Amazon SageMaker introduces one-click onboarding of existing AWS datasets to Amazon SageMaker Unified Studio. This helps AWS customers to start working with their data in minutes, using their existing AWS Identity and Access Management (IAM) roles and permissions. Customers can…

Amazon SageMaker introduces a new notebook experience that provides data and AI teams a high-performance, serverless programming environment for analytics and machine learning (ML) jobs. This helps customers quickly get started working with data without pre-provisioning data processing infrastructure. The…

Amazon SageMaker introduces a built-in AI agent that accelerates the development of data analytics and machine learning (ML) applications. SageMaker Data Agent is available in the new notebook experience in Amazon SageMaker Unified Studio and helps data engineers, analysts, and…

Amazon SageMaker now supports Amazon Athena for Apache Spark, bringing a new notebook experience and fast serverless Spark experience together within a unified workspace. Now, data engineers, analysts, and data scientists can easily query data, run Python code, develop jobs,…

AWS Glue now supports a new Amazon DynamoDB connector that works natively with Apache Spark DataFrames. This enhancement allows Spark developers to work directly with Spark DataFrames, to share code easily across AWS Glue, Amazon EMR, and other Spark environments.…

AWS CloudFormation StackSets offers deployment ordering for auto-deployment mode, enabling you to define the sequence in which your stack instances automatically deploy across accounts and regions. This capability allows you to coordinate complex multi-stack deployments where foundational infrastructure must be…