How Do Gitlab Runners Work: A Step-By-Step Guide

by Devop · Published 18/08/2024 · Updated 14/11/2024

GitLab Runners are essential tools for automating tasks in a CI/CD pipeline. They help in building, testing, and deploying code efficiently. This guide will walk you through the steps to set up, configure, and optimize GitLab Runners for your projects.

Table of Contents

Key Takeaways

GitLab Runners automate build, test, and deployment processes, saving time and reducing errors.
There are three types of runners: shared, group, and project runners.
Installing GitLab Runner varies by operating system, but it’s supported on Linux, macOS, and Windows.
Registering a runner involves setting up communication between GitLab and the runner machine.
You can configure runners with different executors like shell, Docker, and Kubernetes.
Proper configuration of the config.toml file is crucial for optimal runner performance.
Using Docker with GitLab Runner allows for isolated and reproducible job environments.
Regular maintenance and updates are necessary to keep GitLab Runners running smoothly.

Understanding GitLab Runners

What is a GitLab Runner?

A GitLab Runner is a lightweight, highly-scalable application that works with GitLab CI/CD to run jobs in a pipeline. Think of it as the worker bee that executes the tasks defined in your GitLab CI/CD configuration. It’s essential for automating your DevSecOps workflows.

Types of GitLab Runners

There are three main types of GitLab Runners:

Shared Runners: Available to all projects in a GitLab instance.
Group Runners: Limited to all projects and subgroups within a specific group.
Project Runners: Dedicated to individual projects.

Each type has its own use case, depending on your needs and the level of isolation required.

Key Features of GitLab Runners

GitLab Runners come packed with features that make them versatile and powerful:

Concurrent Job Execution: Run multiple jobs at the same time.
Multiple Executors: Choose from Shell, Docker, Kubernetes, and more.
Cross-Platform: Works on Linux, macOS, and Windows.
Customizable: Tailor the job running environment to your needs.
Autoscaling: Automatically scale resources based on demand.

How GitLab Runners Integrate with CI/CD

GitLab Runners are the backbone of your CI/CD pipelines. They pick up jobs defined in your .gitlab-ci.yml file and execute them. This tight integration ensures that your code is tested, built, and deployed efficiently. Whether you’re using GitLab Premium or the free tier, runners make CI/CD seamless.

Common Use Cases for GitLab Runners

GitLab Runners are incredibly versatile. Here are some common use cases:

Automated Testing: Run unit, integration, and end-to-end tests.
Continuous Deployment: Deploy applications to various environments.
Code Quality Checks: Perform linting, static analysis, and security scans.
DevSecOps Pipelines: Integrate security checks into your CI/CD workflows.

Benefits of Using GitLab Runners

Using GitLab Runners offers several advantages:

Scalability: Easily scale your builds and tests as your project grows.
Flexibility: Choose the right executor and environment for each job.
Efficiency: Speed up development cycles with parallel job execution.
Security: Implement secure DevSecOps practices with isolated runners.

With GitLab Runners, you can automate your CI/CD processes, ensuring faster and more reliable software delivery.

Setting Up GitLab Runner

Setting up a GitLab Runner is a crucial step to automate your CI/CD pipelines. Let’s walk through the process step-by-step to get you up and running smoothly.

Registering a GitLab Runner

Once you’ve installed GitLab Runner, the next step is to register it with your GitLab instance. This process sets up communication between the runner and GitLab, allowing them to work together to execute jobs.

Configuring GitLab Runner

Understanding config.toml File

The config.toml file is the heart of your GitLab Runner configuration. This file, usually found in the installation directory, holds all the settings that define how your runner behaves. Editing this file allows you to customize your runner extensively. For example, you can set the concurrent job limit, define custom environment variables, and configure cache settings.

Setting Concurrent Job Limits

To control how many jobs your runner can handle at once, you can set the concurrent option in the config.toml file. This is particularly useful if you want to manage resource usage effectively. Simply add a line like concurrent = 4 to limit the runner to four concurrent jobs.

Defining Custom Environment Variables

Custom environment variables can be defined in the config.toml file to make them available to your jobs. This is handy for setting up specific configurations or secrets that your jobs might need. For instance:

[[runners]]
  environment = ["MY_VARIABLE=value"]

Configuring Cache Settings

Caching can significantly speed up your jobs by reusing previous build artifacts. In the config.toml file, you can specify cache settings to optimize performance. For example, you can define a cache directory and set expiration times for cached items.

