can be a viable alternative. Cloud-based runners offer on-demand scaling, ensuring that sufficient resources are available during peak times without the need to over-provision physical servers. Additionally, services like Cloud-Runner provide high-performance GitLab runners optimized for CI/CD, with the flexibility to handle workload fluctuations​.

By following these strategies, you can optimize your GitLab self-hosted runners, reduce build times, and improve the efficiency of your CI/CD pipeline.