[{"data":1,"prerenderedAt":817},["ShallowReactive",2],{"/en-us/blog/how-to-automate-software-delivery-using-quarkus-and-gitlab":3,"navigation-en-us":41,"banner-en-us":450,"footer-en-us":460,"blog-post-authors-en-us-Cesar Saavedra":698,"blog-related-posts-en-us-how-to-automate-software-delivery-using-quarkus-and-gitlab":712,"blog-promotions-en-us":755,"next-steps-en-us":807},{"id":4,"title":5,"authorSlugs":6,"authors":8,"body":10,"category":11,"categorySlug":11,"config":12,"content":16,"date":20,"description":17,"extension":25,"externalUrl":26,"featured":14,"heroImage":19,"isFeatured":14,"meta":27,"navigation":28,"path":29,"publishedDate":20,"rawbody":30,"seo":31,"slug":13,"stem":35,"tagSlugs":36,"tags":39,"template":15,"updatedDate":26,"__hash__":40},"blogPosts/en-us/blog/how-to-automate-software-delivery-using-quarkus-and-gitlab.yml","How to automate software delivery using Quarkus and GitLab",[7],"cesar-saavedra",[9],"Cesar Saavedra","\n\nIn this day and age, organizations need to deliver innovative solutions faster than ever to their customers to stay competitive. This is why solutions that speed up software development and delivery, such as Quarkus and GitLab, are being adopted by teams across the world.\n\n[Quarkus](https://quarkus.io/), also known as the Supersonic Subatomic Java, is an open source Kubernetes-native Java stack tailored for OpenJDK HotSpot and GraalVM, crafted from respected Java libraries and standards. Quarkus has been steadily growing in popularity and use because of the benefits that it delivers: cost savings, faster time to market/value, and reliability. Quarkus offers two modes: Java and native. Its Java mode builds your application using the JDK and its native mode compiles your Java code into a native executable.\n\nGitLab, the One DevOps Platform, includes capabilities for all DevOps stages, from planning to production, all with a single model and user interface to help you ship secure code faster to any cloud and drive business results. Besides DevOps support, GitLab also offers GitOps support.\n\nThe combination of Quarkus and GitLab can empower your developers and operations teams to collaborate better, spend more time innovating to deliver business value and differentiating capabilities to end users.\n\nIn this article, we show how to automate the software delivery of a generated Quarkus application in Java mode using GitLab Auto DevOps. Below we list the steps how to accomplish this.\n\n## Prerequisite\n\nThe prerequisite for the subsequent instructions is to have a K8s cluster up and running and associated to a group in your GitLab account. For an example on how to do this, please watch this [video](https://youtu.be/QRR3WuwnxXE).\n\n## Generate your Quarkus project using the generator and upload to GitLab\n\n- From a browser window, point to the Quarkus generator site, https://code.quarkus.io, and click on the button **Generate your application**.\n\n![Generate Quarkus app](https://about.gitlab.com/images/blogimages/quarkusone.png){:small.center.}\n\nGenerate a sample Quarkus application using the generator\n\n\n- On the popup window, click on the button **DOWNLOAD THE ZIP**, to download a sample Quarkus application in a ZIP file to your local machine. The downloaded file is named `code-with-quarkus.zip`.\n\n- Unzip the file on your local machine in a directory of your choice. This will create a new directory called `code-with-quarkus` with all the files for the sample Quarkus application.\n\n- From a browser window, open https://gitlab.com, and log in using your GitLab credentials.\n\n- Head over to the GitLab group to which you associated your K8s cluster and create a blank project named `code-with-quarkus`.\n\n![Create project code-with-quarkus](https://about.gitlab.com/images/blogimages/quarkustwo.png)\nCreate project code-with-quarkus\n\n\n- From a Terminal window on your local machine, change directory to the newly unzipped directory `code-with-quarkus` and execute the command `rm .dockerignore` to delete the `.dockerignore` file that came with the sample Quarkus application. After removing this file, execute the following commands to populate your newly create Git project `code-with-quarkus` with the contents of this directory:\n\n**NOTE:** Depending on your version of git installed on your local machine, the commands below may vary. Keep in mind that the goal of the steps below is to upload the project on your local machine to your newly created GitLab project.\n\n```shell\ngit init\ngit remote add origin https://gitlab.com/[REPLACE WITH PATH TO YOUR GROUP]/code-with-quarkus.git\ngit add .\ngit commit -m \"Initial commit\"\ngit push --set-upstream origin master\n```\n\nAt this point, you should have your sample Quarkus application in your GitLab project `code-with-quarkus`.\n\n## Modify the generated Dockerfile.jvm file and indicate its location\n\nSince the location of the Dockerfile is not at the root level of the project, we need to create a project variable DOCKERFILE_PATH and set it to `src/main/docker/Dockerfile.jvm` to indicate to the Auto Build job where to find the Dockerfile to build the container image.\n\n- From your `code-with-quarkus` GitLab project window, select **Settings > CI/CD** from the left vertical navigation menu.\n\n- Scroll to the **Variables** section on the screen and click on the **Expand** button on the right hand side of the section.\n\n- Click on the **Add Variable** button and enter the following values for the fields in the popup:\n\n```text\nKey = DOCKERFILE_PATH\nValue = src/main/docker/Dockerfile.jvm\nType = Variable\nEnvironment scope = All (default)\nProtect variable Flag = ensure this flag is unchecked\nMask variable Flag = ensure this flag is unchecked\n```\n\nThe variable definition should look as follows:\n\n![Add var dockerfilepath](https://about.gitlab.com/images/blogimages/quarkusthree.png)\nAdd DOCKERFILE_PATH variable to the your code-with-quarkus project\n\n\n- Click on the **Add variable** button to complete adding this variable to your project\n\nIn order for Auto Build to work, we need to make some minor modifications to the generated Dockerfile.jvm in the sample Quarkus application.