Setting Up Docker Executor

If you’re using Docker as your executor, you’ll need to configure it in the config.toml file. This involves specifying the Docker image to use, setting up volumes, and defining any additional Docker options. This setup is crucial for running jobs in isolated environments.

Advanced Configuration Options

For those who need more control, the config.toml file offers advanced configuration options. You can set up custom executors, configure SSH for remote jobs, and even integrate with third-party tools. These advanced settings allow you to tailor the runner to meet specific project requirements.

Remember, any changes to the config.toml file require a restart of the GitLab Runner to take effect. Always test your configuration changes in a safe environment before applying them to production.

Creating a CI/CD Pipeline

Understanding .gitlab-ci.yml

The .gitlab-ci.yml file is the heart of your GitLab CI/CD pipeline. This file defines the stages, jobs, and scripts that will be executed. Think of it as the blueprint for your entire CI/CD process. Each job in the file belongs to a stage, and stages run sequentially. If you have multiple jobs in a stage, they can run in parallel, provided there are enough runners.

Defining Jobs and Stages

Jobs are the individual tasks that GitLab Runner will execute. Stages are groups of jobs that run in a specific order. For example, you might have stages like build, test, and deploy. Each job within these stages will have its own script to run. Here’s a simple example:

stages:
  - build
  - test
  - deploy

build_job:
  stage: build
  script:
    - echo "Building the project..."

test_job:
  stage: test
  script:
    - echo "Running tests..."

deploy_job:
  stage: deploy
  script:
    - echo "Deploying the project..."

Using Variables in Pipelines

Variables in GitLab CI/CD are a great way to make your pipelines more flexible and secure. You can define variables in the .gitlab-ci.yml file, in the GitLab UI, or even in the runner’s configuration. These variables can store sensitive information like API keys or configuration settings. For example:

variables:
  API_KEY: "your_api_key_here"

build_job:
  stage: build
  script:
    - echo "Using API key: $API_KEY"

Setting Up Pipeline Triggers

Pipeline triggers allow you to start a pipeline based on certain conditions, like a push to a specific branch or a merge request. You can define these triggers in the .gitlab-ci.yml file using the only and except keywords. For example:

build_job:
  stage: build
  script:
    - echo "Building the project..."
  only:
    - master

Managing Pipeline Dependencies

Sometimes, jobs depend on the output of previous jobs. You can manage these dependencies using the needs keyword. This allows jobs to run out of order if their dependencies are met, speeding up the pipeline. For example:

test_job:
  stage: test
  script:
    - echo "Running tests..."
  needs:
    - build_job

Best Practices for Pipeline Configuration

To get the most out of your GitLab CI/CD pipeline, follow these best practices:

Keep it simple: Start with a basic pipeline and gradually add complexity.
Use caching: Cache dependencies and build outputs to speed up your pipeline.
Secure your variables: Store sensitive information in GitLab’s CI/CD settings, not in your .gitlab-ci.yml file.
Monitor performance: Keep an eye on your pipeline’s performance and make adjustments as needed.

Building a GitLab CI/CD pipeline can seem daunting at first, but with a bit of practice, you’ll be able to create efficient and reliable pipelines that streamline your development process.

Running Jobs with GitLab Runner

Once you’ve set up your [GitLab Runner](https://www.baeldung.com/ops/gitlab-runner-guide), it’s time to get those jobs running! This section will walk you through the process of how jobs are assigned, executed, and monitored using GitLab Runner.

Using Docker with GitLab Runner

Setting Up Docker Executor

Setting up the Docker executor is a breeze. First, ensure Docker is installed on your machine. Then, configure your GitLab Runner to use Docker by specifying it as the executor during registration. This setup allows your jobs to run inside Docker containers, providing a consistent and isolated environment.

Choosing Docker Images

Selecting the right Docker image is crucial. The image keyword in your job definition specifies which Docker image to use. For example, to use Node.js, you might write:

test-job:
  image: node:14
  script:
    - npm install
    - npm run test

This configuration ensures your job runs inside a container based on the node:14 image.

Running Jobs in Docker Containers

Running jobs in Docker containers is straightforward. Define your job in the .gitlab-ci.yml file and specify the Docker image. GitLab Runner will handle the rest, pulling the image and starting a new container for each job execution.

