GitLab Community Edition is a self-hosted Git repository provider with additional features to help with project management and software development. One of the most valuable features that GitLab offers is the builtin continuous integration and delivery tool called GitLab CI.
In this guide, we will demonstrate how to set up GitLab CI to monitor your repositories for changes and run automated tests to validate new code. We will start with a running GitLab installation where we will copy an example repository for a basic Node.js application. After configuring our CI process, when a new commit is pushed to the repository GitLab will use CI runner to execute the test suite against the code in an isolated Docker container.
Before we begin, you’ll need to set up an initial environment. We need a secure GitLab server configured to store our code and manage our CI/CD processes. Additionally, we need a place to run the automated tests. This can either be the same server that GitLab is installed on or a separate host. The below sections cover the requirements in more detail.
To store the source code and configure our CI/CD tasks, we need a GitLab instance installed on an Ubuntu 16.04 server. GitLab currently recommends a server with at least 2 CPU cores and 4GB of RAM. To protect your code from being exposed or tampered with, the GitLab instance will be protected with SSL using Let’s Encrypt. Your server needs to have a domain name or a subdomain associated with it in order to complete this step.
You can complete these requirements using the following tutorials:
sudouser and configure a basic firewall
We will be demonstrating how to share CI/CD runners (the components that run the automated tests) between projects and how to lock them to single projects. If you wish to share CI runners between projects, we strongly recommend that you restrict or disable public sign-ups. If you didn’t modify your settings during installation, go back and follow the optional step from the GitLab installation article on restricting or disabling sign-ups to prevent abuse by outside parties.
GitLab CI Runners are the servers that check out the code and run automated tests to validate new changes. To isolate the testing environment, we will be running all of our automated tests within Docker containers. To do this, we need to install Docker on the server or servers that will be running the tests.
This step can be completed on the GitLab server or on a different Ubuntu 16.04 server to provide additional isolation and avoid resource contention. The following tutorials will install Docker on the host you wish to use to run your tests:
sudouser and configure a basic firewall (you do not have to complete this again if you are setting up the CI runner on the GitLab server)
When you are ready to begin, continue with this guide.
To begin, we will create a new project in GitLab containing the example Node.js application. We will import the original repository directly from GitHub so that we do not have to upload it manually.
Log into GitLab and click the plus icon in the upper-right corner and select New project to add a new project:
On the new project page, click on the Import project tab:
Next, click on the Repo by URL button. Although there is a GitHub import option, it requires a Personal access token and is used to import the repository and additional information. We are only interested in the code and the Git history, so importing by URL is easier.
In the Git repository URL field, enter the following GitHub repository URL:
It should look like this:
Since this is a demonstration, it’s probably best to keep the repository marked Private. When you are finished, click Create project.
The new project will be created based on the repository imported from GitHub.
GitLab CI looks for a file called
.gitlab-ci.yml within each repository to determine how it should test the code. The repository we imported has a
gitlab-ci.yml file already configured for the project. You can learn more about the format by reading the .gitlab-ci.yml reference documentation
Click on the
.gitlab-ci.yml file in the GitLab interface for the project we just created. The CI configuration should look like this:
image: node:latest stages: - build - test cache: paths: - node_modules/ install_dependencies: stage: build script: - npm install artifacts: paths: - node_modules/ test_with_lab: stage: test script: npm test
The file uses the GitLab CI YAML configuration syntax to define the actions that should be taken, the order they should execute, under what conditions they should be run, and the resources necessary to complete each task. When writing your own GitLab CI files, you can visit a syntax linter by going to
/ci/lint in your GitLab instance to validate that your file is formatted correctly.
The configuration file starts off by declaring a Docker
image that should be used to run the test suite. Since Hapi is a Node.js framework, we are using the latest Node.js image:
Next, we explicitly define different continuous integration stages that will run:
stages: - build - test
The names you choose here are arbitrary, but the ordering determines the order of execution for the steps that will follow. Stages are tags that you can apply to individual jobs. GitLab will run jobs of the same stage in parallel and will wait to execute the next stage until all jobs at the current stage are complete. If no stages are defined, GitLab will use three stages called
deploy and assign all jobs to the
test stage by default.
After defining the stages, the configuration includes a
cache: paths: - node_modules/
This specifies files or directories that can be cached (saved for later use) between runs or stages. This can help decrease the amount of time that it takes to run jobs that rely on resources that might not change between runs. Here, we are caching the
node_modules directory, which is where
npm will install the dependencies it downloads.
Our first job is called
install_dependencies: stage: build script: - npm install artifacts: paths: - node_modules/
Jobs can be named anything, but because the names will be used in the GitLab UI, descriptive names are helpful. Usually,
npm install can be combined with the next testing stages, but to better demonstrate the interaction between stages, we are extracting this step to run in its own stage.