\n\n- From your `code-with-quarkus` GitLab project window, navigate to the directory `src/main/docker` and click on the file `Dockerfile.jvm`. Click on the **Edit** button to start making changes to this file.\n\n- At the top of the file, you will see about 77 lines of comments. Replace all the lines following the comments with the following code segment:\n\n```text\n####\nFROM openjdk:11 as builder\nRUN mkdir /build\nADD . /build/\n\nWORKDIR /build\nRUN ./mvnw package\n\nFROM registry.access.redhat.com/ubi8/openjdk-11:1.11\n\nENV LANG='en_US.UTF-8' LANGUAGE='en_US:en'\n\n# We make four distinct layers so if there are application changes the library layers can be re-used\nCOPY --from=builder --chown=185 /build/target/quarkus-app/lib/ /deployments/lib/\nCOPY --from=builder --chown=185 /build/target/quarkus-app/*.jar /deployments/\nCOPY --from=builder --chown=185 /build/target/quarkus-app/app/ /deployments/app/\nCOPY --from=builder --chown=185 /build/target/quarkus-app/quarkus/ /deployments/quarkus/\n\nEXPOSE 8080\nUSER 185\nENV AB_JOLOKIA_OFF=\"\"\nENV JAVA_OPTS=\"-Dquarkus.http.host=0.0.0.0 -Djava.util.logging.manager=org.jboss.logmanager.LogManager\"\nENV JAVA_APP_JAR=\"/deployments/quarkus-run.jar\"\n```\n\nThe lines above add a build stage called`builder` to do the Java build using the openjdk:11 image and adds a `build` working directory to the process. The rest of the lines are effectively the same as the original except that we have updated the paths of the `COPY` commands to find the appropriate files under the `build` working directory.\n\n- Click on the **Commit changes** button at the bottom of the **New file** window to create the new file.\n\n## Update the application port number\n\nThe Auto Deploy job of Auto DevOps defaults to port 5000 for applications but the sample Quarkus application uses port 8080. So, we need to override this value in the helm chart for the Auto Deploy job. This is how you do it:\n\n- From your `code-with-quarkus` GitLab project window, click on **New File** from the pop-down menu next to project root name directory as shown below:\n\n![Select new file](https://about.gitlab.com/images/blogimages/quarkusfour.png)\nSelect New file from your code-with-quarkus project top-level directory\n\n\n- On the **New file** window, enter `.gitlab/auto-deploy-values.yaml` for the name of the new file and paste the following two lines as the content of the file:\n\n```yaml\nservice:\n  internalPort: 8080\n\n```\n\nYour window should look as follows:\n\n![Update application port number for Auto Deploy](https://about.gitlab.com/images/blogimages/quarkusfive.png)\nUpdate the application port number in the helm chart for Auto Deploy\n\n\n- Click on the **Commit changes** button at the bottom of the **New file** window to create the new file.\n\n## Update the version of the JDK\n\nThe sample Quarkus application includes a unit test that is automatically run by the Auto Test job, which uses a Java version not compatible with Quarkus resulting in “java.lang.UnsupportedClassVersionError” exceptions. To solve this, we need to adjust the Java runtime version to 11 since this is the lowest version of the JRE supported by Quarkus. Let’s do this:\n\n- From your `code-with-quarkus` GitLab project window, click on **New File** from the pop-down menu next to project root name directory and name the new file `system.properties`. As its contents, paste the following line into it:\n\n```text\njava.runtime.version=11\n```\n\n- Click on the **Commit changes** button at the bottom of the **New file** window to create the new file.\n\n## Enable Auto DevOps\n\nLastly, we need to enable Auto DevOps for your `code-with-quarkus` GitLab project.\n\n- From your `code-with-quarkus` GitLab project window, select **Settings > CI/CD** from the left vertical navigation menu.\n\n- Scroll to the **Auto DevOps** section on the screen and click on the **Expand** button on the right hand side of the section.\n\n- In the section, check the **Default to Auto DevOps pipeline** checkbox. Then, for Deployment strategy, select on the radio button **Automatic deployment to staging, manual deployment to production**. Finally, click on the **Save changes** button. Here’s an example screenshot:\n\n![Enable Auto DevOps](https://about.gitlab.com/images/blogimages/quarkussix.png)\nEnable Auto DevOps for your sample Quarkus project\n\n\nThis will launch an Auto DevOps pipeline that will build, test and deploy your application first to the staging environment and then give you the option to manually deploy to 100% of the production environment. The completed Auto DevOps pipeline should look like this:\n\n![Completed pipeline](https://about.gitlab.com/images/blogimages/completed-pipe.png)\nCompleted Auto DevOps pipeline for a sample Quarkus application in Java mode\n\n\n## Conclusion\n\nThe combination of Quarkus and GitLab can empower your developers and operations teams to collaborate better, spend more time innovating to deliver business value and differentiating capabilities to end users.\n\nIn this article, we showed how to automate the software delivery of a generated Quarkus application in Java mode using GitLab Auto DevOps. Here is [a working sample project](https://gitlab.com/tech-marketing/sandbox/hn/code-with-quarkus) of this Quarkus application, whose delivery has been automated by GitLab Auto DevOps.