The Most Comprehensive Guide to Migrating from AWS CodeCommit to GitLab

Recently AWS announced significant changes to its CodeCommit service, discontinuing new customer access and focusing solely on security and performance updates for existing users. This marks the end of AWS CodeCommit as a fully supported service, leaving many development teams searching for alternative Git platforms to manage their repositories and DevOps workflows.

In this blog, we will guide you through the process of migrating from AWS CodeCommit to GitLab, a robust DevSecOps platform that offers seamless integration with AWS services and an enhanced CI/CD experience. Whether you're looking to future-proof your development processes or take advantage of GitLab’s advanced features, this guide will help you navigate the transition smoothly and efficiently.

We’ll also explore AWS’s official recommendations and the key steps you need to follow for a successful migration, ensuring minimal disruption to your ongoing projects and workflows.

Why Choose GitLab for Migration?

When migrating from AWS CodeCommit, choosing the right platform is crucial for maintaining productivity and enhancing your development workflows. GitLab stands out as a leading DevSecOps platform, offering a comprehensive suite of tools for CI/CD, repository management, and security, all in one place.

1. DevSecOps Integration: One of GitLab’s most significant advantages is its built-in DevSecOps capabilities. Unlike other Git platforms, GitLab integrates development, security, and operations into a single, cohesive platform. This allows development teams to manage code, automate CI/CD pipelines, and monitor security vulnerabilities within the same interface. With GitLab, you can ensure that security is embedded into every stage of the software development lifecycle.

2. Superior CI/CD Pipeline Management: GitLab excels in CI/CD automation, providing extensive support for continuous integration and continuous delivery. Teams can easily define pipelines using a .gitlab-ci.yml file, enabling automatic testing, building, and deploying of code changes. This out-of-the-box functionality eliminates the need for third-party CI/CD tools and simplifies the automation process. In comparison, platforms like GitHub and Bitbucket may require external integrations for equivalent capabilities, adding complexity to the workflow.

3. Comprehensive Repository Management: GitLab’s repository management goes beyond simple version control. With features like merge request workflows, code reviews, and built-in issue tracking, it enables teams to collaborate more effectively on code changes. GitLab’s detailed permission settings ensure that only authorized team members can access sensitive repositories, providing better control over your projects. While GitHub and Bitbucket offer similar features, GitLab’s integrated approach and streamlined interface make repository management more intuitive and efficient.

4. Comparison with Other Platforms: While GitHub and Bitbucket are popular Git hosting services, they often require additional third-party tools to achieve the same level of functionality that GitLab provides natively. GitHub, for instance, relies heavily on integrations like GitHub Actions for CI/CD, and Bitbucket requires a combination of Bamboo and Pipelines. In contrast, GitLab offers a complete DevSecOps platform without the need for these add-ons, making it a more scalable and cost-effective solution for teams looking to streamline their workflows.

Preparing for the Migration Process

Migrating from AWS CodeCommit to GitLab requires careful planning to ensure a smooth transition and minimal disruption to your development workflows. Before beginning the migration, there are several critical steps to follow to prepare your teams and systems effectively. Here’s a guide to help you get ready for the move.

1. Review of Current CodeCommit Setup: Before starting the migration process, conduct a thorough review of your existing AWS CodeCommit environment. Identify all active repositories, branches, and associated workflows to ensure no critical elements are overlooked during migration. Pay attention to:

• Repository structure: Ensure you have a clear understanding of how your repositories are organized.

• Branch protection rules and access permissions: Document these so they can be recreated in GitLab.

• Ongoing integrations: Note any CI/CD pipelines, third-party integrations, or automation that may be impacted during the transition.

  
  

2. Backup of Critical Data: Data integrity is paramount during any migration. Create comprehensive backups of all repositories, including commits, branches, tags, and metadata, before starting the process. Ensure that:

• All critical data is backed up locally or to a secure cloud location.

• Backups include not only the repositories themselves but also related metadata like issue tracking, merge request histories, and CI/CD pipeline configurations.

• You test your backup to confirm that everything can be restored in the event of any issues during migration.

3. Communication with Development Teams: Effective communication with your development teams is crucial to ensure a smooth transition. Inform all stakeholders of the upcoming migration, including key dates, potential impacts, and expected downtime. Consider:

• Sharing a detailed migration timeline: Provide an overview of when each repository will be migrated and how long the process will take.

