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Amazon SageMaker Studio notebooks now support P5.4xl instance types

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We are pleased to announce general availability of Amazon EC2 P5.4xl instances on SageMaker Studio notebooks.

Amazon EC2 P5.4xl instances  are powered by NVIDIA H100 Tensor Core GPUs and deliver high performance in Amazon EC2 for deep learning (DL) and high performance computing (HPC) applications. They help you accelerate your time to solution by up to 4x compared to previous-generation GPU-based EC2 instances, and reduce cost to train ML models by up to 40%. Customers can use P5 instances for training and deploying complex large language models (LLMs) and diffusion models powering generative AI applications. These applications include question answering, code generation, video and image generation, and speech recognition.

Amazon EC2 P5.4xl instances are available for SageMaker Studio notebooks in the AWS US East (N. Virginia and Ohio), US West (Oregon), Asia Pacific (Mumbai, Tokyo, Jakarta) and South America (São Paulo) regions.

Visit developer guides for instructions on setting up and using JupyterLab  and CodeEditor  applications on SageMaker Studio . For pricing information on these instances, please visit our pricing page .

Announcing Region Expansion of G6 instances on SageMaker Notebook Instances

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We are pleased to announce general availability of Amazon EC2 G6 instances in Asia Pacific (Tokyo, Mumbai, Sydney) and Europe (London, Paris, Frankfurt, Stockholm, Zurich) on SageMaker notebook instances.

Amazon EC2 G6 instances  are powered by up to 8 NVIDIA L4 Tensor Core GPUs with 24 GB of memory per GPU and third generation AMD EPYC processors. G6 instances offer 2x better performance for deep learning inference compared to EC2 G4dn instances. Customers can use G6 instances to interactively test model deployment and for interactive model training for use cases such as generative AI fine-tuning and inference workloads, natural language processing, language translation, computer vision, and recommender engines.

Visit developer guides for instructions on setting up and using JupyterLab  and CodeEditor  applications on SageMaker Studio  and SageMaker notebook instances .

Announcing Region Expansion of P5.48xl instances on SageMaker Studio notebooks

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We are pleased to announce general availability of Amazon EC2 P5.48xl instances in the AWS US West (San Francisco), Asia Pacific (Tokyo, Mumbai, Sydney, Jakarta) and Europe (London, Stockholm) regions on SageMaker Studio notebooks.

Amazon EC2 P5.48xl instances are powered by NVIDIA H100 Tensor Core GPUs and deliver high performance in Amazon EC2 for deep learning (DL) and high performance computing (HPC) applications. They help you accelerate your time to solution by up to 4x compared to previous-generation GPU-based EC2 instances, and reduce cost to train ML models by up to 40%. Customers can use P5 instances for training and deploying complex large language models (LLMs) and diffusion models powering generative AI applications. These applications include question answering, code generation, video and image generation, and speech recognition.

Visit developer guides for instructions on setting up and using JupyterLab  and CodeEditor  applications on SageMaker Studio . For pricing information on these instances, please visit our pricing page .

Amazon FSx for OpenZFS now supports creating Multi-AZ file systems in shared VPCs

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Amazon FSx for OpenZFS now allows you to create Multi-AZ file systems in shared VPCs within your AWS organization, making it easier for you to decentralize network and storage administration.

VPC sharing  is a feature that allows resource owners (“owner accounts”) to share one or more VPC subnets with other accounts (“participant accounts”) in their AWS organization. Participant accounts can then view, create, modify, delete, and manage their application resources in the subnets shared with them. Previously, participant accounts could create Single-AZ OpenZFS file systems in VPCs shared with them, but could only create Multi-AZ file systems in VPCs they owned. Starting today, participant accounts can create any FSx for OpenZFS file system in a shared VPC, allowing organizations to run highly available file systems with centralized network management.

You can create Multi-AZ FSx for OpenZFS file systems from shared VPC participant accounts in all AWS Regions where Amazon FSx for OpenZFS is available . To learn more, visit the FSx for OpenZFS documentation  and the FSx for OpenZFS product page .

Amazon RDS for Oracle now supports M8i and R8i instances with Oracle SE2 License Included

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Amazon RDS for Oracle now offers M8i and R8i instances with Oracle Database Standard Edition 2 (SE2) with the License Included (LI). M8i and R8i instances are powered by custom Intel Xeon 6 processors, available only on AWS, delivering the highest performance and fastest memory bandwidth among comparable Intel processors in the cloud. The new instances offer up to 15% better price-performance, and 2.5x more memory bandwidth compared to previous generation Intel-based instances.

With RDS for Oracle SE2 LI, customers don’t have to separately purchase Oracle license and support. Amazon RDS for Oracle SE2 LI offers subscription based pay-per-use pricing inclusive of software license, support, compute resources, and a managed database service. To use RDS for Oracle SE2 LI, customers can create database instances from the AWS Management Console or using the AWS CLI . and specify the LI option. For more details about how you can lower cost and simplify operations of running Oracle databases, refer to the AWS blog Rethink Oracle Standard Edition Two on Amazon RDS for Oracle .

Configuration details for available instance types can be found on the Amazon RDS for Oracle Instance Types page. Review the AWS blog Rethink Oracle Standard Edition Two on Amazon RDS for Oracle to explore how you can lower cost and simplify operations by using Amazon RDS Oracle SE2 License Included instances for your Oracle databases.

For pricing and AWS Region availability, see Amazon RDS for Oracle Pricing .

Amazon SageMaker Data Agent now available for IAM Identity Center domains

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Amazon SageMaker Data Agent is now available in SageMaker Unified Studio domains configured with IAM Identity Center. Data Agent extends its AI-powered capabilities to help data analysts and engineers streamline their analytics workflows across both SageMaker notebooks and Query Editor environments, eliminating the need to manually write complex SQL joins, aggregations, and Python code.

With Data Agent, you can describe your analysis goals in plain English and receive working Python or SQL code tailored to your connected data sources, including Amazon Athena, Amazon Redshift, Amazon S3, and AWS Glue Data Catalog. The agent maintains conversational context across notebook cells, selected tables, and query history, proposing step-by-step plans before generating code. Use it to calculate quarterly revenue growth rates, generate visualizations, transform DataFrames, or optimize query performance—all through natural language interaction. The “Fix with AI” feature provides intelligent debugging by analyzing execution errors and suggesting corrections, accelerating your development cycle.

This capability is available in all commercial AWS Regions where Amazon SageMaker Unified Studio is supported . To get started, navigate to a project in SageMaker Unified Studio, open a notebook or Query Editor, and select the Data Agent panel. To learn more, visit the Amazon SageMaker Unified Studio page and refer to “Use the SageMaker Data Agent” in the Amazon SageMaker Unified Studio User Guide.

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