[{"data":1,"prerenderedAt":818},["ShallowReactive",2],{"/en-us/blog/migrating-from-bamboo-to-gitlab-cicd":3,"navigation-en-us":39,"banner-en-us":450,"footer-en-us":460,"blog-post-authors-en-us-Abubakar Siddiq Ango":699,"blog-related-posts-en-us-migrating-from-bamboo-to-gitlab-cicd":713,"blog-promotions-en-us":756,"next-steps-en-us":808},{"id":4,"title":5,"authorSlugs":6,"authors":8,"body":10,"category":11,"categorySlug":11,"config":12,"content":16,"date":20,"description":17,"extension":24,"externalUrl":25,"featured":14,"heroImage":19,"isFeatured":14,"meta":26,"navigation":27,"path":28,"publishedDate":20,"rawbody":29,"seo":30,"slug":13,"stem":34,"tagSlugs":35,"tags":37,"template":15,"updatedDate":25,"__hash__":38},"blogPosts/en-us/blog/migrating-from-bamboo-to-gitlab-cicd.yml","How to migrate from Bamboo to GitLab CI/CD",[7],"abubakar-siddiq-ango",[9],"Abubakar Siddiq Ango","_Atlassian is ending support for all Server products in February 2024. [Learn more about the benefits of migrating from Atlassian to GitLab here](https://about.gitlab.com/move-to-gitlab-from-atlassian/)._\n\nThe clock is ticking towards the February 15, 2024, [end-of-life date Atlassian has set for their Server products](https://about.gitlab.com/blog/atlassian-server-ending-move-to-a-single-devsecops-platform/). Users whose workflows rely on on-premises deployments of Atlassian Server products are faced with the choice of upgrading to Atlassian’s Data Center or Cloud products or finding alternatives. \n\nOne of the Atlassian products that is impacted is Bamboo, a CI/CD solution. Whether you're simply looking for a new CI/CD tool or you're looking to consolidate your entire toolchain, the Atlassian Server end of life is a great opportunity to make the move to GitLab to take advantage of the automation, scalability, and security of an end-to-end DevSecOps platform.\n\nIn this blog post, we'll cover the steps you can take to migrate your Bamboo CI/CD setup to GitLab CI/CD.\n\n## How is GitLab CI/CD different from Bamboo?\n\n### Organization\n\nBamboo is structured around Projects and Plans. CI/CD jobs are grouped into stages, which are defined in a Bamboo plan along with other configurations that determine how jobs run. Bamboo projects are used to organize plans, which are classified into Build and Deployment plans. \n\nAs the name implies, Build plans can be configured to pull code from configured repositories and generate artifacts. These artifacts are picked by jobs defined in Deployment plans and are deployed to environments configured in Bamboo. Bamboo jobs are also composed of tasks, which can be a script, a task to pull code from a repository, or a task specific to a technology.\n\nYou also need to add code repositories to a Bamboo plan or a project, making it available to all plans under it, and set triggers for how Bamboo detects changes and runs builds.\n\nGitLab is organized differently. Everything is in a single platform, with your CI/CD configuration provided as part of your code in a `.gitlab-ci.yml` file, from a group’s compliance pipeline configuration, or Auto DevOps when enabled and the `.gitlab-ci.yml` file is not found in a project.\n\nGitlab CI/CD configurations are composed of jobs, grouped into stages. How the jobs are triggered can be controlled by CI/CD `rules` and there is no separate configuration for deployments. Deployment jobs can be defined in the same CI/CD script in a `deploy` stage, with the [deployment environment](https://docs.gitlab.com/ci/environments/) set.\n\n### Agents vs Runners\n\nBamboo uses [Agents](https://confluence.atlassian.com/confeval/development-tools-evaluator-resources/bamboo/bamboo-remote-agents-and-local-agents)\nto run builds and deployments. These can be local agents running on the Bamboo server or\nremote agents running external to the server. GitLab uses a similar concept to agents,\ncalled [GitLab Runner](https://docs.gitlab.com/runner/), which uses [executors](https://docs.gitlab.com/runner/executors/)\nto run builds. Examples of executors include SSH, Docker, and Kubernetes. You can choose to\nuse GitLab [SaaS runners](https://docs.gitlab.com/ci/runners/) or deploy your own [self-managed runners](https://docs.gitlab.com/runner/install/).\n\n### Bamboo Specs vs .gitlab-ci.yml file\n\nBamboo is largely configured via the Bamboo UI but can also be configured as code using Bamboo Specs. Bamboo Specs can be defined using Java and other JVM languages or using YAML, with Java having more complete feature coverage than YAML. Bamboo Specs can be defined and stored in spec repositories, then linked to Bamboo projects.\n\nThe `.gitlab-ci.yml` file is central to the CI/CD workflow in GitLab. When included in a project, the defined configurations are executed against the project; otherwise, [Auto DevOps](https://docs.gitlab.com/topics/autodevops/) automatically builds and deploys your application, when enabled. Templates and CI/CD components can also be added to `.gitlab-ci.yml` for complex use cases.\n\n## How GitLab steps up your workflow\n\nIn addition to building and deploying your application, GitLab provides a suite of features that allows for building secure applications fast and efficiently. These include:\n\n- [Application security](https://docs.gitlab.com/user/application_security/): GitLab analyzes your application across the stages of the software development lifecycle with security scans such as Static Application Security Testing (SAST), Secret Detection, Infrastructure as Code (IaC) Scanning, Dependency Scanning, License Scanning, Coverage-guided Fuzz Testing, Container Scanning, API Security, Dynamic Application Security Testing (DAST), and Operational Security Scanning.