Google Cloud Workbench Extension Brings Cloud ML Power to VS Code

Google has released a VS Code extension that integrates its Workbench Notebooks platform into the popular code editor, allowing developers to tap into cloud computing resources without leaving their local environment. The tool bridges the gap between lightweight desktop development and the heavy computational demands of machine learning work.

Streamlined ML Workflow#

The extension eliminates the friction of context-switching between local IDEs and cloud platforms. Data scientists can now experiment locally, then seamlessly transition to high-performance cloud infrastructure—all within a single interface. Workbench, Google's managed Jupyter environment for data science, has been reimagined as a VS Code extension to keep developers focused on their work.

How to Get Started#

Setting up the extension takes three main steps:

• Install the extension by searching for "Google Cloud Workbench Notebooks" in VS Code's Extensions marketplace (official package: GoogleCloudTools.workbench-notebooks)
• Select a Workbench kernel by opening a notebook file, clicking the Kernel selector in the toolbar, and choosing Workbench from the Google Cloud menu
• Authenticate with your Google Cloud account and select your project and active Workbench instance

Once configured, notebooks run directly on cloud compute while preserving your local VS Code settings and extensions.

Open-Source and Community-Driven#

True to its commitment to the developer ecosystem, Google has open-sourced the extension. The project lives on GitHub, inviting developers to contribute improvements and shape the tool's direction. The extension is available now in the VS Code Marketplace.