Today, we’re announcing the general availability of Amazon SageMaker Unified Studio, a single data and AI development environment where you can find and access all of the data in your organization and act on it using the best tool for the job across virtually any use case. Introduced as preview during AWS re:Invent 2024, my colleague, Antje, summarized it as:

SageMaker Unified Studio (preview) is a single data and AI development environment. It brings together functionality and tools from the range of standalone “studios,” query editors, and visual tools that we have today in Amazon Athena, Amazon EMR, AWS Glue, Amazon Redshift, Amazon Managed Workflows for Apache Airflow (Amazon MWAA), and the existing SageMaker Studio.

Here’s a video to see Amazon SageMaker Unified Studio in action:

SageMaker Unified Studio breaks down silos in data and tools, giving data engineers, data scientists, data analysts, ML developers and other data practitioners a single development experience. This saves development time and simplifies access control management so data practitioners can focus on what really matters to them—building data products and AI applications.

This post focuses on several important announcements that we’re excited to share:

• New capabilities for Amazon Bedrock in SageMaker Unified Studio — The integration now supports new foundation models (FMs), including Anthropic’s Claude 3.7 Sonnet and DeepSeek-R1, enables data sourcing from Amazon Simple Storage Service (Amazon S3) folders within projects for knowledge base creation, extends guardrail functionality to flows, and provides a streamlined user management interface for domain administrators to manage model governance across multiple Amazon Web Service (AWS) accounts.
• Amazon Q Developer is now generally available in SageMaker Unified Studio — Amazon Q Developer, the most capable generative AI assistant for software development, streamlines development in Amazon SageMaker Unified Studio by providing natural language, conversational interfaces that simplify tasks like writing SQL queries, building ETL jobs, troubleshooting, and generating real-time code suggestions. 

To get started, go to the Amazon SageMaker console and create a SageMaker Unified Studio domain. To learn more, visit Create an Amazon SageMaker Unified Studio domain in the AWS documentation.

New capabilities for Amazon Bedrock in SageMaker Unified Studio
The capabilities of Amazon Bedrock within Amazon SageMaker Unified Studio offer a governed collaborative environment for developers to rapidly create and customize generative AI applications. This intuitive interface caters to developers of all skill levels, providing seamless access to the high-performance FMs offered in Amazon Bedrock and advanced customization tools for collaborative development of tailored generative AI applications.

Since the preview launch, several new FMs have become available in Amazon Bedrock and are fully integrated with SageMaker Unified Studio, including Anthropic’s Claude 3.7 Sonnet and DeepSeek-R1. These models can be used for building generative AI apps and chatting in the playground in SageMaker Unified Studio.

Here’s how you can choose Anthropic’s Claude 3.7 Sonnet on the model selection in your project.

You can also source data or documents from S3 folders within your project and select specific FMs when creating knowledge bases. 

During preview, we introduced Amazon Bedrock Guardrails to help you implement safeguards for your Amazon Bedrock application based on your use cases and responsible AI policies. Now, Amazon Bedrock Guardrails is extended to Amazon Bedrock Flows with this general availability release.

Additionally, we have streamlined generative AI setup for associated accounts with a new user management interface in SageMaker Unified Studio, making it straightforward for domain administrators to grant associated account admins access to model governance projects. This enhancement eliminates the need for command line operations, streamlining the process of configuring generative AI capabilities across multiple AWS accounts.

These new features eliminate barriers between data, tools, and builders in the generative AI development process. You and your team will gain a unified development experience by incorporating the powerful generative AI capabilities of Amazon Bedrock — all within the same workspace.

Amazon Q Developer is now generally available in SageMaker Unified Studio
Amazon Q Developer is now generally available in Amazon SageMaker Unified Studio, providing data professionals with generative AI–powered assistance across the entire data and AI development lifecycle.

Amazon Q Developer integrates with the full suite of AWS analytics and AI/ML tools and services within SageMaker Unified Studio, including data processing, SQL analytics, machine learning model development, and generative AI application development, to accelerate collaboration and help teams build data and AI products faster. To get started, you can select Amazon Q Developer icon.

For new users of SageMaker Unified Studio, Amazon Q Developer serves as an invaluable onboarding assistant. It can explain core concepts such as domains and projects, provide guidance on setting up environments, and answer your questions.

Amazon Q Developer helps you discover and understand data using powerful natural language interactions with SageMaker Catalog. What makes this implementation particularly powerful is how Amazon Q Developer combines broad knowledge of AWS analytics and AI/ML services with the user’s context to provide personalized guidance.

You can chat about your data assets through a conversational interface, asking questions such as “Show all payment related datasets” without needing to navigate complex metadata structures.

Amazon Q Developer offers SQL query generation through its integration with the built-in query editor available in SageMaker Unified Studio. Data professionals of varying skill levels can now express their analytical needs in natural language, receiving properly formatted SQL queries in return.

For example, you can ask, “Analyze payment method preferences by age group and region” and Amazon Q Developer will generate the appropriate SQL with proper joins across multiple tables.

Additionally, Amazon Q Developer is also available to assist with troubleshooting and generating real-time code suggestions in SageMaker Unified Studio Jupyter notebooks, as well as building ETL jobs.

Now available

• Availability — Amazon SageMaker Unified Studio is now available in the following AWS Regions: US East (N. Virginia, Ohio), US West (Oregon), Asia Pacific (Seoul, Singapore, Sydney, Tokyo), Canada (Central), Europe (Frankfurt, Ireland, London), South America (São Paulo). Learn more about the availability of these capabilities on supported Region documentation page.
• Amazon Q Developer subscription — The free tier of Amazon Q Developer is available by default in SageMaker Unified Studio, requiring no additional setup or configuration. If you already have Amazon Q Developer Pro Tier subscriptions, you can use those enhanced capabilities within the SageMaker Unified Studio environment. For more information, visit the documentation page.
• Amazon Bedrock capabilities — To learn more about the capabilities of Amazon Bedrock in Amazon SageMaker Unified Studio, refer to this documentation page. 

Start building with Amazon SageMaker Unified Studio today. For more information, visit the Amazon SageMaker Unified Studio page.

Happy building!

— Donnie Prakoso

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