\n\n\n\n\n\n\n\n\n\n\n","devsecops",{"slug":13,"featured":14,"template":15},"how-to-automate-software-delivery-using-quarkus-and-gitlab",false,"BlogPost",{"title":5,"description":17,"authors":18,"heroImage":19,"date":20,"body":10,"category":11,"tags":21},"Here's a step-by-step guide to automated software delivery using Supersonic Subatomic Java (Quarkus) and GitLab.",[9],"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749666915/Blog/Hero%20Images/autodevops.jpg","2022-06-09",[22,23,24],"DevOps","CI/CD","community","yml",null,{},true,"/en-us/blog/how-to-automate-software-delivery-using-quarkus-and-gitlab","seo:\n  title: How to automate software delivery using Quarkus and GitLab\n  description: >-\n    Here's a step-by-step guide to automated software delivery using Supersonic\n    Subatomic Java (Quarkus) and GitLab.\n  ogTitle: How to automate software delivery using Quarkus and GitLab\n  ogDescription: >-\n    Here's a step-by-step guide to automated software delivery using Supersonic\n    Subatomic Java (Quarkus) and GitLab.\n  noIndex: false\n  ogImage: >-\n    https://res.cloudinary.com/about-gitlab-com/image/upload/v1749666915/Blog/Hero%20Images/autodevops.jpg\n  ogUrl: >-\n    https://about.gitlab.com/blog/how-to-automate-software-delivery-using-quarkus-and-gitlab\n  ogSiteName: https://about.gitlab.com\n  ogType: article\n  canonicalUrls: >-\n    https://about.gitlab.com/blog/how-to-automate-software-delivery-using-quarkus-and-gitlab\ncontent:\n  title: How to automate software delivery using Quarkus and GitLab\n  description: >-\n    Here's a step-by-step guide to automated software delivery using Supersonic\n    Subatomic Java (Quarkus) and GitLab.\n  authors:\n    - Cesar Saavedra\n  heroImage: >-\n    https://res.cloudinary.com/about-gitlab-com/image/upload/v1749666915/Blog/Hero%20Images/autodevops.jpg\n  date: '2022-06-09'\n  body: >+\n\n\n    In this day and age, organizations need to deliver innovative solutions\n    faster than ever to their customers to stay competitive. This is why\n    solutions that speed up software development and delivery, such as Quarkus\n    and GitLab, are being adopted by teams across the world.\n\n\n    [Quarkus](https://quarkus.io/), also known as the Supersonic Subatomic Java,\n    is an open source Kubernetes-native Java stack tailored for OpenJDK HotSpot\n    and GraalVM, crafted from respected Java libraries and standards. Quarkus\n    has been steadily growing in popularity and use because of the benefits that\n    it delivers: cost savings, faster time to market/value, and reliability.\n    Quarkus offers two modes: Java and native. Its Java mode builds your\n    application using the JDK and its native mode compiles your Java code into a\n    native executable.\n\n\n    GitLab, the One DevOps Platform, includes capabilities for all DevOps\n    stages, from planning to production, all with a single model and user\n    interface to help you ship secure code faster to any cloud and drive\n    business results. Besides DevOps support, GitLab also offers GitOps support.\n\n\n    The combination of Quarkus and GitLab can empower your developers and\n    operations teams to collaborate better, spend more time innovating to\n    deliver business value and differentiating capabilities to end users.\n\n\n    In this article, we show how to automate the software delivery of a\n    generated Quarkus application in Java mode using GitLab Auto DevOps. Below\n    we list the steps how to accomplish this.\n\n\n    ## Prerequisite\n\n\n    The prerequisite for the subsequent instructions is to have a K8s cluster up\n    and running and associated to a group in your GitLab account. For an example\n    on how to do this, please watch this [video](https://youtu.be/QRR3WuwnxXE).\n\n\n    ## Generate your Quarkus project using the generator and upload to GitLab\n\n\n    - From a browser window, point to the Quarkus generator site,\n    https://code.quarkus.io, and click on the button **Generate your\n    application**.\n\n\n    ![Generate Quarkus\n    app](https://about.gitlab.com/images/blogimages/quarkusone.png){:small.center.}\n\n\n    Generate a sample Quarkus application using the generator\n\n\n\n    - On the popup window, click on the button **DOWNLOAD THE ZIP**, to download\n    a sample Quarkus application in a ZIP file to your local machine. The\n    downloaded file is named `code-with-quarkus.zip`.\n\n\n    - Unzip the file on your local machine in a directory of your choice. This\n    will create a new directory called `code-with-quarkus` with all the files\n    for the sample Quarkus application.\n\n\n    - From a browser window, open https://gitlab.com, and log in using your\n    GitLab credentials.\n\n\n    - Head over to the GitLab group to which you associated your K8s cluster and\n    create a blank project named `code-with-quarkus`.\n\n\n    ![Create project\n    code-with-quarkus](https://about.gitlab.com/images/blogimages/quarkustwo.png)\n\n    Create project code-with-quarkus\n\n\n\n    - From a Terminal window on your local machine, change directory to the\n    newly unzipped directory `code-with-quarkus` and execute the command `rm\n    .dockerignore` to delete the `.dockerignore` file that came with the sample\n    Quarkus application. After removing this file, execute the following\n    commands to populate your newly create Git project `code-with-quarkus` with\n    the contents of this directory:\n\n\n    **NOTE:** Depending on your version of git installed on your local machine,\n    the commands below may vary. Keep in mind that the goal of the steps below\n    is to upload the project on your local machine to your newly created GitLab\n    project.\n\n\n    ```shell\n\n    git init\n\n    git remote add origin https://gitlab.com/[REPLACE WITH PATH TO YOUR\n    GROUP]/code-with-quarkus.git\n\n    git add .\n\n    git commit -m \"Initial commit\"\n\n    git push --set-upstream origin master\n\n    ```\n\n\n    At this point, you should have your sample Quarkus application in your\n    GitLab project `code-with-quarkus`.\n\n\n    ## Modify the generated Dockerfile.jvm file and indicate its location\n\n\n    Since the location of the Dockerfile is not at the root level of the\n    project, we need to create a project variable DOCKERFILE_PATH and set it to\n    `src/main/docker/Dockerfile.jvm` to indicate to the Auto Build job where to\n    find the Dockerfile to build the container image.