\n- Compliance and security policies: Understanding the results of security scans and putting policies in place is crucial to ensuring secure applications. You can set up Scan Execution or Result policies to ensure additional scans or approval requirements are added to comply with regulatory or self-imposed requirements.\n- [CI/CD catalog](https://docs.gitlab.com/ci/components/catalog/): Parts of CI/CD configurations that are used across multiple projects can be turned into [components](https://docs.gitlab.com/ci/components/#components-repository) stored in component repositories that are discoverable in the CI/CD catalog.\n- Packages and registries: Custom or local replicas of popular packages can be hosted with the [GitLab Package Registry](https://docs.gitlab.com/user/packages/package_registry/). You can also host container images with the [GitLab Container Registry](https://docs.gitlab.com/user/packages/container_registry/) and Terraform modules with the [GitLab Terraform Module Registry](https://docs.gitlab.com/user/packages/terraform_module_registry/). If you frequently use public images or packages, you can use the [Dependency Proxy](https://docs.gitlab.com/user/packages/dependency_proxy/) to maintain a local cache.\n\n[Learn more about other ways to automate your entire workflow with GitLab CI/CD](https://about.gitlab.com/solutions/continuous-integration/).\n\n## Convert Bamboo Specs to .gitlab-ci.yml script\n\nFor the purpose of this blog post, we will focus on [Bamboo YAML Specs](https://docs.atlassian.com/bamboo-specs-docs/9.3.0/specs.html?yaml). You can export your Bamboo Plans as YAML Spec — [learn more here](https://confluence.atlassian.com/bamboo/exporting-existing-plan-configuration-to-bamboo-yaml-specs-1018270696.html). Now, lets walk through converting your Bamboo YAML Specs into GitLab CI/CD configuration.\n\n### Container image\n\nFirst is defining the container image of the container your jobs will run in. By default, Bamboo uses Agents, which depend on how the host machines are configured. You can replicate the Agent’s environment into a container image hosted in the [GitLab Container Registry](https://docs.gitlab.com/user/packages/container_registry/).  \n\nIf you already run Bamboo jobs in a container image, it will look like this in your spec:\n\n```yaml\n---\nversion: 2\n# ...\ndocker: ubuntu\n```\n\nThis might be defined at the plan or job level. You can define it in GitLab as follows:\n\n```yaml\nimage: ubuntu\n```\n\n[Learn more about running CI/CD jobs in containers here](https://docs.gitlab.com/ci/docker/using_docker_images/). If your use case does not include containers, you can explore [other executors](https://docs.gitlab.com/runner/executors/).\n\n### Stages\n\nIn Bamboo, stages and their list of jobs are defined first, before the job definitions:\n\n```yaml\nversion: 2\nstages:\n  - First Stage:\n      jobs:\n        - Job 1A \n        - Job 1B\n  - Second Stage:\n      jobs:\n        - Job 2A \n        - Job 2B\n\nJob 1A:\n  tasks:\n    - clean\n    - script\n        - touch file1A.txt\n\nJob 1B:\n  tasks:\n    - clean\n    - script\n        - touch file1B.txt\n\nJob 2A:\n  tasks:\n    - clean\n    - script\n        - touch file2A.txt\n\nJob 2B:\n  tasks:\n    - clean\n    - script\n        - touch file2B.txt\n\n```\n\nIn GitLab, you list your stages in the order in which you want their jobs to run:\n\n```yaml\nstages:\n  - build\n  - test\n  - deploy\n\njob1:\n  stage: build\n  script:\n    - echo \"This job compiles code.\"\n\njob2:\n  stage: test\n  script:\n    - echo \"This job tests the compiled code. It runs when the build stage completes.\"\n\njob3:\n  script:\n    - echo \"This job also runs in the test stage\".\n\njob4:\n  stage: deploy\n  script:\n    - echo \"This job deploys the code. It runs when the test stage completes.\"\n  environment: production\n\n```\n\nAll the jobs in a stage run in parallel and when they succeed, execution proceeds to the next stage. This only changes in complex pipelines where a job depends on another using [`needs`](https://docs.gitlab.com/ci/yaml/#needs).\n\n### Variables\n\nBamboo has System, Global, Project, Plan, and Build-specific variables, which can be accessed using the format `${system.variableName}` for system variables and `${bamboo.variableName}` for others. Periods (.) are replaced by underscores (_) when variables are accessed in scripts.\n\n```yaml\nversion: 2\n# ...\nvariables:\n  username: admin\n  releaseType: milestone\n\nDefault job:\n  tasks:\n    - script: echo 'Release Type is $bamboo_releaseType'\n\n```\n\nIn GitLab, variables can be defined at group, project, CI Script, and job levels. In GitLab self-managed and GitLab Dedicated, administrators can define variables at the instance level. GitLab allows protecting, masking, and expanding variables. Protected variables are only accessible for pipelines running against the default or protected branches. [Learn more about CI/CD variables](https://docs.gitlab.com/ci/variables/) and [where you can use them](https://docs.gitlab.com/ci/variables/where_variables_can_be_used/).\n\nHere is an example:\n\n```yaml\nvariables:\n  GLOBAL_VAR: \"A global variable\"\n\njob1:\n  variables:\n    JOB_VAR: \"A job variable\"\n  script:\n    - echo \"Variables are '$GLOBAL_VAR' and '$JOB_VAR'\"\n\njob2:\n  script:\n    - echo \"Variables are '$GLOBAL_VAR' and '$JOB_VAR'\"\n\n```\n\n### Build Jobs\n\nBamboo Build Jobs are composed of tasks, each of which is a small unit of work that can be anything from checking out source code to injecting variables or running a script.