Set up Amazon Q Developer for your users - Amazon SageMaker AI

Set up Amazon Q Developer for your users

Amazon Q Developer is a generative AI conversational assistant. You can set up Amazon Q Developer within a new domain or an existing domain. Use the following information to set up Amazon Q Developer.

With Amazon Q Developer, your users can:

  • Receive step-by-step guidance on using SageMaker AI features independently or in combination with other AWS services.

  • Get sample code to get started on your ML tasks such as data preparation, training, inference, and MLOps.

  • Receive troubleshooting assistance to debug and resolve errors encountered while running code in JupyterLab.

Note

Amazon Q Developer in Studio doesn't use user content to improve the service, regardless of whether you use the Free-tier or Pro-tier subscription. For IDE-level telemetry sharing, Amazon Q might track your users' usage, such as the number of questions asked and whether recommendations were accepted or rejected. This telemetry data doesn't include personally identifiable information such as the users' IP address. For more information on data protection and instructions for opting out, see Opt out of data sharing in the IDE.

You can set up Amazon Q Developer with either a Pro or Free tier subscription. The Pro tier is a paid subscription service with higher usage limits and other features. For more information about the differences between the tiers, see Understanding tiers of service for Amazon Q Developer.

For information about subscribing to Amazon Q Developer Pro, see Subscribing to Amazon Q Developer Pro.

To set up Amazon Q Developer Free Tier within JupyterLab, use the following procedure:

To set up Amazon Q Developer Free Tier

  1. Add the following policy to the IAM role that you've used to create your JupyterLab space:

    {
	"Version": "2012-10-17",
	"Statement": [
		{
			"Effect": "Allow",
			"Action": [
				"q:SendMessage"
			],
			"Resource": [
				"*"
			]
		}
		{
			"Sid": "AmazonQDeveloperPermissions",
			"Effect": "Allow",
			"Action": [
				"codewhisperer:GenerateRecommendations"
			],
			"Resource": "*"
		}
	]
}

  2. Navigate to Amazon SageMaker Studio.

  3. Open your JupyterLab space.

  4. Navigate to the Launcher and choose Terminal.

  5. Specify restart-jupyter-server.

  6. Restart your browser and navigate back to Amazon SageMaker Studio.

Prerequisites

To set up Amazon Q Pro within JupyterLab, you must have:

  • An Amazon SageMaker AI domain set up for your organization with IAM Identity Center configured as the means of access.

  • An Amazon Q Developer Pro subscription.

If you're updating a domain that you've already set up for your organization, you need to update it to use Amazon Q Developer. You can use either the AWS Management Console or the AWS Command Line Interface to update a domain.

You must use the ARN of your Amazon Q Developer profile. You can find the Q Profile ARN on the Q Developer Settings page.

You can use the following AWS Command Line Interface command to update your domain:


aws --region AWS Region sagemaker update-domain --domain-id domain-id --domain-settings-for-update "AmazonQSettings={Status=ENABLED,QProfileArn=Q-Profile-ARN}"

You can also use the following procedure to update the domain within the AWS Management Console.

  1. Navigate to the Amazon SageMaker AI console.

  2. Choose domains.

  3. Select App Configurations.

  4. For Amazon Q Developer for SageMaker AI Applications, choose Edit.

  5. Select Enable Amazon Q Developer on this domain.

  6. Provide the Q Profile ARN.

  7. Choose Submit.

You must use the ARN of your Amazon Q Developer profile. You can find the ARN of the Q Profile on the Amazon Q account details page of the Amazon Q Developer console.

The Set up for organizations is an advanced setup for the Amazon SageMaker AI domain that lets you use IAM Identity Center. For information about how you can set up the domain and information about setting up IAM Identity Center, see Use custom setup for Amazon SageMaker AI.

When setting up Amazon Q Developer in a new domain, you can either use the AWS Management Console or the following AWS Command Line Interface command from your local machine:


                    
aws --region AWS Region sagemaker create-domain --domain-id domain-id --domain-name "example-domain-name" --vpc-id example-vpc-id --subnet-ids example-subnet-ids --auth-mode SSO --default-user-settings "ExecutionRole=arn:aws:iam::111122223333:role/IAM-role",--domain-settings "AmazonQSettings={status=ENABLED,qProfileArn=Q-profile-ARN" --query example-domain-ARN--output text

You can use the following AWS CLI command to disable Amazon Q Developer:


aws --region AWS Region sagemaker update-domain --domain-id domain-id --domain-settings-for-update "AmazonQSettings={Status=DISABLED,QProfileArn=Q-Profile-ARN}"

You can set up Amazon Q Developer within a new domain or an existing domain. Use the following information to set up Amazon Q Developer.

We recommend using the latest version of the AWS Command Line Interface. For information about updating the AWS CLI, see Install or update to the latest version of the AWS Command Line Interface.

If you need to establish a connection between Amazon Q Developer and your VPC, see Creating an interface VPC endpoint for Amazon Q .

Note

Amazon Q Developer has the following limitations:

  • It doesn't support shared spaces.

  • Amazon Q Developer in JupyterLab detects whether a code suggestion might be too similar to publicly available code. The reference tracker can flag suggestions with repository URLs and licenses, or filter them out. This allows you to review the referenced code and its usage before you adopt it. All references are logged for you to review later to ensure that your code flow is not disturbed and that you can keep coding without interruption.

    For more information about code references, see Using code references - Amazon Q Developer and AI Coding Assistant - Amazon Q Developer FAQs.

  • Amazon Q processes all user interaction data within the US East (N. Virginia) AWS Region. For more information about how Amazon Q processes data and the AWS Regions it supports, see Supported Regions for Amazon Q Developer.

  • Amazon Q only works within Amazon SageMaker Studio. It is not supported within Amazon SageMaker Studio Classic.

  • Amazon Q works within SageMaker Distribution Images version 2.0 and above.

  • Amazon Q works within the Jupyter AI extension. You can't use other 3P models within the extension while you're using Amazon Q.