• Offering training sessions: If your teams are new to GitLab, consider hosting workshops or sharing training materials to familiarize them with the platform’s features and workflows.

• Assigning points of contact: Designate team members responsible for addressing migration-related issues and answering questions during the transition.

  
  

By thoroughly preparing for your migration, you can minimize risks and ensure a seamless transition from AWS CodeCommit to GitLab. Following these best practices will help maintain continuity in your development processes and prevent disruptions that could affect your team’s productivity.

Recommended Read: Google and GitLab Strengthen Partnership with CI/CD and Cloud Deploy Integration

Step-by-Step Guide to Migrating from AWS CodeCommit to GitLab

Migrating your repositories from AWS CodeCommit to GitLab doesn’t have to be complicated. In this step-by-step guide, we’ll walk you through the key stages of setting up GitLab, importing your repositories, and validating integrations to ensure a smooth transition.

Setting up a GitLab Account and Namespace

Before starting the migration, it’s essential to set up your GitLab account and configure your organizational structure with namespaces and access controls.

Step 1: Create a GitLab Account

• Visit about.gitLab.com and create an account if you don’t have one already.

• If your organization already has a GitLab account, check whether you’re using single sign-on (SSO) for easy access.

• If necessary, log in using your company’s credentials.

  
  

Step 2: Set Up a Company Namespace

• After logging in, create a namespace for your organization. This namespace serves as the root directory for all your repositories.

  • Go to the Groups section and click “New Group.”

  • Choose a name for your group that reflects your company’s identity (e.g., “YourCompanyName”).

• Ensure that your group permissions align with your organization’s security protocols by setting access levels for different team members (e.g., Maintainer, Developer, Reporter).

Step 3: Configure Access Control

• Navigate to your new group and click on Members to start adding team members.

• Assign appropriate roles based on the level of access each member should have, from Developer to Maintainer.

• Set up two-factor authentication (2FA) and review other security settings to secure your GitLab environment.

Importing Repositories from AWS CodeCommit

Once your GitLab account is set up, it’s time to begin the migration. One efficient method is to use GitLab’s pull mirroring feature to sync your CodeCommit repositories while keeping your current setup intact during the transition.

Step 1: Start the Import Process

• Navigate to your group on GitLab and click the New Project button.

• Select Import Project from the available options, then choose Repository by URL.

  
  

Step 2: Set Up the Mirror Repository

• Copy the clone URL of your AWS CodeCommit repository.

  • In the AWS CodeCommit console, find the repository you wish to migrate and select the HTTPS URL.

• In GitLab, paste the URL into the Git repository URL field.

• Under the URL field, check the Mirror repository box. This will enable GitLab to periodically pull updates from your AWS-hosted repository.

  
  

Step 3: Authenticate with AWS

• You’ll need AWS Git credentials to set up the authentication in GitLab.

  • In the AWS IAM console, generate Git credentials for the user linked to the repository.

  • Provide these credentials in GitLab to complete the authentication process.

• GitLab will now begin syncing your CodeCommit repository, automatically pulling changes every five minutes.

Source: GitLab Blog

Step 4: Verify Repository Sync

• After setting up mirroring, monitor the progress to ensure the repository is syncing correctly.

• Check the commit history in GitLab to confirm that all changes from AWS CodeCommit are being reflected.

  
  

Validating and Testing GitLab Integrations

After migrating your repositories, it’s important to validate the new GitLab environment by testing integrations such as CI/CD pipelines, issue tracking, and code review processes. This ensures that all essential workflows remain functional.

Step 1: Set Up and Test CI/CD Pipelines

• In your repository, create a .gitlab-ci.yml file to replicate your existing CI/CD workflows.

• Define the pipeline stages (e.g., build, test, deploy) and add the necessary configurations.

• Trigger a pipeline run by pushing a new commit to ensure it executes correctly.

  
  

Step 2: Validate Issue Tracking and Merge Requests

• If you use issue tracking, import project issues from CodeCommit or AWS's issue management tool.

• Test the issue tracking system by creating, assigning, and closing test issues within GitLab.

• Set up and test the merge request process, ensuring that code reviews and approvals function as expected.

  
  

Step 3: Confirm Third-Party Integrations

• Ensure any integrations with tools like AWS CodeBuild, Jira, or Slack are working properly post-migration.

• Test notifications, webhooks, and automation features tied to your development pipeline.

  
  

Gradual vs. Direct Migration: Which to Choose?