\n\n```yaml\nversion: 2\nstages:\n  - Run Tests:\n      jobs:\n        - Test Ruby \n\nTest Ruby :\n  key: TEST\n  tasks:\n  - checkout:\n      force-clean-build: false\n      description: Checkout Default Repository\n  - script:\n      interpreter: SHELL\n      scripts:\n      - |-\n        ruby -v  # Print out ruby version for debugging\n        bundle config set --local deployment true  \n        bundle install -j $(nproc)\n        rubocop\n        rspec spec\n      description: run bundler & rspec\n\n```\n\nIn this example, the plan has two tasks, checkout and script. The checkout tasks pull an updated version of the code repository, which is made available for the script task to execute its commands against. \n\n[Jobs in GitLab](https://docs.gitlab.com/ci/jobs/) are composed of script commands:\n\n```text\nimage: ruby:latest\n\nstages:\n  - test\n\nrspec:\n  stage: test\n  script:\n    - ruby -v\n    - bundle config set --local deployment true \n    - bundle install -j $(nproc)\n    - rubocop\n    - rspec spec\n\n```\n\nIn the example above, the stage the job belongs to is specified with the `stage` keyword and the commands to be executed by the GitLab runner for the job are listed under `script`.\n\nIn Bamboo, you can use [executables](https://confluence.atlassian.com/bamboo/defining-a-new-executable-capability-289277164.html), such as Ant, Maven, or PHPUnit, in a task to build your application. In GitLab, you can package the binaries you need in a custom container image and use it as your CI/CD image.\n\n### Deployment jobs\n\nIn Bamboo, Deployment projects organize software releases or environments applications are deployed to. A deployment plan can have a release definition:\n\n```yaml\n---\nversion: 2\n\ndeployment:\n  name: Release Software\n  source-plan: BUILD-APP\n\nrelease-naming: release-1.1\n```\n\nFor releases, you specify the plan it should get the generated artifacts from. And for deployment for environments:\n\n```yaml\n---\nversion: 2\n# ...\nenvironments:\n  - Test\n  - QA\n  - Prod\n\nTest:\n  tasks:\n    - clean\n    - artifact-download:\n        destination: /workdir\n\n```\n\nIn GitLab CI/CD, you can create a [deployment job](https://docs.gitlab.com/ci/jobs/#deployment-jobs)\nthat deploys to an [environment](https://docs.gitlab.com/ci/environments/) or create a [release](https://docs.gitlab.com/user/project/releases/).\nFor deploying to an environment, you use the [`environment`](https://docs.gitlab.com/ci/yaml/#environment) keyword:\n\n```yaml\ndeploy-to-production:\n  stage: deploy\n  script:\n    - # Run Deployment script\n    - ./.ci/deploy_prod.sh\n  environment:\n    name: production\n\n```\n\nIf you are creating a release instead, you use the [`release`](https://docs.gitlab.com/ci/yaml/#release)\nkeyword along with the [release-cli](https://gitlab.com/gitlab-org/release-cli/-/tree/master/docs)\ntool to create releases for [Git tags](https://docs.gitlab.com/user/project/repository/tags/).\nThe `release` section is executed after the `script` section, which must exist.\nIf you don’t have any script commands to run, you can put a placeholder command;\nfor example, `echo` a message.\n\n```yaml\nrelease_job:\n  stage: release\n  image: registry.gitlab.com/gitlab-org/release-cli:latest\n  rules:\n    - if: $CI_COMMIT_TAG                  # Run this job when a tag is created manually\n  script:\n    - echo \"Building release version\"\n  release:\n    tag_name: $CI_COMMIT_TAG\n    name: 'Release $CI_COMMIT_TAG'\n    description: 'Release created using the release-cli.'\n\n```\n\n### Rules and workflows\n\nIn Bamboo, triggers can be used to control how Jobs are executed. Triggers can be a periodic poll of the repository for changes or a webhook that notifies Bamboo of changes to the repository. Trigger conditions can be enabled in the Bamboo web UI to make sure the build only runs if other plans are passing.\n\nExample of a trigger:\n\n```yaml\n---\nversion: 2\ntriggers:\n  - polling: 130\n  - cron: 0 * * * ? *\n\n```\n\nIn GitLab, [CI/CD pipelines](https://docs.gitlab.com/ci/pipelines/) can be triggered by a commit/push, a merge, manually, on schedule, or with [pipeline subscriptions](https://docs.gitlab.com/ci/pipelines/#trigger-a-pipeline-when-an-upstream-project-is-rebuilt). Jobs in a pipeline can further be controlled using `rules` or `workflow`. Learn more about [Job Control](https://docs.gitlab.com/ci/jobs/job_control/) and [pipeline workflows](https://docs.gitlab.com/ci/yaml/workflow/#) in GitLab CI/CD. \n\nHere's an example using `rules` in GitLab CI/CD:\n\n```yaml\nworkflow:\n  rules:\n    - changes:\n      - .gitlab/**/**.md\n      when: never\n\n```\n In this example, pipelines are never executed when `.md` files changed in the `.gitlab` folder.\n\n#### Artifacts\n\nYou can define Job artifacts using the `artifacts` keyword in both GitLab and Bamboo.\n\nIn Bamboo, artifacts can be defined as follows:\n\n```yaml\n---\nversion: 2\n# ...\n  artifacts:\n    -\n      name: Test Reports\n      location: target/reports\n      pattern: '*.xml'\n      required: false\n      shared: false\n    -\n      name: Special Reports\n      location: target/reports\n      pattern: 'special/*.xml'\n      shared: true\n\n```\n\nIn the Bamboo Spec above, artifacts are defined with a name, location, pattern, and optionally\nthe ability to share the artifacts with other jobs or plans. You can go further to define jobs that\ncan subscribe to the artifact.\n\n`artifact-subscriptions` is used to access artifacts from another job in the same plan:\n\n```yaml\nTest app:\n  artifact-subscriptions:\n    -\n      artifact: Test Reports\n      destination: deploy\n\n```\n\n`artifact-download` is used to access artifacts from jobs in a different plan.\n\n```yaml\n---\nversion: 2\n# ...\n  tasks:\n    - artifact-download: \n        source-plan: PROJECTKEY-PLANKEY\n\n```\n\nYou need to provide the key of the plan you are downloading artifacts from in the `source-plan` keyword.