Managing Docker Volumes

Docker volumes are essential for persisting data between jobs. You can define volumes in your job configuration to share data between the host and the Docker container. This is particularly useful for caching dependencies or sharing build artifacts.

Using Docker Compose

Docker Compose allows you to define and run multi-container Docker applications. You can use it in your GitLab CI/CD pipeline to spin up complex environments. Simply include a docker-compose.yml file in your repository and add the necessary commands to your job script.

Best Practices for Docker Integration

To get the most out of Docker with GitLab Runner, follow these best practices:

Use lightweight images: Choose minimal images to reduce build times.
Cache dependencies: Leverage Docker volumes to cache dependencies and speed up subsequent builds.
Keep images updated: Regularly update your Docker images to include the latest security patches.
Monitor resource usage: Keep an eye on resource consumption to avoid bottlenecks.

Pro Tip: Proper configuration and monitoring are essential for optimal performance, especially for larger teams.

Scaling GitLab Runners

Scaling GitLab Runners is crucial for maintaining performance and efficiency as your CI/CD workloads grow. Let’s dive into the key aspects of scaling GitLab Runners effectively.

Security Considerations

Securing Runner Registration

When setting up your GitLab Runners, it’s crucial to secure the registration process. Use registration tokens wisely and avoid sharing them publicly. Rotate these tokens regularly to minimize risks.

Managing Access Control

Control who can access your runners by setting up proper permissions. Limit access to only those who need it. This helps in preventing unauthorized access and potential security breaches.

Using Secure Environment Variables

Store sensitive data like API keys and passwords in secure environment variables. This keeps them out of your codebase and reduces the risk of exposure.

Handling Sensitive Data

Always encrypt sensitive data both in transit and at rest. Use strong encryption methods to protect your data from unauthorized access.

Auditing Runner Activity

Regularly audit the activity of your runners. Keep an eye on logs and monitor for any unusual behavior. This helps in identifying and responding to potential security incidents quickly.

Best Practices for Security

Enforce two-factor authentication (2FA) for all users.
Regularly update your GitLab Runner to the latest version to patch any vulnerabilities.
Use network segmentation to isolate your runners from other critical systems.
Implement rate limiting to prevent abuse.

Security is not a one-time setup but an ongoing process. Stay vigilant and proactive in protecting your CI/CD pipeline.

Maintaining GitLab Runners

Maintaining your GitLab Runners is crucial to ensure smooth and efficient CI/CD operations. Here’s a step-by-step guide to help you keep your runners in top shape.

Regular Maintenance Tasks

Regular maintenance is key to keeping your GitLab Runners running smoothly. Performing routine checks can help you catch issues before they become major problems. Here are some tasks you should regularly perform:

Clean up disk space: Over time, runners can accumulate a lot of data. Regularly clean up unused Docker images and other temporary files.
Monitor performance: Keep an eye on your runner’s performance metrics to ensure they are operating efficiently.
Update configurations: Make sure your runner configurations are up-to-date with the latest best practices.

Updating GitLab Runner

Keeping your GitLab Runner updated is essential for compatibility and security. GitLab frequently releases updates that include new features, bug fixes, and security patches. To update your runner:

Check for updates: Regularly visit the GitLab Runner releases page to see if a new version is available.
Backup configurations: Before updating, make sure to backup your runner’s configuration files.
Install the update: Follow the official GitLab documentation to install the latest version.

Handling Disk Space Issues

Disk space issues can cause your runners to fail. To avoid this, regularly clean up your runner’s disk space. You can use commands like docker system prune to remove unused data. Additionally, consider setting up automated scripts to handle this task.

Monitoring Runner Health

Monitoring the health of your runners is crucial for maintaining their performance. Use monitoring tools to track metrics such as CPU usage, memory usage, and disk I/O. This will help you identify and resolve issues quickly.

Automating Maintenance Tasks

Automating maintenance tasks can save you a lot of time and effort. Use scripts and cron jobs to automate routine tasks like cleaning up disk space and updating configurations. This ensures that your runners are always in optimal condition without requiring constant manual intervention.

Best Practices for Maintenance

Following best practices can help you maintain your GitLab Runners more effectively. Here are some tips:

Regularly review configurations: Make sure your runner configurations are aligned with the latest best practices.
Automate where possible: Use automation to handle routine maintenance tasks.
Monitor performance: Keep an eye on your runner’s performance metrics to catch issues early.
Stay updated: Regularly update your runners to benefit from the latest features and security patches.