\n\n\n    - From your `code-with-quarkus` GitLab project window, select **Settings >\n    CI/CD** from the left vertical navigation menu.\n\n\n    - Scroll to the **Variables** section on the screen and click on the\n    **Expand** button on the right hand side of the section.\n\n\n    - Click on the **Add Variable** button and enter the following values for\n    the fields in the popup:\n\n\n    ```text\n\n    Key = DOCKERFILE_PATH\n\n    Value = src/main/docker/Dockerfile.jvm\n\n    Type = Variable\n\n    Environment scope = All (default)\n\n    Protect variable Flag = ensure this flag is unchecked\n\n    Mask variable Flag = ensure this flag is unchecked\n\n    ```\n\n\n    The variable definition should look as follows:\n\n\n    ![Add var\n    dockerfilepath](https://about.gitlab.com/images/blogimages/quarkusthree.png)\n\n    Add DOCKERFILE_PATH variable to the your code-with-quarkus project\n\n\n\n    - Click on the **Add variable** button to complete adding this variable to\n    your project\n\n\n    In order for Auto Build to work, we need to make some minor modifications to\n    the generated Dockerfile.jvm in the sample Quarkus application.\n\n\n    - From your `code-with-quarkus` GitLab project window, navigate to the\n    directory `src/main/docker` and click on the file `Dockerfile.jvm`. Click on\n    the **Edit** button to start making changes to this file.\n\n\n    - At the top of the file, you will see about 77 lines of comments. Replace\n    all the lines following the comments with the following code segment:\n\n\n    ```text\n\n    ####\n\n    FROM openjdk:11 as builder\n\n    RUN mkdir /build\n\n    ADD . /build/\n\n\n    WORKDIR /build\n\n    RUN ./mvnw package\n\n\n    FROM registry.access.redhat.com/ubi8/openjdk-11:1.11\n\n\n    ENV LANG='en_US.UTF-8' LANGUAGE='en_US:en'\n\n\n    # We make four distinct layers so if there are application changes the\n    library layers can be re-used\n\n    COPY --from=builder --chown=185 /build/target/quarkus-app/lib/\n    /deployments/lib/\n\n    COPY --from=builder --chown=185 /build/target/quarkus-app/*.jar\n    /deployments/\n\n    COPY --from=builder --chown=185 /build/target/quarkus-app/app/\n    /deployments/app/\n\n    COPY --from=builder --chown=185 /build/target/quarkus-app/quarkus/\n    /deployments/quarkus/\n\n\n    EXPOSE 8080\n\n    USER 185\n\n    ENV AB_JOLOKIA_OFF=\"\"\n\n    ENV JAVA_OPTS=\"-Dquarkus.http.host=0.0.0.0\n    -Djava.util.logging.manager=org.jboss.logmanager.LogManager\"\n\n    ENV JAVA_APP_JAR=\"/deployments/quarkus-run.jar\"\n\n    ```\n\n\n    The lines above add a build stage called`builder` to do the Java build using\n    the openjdk:11 image and adds a `build` working directory to the process.\n    The rest of the lines are effectively the same as the original except that\n    we have updated the paths of the `COPY` commands to find the appropriate\n    files under the `build` working directory.\n\n\n    - Click on the **Commit changes** button at the bottom of the **New file**\n    window to create the new file.\n\n\n    ## Update the application port number\n\n\n    The Auto Deploy job of Auto DevOps defaults to port 5000 for applications\n    but the sample Quarkus application uses port 8080. So, we need to override\n    this value in the helm chart for the Auto Deploy job. This is how you do it:\n\n\n    - From your `code-with-quarkus` GitLab project window, click on **New File**\n    from the pop-down menu next to project root name directory as shown below:\n\n\n    ![Select new\n    file](https://about.gitlab.com/images/blogimages/quarkusfour.png)\n\n    Select New file from your code-with-quarkus project top-level directory\n\n\n\n    - On the **New file** window, enter `.gitlab/auto-deploy-values.yaml` for\n    the name of the new file and paste the following two lines as the content of\n    the file:\n\n\n    ```yaml\n\n    service:\n      internalPort: 8080\n\n    ```\n\n\n    Your window should look as follows:\n\n\n    ![Update application port number for Auto\n    Deploy](https://about.gitlab.com/images/blogimages/quarkusfive.png)\n\n    Update the application port number in the helm chart for Auto Deploy\n\n\n\n    - Click on the **Commit changes** button at the bottom of the **New file**\n    window to create the new file.\n\n\n    ## Update the version of the JDK\n\n\n    The sample Quarkus application includes a unit test that is automatically\n    run by the Auto Test job, which uses a Java version not compatible with\n    Quarkus resulting in “java.lang.UnsupportedClassVersionError” exceptions. To\n    solve this, we need to adjust the Java runtime version to 11 since this is\n    the lowest version of the JRE supported by Quarkus. Let’s do this:\n\n\n    - From your `code-with-quarkus` GitLab project window, click on **New File**\n    from the pop-down menu next to project root name directory and name the new\n    file `system.properties`. As its contents, paste the following line into it:\n\n\n    ```text\n\n    java.runtime.version=11\n\n    ```\n\n\n    - Click on the **Commit changes** button at the bottom of the **New file**\n    window to create the new file.\n\n\n    ## Enable Auto DevOps\n\n\n    Lastly, we need to enable Auto DevOps for your `code-with-quarkus` GitLab\n    project.\n\n\n    - From your `code-with-quarkus` GitLab project window, select **Settings >\n    CI/CD** from the left vertical navigation menu.\n\n\n    - Scroll to the **Auto DevOps** section on the screen and click on the\n    **Expand** button on the right hand side of the section.\n\n\n    - In the section, check the **Default to Auto DevOps pipeline** checkbox.