\n\nIn GitLab, all artifacts from completed jobs in the previous stages are downloaded by default.\nHere is an example of an artifact definition in GitLab:\n\n```yaml\npdf:\n  script: xelatex mycv.tex\n  artifacts:\n    name: \"pdf-files\"\n    public: false\n    untracked: true\n    paths:\n      - pdfs/\n    exclude:\n      - pdfs/*.tex\n\n```\n\nIn the CI/CD script above:\n\n- The name of the artifact is specified laterally. You can choose to make it dynamic by using a CI/CD variable.\n- The `public` keyword is used to set whether the artifact should be publicly available. This is not enabled by default\n  on self-managed GitLab instances. An administrator can enable it with the [feature flag](https://docs.gitlab.com/administration/feature_flags/)\n  named `non_public_artifacts`.\n- You can set the `untracked` to include or exclude Git untracked files along with those specified using `paths`.\n\nRead more about GitLab CI/CD [job artifacts](https://docs.gitlab.com/ci/jobs/job_artifacts/).\n\n## How to plan your migration\n\nPlanning a migration to Gitlab CI/CD from Bamboo doesn't start with converting your Bamboo plan to GitLab CI/CD scripts. It starts with aligning with your leadership and stakeholders and clearly communicating the vision of the migration. [Check out our documentation to learn more about managing organizational changes](https://docs.gitlab.com/ci/migration/plan_a_migration/). Once you have the necessary buy-in, you can proceed with the following steps:\n\n- [Import your projects](https://docs.gitlab.com/user/project/import/) to GitLab.\n- Identify the necessary binaries and build tools needed to build your application, along with their dependencies.\n- Define the flow of your pipeline, which jobs depend on each other, and the necessary triggers.\n- Learn more about [key GitLab CI/CD features](https://docs.gitlab.com/ci/).\n- Identify the credentials and variables needed in your pipeline and define them in the variable section of your project's CI/CD settings or using a secret manager.\n- Follow [this tutorial](https://docs.gitlab.com/ci/quick_start/) to create your first GitLab pipeline; you can also explore more [complex pipelines](https://docs.gitlab.com/ci/quick_start/tutorial/).\n- Iterate and test your GitLab CI/CD pipelines and review [.gitlab-ci.yml keyword reference](https://docs.gitlab.com/ci/yaml/).\n\nReady to make the move? [We’re here to help](https://about.gitlab.com/sales/).\n","devsecops",{"slug":13,"featured":14,"template":15},"migrating-from-bamboo-to-gitlab-cicd",false,"BlogPost",{"title":5,"description":17,"authors":18,"heroImage":19,"date":20,"body":10,"category":11,"tags":21},"With the fast approaching EOL of Atlassian Server products, including Bamboo, this blog post explains how users of Bamboo can migrate to GitLab CI/CD.",[9],"https://res.cloudinary.com/about-gitlab-com/image/upload/v1749658924/Blog/Hero%20Images/securitylifecycle-light.png","2023-10-26",[22,23],"DevSecOps","DevSecOps platform","yml",null,{},true,"/en-us/blog/migrating-from-bamboo-to-gitlab-cicd","seo:\n  title: How to migrate from Bamboo to GitLab CI/CD\n  description: >-\n    With the fast approaching EOL of Atlassian Server products, including\n    Bamboo, this blog post explains how users of Bamboo can migrate to GitLab\n    CI/CD.\n  ogTitle: How to migrate from Bamboo to GitLab CI/CD\n  ogDescription: >-\n    With the fast approaching EOL of Atlassian Server products, including\n    Bamboo, this blog post explains how users of Bamboo can migrate to GitLab\n    CI/CD.\n  noIndex: false\n  ogImage: >-\n    https://res.cloudinary.com/about-gitlab-com/image/upload/v1749658924/Blog/Hero%20Images/securitylifecycle-light.png\n  ogUrl: https://about.gitlab.com/blog/migrating-from-bamboo-to-gitlab-cicd\n  ogSiteName: https://about.gitlab.com\n  ogType: article\n  canonicalUrls: https://about.gitlab.com/blog/migrating-from-bamboo-to-gitlab-cicd\ncontent:\n  title: How to migrate from Bamboo to GitLab CI/CD\n  description: >-\n    With the fast approaching EOL of Atlassian Server products, including\n    Bamboo, this blog post explains how users of Bamboo can migrate to GitLab\n    CI/CD.\n  authors:\n    - Abubakar Siddiq Ango\n  heroImage: >-\n    https://res.cloudinary.com/about-gitlab-com/image/upload/v1749658924/Blog/Hero%20Images/securitylifecycle-light.png\n  date: '2023-10-26'\n  body: >\n    _Atlassian is ending support for all Server products in February 2024.\n    [Learn more about the benefits of migrating from Atlassian to GitLab\n    here](https://about.gitlab.com/move-to-gitlab-from-atlassian/)._\n\n\n    The clock is ticking towards the February 15, 2024, [end-of-life date\n    Atlassian has set for their Server\n    products](https://about.gitlab.com/blog/atlassian-server-ending-move-to-a-single-devsecops-platform/).\n    Users whose workflows rely on on-premises deployments of Atlassian Server\n    products are faced with the choice of upgrading to Atlassian’s Data Center\n    or Cloud products or finding alternatives. \n\n\n    One of the Atlassian products that is impacted is Bamboo, a CI/CD solution.\n    Whether you're simply looking for a new CI/CD tool or you're looking to\n    consolidate your entire toolchain, the Atlassian Server end of life is a\n    great opportunity to make the move to GitLab to take advantage of the\n    automation, scalability, and security of an end-to-end DevSecOps platform.\n\n\n    In this blog post, we'll cover the steps you can take to migrate your Bamboo\n    CI/CD setup to GitLab CI/CD.\n\n\n    ## How is GitLab CI/CD different from Bamboo?