Dec 16, 2025: Notebooks in Workspaces (Preview)¶
Snowflake Notebooks in Workspaces is now available in preview. This new notebook experience provides a fully-managed, end-to-end environment for data science and machine learning development on Snowflake data, combining the familiar Jupyter notebook interface with enterprise-grade compute, governance, and collaboration capabilities.
Notebooks in Workspaces runs on a Container Runtime powered by Snowpark Container Services, offering preconfigured containers optimized for AI/ML workloads with access to CPUs and GPUs, parallel data loading, and distributed training APIs for popular ML packages.
Key features¶
Integration with Workspaces
Notebooks are files in Workspaces, enabling easy file management and organization.
Git integration provides version control and collaboration across development environments.
Updates to compute and cost management
CPU or GPU compute pools match your workload requirements.
Shared container service connections reduce start-up time and improve resource utilization.
Background kernel persistence ensures uninterrupted execution of long-running processes.
Simplified idle time configuration prevents unused compute resources from running indefinitely.
Service-level External Access Integration (EAI) management applies to all notebooks in the workspace.
Jupyter compatibility
Standard Jupyter magic commands for familiar development experience.
Pre-installed data science and machine learning packages.
Install additional packages via
pip, PyPI, or file upload.
Enhanced editing experience
Bidirectional SQL and Python cell referencing for seamless language switching.
Interactive datagrid and automated chart builder for data visualization.
Enhanced minimap with cell status tracking and table of contents.
For details, see Snowflake Notebooks in Workspaces.