By adopting best practices such as using parent-child pipeline architecture, applying rules: changes, leveraging yaml anchors, and strategically utilizing needs, you can ensure your GitLab Runners are always performing at their best.

Troubleshooting Common Issues

Runner Registration Problems

Having trouble registering your GitLab Runner? Double-check your registration token and ensure it’s correct. Sometimes, the issue lies in the token itself. If you’re still facing problems, try restarting the GitLab Runner service. This often resolves minor glitches.

Job Execution Failures

Jobs not running as expected? First, check the job logs for any error messages. These logs can provide valuable insights into what’s going wrong. If you’re using Docker, ensure that your Docker images are up-to-date and compatible with your runner configuration.

Docker Integration Issues

Docker integration can be tricky. Make sure your Docker daemon is running and properly configured. If you’re encountering issues, try restarting the Docker service. Also, verify that your Docker images are correctly specified in your .gitlab-ci.yml file.

Network Connectivity Problems

Network issues can disrupt your CI/CD pipelines. Ensure that your GitLab Runner can communicate with your GitLab instance. Check your firewall settings and network configurations to rule out any connectivity problems.

Resource Limitations

Running out of resources? Monitor your CPU, memory, and disk usage. If your runner is consistently hitting resource limits, consider scaling up your infrastructure or optimizing your jobs to use fewer resources.

Where to Get Help

Still stuck? The GitLab community is a great place to seek help. You can also refer to the [official GitLab documentation](https://docs.gitlab.com) for more detailed troubleshooting steps. Don’t forget to check out the GitLab forums and support channels for additional assistance.

Advanced GitLab Runner Features

Using Custom Executors

Custom executors allow you to define how your jobs are run. This is useful if you need to run jobs in a specific environment or with particular tools. You can create your own executor by writing a simple script that follows the GitLab Runner’s executor interface.

Setting Up SSH for Remote Jobs

Running jobs on remote machines via SSH can be a game-changer. It allows you to leverage the power of remote servers without needing to install GitLab Runner on them. Just configure your runner to use the SSH executor and provide the necessary credentials.

Integrating with Third-Party Tools

GitLab Runner can integrate with various third-party tools to enhance your CI/CD pipeline. Whether it’s a security scanner, a deployment tool, or a monitoring service, you can easily plug it into your pipeline. This flexibility makes GitLab Runner a powerful tool in your DevOps toolkit.

Using GitLab Runner with Auto DevOps

Auto DevOps simplifies the setup of CI/CD pipelines by providing pre-configured templates. When you use GitLab Runner with Auto DevOps, you can quickly get your projects up and running with minimal configuration. This is perfect for teams that want to maximize their CI/CD efficiency.

Leveraging GitLab Runner API

The GitLab Runner API allows you to automate and manage your runners programmatically. You can register new runners, check their status, and even remove them when they’re no longer needed. This is particularly useful for large-scale environments where manual management would be cumbersome.

Advanced Caching Techniques

Caching can significantly speed up your CI/CD pipelines by reusing previously downloaded dependencies and build artifacts. GitLab Runner supports advanced caching techniques that allow you to fine-tune what gets cached and for how long. This can lead to faster build times and more efficient use of resources.

By mastering these advanced features, you can take your CI/CD pipelines to the next level, ensuring they are both efficient and robust.

Optimizing GitLab Runner Performance

Optimizing the performance of your GitLab Runner can make a huge difference in your CI/CD pipeline. Let’s dive into some key areas to focus on.

Improving Job Execution Speed

To optimize your pipeline for efficiency, start by minimizing job run times. This includes reducing dependencies and using caching. Regularly review your pipeline to identify and eliminate bottlenecks.

Optimizing Resource Usage

Efficiently managing resources is crucial. Monitor your runner’s CPU, memory, and disk usage. Adjust resource limits to ensure jobs run smoothly without overloading the system.

Reducing Job Queue Times

Long job queues can slow down your development process. Use multiple runners to distribute the load and reduce wait times. Feel free to refer back to this guide as you configure and optimize your runners.

Using Efficient Docker Images

Choosing the right Docker images can significantly impact performance. Opt for lightweight images that include only the necessary dependencies. This reduces the time needed to pull and start containers.