\n\n\n    ### Organization\n\n\n    Bamboo is structured around Projects and Plans. CI/CD jobs are grouped into\n    stages, which are defined in a Bamboo plan along with other configurations\n    that determine how jobs run. Bamboo projects are used to organize plans,\n    which are classified into Build and Deployment plans. \n\n\n    As the name implies, Build plans can be configured to pull code from\n    configured repositories and generate artifacts. These artifacts are picked\n    by jobs defined in Deployment plans and are deployed to environments\n    configured in Bamboo. Bamboo jobs are also composed of tasks, which can be a\n    script, a task to pull code from a repository, or a task specific to a\n    technology.\n\n\n    You also need to add code repositories to a Bamboo plan or a project, making\n    it available to all plans under it, and set triggers for how Bamboo detects\n    changes and runs builds.\n\n\n    GitLab is organized differently. Everything is in a single platform, with\n    your CI/CD configuration provided as part of your code in a `.gitlab-ci.yml`\n    file, from a group’s compliance pipeline configuration, or Auto DevOps when\n    enabled and the `.gitlab-ci.yml` file is not found in a project.\n\n\n    Gitlab CI/CD configurations are composed of jobs, grouped into stages. How\n    the jobs are triggered can be controlled by CI/CD `rules` and there is no\n    separate configuration for deployments. Deployment jobs can be defined in\n    the same CI/CD script in a `deploy` stage, with the [deployment\n    environment](https://docs.gitlab.com/ci/environments/) set.\n\n\n    ### Agents vs Runners\n\n\n    Bamboo uses\n    [Agents](https://confluence.atlassian.com/confeval/development-tools-evaluator-resources/bamboo/bamboo-remote-agents-and-local-agents)\n\n    to run builds and deployments. These can be local agents running on the\n    Bamboo server or\n\n    remote agents running external to the server. GitLab uses a similar concept\n    to agents,\n\n    called [GitLab Runner](https://docs.gitlab.com/runner/), which uses\n    [executors](https://docs.gitlab.com/runner/executors/)\n\n    to run builds. Examples of executors include SSH, Docker, and Kubernetes.\n    You can choose to\n\n    use GitLab [SaaS runners](https://docs.gitlab.com/ci/runners/) or deploy\n    your own [self-managed\n    runners](https://docs.gitlab.com/runner/install/).\n\n\n    ### Bamboo Specs vs .gitlab-ci.yml file\n\n\n    Bamboo is largely configured via the Bamboo UI but can also be configured as\n    code using Bamboo Specs. Bamboo Specs can be defined using Java and other\n    JVM languages or using YAML, with Java having more complete feature coverage\n    than YAML. Bamboo Specs can be defined and stored in spec repositories, then\n    linked to Bamboo projects.\n\n\n    The `.gitlab-ci.yml` file is central to the CI/CD workflow in GitLab. When\n    included in a project, the defined configurations are executed against the\n    project; otherwise, [Auto\n    DevOps](https://docs.gitlab.com/topics/autodevops/) automatically builds\n    and deploys your application, when enabled. Templates and CI/CD components\n    can also be added to `.gitlab-ci.yml` for complex use cases.\n\n\n    ## How GitLab steps up your workflow\n\n\n    In addition to building and deploying your application, GitLab provides a\n    suite of features that allows for building secure applications fast and\n    efficiently. These include:\n\n\n    - [Application\n    security](https://docs.gitlab.com/user/application_security/): GitLab\n    analyzes your application across the stages of the software development\n    lifecycle with security scans such as Static Application Security Testing\n    (SAST), Secret Detection, Infrastructure as Code (IaC) Scanning, Dependency\n    Scanning, License Scanning, Coverage-guided Fuzz Testing, Container\n    Scanning, API Security, Dynamic Application Security Testing (DAST), and\n    Operational Security Scanning.\n\n    - Compliance and security policies: Understanding the results of security\n    scans and putting policies in place is crucial to ensuring secure\n    applications. You can set up Scan Execution or Result policies to ensure\n    additional scans or approval requirements are added to comply with\n    regulatory or self-imposed requirements.\n\n    - [CI/CD catalog](https://docs.gitlab.com/ci/components/catalog/):\n    Parts of CI/CD configurations that are used across multiple projects can be\n    turned into\n    [components](https://docs.gitlab.com/ci/components/#components-repository)\n    stored in component repositories that are discoverable in the CI/CD catalog.\n\n    - Packages and registries: Custom or local replicas of popular packages can\n    be hosted with the [GitLab Package\n    Registry](https://docs.gitlab.com/user/packages/package_registry/).\n    You can also host container images with the [GitLab Container\n    Registry](https://docs.gitlab.com/user/packages/container_registry/)\n    and Terraform modules with the [GitLab Terraform Module\n    Registry](https://docs.gitlab.com/user/packages/terraform_module_registry/).\n    If you frequently use public images or packages, you can use the [Dependency\n    Proxy](https://docs.gitlab.com/user/packages/dependency_proxy/)\n    to maintain a local cache.\n\n\n    [Learn more about other ways to automate your entire workflow with GitLab\n    CI/CD](https://about.gitlab.com/solutions/continuous-integration/).\n\n\n    ## Convert Bamboo Specs to .gitlab-ci.yml script\n\n\n    For the purpose of this blog post, we will focus on [Bamboo YAML\n    Specs](https://docs.atlassian.com/bamboo-specs-docs/9.3.0/specs.html?yaml).\n    You can export your Bamboo Plans as YAML Spec — [learn more\n    here](https://confluence.atlassian.com/bamboo/exporting-existing-plan-configuration-to-bamboo-yaml-specs-1018270696.html).