\n    Then, for Deployment strategy, select on the radio button **Automatic\n    deployment to staging, manual deployment to production**. Finally, click on\n    the **Save changes** button. Here’s an example screenshot:\n\n\n    ![Enable Auto\n    DevOps](https://about.gitlab.com/images/blogimages/quarkussix.png)\n\n    Enable Auto DevOps for your sample Quarkus project\n\n\n\n    This will launch an Auto DevOps pipeline that will build, test and deploy\n    your application first to the staging environment and then give you the\n    option to manually deploy to 100% of the production environment. The\n    completed Auto DevOps pipeline should look like this:\n\n\n    ![Completed\n    pipeline](https://about.gitlab.com/images/blogimages/completed-pipe.png)\n\n    Completed Auto DevOps pipeline for a sample Quarkus application in Java mode\n\n\n\n    ## Conclusion\n\n\n    The combination of Quarkus and GitLab can empower your developers and\n    operations teams to collaborate better, spend more time innovating to\n    deliver business value and differentiating capabilities to end users.\n\n\n    In this article, we showed how to automate the software delivery of a\n    generated Quarkus application in Java mode using GitLab Auto DevOps. Here is\n    [a working sample\n    project](https://gitlab.com/tech-marketing/sandbox/hn/code-with-quarkus) of\n    this Quarkus application, whose delivery has been automated by GitLab Auto\n    DevOps.\n\n\n\n\n\n\n\n\n\n\n  category: devsecops\n  tags:\n    - DevOps\n    - CI/CD\n    - community\nconfig:\n  slug: how-to-automate-software-delivery-using-quarkus-and-gitlab\n  featured: false\n  template: 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Dame uses GitLab for Education to manage student assignments, distribute course materials, and provide inline code feedback at scale.\n",[718],"Rod Burns","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749659537/Blog/Hero%20Images/display-article-image-0679-1800x945-fy26.png","2026-04-29","For instructors teaching software development, one of the biggest logistical challenges is assignment distribution and feedback at scale. How do you give large groups of students access to course materials, keep solution code private, and still deliver meaningful, contextual feedback without lots of administrative overhead?\n\nThe **[GitLab for Education program](https://about.gitlab.com/solutions/education/)** provides qualifying institutions with free access to **GitLab Ultimate**, enabling instructors to build professional-grade workflows that mirror real-world software development environments. In this article, you'll learn how Stephen G. Dame, a lecturer in the Computing and Software Systems department at the University of Washington, Bothell, uses simple workflows in GitLab to manage everything from course materials to student feedback across multiple classes.\n\n## From aerospace to academia: Bringing GitLab to the classroom\n\nDame came to academia with years of experience as a chief software engineer at Boeing Commercial Airplanes, where GitLab was used for aerospace projects. As an adjunct professor, he became an early advocate for GitLab within the university, joining the GitLab for Education program to access the full feature set needed to run structured, scalable course workflows.\n\n> **\"GitLab provides the greatest way to organize multiple classes, student assignments, lectures, and code samples through the use of Groups and Subgroups, which I found to be unique to GitLab compared to other repository platforms.\"**\n>\n> - Stephen G. Dame, University of Washington, Bothell\n\n## Set up groups: Build the right structure before writing a line of code\n\nThe foundation of an effective GitLab-based course is a well-planned group hierarchy. GitLab's **[Groups and Subgroups](https://docs.gitlab.com/tutorials/manage_user/#create-the-organization-parent-group-and-subgroups)** allow instructors to model the natural structure of a university department institution, course, and role with precise, inheritable permissions at every level.\n\nDame's structure places the university at the root (`UWTeaching`), with each course occupying its own subgroup (e.g. `css430`). Within each course sit repositories for `lecture-materials` and `code`, alongside dedicated Subgroups for `students` and `graders`. Instructor materials remain private, while student and grader subgroups are configured with controlled permissions so that assignment briefs and solutions are visible only to the right people.\n\n![Screenshot of GitLab group hierarchy — institution, course subgroup, and per-student subgroups](https://res.cloudinary.com/about-gitlab-com/image/upload/v1777463673/dpxfnitv76pdmvcqtgag.png)\n\nPermissions cascade downward through the hierarchy via **Manage > Members**, allowing Dame to add students to a course's `students` subgroup with `Reporter` access and an expiration date tied to the end of the academic quarter. Students can clone and pull from assignment repositories but cannot push — keeping solution code firmly under instructor control.\n\nStudents are guided to set up SSH keys across all their working environments (local machines, cloud shells, virtual machines) so they can clone repositories and receive weekly updates via `git pull`. They copy relevant code into their own private repositories to manage their own version history.