We mark the stage explicitly as “build” with the
stage directive. Next, we specify the actual commands to run using the
script directive. You can include multiple commands by adding additional lines within the
artifacts subsection is used to specify file or directory paths to save and pass between stages. Because the
npm install command installs the dependencies for the project, our next step will need access to the downloaded files. Declaring the
node_modules path ensures that the next stage will have access to the files. These will also be available to view or download in the GitLab UI after the test, so this is useful for build artifacts like binaries as well. If you want to save everything produced during the stage, replace the entire
paths section with
Finally, the second job called
test_with_lab declares the command that will actually run the test suite:
test_with_lab: stage: test script: npm test
We place this in the
test stage. Since this is a later stage, it has access to the artifacts produced by the
build stage, which are the project dependencies in our case. Here, the
script section demonstrates the single-line YAML syntax that can be used when there’s only a single item. We could have used this same syntax in the previous job as well since only one command was specified.
Now that you have a basic idea of how the
.gitlab-ci.yml file defines CI/CD tasks, we can define one or more runners capable of executing the testing plan.
Since our repository includes a
.gitlab-ci.yml file, any new commits will trigger a new CI run. If no runners are available, the CI run will be set to “pending”. Before we define a runner, let’s trigger a CI run to see what a job looks like in the pending state. Once a runner is available, it will immediately pick up the pending run.
Back in the
hello_hapi GitLab project repository view, click on the plus sign next to the branch and project name and select New file from the menu:
On the next page, enter
dummy_file in the File name field and enter some text in the main editing window:
Click Commit changes at the bottom when you are finished.
Now, return to the main project page. A small paused icon will be attached to the most recent commit. If you mouse over the icon, it will display “Commit:pending”:
This means that the tests that validate code changes have not been run yet.
To get more information, go to the top of the page and click Pipelines. You will be taken to the pipeline overview page, where you can see that the CI run is marked as pending and labeled as “stuck”:
Note: Along the right-hand side is a button for the CI Lint tool. This is where you can check the syntax of any
gitlab-ci.yml files you write.
From here, you can click the pending status to get more details about the run. This view displays the different stages of our run, as well as the individual jobs associated with each stage:
Finally, click on the install_dependencies job. This will give you the specific details about what is delaying the run:
Here, the message indicates that the job is stuck because of a lack of runners. This is expected since we haven’t configured any yet. Once a runner is available, this same interface can be used to see the output. This is also the location where you can download artifacts produced during the build.
Now that we know what a pending job looks like, we can assign a CI runner to our project to pick up the pending job.
We’re now ready to set up a GitLab CI runner. To do this, we need to install the GitLab CI runner package on the system and start the GitLab runner service. The service can run multiple runner instances for different projects.
As mentioned in the prerequisites, you can complete these steps on the same server that hosts your GitLab instance or a different server if you want to be sure to avoid resource contention. Remember that whichever host you choose, you need Docker installed for the configuration we will be using.
The process of installing the GitLab CI runner service is similar to the process used to install GitLab itself. We will download a script to add a GitLab repository to our
apt source list. After running the script, we will download the runner package. We can then configure it to serve our GitLab instance.
Start by downloading the latest version of the GitLab CI runner repository configuration script to the
/tmp directory (this is a different repository than the one used by the GitLab server):
- curl -L https://packages.gitlab.com/install/repositories/runner/gitlab-runner/script.deb.sh -o /tmp/gl-runner.deb.sh
Feel free to examine the downloaded script to ensure that you are comfortable with the actions that it will take. You can also find a hosted version of the script here:
- less /tmp/gl-runner.deb.sh
Once you are satisfied with the safety of the script, run the installer:
- sudo bash /tmp/gl-runner.deb.sh
The script will set up your server to use the GitLab maintained repositories. This lets you manage GitLab runner packages with the same package management tools you use for your other system packages. Once this is complete, you can proceed with the installation using
- sudo apt-get install gitlab-runner
This will install the GitLab CI runner package on the system and start the GitLab runner service.
Next, we need to set up a GitLab CI runner so that it can begin accepting work.
To do this, we need a GitLab runner token so that the runner can authenticate with the GitLab server. The type of token we need depends on how we want to use this runner.
A project specific runner is useful if you have specific requirements for the runner. For instance, if your
gitlab-ci.yml file defines deployment tasks that require credentials, a specific runner may be required to authenticate correctly into the deployment environment. If your project has resource intensive steps in the CI process, this might also be a good idea. A project specific runner will not accept jobs from other projects.
On the other hand, a shared runner is a general purpose runner that can be used by multiple projects. Runners will take jobs from the projects according to an algorithm that accounts for the number of jobs currently being run for each project. This type of runner is more flexible. You will need to log into GitLab with an admin account to set up shared runners.
We will demonstrate how to get the runner tokens for both of these runner types below. Choose the method that suits you best.