\n    Now, lets walk through converting your Bamboo YAML Specs into GitLab CI/CD\n    configuration.\n\n\n    ### Container image\n\n\n    First is defining the container image of the container your jobs will run\n    in. By default, Bamboo uses Agents, which depend on how the host machines\n    are configured. You can replicate the Agent’s environment into a container\n    image hosted in the [GitLab Container\n    Registry](https://docs.gitlab.com/user/packages/container_registry/).  \n\n\n    If you already run Bamboo jobs in a container image, it will look like this\n    in your spec:\n\n\n    ```yaml\n\n    ---\n\n    version: 2\n\n    # ...\n\n    docker: ubuntu\n\n    ```\n\n\n    This might be defined at the plan or job level. You can define it in GitLab\n    as follows:\n\n\n    ```yaml\n\n    image: ubuntu\n\n    ```\n\n\n    [Learn more about running CI/CD jobs in containers\n    here](https://docs.gitlab.com/ci/docker/using_docker_images/). If\n    your use case does not include containers, you can explore [other\n    executors](https://docs.gitlab.com/runner/executors/).\n\n\n    ### Stages\n\n\n    In Bamboo, stages and their list of jobs are defined first, before the job\n    definitions:\n\n\n    ```yaml\n\n    version: 2\n\n    stages:\n      - First Stage:\n          jobs:\n            - Job 1A \n            - Job 1B\n      - Second Stage:\n          jobs:\n            - Job 2A \n            - Job 2B\n\n    Job 1A:\n      tasks:\n        - clean\n        - script\n            - touch file1A.txt\n\n    Job 1B:\n      tasks:\n        - clean\n        - script\n            - touch file1B.txt\n\n    Job 2A:\n      tasks:\n        - clean\n        - script\n            - touch file2A.txt\n\n    Job 2B:\n      tasks:\n        - clean\n        - script\n            - touch file2B.txt\n\n    ```\n\n\n    In GitLab, you list your stages in the order in which you want their jobs to\n    run:\n\n\n    ```yaml\n\n    stages:\n      - build\n      - test\n      - deploy\n\n    job1:\n      stage: build\n      script:\n        - echo \"This job compiles code.\"\n\n    job2:\n      stage: test\n      script:\n        - echo \"This job tests the compiled code. It runs when the build stage completes.\"\n\n    job3:\n      script:\n        - echo \"This job also runs in the test stage\".\n\n    job4:\n      stage: deploy\n      script:\n        - echo \"This job deploys the code. It runs when the test stage completes.\"\n      environment: production\n\n    ```\n\n\n    All the jobs in a stage run in parallel and when they succeed, execution\n    proceeds to the next stage. This only changes in complex pipelines where a\n    job depends on another using\n    [`needs`](https://docs.gitlab.com/ci/yaml/#needs).\n\n\n    ### Variables\n\n\n    Bamboo has System, Global, Project, Plan, and Build-specific variables,\n    which can be accessed using the format `${system.variableName}` for system\n    variables and `${bamboo.variableName}` for others. Periods (.) are replaced\n    by underscores (_) when variables are accessed in scripts.\n\n\n    ```yaml\n\n    version: 2\n\n    # ...\n\n    variables:\n      username: admin\n      releaseType: milestone\n\n    Default job:\n      tasks:\n        - script: echo 'Release Type is $bamboo_releaseType'\n\n    ```\n\n\n    In GitLab, variables can be defined at group, project, CI Script, and job\n    levels. In GitLab self-managed and GitLab Dedicated, administrators can\n    define variables at the instance level. GitLab allows protecting, masking,\n    and expanding variables. Protected variables are only accessible for\n    pipelines running against the default or protected branches. [Learn more\n    about CI/CD variables](https://docs.gitlab.com/ci/variables/)\n    and [where you can use\n    them](https://docs.gitlab.com/ci/variables/where_variables_can_be_used/).\n\n\n    Here is an example:\n\n\n    ```yaml\n\n    variables:\n      GLOBAL_VAR: \"A global variable\"\n\n    job1:\n      variables:\n        JOB_VAR: \"A job variable\"\n      script:\n        - echo \"Variables are '$GLOBAL_VAR' and '$JOB_VAR'\"\n\n    job2:\n      script:\n        - echo \"Variables are '$GLOBAL_VAR' and '$JOB_VAR'\"\n\n    ```\n\n\n    ### Build Jobs\n\n\n    Bamboo Build Jobs are composed of tasks, each of which is a small unit of\n    work that can be anything from checking out source code to injecting\n    variables or running a script.\n\n\n    ```yaml\n\n    version: 2\n\n    stages:\n      - Run Tests:\n          jobs:\n            - Test Ruby \n\n    Test Ruby :\n      key: TEST\n      tasks:\n      - checkout:\n          force-clean-build: false\n          description: Checkout Default Repository\n      - script:\n          interpreter: SHELL\n          scripts:\n          - |-\n            ruby -v  # Print out ruby version for debugging\n            bundle config set --local deployment true  \n            bundle install -j $(nproc)\n            rubocop\n            rspec spec\n          description: run bundler & rspec\n\n    ```\n\n\n    In this example, the plan has two tasks, checkout and script. The checkout\n    tasks pull an updated version of the code repository, which is made\n    available for the script task to execute its commands against. \n\n\n    [Jobs in GitLab](https://docs.gitlab.com/ci/jobs/) are composed of script\n    commands:\n\n\n    ```text\n\n    image: ruby:latest\n\n\n    stages:\n      - test\n\n    rspec:\n      stage: test\n      script:\n        - ruby -v\n        - bundle config set --local deployment true \n        - bundle install -j $(nproc)\n        - rubocop\n        - rspec spec\n\n    ```\n\n\n    In the example above, the stage the job belongs to is specified with the\n    `stage` keyword and the commands to be executed by the GitLab runner for the\n    job are listed under `script`.