\n\n**Tip for large classes:** For larger cohorts, adding students by hand is impractical. GitLab's REST API lets you automate subgroup creation and membership from a list of usernames. Below is a sample Python script that handles this:\n\n```python\n    import gitlab\n    from datetime import datetime\n\n    # Connect to your GitLab instance\n    gl = gitlab.Gitlab('https://gitlab.com', private_token='YOUR_PRIVATE_TOKEN')\n\n    # Target parent group ID (e.g., the ID for \"css430 > students\")\n    parent_group_id = 12345678\n\n    # Set expiration: typically the beginning of the next month after quarter end\n    expiry_date = '2025-01-01'\n\n    # List of collected student usernames\n    student_list = ['alice_css430', 'bob_css430', 'carol_css430', 'dave_css430', 'eve_css430']\n\n    for username in student_list:\n        try:\n            # 1. Create a personal subgroup for the student\n            subgroup = gl.groups.create({\n                'name': username,\n                'path': username,\n                'parent_id': parent_group_id,\n                'visibility': 'private'\n            })\n\n            # 2. Add student to the new subgroup with Expiration\n            user = gl.users.list(username=username)[0]\n            subgroup.members.create({\n                'user_id': user.id,\n                'access_level': gitlab.const.REPORTER_ACCESS,\n                'expires_at': expiry_date\n            })\n            print(f\"Success: Subgroup created and student added for {username}\")\n        except Exception as e:\n            print(f\"Error processing {username}: {e}\")\n```\nThere is also an [open source project that automates class management](https://gitlab.com/edu-docs/class-management-automation) published by GitLab that provides additional tooling for this workflow.\n## Give feedback where the work actually lives\n\nOnce the structure is in place, the feedback workflow is where GitLab's value becomes most apparent to students. Dame asks students to submit assignments by opening a **[merge request](https://docs.gitlab.com/user/project/merge_requests/)** in their repository. This gives instructors an immediate, clean diff of everything the student has written.\n![A GitLab merge request showing inline code comment function for an instructor](https://res.cloudinary.com/about-gitlab-com/image/upload/v1777467468/icclzyglbkwlvfysggbi.png)\nInstructors can click any line of code and leave an **inline comment** — not just flagging what is wrong, but explaining why, and pointing to what to look at next. Students receive this feedback in direct context with their code, which is far more actionable than a comment at the bottom of a submitted document.\n\n## Join GitLab for Education\n\nSetting up your first GitLab assignment takes some initial effort, but once the structure is in place it largely runs itself. The real payoff goes beyond organization: Students graduate having worked daily in an environment that mirrors professional software development, building habits around [version control](https://about.gitlab.com/topics/version-control/) and [code review](https://docs.gitlab.com/development/code_review/) rather than learning them as abstract concepts.\n\nIf you are just getting started, keep it simple. Begin with a single course group, one assignment template, and a basic pipeline. The structure will grow naturally alongside your confidence with the platform.\n\nMake sure to **[sign up for GitLab for Education](https://about.gitlab.com/solutions/education/join/)** so that you and your students can access all top-tier features, including unlimited reviewers on merge requests, additional compute minutes, and expanded storage.\n\n> [Apply to the GitLab for Education program today](https://about.gitlab.com/solutions/education/join/).",[620,723],"open source",{"featured":14,"template":15,"slug":725},"teaching-software-development-the-easy-way-using-gitlab",{"content":727,"config":739},{"description":728,"authors":729,"heroImage":731,"date":732,"title":733,"body":734,"category":11,"tags":735},"AI-generated code is 34% of development work. Discover how to balance productivity gains with quality, reliability, and security.",[730],"Manav Khurana","https://res.cloudinary.com/about-gitlab-com/image/upload/v1767982271/e9ogyosmuummq7j65zqg.png","2026-01-08","AI is reshaping DevSecOps: Attend GitLab Transcend to see what’s next","AI promises a step change in innovation velocity, but most software teams are hitting a wall. According to our latest [Global DevSecOps Report](https://about.gitlab.com/developer-survey/), AI-generated code now accounts for 34% of all development work. Yet 70% of DevSecOps professionals report that AI is making compliance management more difficult, and 76% say agentic AI will create unprecedented security challenges.\n\nThis is the AI paradox: AI accelerates coding, but software delivery slows down as teams struggle to test, secure, and deploy all that code.\n\n## Productivity gains meet workflow bottlenecks\nThe problem isn't AI itself. It's how software gets built today. The traditional DevSecOps lifecycle contains hundreds of small tasks that developers must navigate manually: updating tickets, running tests, requesting reviews, waiting for approvals, fixing merge conflicts, addressing security findings. These tasks drain an average of seven hours per week from every team member, according to our research.\n\nDevelopment teams are producing code faster than ever, but that code still crawls through fragmented toolchains, manual handoffs, and disconnected processes. In fact, 60% of DevSecOps teams use more than five tools for software development overall, and 49% use more than five AI tools. This fragmentation creates collaboration barriers, with 94% of DevSecOps professionals experiencing factors that limit collaboration in the software development lifecycle.\n\nThe answer isn't more tools. It's intelligent orchestration that brings software teams and their AI agents together across projects and release cycles, with enterprise-grade security, governance, and compliance built in.\n\n## Seeking deeper human-AI partnerships\nDevSecOps professionals don't want AI to take over — they want reliable partnerships. The vast majority (82%) say using agentic AI would increase their job satisfaction, and 43% envision an ideal future with a 50/50 split between human and AI contributions. They're ready to trust AI with 37% of their daily tasks without human review, particularly for documentation, test writing, and code reviews.\n\nWhat we heard resoundingly from DevSecOps professionals is that AI won't replace them; rather, it will fundamentally reshape their roles. 