Share serverless compute among notebooks in Asset Bundles

The Shared Serverless for Asset Bundles feature allows multiple notebooks and files within the same bundle to use the same serverless compute and a centralized environment. This simplifies project execution and dependency management.### Use casesImagine you have a project with multiple notebooks that require the same libraries and dependencies. With this feature, you centralize the configuration and avoid recreating environments for each file. What you can do:- Share serverless compute among files in the same bundle.- Define dependencies and environment uniformly in the pyproject.toml file.- Optimize compute resource usage in projects based on Databricks Asset Bundles.### How to useTo use this feature, workspace administrators must first enable Project-Scoped Shared Compute on the Databricks Previews page. Then, configure your project environment in the pyproject.toml file at the root of the bundle.### Limitations and requirements- The feature is in Beta.- It is not intended for production use.- Available for workspace admins to enable on the Previews page.