\n\n\n    In Bamboo, you can use\n    [executables](https://confluence.atlassian.com/bamboo/defining-a-new-executable-capability-289277164.html),\n    such as Ant, Maven, or PHPUnit, in a task to build your application. In\n    GitLab, you can package the binaries you need in a custom container image\n    and use it as your CI/CD image.\n\n\n    ### Deployment jobs\n\n\n    In Bamboo, Deployment projects organize software releases or environments\n    applications are deployed to. A deployment plan can have a release\n    definition:\n\n\n    ```yaml\n\n    ---\n\n    version: 2\n\n\n    deployment:\n      name: Release Software\n      source-plan: BUILD-APP\n\n    release-naming: release-1.1\n\n    ```\n\n\n    For releases, you specify the plan it should get the generated artifacts\n    from. And for deployment for environments:\n\n\n    ```yaml\n\n    ---\n\n    version: 2\n\n    # ...\n\n    environments:\n      - Test\n      - QA\n      - Prod\n\n    Test:\n      tasks:\n        - clean\n        - artifact-download:\n            destination: /workdir\n\n    ```\n\n\n    In GitLab CI/CD, you can create a [deployment\n    job](https://docs.gitlab.com/ci/jobs/#deployment-jobs)\n\n    that deploys to an\n    [environment](https://docs.gitlab.com/ci/environments/) or\n    create a [release](https://docs.gitlab.com/user/project/releases/).\n\n    For deploying to an environment, you use the\n    [`environment`](https://docs.gitlab.com/ci/yaml/#environment) keyword:\n\n\n    ```yaml\n\n    deploy-to-production:\n      stage: deploy\n      script:\n        - # Run Deployment script\n        - ./.ci/deploy_prod.sh\n      environment:\n        name: production\n\n    ```\n\n\n    If you are creating a release instead, you use the\n    [`release`](https://docs.gitlab.com/ci/yaml/#release)\n\n    keyword along with the\n    [release-cli](https://gitlab.com/gitlab-org/release-cli/-/tree/master/docs)\n\n    tool to create releases for [Git\n    tags](https://docs.gitlab.com/user/project/repository/tags/).\n\n    The `release` section is executed after the `script` section, which must\n    exist.\n\n    If you don’t have any script commands to run, you can put a placeholder\n    command;\n\n    for example, `echo` a message.\n\n\n    ```yaml\n\n    release_job:\n      stage: release\n      image: registry.gitlab.com/gitlab-org/release-cli:latest\n      rules:\n        - if: $CI_COMMIT_TAG                  # Run this job when a tag is created manually\n      script:\n        - echo \"Building release version\"\n      release:\n        tag_name: $CI_COMMIT_TAG\n        name: 'Release $CI_COMMIT_TAG'\n        description: 'Release created using the release-cli.'\n\n    ```\n\n\n    ### Rules and workflows\n\n\n    In Bamboo, triggers can be used to control how Jobs are executed. Triggers\n    can be a periodic poll of the repository for changes or a webhook that\n    notifies Bamboo of changes to the repository. Trigger conditions can be\n    enabled in the Bamboo web UI to make sure the build only runs if other plans\n    are passing.\n\n\n    Example of a trigger:\n\n\n    ```yaml\n\n    ---\n\n    version: 2\n\n    triggers:\n      - polling: 130\n      - cron: 0 * * * ? *\n\n    ```\n\n\n    In GitLab, [CI/CD pipelines](https://docs.gitlab.com/ci/pipelines/) can\n    be triggered by a commit/push, a merge, manually, on schedule, or with\n    [pipeline\n    subscriptions](https://docs.gitlab.com/ci/pipelines/#trigger-a-pipeline-when-an-upstream-project-is-rebuilt).\n    Jobs in a pipeline can further be controlled using `rules` or `workflow`.\n    Learn more about [Job\n    Control](https://docs.gitlab.com/ci/jobs/job_control/) and [pipeline\n    workflows](https://docs.gitlab.com/ci/yaml/workflow/#) in GitLab\n    CI/CD. \n\n\n    Here's an example using `rules` in GitLab CI/CD:\n\n\n    ```yaml\n\n    workflow:\n      rules:\n        - changes:\n          - .gitlab/**/**.md\n          when: never\n\n    ```\n     In this example, pipelines are never executed when `.md` files changed in the `.gitlab` folder.\n\n    #### Artifacts\n\n\n    You can define Job artifacts using the `artifacts` keyword in both GitLab\n    and Bamboo.\n\n\n    In Bamboo, artifacts can be defined as follows:\n\n\n    ```yaml\n\n    ---\n\n    version: 2\n\n    # ...\n      artifacts:\n        -\n          name: Test Reports\n          location: target/reports\n          pattern: '*.xml'\n          required: false\n          shared: false\n        -\n          name: Special Reports\n          location: target/reports\n          pattern: 'special/*.xml'\n          shared: true\n\n    ```\n\n\n    In the Bamboo Spec above, artifacts are defined with a name, location,\n    pattern, and optionally\n\n    the ability to share the artifacts with other jobs or plans. You can go\n    further to define jobs that\n\n    can subscribe to the artifact.\n\n\n    `artifact-subscriptions` is used to access artifacts from another job in the\n    same plan:\n\n\n    ```yaml\n\n    Test app:\n      artifact-subscriptions:\n        -\n          artifact: Test Reports\n          destination: deploy\n\n    ```\n\n\n    `artifact-download` is used to access artifacts from jobs in a different\n    plan.\n\n\n    ```yaml\n\n    ---\n\n    version: 2\n\n    # ...\n      tasks:\n        - artifact-download: \n            source-plan: PROJECTKEY-PLANKEY\n\n    ```\n\n\n    You need to provide the key of the plan you are downloading artifacts from\n    in the `source-plan` keyword.\n\n\n    In GitLab, all artifacts from completed jobs in the previous stages are\n    downloaded by default.