Announcing General Availability of GitLab Duo with Amazon Q
April 18, 2025Announcing General Availability of GitLab Duo with Amazon Q
Today, we’re excited to announce the general availability of GitLab Duo with Amazon Q. This new offering is an integrated product, bringing together GitLab’s DevSecOps platform with Amazon Q’s generative AI capabilities. Gitlab Duo with Amazon Q embeds Amazon Q agent capabilities directly in GitLab’s DevSecOps platform to accelerate complex, multi-step tasks across the entire software development lifecycle.
In today’s fast-paced software development environment, developers are constantly looking for ways to improve productivity while maintaining best practices for code quality, security, and deployment. The integration of GitLab Duo with Amazon Q addresses these needs by combining GitLab’s comprehensive DevSecOps platform with Amazon Q’s intelligent coding assistance.
This integration enables developers to leverage AI throughout their entire workflow—from idea conception to deployment—all within the familiar GitLab environment they already use. For new and existing Amazon Q Developer users, this integration also leverages the same Q Developer agents available in the IDE, providing a consistent experience across different interfaces.
Key Benefits and Features
The GitLab Duo with Amazon Q integration delivers significant value to development teams by creating a more efficient, secure, and collaborative workflow.
This integration eliminates the need to switch between different tools and environments, as developers can access powerful AI assistance directly within GitLab. GitLab helps automate building, testing, packaging, and deployment of secure code, streamlining the entire development lifecycle. What makes this particularly powerful is how the AI agents utilize the context throughout a GitLab project to keep the SLDC “loop” going. So whether you are troubleshooting a failed pipeline, investigating a vulnerability, or writing a new feature, Amazon Q agents can leverage the appropriate context to assist you with the task at hand.
Security and compliance are foundational elements of this integration. End-to-end security controls are built directly into the platform. The Amazon Q agents come with appropriate guardrails to help customers meet compliance without affecting development velocity, all while leveraging AWS’s cloud infrastructure to scale your AI-enhanced development workflows with confidence. You can ask Amazon Q agents to help remediate a finding in the project’s vulnerability reports or help troubleshoot a failed pipeline.
Throughout your development workflow, you’ll find collaborative AI agents ready to assist with various tasks. Whether you need to upgrade Java code from version 8 or 11 to 17, get AI-powered code review suggestions, automatically generate comprehensive test cases, or transform ideas into complete merge requests—Amazon Q is there to help at every step. These intelligent agents work alongside your team, enhancing productivity.
Use Cases and Examples
To demonstrate how GitLab and Amazon Q complement each other to accelerate development productivity and help organizations with application security, I’ll be using a Java application enjoyed by puzzle enthusiasts.
Idea to Merge Request
Whether you are looking to scale your developer teams or streamline the processes between feature requests and production, GitLab Duo with Amazon Q is now integrated into GitLab’s platform, so you can begin development simply by assigning a GitLab issue to Amazon Q Developer agents.
I start by creating a task in my GitLab project. I want to create a new feature to support multiple languages in the Q words game.
From here I assign the task directly to the Amazon Q agent by using GitLab’s quick action /q dev in the issue’s comment section.
The agent will automatically open up a merge request for me to review with suggested code changes. Here you can see changes the agent made across 11 files, accounting for front-end, API, and styling changes. In the past I would have opened my IDE, cloned the project, and coded these changes myself. Using GitLab Duo with Amazon Q, I just review and test the new code before I am ready to deploy.
Code Reviews
Code reviews play a critical function during the development life-cycle. They act as a quality gate to help maintain high quality security and coding standards. While important, code reviews add latency to software delivery, especially when reviewers are not available or when changes are complex.
The Amazon Q agent for Code Reviews in GitLab helps teams move faster through their code review. Using the quick action /q review in a merge request comment field sends the merge request to Amazon Q, where it will identify security and quality risks associated with code changes in the merge request.
I start by opening an open merge request. In this example, another developer had the task to add authentication to the Q words application.
I then invoke the agent with the /q review quick action.
The review is returned as inline code suggestions to the merge request. Here you can see an example of a finding from the review agent. Comments include a description of the findings as well as guidance and links to help improve the code.
I next use the Gitlab Duo with Amazon Q chat agent in the web interface to ask for a summary of the change and ask it to highlight any critical issues. GitLab Duo chat allows me to ask questions about the current resource in the URL. In this example it is the merge request, but it could also be a GitLab issue I want to explain or a summary of a code file in a repository.
Test Generation
Next, I ask GitLab Duo with Amazon Q to generate tests using the /q test quick action. Adding this action to the comment field will generate recommended tests when the MR lacks sufficient tests.
The summary I receive from GitLab Duo with Amazon Q helps me understand the scope of the changes and focuses my attention to the more important aspects of the change. Along with the tests that Q Developer agents recommended, I am able to approve the merge request in less time.
Java Transformation
Upgrading Java applications from older versions to Java 17 can be time-consuming and error-prone. With GitLab Duo and Amazon Q, I can leverage the transform agent to help me automate the migration from the current Java 8 code to Java 17 along with upgrading the project’s dependencies. I start by creating a new issue in my GitLab project that indicates the Java upgrade.
To begin the upgrade, I use the GitLab Q quick action /q transform to begin the upgrade process. The Amazon Q transformation agent asks me to update the gitlab-ci.yaml file to continue the process.
I can follow the agent’s progress by watching for updates in the Issue’s details. GitLab Duo with Amazon Q will also add a transformation plan to the issue so I can understand what types of changes will be involved to complete the upgrade.
When the transform is complete, a new merge request is opened for me to review. As you can see, my pom.xml file was updated to compile on Java 17 as well as additional changes to ensure the project compiles. It also includes a report detailing next steps to consider before merging and deploying the updated Java code.
Conclusion
In this post, I demonstrated how GitLab Duo with Amazon Q can help scale and improve application development. Using GitLab Duo with Amazon Q, I was able to quickly add additional features, review code changes, and upgrade my application to Java 17 all within GitLab’s collaborative interface. I now have a secure and modern java app that I can use to practice my Español.
The general availability of GitLab Duo with Amazon Q marks a significant milestone in AI-assisted software development. By combining GitLab’s comprehensive DevSecOps platform with Amazon Q ‘s generative AI capabilities, this integration empowers development teams to work more efficiently while maintaining high standards of security and compliance.
Organizations can now leverage this powerful integration to accelerate their software development lifecycle, reduce manual effort, and ship more secure code faster. The seamless developer experience, enterprise-grade security, and collaborative AI agents throughout the workflow make this integration a valuable addition to any development team’s toolkit. We’re excited to see how customers leverage this integration to transform their development processes and achieve new levels of productivity and innovation.
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