Using Amazon Q Developer with Amazon SageMaker Unified Studio - Amazon SageMaker Unified Studio
About signing upPromptsContext filesCommand referenceRegionStart using Amazon Q chatStart using Amazon Q CLI

Using Amazon Q Developer with Amazon SageMaker Unified Studio

Amazon SageMaker Unified Studio has an integration with Amazon Q Developer with which you can interact with AWS resources through a conversational interface. You can ask questions about your assets in Amazon SageMaker Unified Studio using simple, natural language queries within the Amazon Q Developer chat interface.

For getting started flows that walk you through implementing Amazon Q Developer in Amazon SageMaker Unified Studio, see Getting started with Amazon Q Developer generative AI chat and command line tools.

Amazon Q Developer provides contextual generative AI assistance through Amazon Q chat or Amazon Q CLI. It helps data engineers, ML data developers, and other users in Amazon SageMaker Unified Studio with:

  • Creating and analyzing code

  • Understanding and managing workspaces

  • Running AWS CLI commands

  • Setting up projects and pipelines

  • Creating functions for you

  • Configuring Jupyter notebooks

Amazon Q Developer implements Model Context Protocol (MCP) integration, allowing you to configure your MCP information when using Q chat or Q CLI. For more information about MCP integration, see Using MCP with Amazon Q Developer.

About signing up

Users in Amazon SageMaker Unified Studio can access Amazon Q Developer by signing in with their Amazon SageMaker Unified Studio SSO that is configured for either the Amazon Q Developer Free Tier or Pro Tier. For more information, see Amazon Q Developer pricing.

For more detail about setting up Q assistance in Amazon SageMaker Unified Studio, see Using the coding assistant.

Prompts

Include relevant information in your prompts to provide additional context for more accurate assistance.

  • Your level of familiarity or expertise

  • Information about your role

  • A brief description of the goal or outcome for the task

Context files

Amazon Q Developer is contextually aware of your workspace and can use additional information that you configure, such as:

  • Python development rules loaded for a developer profile

  • Public sources

  • MCP sources

  • Custom context.json file

For more information about managing context, see Context management and profiles in the Amazon Q Developer User Guide.

Command reference

Amazon Q Developer includes comprehensive command reference pages:

Region

When you use Amazon Q Developer in Amazon SageMaker Unified Studio, your content is stored in the US East (N. Virginia) Region and may be processed in other US Regions. For more information, access Amazon Q Developer documentation here and here.

Note

Amazon Q Developer in Amazon SageMaker Unified Studio only supports Amazon Q Developer profiles configured in the US East (N. Virginia) Region.

Start using Amazon Q chat

To start using Amazon Q Developer to chat about your project and your assets:

  1. Log in to your AWS account and navigate to Amazon SageMaker Unified Studio.

  2. Select the Amazon Q Developer chat interface within Amazon SageMaker Unified Studio.

  3. Begin typing your query in natural language, asking Q to list Amazon SageMaker AI catalog assets published in the catalog. For example, you can say: "Find me data on sales".

  4. To open JupyterLab, choose Build, and then choose JupyterLab. If you are in JupyterLab, you can chat with Q with additional Amazon Q chat contextual awareness.

    For a flow that walks you through getting started with Q chat in JupyterLab, see Getting started using Q chat.

Amazon Q Developer interprets your query, executes the appropriate API calls, and returns the results directly in the chat interface.

Start using Amazon Q CLI

To start using Amazon Q Developer to interact with Q CLI about your project and your assets:

  1. Log in to your AWS account and navigate to Amazon SageMaker Unified Studio.

  2. To open JupyterLab, choose Build, and then choose JupyterLab.

    For a flow that walks you through getting started with Q CLI in JupyterLab, see Getting started with Q CLI.