83% of DevSecOps professionals believe AI will significantly change their work within five years, and notably, 76% think this will create more engineering jobs, not fewer. As coding becomes easier with AI, engineers who can architect systems, ensure quality, and apply business context will be in high demand.\n\nCritically, 88% agree there are essential human qualities that AI will never fully replace, including creativity, innovation, collaboration, and strategic vision.\n\nSo how can organizations bridge the gap between AI’s promise and the reality of fragmented workflows?\n\n## Join us at GitLab Transcend: Explore how to drive real value with agentic AI\nOn February 10, 2026, GitLab will be hosting Transcend, where we'll reveal how intelligent orchestration transforms AI-powered software development. You'll get a first look at GitLab's upcoming product roadmap and learn how teams are solving real-world challenges by modernizing development workflows with AI.\n\nOrganizations winning in this new era balance AI adoption with security, compliance, and platform consolidation. AI offers genuine productivity gains when implemented thoughtfully — not by replacing human developers, but by freeing DevSecOps professionals to focus on strategic thinking and creative innovation.\n\n[Register for Transcend today](https://about.gitlab.com/events/transcend/virtual/) to secure your spot and discover how intelligent orchestration can help your software teams stay in flow.",[736,737,738],"AI/ML","DevOps platform","security",{"featured":28,"template":15,"slug":740},"ai-is-reshaping-devsecops-attend-gitlab-transcend-to-see-whats-next",{"content":742,"config":753},{"title":743,"description":744,"authors":745,"heroImage":747,"date":748,"body":749,"category":11,"tags":750},"Atlassian ending Data Center as GitLab maintains deployment choice","As Atlassian transitions Data Center customers to cloud-only, GitLab presents a menu of deployment choices that map to business needs.",[746],"Emilio Salvador","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750098354/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%281%29_5XrohmuWBNuqL89BxVUzWm_1750098354056.png","2025-10-07","Change is never easy, especially when it's not your choice. Atlassian's announcement that [all Data Center products will reach end-of-life by March 28, 2029](https://www.atlassian.com/blog/announcements/atlassian-ascend), means thousands of organizations must now reconsider their DevSecOps deployment and infrastructure. But you don't have to settle for deployment options that don't fit your needs. GitLab maintains your freedom to choose — whether you need self-managed for compliance, cloud for convenience, or hybrid for flexibility — all within a single AI-powered DevSecOps platform that respects your requirements.\n\nWhile other vendors force migrations to cloud-only architectures, GitLab remains committed to supporting the deployment choices that match your business needs. Whether you're managing sensitive government data, operating in air-gapped environments, or simply prefer the control of self-managed deployments, we understand that one size doesn't fit all.\n\n## The cloud isn't the answer for everyone\n\nFor the many companies that invested millions of dollars in Data Center deployments, including those that migrated to Data Center [after its Server products were discontinued](https://about.gitlab.com/blog/atlassian-server-ending-move-to-a-single-devsecops-platform/), this announcement represents more than a product sunset. It signals a fundamental shift away from customer-centric architecture choices, forcing enterprises into difficult positions: accept a deployment model that doesn't fit their needs, or find a vendor that respects their requirements.\n\nMany of the organizations requiring self-managed deployments represent some of the world's most important organizations: healthcare systems protecting patient data, financial institutions managing trillions in assets, government agencies safeguarding national security, and defense contractors operating in air-gapped environments.\n\nThese organizations don't choose self-managed deployments for convenience; they choose them for compliance, security, and sovereignty requirements that cloud-only architectures simply cannot meet. Organizations operating in closed environments with restricted or no internet access aren't exceptions — they represent a significant portion of enterprise customers across various industries.\n\n![GitLab vs. Atlassian comparison table](https://res.cloudinary.com/about-gitlab-com/image/upload/v1759928476/ynl7wwmkh5xyqhszv46m.jpg)\n\n## The real cost of forced cloud migration goes beyond dollars\n\nWhile cloud-only vendors frame mandatory migrations as \"upgrades,\" organizations face substantial challenges beyond simple financial costs:\n\n* **Lost integration capabilities:** Years of custom integrations with legacy systems, carefully crafted workflows, and enterprise-specific automations become obsolete. Organizations with deep integrations to legacy systems often find cloud migration technically infeasible.\n\n* **Regulatory constraints:** For organizations in regulated industries, cloud migration isn't just complex — it's often not permitted. Data residency requirements, air-gapped environments, and strict regulatory frameworks don't bend to vendor preferences. The absence of single-tenant solutions in many cloud-only approaches creates insurmountable compliance barriers.\n\n* **Productivity impacts:** Cloud-only architectures often require juggling multiple products: separate tools for planning, code management, CI/CD, and documentation. Each tool means another context switch, another integration to maintain, another potential point of failure. GitLab research shows [30% of developers spend at least 50% of their job maintaining and/or integrating their DevSecOps toolchain](https://about.gitlab.com/developer-survey/). Fragmented architectures exacerbate this challenge rather than solving it.