Parallelizing Jobs

Running more jobs in parallel can improve overall pipeline efficiency. Configure your pipeline to execute independent jobs simultaneously, reducing the total build time.

Monitoring Performance Metrics

Keep an eye on performance metrics to identify areas for improvement. Use tools like Prometheus to collect and analyze data on job execution times, resource usage, and more.

Unlock your team’s potential with our guide to optimizing development through CI/CD best practices—covering everything from tool automation to secure environments.

By focusing on these areas, you can ensure your GitLab Runner is running at peak performance, helping you deliver faster and more reliable builds.

GitLab Runner in Different Environments

Using Runners in Cloud Environments

Running GitLab Runners in the cloud is a popular choice for many teams. Cloud environments offer scalability and flexibility, making it easy to handle varying workloads. You can set up runners on platforms like AWS, Azure, or Google Cloud. This setup allows you to leverage cloud resources efficiently, ensuring that your CI/CD pipelines run smoothly.

Setting Up Runners on Premises

For those who prefer to keep everything in-house, setting up GitLab Runners on-premises is a viable option. This approach gives you complete control over your infrastructure and data. You’ll need to ensure that your hardware meets the prerequisites for installation and that you have a robust network setup to handle the runner’s operations.

Using Runners in Hybrid Environments

A hybrid environment combines the best of both worlds: cloud and on-premises. This setup allows you to run some runners in the cloud while keeping others on-premises. It’s ideal for organizations that need to balance security and scalability. You can manage sensitive data on-premises while taking advantage of the cloud’s scalability for less sensitive tasks.

Integrating with AWS

Integrating GitLab Runners with AWS is straightforward. AWS offers various services like EC2 and ECS that can host your runners. You can use AWS’s auto-scaling features to ensure that you always have the right number of runners available, optimizing resource usage and cost.

Integrating with Azure

Azure provides robust support for GitLab Runners. You can set up runners on Azure VMs or use Azure Kubernetes Service (AKS) for containerized runners. Azure’s extensive service offerings make it easy to integrate GitLab Runners into your existing workflows, enhancing your CI/CD pipeline’s efficiency.

Integrating with Google Cloud

Google Cloud is another excellent option for hosting GitLab Runners. You can use Google Compute Engine for VM-based runners or Google Kubernetes Engine (GKE) for containerized runners. Google Cloud’s powerful tools and services help streamline your CI/CD processes, ensuring that your pipelines run efficiently and effectively.

GitLab Runner Best Practices

When it comes to using GitLab Runners, following best practices can make a huge difference in efficiency and security. Here are some key tips to keep in mind:

Choosing the Right Executor

Selecting the appropriate executor is crucial. GitLab Runners support various executors like Shell, Docker, and Kubernetes. Choosing the right executor depends on your project’s needs. For instance, Docker is great for isolated environments, while Shell might be simpler for straightforward tasks.

Efficiently Managing Resources

Resource management is vital for optimal performance. Limit the number of concurrent jobs to avoid overloading your runner. Use caching to speed up job execution and reduce redundant tasks. Efficiently managing resources ensures that your CI/CD pipeline runs smoothly.

Ensuring High Availability

High availability is essential for continuous integration and deployment. Set up multiple runners to handle the load and avoid downtime. Ensuring high availability can be achieved by using autoscaling features and load balancing jobs across runners.

Implementing Robust Security Measures

Security should never be an afterthought. Secure your runner registration and manage access control carefully. Use secure environment variables and handle sensitive data with care. Implementing robust security measures protects your pipeline from potential threats.

Regularly Updating Runners

Keeping your runners updated is crucial for compatibility and security. Regular updates ensure that you have the latest features and security patches. Regularly updating runners helps maintain a stable and secure CI/CD environment.

Documenting Runner Configurations

Documentation is key to maintaining a well-organized CI/CD pipeline. Document your runner configurations, including executor types, resource limits, and security settings. Documenting runner configurations makes it easier to manage and troubleshoot your runners.

Case Studies and Real-World Examples

Enterprise Use Case

In the enterprise world, GitLab Runners have been a game-changer. Large companies often deal with complex CI/CD pipelines, and GitLab Runners help streamline these processes. For instance, a major tech firm used GitLab Runners to reduce their deployment time by 50%. This not only improved their efficiency but also allowed them to focus more on innovation.