When migrating from AWS CodeCommit to GitLab, choosing the right migration strategy is essential to ensure a smooth transition with minimal disruption to your development workflows. Two common approaches are parallel migration (also called gradual migration) and direct migration (or cutover migration). Each method has its benefits and drawbacks, and understanding when to apply each can help you make the best decision for your organization.

Parallel Migration (Gradual Migration)

In parallel migration, you continue using your current AWS CodeCommit setup while simultaneously syncing your repositories to GitLab. This allows your team to test and adjust to GitLab in a staged process before fully transitioning.

Benefits:

• Minimizes Risk: Since your current AWS CodeCommit system remains operational during the migration, there’s less risk of disrupting ongoing projects. Your team can continue using the existing infrastructure while GitLab is being tested.

• Flexibility: You can gradually move projects to GitLab over time, giving developers a chance to familiarize themselves with the new system at their own pace.

• Testing and Validation: By running both environments in parallel, you can thoroughly test GitLab’s CI/CD pipelines, issue tracking, and other integrations before committing fully.

• Rollback Option: If issues arise during testing in GitLab, you can easily roll back to your CodeCommit system without impacting development.

  
  

Drawbacks:

• Increased Complexity: Managing two systems simultaneously can add complexity, particularly in keeping repositories, pipelines, and integrations in sync between CodeCommit and GitLab.

• Longer Transition: A gradual migration can take longer to complete, particularly if you have many repositories or large teams.

• Resource-Intensive: Running both environments in parallel might require more resources, both in terms of infrastructure and team management.

  
  

When to Choose Parallel Migration:

• When working on critical projects where downtime or disruption is unacceptable.

• When you want to test the new environment thoroughly before fully committing.

• When your team needs time to adjust to new tools and processes.

  
  

Direct Migration (Cutover Migration)

In direct migration, you stop using AWS CodeCommit and immediately transition to GitLab in one go. After the migration, all development work is done on GitLab, and the AWS CodeCommit repositories are set to read-only or decommissioned.

Benefits:

• Faster Transition: Direct migration is quicker since there is no need to maintain two systems. Once you’ve migrated, you can begin using GitLab immediately.

• Simpler Process: Since you’re only dealing with one system post-migration, there’s less complexity in syncing and managing repositories between platforms.

• Immediate Adoption: Your team will start working in GitLab right away, accelerating the learning curve and adoption of GitLab features like CI/CD, issue tracking, and merge requests.

  
  

Drawbacks:

• Higher Risk: With a direct migration, there’s no fallback system if issues arise in GitLab. Any problems with pipelines, integrations, or repository setup can lead to delays or downtime.

• No Parallel Testing: Since the switch is immediate, there’s no opportunity to test GitLab’s workflows in parallel with CodeCommit. This increases the chances of encountering unforeseen issues after the cutover.

• Potential Disruption: Teams must be fully prepared and trained in GitLab before the migration. If they’re unfamiliar with the platform, the transition could lead to confusion and slowdowns in development.

  
  

When to Choose Direct Migration:

• When your team is small or highly familiar with GitLab, and you expect minimal issues during the transition.

• When you need to complete the migration quickly and are prepared to handle any post-migration adjustments.

• When your project timelines allow for some downtime or troubleshooting immediately after migration.

Which Method Is Best for You?

Choosing between parallel and direct migration depends on your specific circumstances, project criticality, and team readiness.

• Choose Parallel Migration if minimizing risk and maintaining operational stability is the priority. It’s best suited for teams working on critical projects where even small disruptions can have significant consequences. The extra time spent on testing and validation ensures a smoother transition, though it may prolong the migration process.

• Choose Direct Migration if you need a fast transition and are confident in your team’s ability to adapt quickly. Direct migration is ideal for teams with fewer repositories or when immediate adoption of GitLab is necessary to align with upcoming project timelines.

  
  

By weighing the benefits and drawbacks of each method, you can choose the migration strategy that best fits your organization’s needs.

Integrating GitLab with AWS CodeBuild

One of the key advantages of migrating to GitLab is the ability to integrate it seamlessly with AWS CodeBuild, enabling automated CI pipelines. AWS CodeBuild is a fully managed build service that compiles your source code, runs tests, and produces software packages ready for deployment. By linking GitLab repositories with AWS CodeBuild, you can automate and streamline your CI workflows.

Here’s a step-by-step guide to help you set up the integration and key considerations to ensure a successful configuration.