\n\n    Here is an example of an artifact definition in GitLab:\n\n\n    ```yaml\n\n    pdf:\n      script: xelatex mycv.tex\n      artifacts:\n        name: \"pdf-files\"\n        public: false\n        untracked: true\n        paths:\n          - pdfs/\n        exclude:\n          - pdfs/*.tex\n\n    ```\n\n\n    In the CI/CD script above:\n\n\n    - The name of the artifact is specified laterally. You can choose to make it\n    dynamic by using a CI/CD variable.\n\n    - The `public` keyword is used to set whether the artifact should be\n    publicly available. This is not enabled by default\n      on self-managed GitLab instances. An administrator can enable it with the [feature flag](https://docs.gitlab.com/administration/feature_flags/)\n      named `non_public_artifacts`.\n    - You can set the `untracked` to include or exclude Git untracked files\n    along with those specified using `paths`.\n\n\n    Read more about GitLab CI/CD [job\n    artifacts](https://docs.gitlab.com/ci/jobs/job_artifacts/).\n\n\n    ## How to plan your migration\n\n\n    Planning a migration to Gitlab CI/CD from Bamboo doesn't start with\n    converting your Bamboo plan to GitLab CI/CD scripts. It starts with aligning\n    with your leadership and stakeholders and clearly communicating the vision\n    of the migration. [Check out our documentation to learn more about managing\n    organizational\n    changes](https://docs.gitlab.com/ci/migration/plan_a_migration/).\n    Once you have the necessary buy-in, you can proceed with the following\n    steps:\n\n\n    - [Import your projects](https://docs.gitlab.com/user/project/import/) to\n    GitLab.\n\n    - Identify the necessary binaries and build tools needed to build your\n    application, along with their dependencies.\n\n    - Define the flow of your pipeline, which jobs depend on each other, and the\n    necessary triggers.\n\n    - Learn more about [key GitLab CI/CD\n    features](https://docs.gitlab.com/ci/).\n\n    - Identify the credentials and variables needed in your pipeline and define\n    them in the variable section of your project's CI/CD settings or using a\n    secret manager.\n\n    - Follow [this\n    tutorial](https://docs.gitlab.com/ci/quick_start/) to create\n    your first GitLab pipeline; you can also explore more [complex\n    pipelines](https://docs.gitlab.com/ci/quick_start/tutorial/).\n\n    - Iterate and test your GitLab CI/CD pipelines and review [.gitlab-ci.yml\n    keyword reference](https://docs.gitlab.com/ci/yaml/).\n\n\n    Ready to make the move? 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software development the easy way using GitLab","Learn how University of Washington lecturer Stephen G. Dame uses GitLab for Education to manage student assignments, distribute course materials, and provide inline code feedback at scale.\n",[719],"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/).",[621,724],"open source",{"featured":14,"template":15,"slug":726},"teaching-software-development-the-easy-way-using-gitlab",{"content":728,"config":740},{"description":729,"authors":730,"heroImage":732,"date":733,"title":734,"body":735,"category":11,"tags":736},"AI-generated code is 34% of development work. Discover how to balance productivity gains with quality, reliability, and security.",[731],"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.",[737,738,739],"AI/ML","DevOps platform","security",{"featured":27,"template":15,"slug":741},"ai-is-reshaping-devsecops-attend-gitlab-transcend-to-see-whats-next",{"content":743,"config":754},{"title":744,"description":745,"authors":746,"heroImage":748,"date":749,"body":750,"category":11,"tags":751},"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.",[747],"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.",[572,22,752,753],"product","features",{"featured":27,"template":15,"slug":755},"atlassian-ending-data-center-as-gitlab-maintains-deployment-choice",{"promotions":757},[758,772,783,794],{"id":759,"categories":760,"header":762,"text":763,"button":764,"image":769},"ai-modernization",[761],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":765,"config":766},"Get your AI maturity score",{"href":767,"dataGaName":768,"dataGaLocation":243},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":770},{"src":771},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":773,"categories":774,"header":775,"text":763,"button":776,"image":780},"devops-modernization",[752,11],"Are you just managing tools or shipping innovation?",{"text":777,"config":778},"Get your DevOps maturity score",{"href":779,"dataGaName":768,"dataGaLocation":243},"/assessments/devops-modernization-assessment/",{"config":781},{"src":782},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":784,"categories":785,"header":786,"text":763,"button":787,"image":791},"security-modernization",[739],"Are you trading speed for security?",{"text":788,"config":789},"Get your security maturity score",{"href":790,"dataGaName":768,"dataGaLocation":243},"/assessments/security-modernization-assessment/",{"config":792},{"src":793},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"id":795,"paths":796,"header":799,"text":800,"button":801,"image":806},"github-azure-migration",[797,798],"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":802,"config":803},"See how GitLab compares to GitHub",{"href":804,"dataGaName":805,"dataGaLocation":243},"/compare/gitlab-vs-github/github-azure-migration/","github azure migration",{"config":807},{"src":782},{"header":809,"blurb":810,"button":811,"secondaryButton":816},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":812,"config":813},"Get your free trial",{"href":814,"dataGaName":50,"dataGaLocation":815},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":506,"config":817},{"href":54,"dataGaName":55,"dataGaLocation":815},1777493606852]