Creating an issue in CodeCatalyst
Development teams create issues to help track and manage their work. You can create issues within a project based on your needs. For example, you could create an issue to track updating a variable in your code. You can assign issues to other users in the project, use labels to help you track your work, and more.
Follow these instructions to create an issue in CodeCatalyst.
To create an issue
Open the CodeCatalyst console at https://codecatalyst.aws/
. -
Navigate to the project where you want to create an issue.
-
On the project home page, choose Create issue. Alternatively, in the navigation pane, choose Issues.
-
Choose Create issue.
Note
You can also add issues inline when using a grid view.
-
Enter a title for the issue.
-
(Optional) Enter a Description. You can use Markdown to add formatting.
-
(Optional) Choose a Status, Priority, and Estimation for the issue.
Note
If the project's estimation setting is set to Hide estimates, there will not be an Estimation field.
-
(Optional) Add tasks to the issue. Tasks can be used to break down the work of an issue into smaller objectives. To add a task, choose + Add tasks. Then, input the task name in the text field and press enter. After adding tasks, you can mark them as complete by choosing the checkbox, or reorder them by choosing and dragging the task from the left side of the checkbox.
-
(Optional) Add an existing label or create a new label and add it by choosing + Add label.
-
To add an existing label, choose the label from the list. You can enter a search term in the field to search all labels containing that term in the project.
-
To create a new label and add it, enter the name of the label you want to create in the search field and press enter.
-
-
(Optional) Add an assignee by choosing + Add an assignee. You can quickly add yourself as the assignee by choosing + Add me.
Tip
You can choose to assign an issue to Amazon Q to have Amazon Q try to solve the issue. For more information, see Tutorial: Using CodeCatalyst generative AI features to speed up your development work. This feature is only available in the US West (Oregon) Region.
This functionality requires that generative AI features are enabled for the space. For more information, see Managing generative AI features.
-
(Optional) Add an existing custom field or create a new custom field. Issues can have multiple custom fields.
-
To add an existing custom field, choose the custom field from the list. You can enter a search term in the field to search all custom fields containing that term in the project.
-
To create a new custom field and add it, enter the name of the custom field you want to create in the search field and press enter. Then choose the type of custom field you want to create and set a value.
-
-
Choose Create issue. A notification appears in the lower right corner: If the issue was created successfully, a confirmation message appears saying the issue was successfully created. If the issue was not created successfully, an error message with the reason for the failure appears. You can then choose Retry to edit and retry creating the issue, or choose Discard to discard the issue. Both options will dismiss the notification.
Note
You cannot link a pull request to an issue when you create it. However, you can edit it after you create it to add links to pull requests.
Best practices when creating and working with issues assigned to Amazon Q
When you create issues, sometimes some of them linger. The causes for this can be complex and variable. Sometimes it's because it's not clear who should work on it. Other times the issue requires research into or expertise with a particular part of the code base and the best candidates for the work are busy with other issues. Often there is other urgent work must be attended to first. Any or all of these causes can result in issues that aren't worked on. CodeCatalyst includes integration with a generative AI assistant called Amazon Q that can analyze an issue based on its title and its description. If you assign the issue to Amazon Q, it will attempt to create a draft solution for you to evaluate. This can help you and your team to focus and optimize work on issues that require your attention, while Amazon Q works on a solution for problems you don't have resources to address immediately.
Note
Note
Powered by Amazon Bedrock: AWS implements automated abuse detection. Because the Write description for me, Create content summary, Recommend tasks, Use Amazon Q to create or add features to a project, and Assign issues to Amazon Q feature with Amazon Q Developer Agent for software development features are built on Amazon Bedrock, users can take full advantage of the controls implemented in Amazon Bedrock to enforce safety, security, and the responsible use of artificial intelligence (AI).
Amazon Q performs best on simple issues and straightforward problems. For best results, use plain language to clearly explain what you want done. The following are some best practices to help you create issues optimized for Amazon Q to work on.
Important
Generative AI features are only available in the US West (Oregon) Region.
-
Keep it simple. Amazon Q does best with simple code changes and fixes that can be explained in the title and description of the issue. Don't assign issues with vague titles or overly flowery or contradictory descriptions.
-
Be specific. The more information you can provide about the exact changes needed to resolve the issue, the more likely Amazon Q will be able to create a solution that solves the issue. If possible, include specific details such as the name of APIs you want changed, methods you want updated, tests that need changes, and any other details you can think of.
-
Make sure you have all the details included in the title and description of the issue before assigning it to Amazon Q. You can't change the title or description of an issue after you assign it to Amazon Q, so make sure you have all the information required in an issue before you assign it to Amazon Q.
-
Only assign issues that require code changes in a single source repository. Amazon Q can only work on code in a single source repository in CodeCatalyst. Linked repositories are not supported. Make sure that the issue only requires changes in a single source repository before you assign that issue to Amazon Q.
-
Use the default suggested by Amazon Q for approving each step. By default, Amazon Q will require your approval for each step it takes. This allows you to interact with Amazon Q in comments not only on the issue, but also on any pull request it creates. This provides a more interactive experience with Amazon Q that helps you adjust its approach and refine the code it creates to solve the issue.
Note
Amazon Q does not respond to individual comments in issues or pull requests, but it will review them when asked to reconsider its approach or create a revision.
-
Always carefully review the approach suggested by Amazon Q. Once you approve its approach, Amazon Q will start work on generating code based on that approach. Make sure that the approach seems correct and includes all the details you expect before you tell Amazon Q to proceed.
-
Make sure to only allow Amazon Q to work on workflows if you don't have existing workflows that might deploy them before they're reviewed. Your project might have workflows configured to start runs on pull request events. If so, any pull request that Amazon Q creates that includes creating or updating workflow YAML might start a run of those workflows included in the pull request. As a best practice, don't choose to allow Amazon Q to work on workflow files unless you are sure there are no workflows in your project that will automatically run these workflows before you review and approve the pull request it creates.
For more information, see Tutorial: Using CodeCatalyst generative AI features to speed up your development work and Managing generative AI features.