Small Business Use Case

Small businesses benefit immensely from GitLab Runners too. A startup, for example, leveraged GitLab Runners to automate their testing and deployment processes. This automation saved them countless hours and resources, enabling them to scale quickly without compromising on quality.

Open Source Project Use Case

Open source projects thrive on collaboration and efficiency. GitLab Runners have been instrumental in managing contributions and ensuring smooth CI/CD workflows. An open-source project saw a significant boost in productivity after integrating GitLab Runners, making it easier for contributors to test and deploy their code.

Educational Institution Use Case

Educational institutions are also reaping the benefits of GitLab Runners. A university’s computer science department used GitLab Runners to manage their students’ projects. This not only streamlined the submission process but also provided students with hands-on experience in CI/CD practices.

Freelancer Use Case

Freelancers often juggle multiple projects and clients. GitLab Runners help them maintain a seamless workflow. A freelance developer used GitLab Runners to automate their deployment process, allowing them to deliver projects faster and with fewer errors.

Community Contributions

The GitLab community is vibrant and ever-growing. Community contributions have played a significant role in enhancing GitLab Runners. From adding new features to improving existing ones, the community’s input has been invaluable. This collaborative effort ensures that GitLab Runners continue to evolve and meet the needs of users worldwide.

Future of GitLab Runners

Upcoming Features

GitLab is always evolving, and the latest GitLab CI/CD topics are no exception. Expect more automation, better performance, and enhanced security features. Keep an eye out for updates that make your CI/CD pipelines even more efficient.

Community Contributions

The GitLab community is vibrant and active. Contributions from users help shape the future of GitLab Runners. Whether it’s bug fixes, new features, or documentation improvements, the community plays a crucial role.

Integration with Emerging Technologies

GitLab is expanding its integrations with various platforms. For instance, GitLab announces expanded integrations with Google Cloud. This means you can expect smoother workflows and more robust CI/CD capabilities.

Predictions for CI/CD

The future of CI/CD looks promising with advancements in AI and machine learning. Features like GitLab Duo-powered root cause analysis are just the beginning. These technologies will make your pipelines smarter and more reliable.

GitLab Runner Roadmap

The roadmap for GitLab Runner includes exciting updates. For example, GitLab 17.2 released with log streaming and other enhancements. Stay tuned for more features that will make your CI/CD processes even more seamless.

How to Get Involved

Want to shape the future of GitLab Runners? Join the community forums, contribute to the codebase, or simply provide feedback. Your input can make a big difference in the development of new features and improvements.

Resources and Further Reading

Official GitLab Documentation

For the most comprehensive and up-to-date information, always refer to the [official GitLab documentation](https://docs.gitlab.com/runner/). It covers everything from installation to advanced configurations and troubleshooting.

Community Forums and Support

Join the conversation with other GitLab users on the [GitLab Community Forum](https://forum.gitlab.com/). It’s a great place to ask questions, share experiences, and get advice on running GitLab Runners.

Online Courses and Tutorials

If you prefer a more structured learning path, check out these online courses:

GitLab CI: Pipelines, CI/CD and DevOps for Beginners on Udemy
Learning GitLab on LinkedIn Learning
GitLab CI/CD: From Zero to Hero on Coursera

GitLab Runner GitHub Repository

For those who want to dive into the code, the [GitLab Runner GitHub repository](https://github.com/gitlabhq/gitlab-runner) is the place to go. Here, you can explore the source code, contribute to the project, and stay updated with the latest releases.

Staying Updated with GitLab News

Keep up with the latest news and updates from GitLab by following their official blog and subscribing to their newsletter. This way, you’ll never miss out on new features, updates, and best practices.

Pro Tip: Bookmark these resources and refer to them whenever you need help or want to learn something new about GitLab Runners.

Looking to dive deeper into the topics we’ve covered? Check out our website for more resources and detailed guides. You’ll find everything you need to expand your knowledge and stay ahead in your field. Don’t miss out on the latest updates and expert insights!

Conclusion

In summary, GitLab Runners are powerful tools that automate the build, test, and deployment processes in your CI/CD pipeline. Setting up a GitLab Runner might seem tricky at first, but with the right steps, it becomes straightforward. From installing the runner on your machine to registering and configuring it, each step is crucial for ensuring smooth and efficient job execution. While maintaining your runners requires some effort, the flexibility and control they offer make it worthwhile. By mastering GitLab Runners, you can significantly enhance your development workflow, making it faster and more reliable. Thanks for following along!