As of November 7, 2025, you can't create new repository associations in Amazon CodeGuru Reviewer. To learn about services with capabilities similar to CodeGuru Reviewer, see [Amazon CodeGuru Reviewer availability change](https://docs.aws.amazon.com/codeguru/latest/reviewer-ug/codeguru-reviewer-availability-change.html). # Getting started with CodeGuru Reviewer Getting started In this section, you learn what you need to do to get started with Amazon CodeGuru Reviewer so it can start to analyze your source code and provide code reviews. To use CodeGuru Reviewer to create code reviews with example source code in a real repository, see [Tutorial: monitor source code in a GitHub repository](tutorial-github-reviewer.md). **Topics** + [ # Step 1: Get set up ](getting-started-prequisites.md) + [ # Step 2: Associate a repository ](getting-started-associate-repository.md) + [ # Step 3: Get recommendations ](get-results.md) + [ # Step 4: Provide feedback ](provide-feedback.md) # Step 1: Get set up Before you get started, you must prepare by running through the steps in [Setting up Amazon CodeGuru Reviewer](setting-up-codeguru-reviewer.md). # Step 2: Associate a repository You must create a repository association to grant CodeGuru Reviewer access to read your source code and create notifications on your repository. The notifications initiate an analysis on the updated source code every time you create a pull request. When you create your repository association, CodeGuru Reviewer automatically creates a full repository analysis code review. You must initiate future full repository analysis code reviews. For more information, see [Working with repository associations in Amazon CodeGuru Reviewer](working-with-repositories.md). **Note** The source code reviewed by CodeGuru Reviewer is not stored. For more information, see [Captured data in CodeGuru Reviewer](data-protection.md#data-captured). To create a repository association, choose one of the following. + If your repository type is AWS CodeCommit, see [Create a CodeCommit repository association](create-codecommit-association.md). + If your repository type is Bitbucket, see [ Create a Bitbucket repository association](create-bitbucket-association.md). + If your repository type is GitHub or GitHub Enterprise Cloud, see [Create a GitHub or GitHub Enterprise Cloud repository association](create-github-association.md). + If your repository type is GitHub Enterprise Server, see [Create a GitHub Enterprise Server repository association](create-github-enterprise-association.md). # Step 3: Get recommendations CodeGuru Reviewer uses code reviews to provide [different kinds of recommendations](recommendations.md) to help improve your code. These recommendations are focused on best practices and resolving potential defects in code that are difficult for developers to find. After CodeGuru Reviewer completes an incremental code review or a full repository analysis code review, you can view recommendations. You can then choose whether to incorporate the recommendations, and you can provide feedback about whether the recommendations were helpful. **Note** We recommend that you use both CodeGuru Reviewer and traditional peer review processes during the code review stage. Using a combination of code review processes helps to identify more issues before they reach production. For more information, see the following topics: + [View code review details](view-code-review-details.md) + [Get recommendations using full repository analysis](create-code-reviews.md#get-repository-scan) + [Get recommendations using incremental code reviews](create-code-reviews.md#get-pull-request-scan) + [Get recommendations using GitHub Actions and a CI/CD workflow](https://docs.aws.amazon.com/codeguru/latest/reviewer-ug/working-with-cicd.html) ## About full repository analysis and incremental code reviews You can receive recommendations in code reviews by creating a full repository analysis or submitting a pull request. After you associate a repository, CodeGuru Reviewer automatically creates a full repository analysis code review, and every pull request in that repository creates an incremental code review. You can also choose to create additional full repository analysis code reviews. | Type of code review | Is the review automatic after I associate the repository? | Where can I see recommendations? | What code is reviewed? | | --- | --- | --- | --- | | Full repository analysis | Your first full repository analysis is done automatically when you associate your repository. After that, you must request a full repository analysis in the CodeGuru Reviewer console or by using the AWS CLI or AWS SDK. | In the CodeGuru Reviewer console, or by using the AWS CLI or AWS SDK. | All the code in the branch is reviewed. | | Incremental code review | Yes. After associating the repository, every time you do a pull