Posted On: Nov 30, 2023
Starting today, SageMaker Studio offers a suite of IDEs, including Code Editor based on Code-OSS Visual Studio Code Open Source, improved and faster JupyterLab, and RStudio. ML practitioners can choose their preferred IDE to accelerate ML development, for example, a data scientist could use JupyterLab and training jobs in Studio to explore data and tune models, while an MLOPs engineer could choose the Code Editor and the pipelines tool in Studio to deploy and monitor models in production. Your IDE will open in a separate tab allowing users to work with a full screen experience. Additionally, users can now view their training jobs, including jobs they may have scheduled from notebooks and training jobs they may have initiated from JumpStart. We are also excited to announce a new interactive experience in SageMaker Studio to deploy models with optimal configurations in as little as three clicks. Users can also now monitor and manage their endpoints in Studio without having to navigate to AWS Console. SageMaker Studio comes with an improved JumpStart experience. It is now easy to discover, import, fine tune and deploy a foundational model with just a few clicks.
Amazon SageMaker Studio is available in all Amazon Web Services regions where Amazon SageMaker is currently available, except China and the Amazon Web Services GovCloud (US) regions.
To get started, refer to the Amazon SageMaker Studio documentation.