If you would like the runner to be tied to a specific project, begin by navigating to the project’s page in the GitLab interface.
From here, click the Settings item in the left-hand menu. Afterwards, click the CI/CD item in the submenu:
On this page, you will see a Runners settings section. Click the Expand button to see more details. In the detail view, the left-hand side will explain how to register a project-specific runner. Copy the registration token displayed in step 4 of the instructions:
If you wish to disable any active shared runners for this project, you can do so by clicking the Disable shared Runners button on the right-hand side. This is optional.
When you are ready, skip ahead to learn how to register your runner using the pieces of information you collected from this page.
To find the information required to register a shared runner, you will need to be logged in with an administrative account.
Begin by clicking the wrench icon in the top navigation bar to access the admin area. In the Overview section of the left-hand menu, click Runners to access the shared runner configuration page:
Copy the registration token displayed towards the top of the page:
We will use this token to register a GitLab CI runner for the project.
Now that you have a token, go back to the server where your GitLab CI runner service is installed.
To register a new runner, type the following command:
- sudo gitlab-runner register
You will be asked a series of questions to configure the runner:
Please enter the gitlab-ci coordinator URL (e.g. https://gitlab.com/)
Enter your GitLab server’s domain name, using
https:// to specify SSL. You can optionally append
/ci to the end of your domain, but recent versions will redirect automatically.
Please enter the gitlab-ci token for this runner
The token you copied in the last section.
Please enter the gitlab-ci description for this runner
A name for this particular runner. This will show up in the runner service’s list of runners on the command line and in the GitLab interface.
Please enter the gitlab-ci tags for this runner (comma separated)
These are tags that you can assign to the runner. GitLab jobs can express requirements in terms of these tags to make sure they are run on a host with the correct dependencies.
You can leave this blank in this case.
Whether to lock Runner to current project [true/false]
Assigns the runner to the specific project. It cannot be used by other projects.
Select “false” here.
Please enter the executor
The method used by the runner to complete jobs.
Choose “docker” here.
Please enter the default Docker image (e.g. ruby:2.1)
The default image used to run jobs when the
.gitlab-ci.yml file does not include an image specification. It’s best to specify a general image here and define more specific images in your
.gitlab-ci.yml file as we have done.
We will enter “alpine:latest” here as a small, secure default.
After answering the prompts, a new runner will be created capable of running your project’s CI/CD tasks.
You can see the runners that the GitLab CI runner service currently has available by typing:
- sudo gitlab-runner list
OutputListing configured runners ConfigFile=/etc/gitlab-runner/config.toml example-runner Executor=docker Token=e746250e282d197baa83c67eda2c0b URL=https://example.com
Now that we have a runner available, we can return to the project in GitLab.
Back in your web browser, return to your project in GitLab. Depending on how long it has been since registering your runner, the runner may be currently running:
Or it might have completed already:
Regardless of the state, click on the running or passed icon (or failed if you ran into a problem) to view the current state of the CI run. You can get a similar view by clicking the top Pipelines menu.
You will be taken to the pipeline overview page where you can see the status of the GitLab CI run:
Under the Stages header, there will be a circle indicating the status of each of the stages in the run. If you click on the stage, you can see the individual jobs associated with the stage:
Click on the install_dependencies job within the build stage. This will take you to the job overview page:
Now, instead of displaying a message about no runners being available, the output of the job is displayed. In our case, this means that you can see the results of
npm installing each of the packages.
Along the right-hand side, you can see some other items as well. You can view other jobs by changing the Stage and clicking the runs below. You can also view or download any artifacts produced by the run.
In this guide, we’ve added a demonstration project to a GitLab instance to showcase the continuous integration and deployment capabilities of GitLab CI. We discussed how to define a pipeline in
gitlab-ci.yml files to build and test your applications and how to assign jobs to stages to define their relationship to one another. We then set up a GitLab CI runner to pick up CI jobs for our project and demonstrated how to find information about individual GitLab CI runs.
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Hi there, a tip about security. The ssl is depecrated, currentily is the tls.
Hi Can you please explain why you have a cache and an artifact set up? Many thanks.
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Is there a tutorial to deploy an app through bitbucket pipelines to digitalocean’s kubernetes cluster ?
I have followed all your steps on centos, everything is working docker container also launched. I am able to access application using http://localhost:3000/hello/Hoper but if i am trying to access it using public IP then it is not accessible. While launching container its assigning dynamic IP’s which are not mapped/accessible from outside server. Can you please tell me how to bind this container to servers IP instead of virtual IP?
Curious, is there any particular way to spin up a droplet on-demand prior to a pipeline running? Current setup involves maybe 1 or 2 pipelines running in a day which say takes a total of 20 minutes. Rather frustrating having to keep a droplet up for 23 hours 40 minutes doing nothing.