Today, AWS announces the ability to remotely connect from Kiro and Cursor IDEs to Amazon SageMaker Studio. This new capability allows data scientists, ML engineers, and developers to leverage their Kiro and Cursor setup – including its spec-driven development, conversational coding, and automated feature generation capabilities – while accessing the scalable compute resources of Amazon SageMaker Studio. By connecting Kiro and Cursor to SageMaker Studio using the AWS Toolkit extension, you can eliminate context switching between your local IDE and cloud infrastructure, maintaining your existing agentic development workflows within a single environment for all your AWS analytics and AI/ML services.
SageMaker Studio, offers a broad set of fully managed cloud interactive development environments (IDE), including JupyterLab and Code Editor based on Code-OSS (Open-Source Software), and VS Code IDE as remote IDE. Starting today, you can also use your customized local Kiro and Cursor setup – complete with specs, steering files, and hooks – while accessing your compute resources and data on Amazon SageMaker. You can authenticate using the AWS Toolkit extension in Kiro or Cursor or through SageMaker Studio’s web interface. Once authenticated, connect to any of your SageMaker Studio development environments in a few simple clicks. You maintain the same security boundaries as SageMaker Studio’s web-based environments while developing AI models and analyzing data in local IDE of your choice – Kiro or Cursor.
To learn more, refer to the SageMaker user guide.
Categories: general:products/amazon-sagemaker
Source: Amazon Web Services