request there is a code review. | In the CodeGuru Reviewer console, in the AWS CLI or AWS SDK, or in pull request comments in the repository source provider. | The code that is changed in the pull request is reviewed. | | GitHub Actions code review in a CI/CD workflow | Yes. After enabling CodeGuru Reviewer on your GitHub repository, for every push, pull, or scheduled repository scan there is a code review. | In the GitHub **Security** tab. | The code that is changed in the push, pull, or scheduled repository scan. | # Step 4: Provide feedback CodeGuru Reviewer is based on program analysis and machine learning models, so it's constantly improving. To assist in the machine learning process and enhance the experience with CodeGuru Reviewer, you can provide feedback on the recommendations in the **Code reviews** page on the CodeGuru Reviewer console. You can also provide feedback directly in the pull requests to indicate whether they were helpful to you. Your feedback and comments are shared with CodeGuru Reviewer. This can help CodeGuru Reviewer to improve its models and become more helpful to you and others in the future. When you provide feedback, your code is not shared. For more information, see [Captured data in CodeGuru Reviewer](data-protection.md#data-captured). **Note** The source code reviewed by CodeGuru Reviewer is not stored. For more information, see [Captured data in CodeGuru Reviewer](data-protection.md#data-captured). **Topics** + [ ## Provide feedback using the CodeGuru Reviewer console ](#provide-feedback-in-console) + [ ## Provide feedback using pull request comments ](#provide-feedback-in-pull-requests) + [ ## Provide feedback using the CLI ](#provide-feedback-cli) ## Provide feedback using the CodeGuru Reviewer console You can provide feedback for recommendations on incremental code reviews or full repository analysis code reviews [using the **Code reviews** page](https://docs.aws.amazon.com//codeguru/latest/reviewer-ug/give-feedback-from-code-review-details.html) of the CodeGuru Reviewer console. Choose the name of a code review to view details and recommendations from that code review. Then choose the thumbs-up or thumbs-down icon under each recommendation to indicate whether the recommendation was helpful. ## Provide feedback using pull request comments You can also provide feedback for incremental code reviews by replying to comments in pull requests, without leaving your repository context. In AWS CodeCommit you can view the recommendations on the **Activity** or **Changes** tab. A thumbs-up or thumbs-down icon is provided next to comments made by CodeGuru Reviewer. Choose a thumbs-up icon if the recommendation was helpful and a thumbs-down icon if it wasn't. In other repository source providers, you can reply to a comment made by CodeGuru Reviewer, and include either a thumbs-up or thumbs-down emoji in your comment to indicate whether it was helpful or not. For more information, see [Using emoji](https://docs.github.com/en/github/writing-on-github/basic-writing-and-formatting-syntax#using-emoji) on the GitHub website and [Use symbols, emojis, and special characters](https://support.atlassian.com/confluence-cloud/docs/use-symbols-emojis-and-special-characters/) on the Bitbucket website. The following image shows an example of feedback in CodeCommit. ![\[Example positive feedback in CodeCommit with the thumbs-up icon.\]](http://docs.aws.amazon.com/codeguru/latest/reviewer-ug/images/guru-feedback-codecommit.png) ## Provide feedback using the CLI You can also use the AWS CLI or the AWS SDK to provide feedback on recommendations. If you have the code review ARN, you can call [https://docs.aws.amazon.com/codeguru/latest/reviewer-api/API_ListRecommendations.html](https://docs.aws.amazon.com/codeguru/latest/reviewer-api/API_ListRecommendations.html). This returns the list of all recommendations for a completed code review. You can then use [https://docs.aws.amazon.com/codeguru/latest/reviewer-api/API_PutRecommendationFeedback.html](https://docs.aws.amazon.com/codeguru/latest/reviewer-api/API_PutRecommendationFeedback.html) to store reactions and send feedback as UTF-8 text code for emojis. To view the feedback that you have submitted, call [https://docs.aws.amazon.com/codeguru/latest/reviewer-api/API_DescribeRecommendationFeedback.html](https://docs.aws.amazon.com/codeguru/latest/reviewer-api/API_DescribeRecommendationFeedback.html) using the `RecommendationId`. To view feedback from all users, call [https://docs.aws.amazon.com/codeguru/latest/reviewer-api/API_ListRecommendationFeedback.html](https://docs.aws.amazon.com/codeguru/latest/reviewer-api/API_ListRecommendationFeedback.html) by using a filter on `RecommendationIds` and `UserIds`. For more information, see the [Amazon CodeGuru Reviewer API Reference](https://docs.aws.amazon.com/codeguru/latest/reviewer-api/Welcome.html).