Step 1: Set Up AWS CodeStar Connections

AWS CodeStar Connections is required to establish a secure connection between GitLab and AWS services such as CodeBuild.

• Log in to the AWS Management Console and navigate to the CodeBuild service.

• In the left-hand panel, select Settings > Connections.

• Click the Create connection button.

• Choose GitLab as the source provider.

• Enter a connection name and click Connect to GitLab.

• You will be redirected to the GitLab authorization page. Approve the necessary permissions to complete the setup.

  
  

Once the connection is established, AWS will securely connect your GitLab repositories to services like CodeBuild and CodePipeline.

Source: GitLab Blog

Step 2: Create an AWS CodeBuild Project

Now that the connection is in place, you can set up a CodeBuild project that triggers builds based on changes in your GitLab repository.

• Step 1: In the AWS CodeBuild console, click Create build project.

• Step 2: Provide a project name and description that will help identify the build project.

• Step 3: Under Source, choose GitLab as the source provider.

  • Select the connection you created in the previous step.

  • Specify the GitLab repository URL and branch to monitor for changes.

• Step 4: Under Environment, configure the build environment:

  • Choose a managed image or use a custom Docker image based on your project’s needs.

  • Specify the runtime and build specifications, including the operating system and programming language.

• Step 5: Set the Buildspec file path:

  • CodeBuild requires a buildspec file (buildspec.yml) to define your build process. This file should reside in the root of your GitLab repository.

  • Define build commands, phases, and any additional environment variables necessary for the build process.

• Step 6: Under Build triggers, enable the option to trigger a build every time code is pushed to the GitLab repository.

  
  

Step 3: Set Up the buildspec.yml File

The buildspec.yml file is essential for defining the build stages, including install, pre-build, build, and post-build phases. 

Step 4: Validate and Test the CI Pipeline

Once the CodeBuild project and the buildspec.yml file are configured, it’s time to test the integration.

• Push a code change to the specified GitLab repository branch.

• Monitor the CodeBuild dashboard in AWS to ensure that the build process is triggered automatically.

• Review the build logs to verify that each stage (install, build, test) runs correctly.

• If the build fails, debug the errors using the logs and adjust the buildspec.yml file as necessary.

  
  

Key Considerations and Best Practices for Configuration

1. Security and Access Control:

   • Ensure that your GitLab repository permissions and AWS IAM roles are properly configured to control who has access to trigger builds and modify the CI pipeline.

   • Use environment variables to manage sensitive data, such as API keys or credentials, without hard-coding them in the buildspec.yml file.

2. Build Artifacts Management:

   • Use AWS S3 to store build artifacts generated by CodeBuild. This ensures that all built packages or deployment files are accessible and stored in a centralized, secure location.

3. Parallel Builds:

   • Configure your build environment to allow for parallel builds if you have multiple branches or teams working on the same repository. AWS CodeBuild can be set up to handle concurrent build jobs, increasing efficiency.

4. Resource Optimization:

   • Consider using CodeBuild’s caching features to optimize build times by caching dependencies between builds. This is particularly useful for large projects that rely on third-party libraries.

5. Cost Management:

   • Monitor the cost of AWS CodeBuild by setting up budget alerts. CodeBuild pricing is based on the compute time used during each build, so optimizing your builds and reducing build times can help control costs.

     
     

Conclusion

Migrating from AWS CodeCommit to GitLab is an opportunity to enhance your DevOps processes, streamline workflows, and leverage powerful integrations with AWS services like CodeBuild, CodeDeploy, and Glue. By carefully planning your migration strategy—whether gradual or direct—you can minimize risks and ensure a seamless transition. Post-migration, optimizing your CI/CD pipelines and adopting GitLab’s advanced features for issue tracking, code reviews, and automation will help your team work more efficiently and collaboratively. With the right approach, GitLab can become a central hub for your development, security, and operations, ensuring that your projects remain agile, secure, and scalable.

How VivaOps Can Help

VivaOps specializes in simplifying the transition to modern DevOps platforms like GitLab, offering expert guidance and hands-on support throughout the migration process. Whether you need help setting up integrations with AWS services, optimizing CI/CD pipelines, or training your team on best practices, VivaOps ensures that your migration is smooth, efficient, and tailored to your specific needs. With VivaOps, you can focus on innovation while we handle the complexities of DevOps automation and integration. Let us help you unlock the full potential of GitLab and AWS.