\n\n## GitLab offers choice, commitment, and consolidation\n\nEnterprise customers deserve a trustworthy technology partner. That's why we've committed to supporting a range of deployment options — whether you need on-premises for compliance, hybrid for flexibility, or cloud for convenience, the choice remains yours. That commitment continues with [GitLab Duo](https://about.gitlab.com/gitlab-duo-agent-platform/), our AI solution that supports developers at every stage of their workflow.\n\nBut we offer more than just deployment flexibility. While other vendors might force you to cobble together their products into a fragmented toolchain, GitLab provides everything in a **comprehensive AI-native DevSecOps platform**. Source code management, CI/CD, security scanning, Agile planning, and documentation are all managed within a single application and a single vendor relationship.\n\nThis isn't theoretical. When Airbus and [Iron Mountain](https://about.gitlab.com/customers/iron-mountain/) evaluated their existing fragmented toolchains, they consistently identified challenges: poor user experience, missing functionalities like built-in security scanning and review apps, and management complexity from plugin troubleshooting. **These aren't minor challenges; they're major blockers for modern software delivery.**\n\n## Your migration path: Simpler than you think\n\nWe've helped thousands of organizations migrate from other vendors, and we've built the tools and expertise to make your transition smooth:\n\n* **Automated migration tools:** Our [Bitbucket Server importer](https://docs.gitlab.com/user/import/bitbucket_server/) brings over repositories, pull requests, comments, and even Large File Storage (LFS) objects. For Jira, our [built-in importer](https://docs.gitlab.com/user/project/import/jira/) handles issues, descriptions, and labels, with professional services available for complex migrations.\n\n* **Proven at scale:** A 500 GiB repository with 13,000 pull requests, 10,000 branches, and 7,000 tags is likely to [take just 8 hours to migrate](https://docs.gitlab.com/user/import/bitbucket_server/) from Bitbucket to GitLab using parallel processing.\n\n* **Immediate ROI:** A [Forrester Consulting Total Economic Impact™ study commissioned by GitLab](https://about.gitlab.com/resources/study-forrester-tei-gitlab-ultimate/) found that investing in GitLab Ultimate confirms these benefits translate to real bottom-line impact, with a three-year 483% ROI, 5x time saved in security related activities, and 25% savings in software toolchain costs.\n\n## Start your journey to a unified DevSecOps platform\n\nForward-thinking organizations aren't waiting for vendor-mandated deadlines. They're evaluating alternatives now, while they have time to migrate thoughtfully to platforms that protect their investments and deliver on promises.\n\nOrganizations invest in self-managed deployments because they need control, compliance, and customization. When vendors deprecate these capabilities, they remove not just features but the fundamental ability to choose environments matching business requirements.\n\nModern DevSecOps platforms should offer complete functionality that respects deployment needs, consolidates toolchains, and accelerates software delivery, without forcing compromises on security or data sovereignty.\n\n[Talk to our sales team](https://about.gitlab.com/sales/) today about your migration options, or explore our [comprehensive migration resources](https://about.gitlab.com/move-to-gitlab-from-atlassian/) to see how thousands of organizations have already made the switch.\n\nYou also can [try GitLab Ultimate with GitLab Duo Enterprise](https://about.gitlab.com/free-trial/devsecops/) for free for 30 days to see what a unified DevSecOps platform can do for your organization.",[571,564,751,752],"product","features",{"featured":28,"template":15,"slug":754},"atlassian-ending-data-center-as-gitlab-maintains-deployment-choice",{"promotions":756},[757,771,782,793],{"id":758,"categories":759,"header":761,"text":762,"button":763,"image":768},"ai-modernization",[760],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":764,"config":765},"Get your AI maturity score",{"href":766,"dataGaName":767,"dataGaLocation":244},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":769},{"src":770},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":772,"categories":773,"header":774,"text":762,"button":775,"image":779},"devops-modernization",[751,11],"Are you just managing tools or shipping innovation?",{"text":776,"config":777},"Get your DevOps maturity score",{"href":778,"dataGaName":767,"dataGaLocation":244},"/assessments/devops-modernization-assessment/",{"config":780},{"src":781},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":783,"categories":784,"header":785,"text":762,"button":786,"image":790},"security-modernization",[738],"Are you trading speed for security?",{"text":787,"config":788},"Get your security maturity score",{"href":789,"dataGaName":767,"dataGaLocation":244},"/assessments/security-modernization-assessment/",{"config":791},{"src":792},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"id":794,"paths":795,"header":798,"text":799,"button":800,"image":805},"github-azure-migration",[796,797],"migration-from-azure-devops-to-gitlab","integrating-azure-devops-scm-and-gitlab","Is your team ready for GitHub's Azure move?","GitHub is already rebuilding around Azure. Find out what it means for you.",{"text":801,"config":802},"See how GitLab compares to GitHub",{"href":803,"dataGaName":804,"dataGaLocation":244},"/compare/gitlab-vs-github/github-azure-migration/","github azure migration",{"config":806},{"src":781},{"header":808,"blurb":809,"button":810,"secondaryButton":815},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":811,"config":812},"Get your free trial",{"href":813,"dataGaName":52,"dataGaLocation":814},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":506,"config":816},{"href":56,"dataGaName":57,"dataGaLocation":814},1777493598512]