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ML Development in VS Code with Google Cloud Power: Workbench Extension Now Available

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ML Development in VS Code with Google Cloud Power: Workbench Extension Now Available - Google Developers Blog

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ML Development in VS Code with Google Cloud Power: Workbench Extension Now Available

JULY 1, 2026

Andrii Lobanov

Software Engineer

Alex Kallaur

Software Engineering Manager

Diego Granados

Product Manager

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For data scientists and developers, the ideal workflow combines the familiarity of a local IDE with the heavy-lifting capabilities of the cloud. Today, we are bridging that gap with the launch of the Google Cloud Workbench Notebooks extension for VS Code. This new tool allows you to harness the scalable infrastructure of Google Cloud directly within your local development environment.

Gemini Enterprise Agent Platform Workbench has long been a go-to platform for managed Jupyter environments optimized for data science. By bringing Workbench into VS Code, we are enabling a more fluid experience where you can manage your code and cloud-based notebooks in a single interface.

This integration is specifically designed to streamline the ML lifecycle . By eliminating context switching , developers can move from local experimentation to high-performance cloud compute without disruption.

⚡ Enterprise Power meets Local Productivity

The Workbench VS Code extension offers a seamless bridge between your desktop and Google Cloud's AI-optimized infrastructure:

  • Connect and Scale: Easily connect your local VS Code environment to managed cloud environments, accessing high-performance compute when your local machine needs more power.
  • Optimized Workflows: Run notebooks directly on Workbench instances without leaving your IDE, maintaining your preferred local settings and extensions.
  • Open Source Innovation: In line with our commitment to the developer ecosystem, the extension is fully open-sourced , allowing for community-driven contributions and transparency.

🚀 Launch your Workbench Workflow in VS Code

Transitioning your data science projects to the cloud is straightforward. Follow these steps to integrate your local environment with Gemini Agent Platform Workbench:

  • Equip your IDE: Head to the Extensions view in VS Code and search for "Google Cloud Workbench Notebooks". Ensure you install the official package (GoogleCloudTools.workbench-notebooks). This extension works in tandem with the Jupyter extension to provide a seamless notebook experience.
  • Initiate a Cloud Connection: Open a notebook (.ipynb) and use the Select Kernel option located in the editor's toolbar. Navigate through the Google Cloud menu and choose Workbench as your compute provider.
  • Authenticate and Access: A quick sign-in process will link your Google Cloud account. Once authenticated, pick your desired project and select an active Workbench instance to begin executing your code on high-performance infrastructure.

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Next steps

As part of our commitment to the developer ecosystem, the extension is fully open-sourced to support community-driven innovation. This project is a launchpad for bringing the best of Google Cloud's functionality to users everywhere, and we're just getting started.

We are thrilled to finally bring these two platforms together. Download the extension from the VS Code Marketplace today, and contribute to the project on GitHub !

Happy coding!

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