Amazon SageMaker

Amazon SageMaker Unified Studio now supports custom Tooling blueprints

, giving domain administrators the ability to define the foundation of every project by using their own AWS CloudFormation templates.

Amazon SageMaker Unified Studio now supports two new connection capabilities: Iceberg REST Catalog connections and IAM authentication for Amazon DocumentDB

Amazon SageMaker Unified Studio now supports two new connection capabilities: (1) Iceberg REST Catalog (IRC) connections for external Apache Iceberg catalogs, and (2) IAM authentication for Amazon DocumentDB.

Run interactive workloads on Amazon EMR on EKS with Spark Connect

Amazon EMR on EKS now supports interactive Apache Spark sessions with Spark Connect. Data engineers and data scientists can develop and debug Apache Spark applications interactively from managed notebooks in Amazon SageMaker Unified Studio and their own IDEs, such as Jupyter and…

Amazon SageMaker HyperPod now supports model caching for faster inference autoscaling and reduced cold starts

Amazon SageMaker HyperPod now supports model caching, an inference optimization that pre-loads model weights and container images onto cluster nodes so pods start in seconds instead of minutes.

Amazon SageMaker Unified Studio now supports ODBC connections for Microsoft Power BI and other analytics tools

Amazon SageMaker Unified Studio now supports ODBC connections, so data users can connect Microsoft Power BI and other ODBC-compatible tools directly to governed data in SageMaker Unified Studio projects using the Amazon Athena ODBC driver.

Amazon SageMaker Feature Store now supports individual feature updates to lower write latency

Amazon SageMaker Feature Store is a fully managed capability that makes it easy to compute, store, and retrieve features for training and deploying AI models.

Amazon SageMaker AI Batch Transform now supports G6e instances

Amazon SageMaker AI now supports Amazon EC2 G6e instances for batch transform. Batch Transform enables you to run predictions on datasets stored in Amazon S3 and is suited for large datasets that do not require a persistent inference endpoint.

Amazon SageMaker Unified Studio Workflows support Python and Bash operators

Amazon SageMaker Unified Studio Workflows now supports PythonOperator and BashOperator, enabling you to run custom Python functions and shell commands directly in your serverless workflows without provisioning separate compute resources.

Amazon SageMaker Unified Studio CI/CD adds notebook promotion and AI-assisted manifest generation

Amazon SageMaker Unified Studio CI/CD expands its open-source deployment toolkit with two new capabilities: (1) an AI agent skill that automates manifest authoring, and (2) native notebook promotion across environments.

Generative AI Inference Recommendation for Amazon SageMaker now available in the SageMaker AI Studio

Amazon SageMaker AI now offers Generative AI Inference Recommendations in SageMaker AI Studio, giving customers a guided, low-code, no-code path to find the best inference configuration for their workload.

Amazon SageMaker notebooks now support trusted identity propagation

Amazon SageMaker Notebooks now support Trusted Identity Propagation (TIP) with Amazon Athena, Amazon Redshift, and Amazon EMR Serverless, enabling per-user access control for data analytics.

Amazon SageMaker Unified Studio now supports data profiling and anomaly detection

, powered by AWS Glue Data Quality. Data stewards, engineers and analysts can generate statistical profiles of their data to understand its shape and completeness, and track how these statistics change over time.

AWS Glue adds one-click access to SageMaker Unified Studio from the AWS console

AWS Glue now provides direct access to Amazon SageMaker Unified Studio, helping data engineers and analysts move from viewing the catalog in the Glue console to querying their data, running data quality checks, and building data pipelines in SageMaker Unified Studio with a…

NVIDIA Nemotron 3.5 Lightning model is now available on Amazon SageMaker JumpStart

NVIDIA's Nemotron 3.5 Lightning is now available on Amazon SageMaker JumpStart, giving AWS customers access to the fastest open model in its class for persistent agent workloads and rapid task execution.

Amazon SageMaker Studio notebooks now support G7 instance types

Amazon G7 instances, powered by NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs, deliver up to 4.6x AI inference performance compared to previous-generation G6 instances.

Amazon SageMaker AI serverless model customization now supports full fine-tuning

for over 25 open-source models. These include popular models from gpt-oss, Gemma, Llama, Nemotron, and Qwen model families.

Amazon SageMaker Unified Studio now supports Teradata Vantage

as a data source, enabling you to query and analyze your enterprise data warehouse data directly alongside your other data assets.

Amazon SageMaker Unified Studio brings richer Git version control to all project tools

Amazon SageMaker Unified Studio gives project members full Git version control directly within the tools you already use - Query Editor, Visual ETL, Workflows, and Notebooks.

Announcing region expansion of G6 instances on SageMaker AI Inference

We are pleased to announce the availability of Amazon EC2 G6 instances in the AWS GovCloud (US-East) region on Amazon SageMaker AI inference.

Announcing region expansion of G7e instances on SageMaker AI inference

We are pleased to announce the availability of Amazon EC2 G7e instances in Asia Pacific (Seoul), Europe (London), and Asia Pacific (Tokyo) on Amazon SageMaker AI inference.