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databricks Platform · Updated Nov 5, 2025

Serverless notebook tasks can now use jobs environment

The ability to use a job environment in serverless notebook tasks is now generally available, allowing you to use the notebook's environment or select a specific job environment.

What it does

The ability to use a job environment in serverless notebook tasks is now generally available, allowing you to use the notebook's environment or select a specific job environment. Previously, serverless notebook tasks always inherited the serverless environment from the notebook. This page explains how to configure the serverless environment for notebooks and job tasks.

Why it matters

When a job runs, any task that shares the same set of dependencies as a completed task in the same run finishes faster, because the cache already contains the required dependencies.

Key capabilities
Previous versions of Standard, ML
Previous versions of Standard, ML, and AI environments.
Custom: Specify a custom environment
Custom: Specify a custom environment using a YAML file. Workspace environments: Lists all compatible base environments…
Architecture
Databricks Platform → Platform
In short

The ability to use a job environment in serverless notebook tasks is now generally available, allowing you to use the notebook's environment or select a specific job environment. Previously, serverless notebook tasks always inherited the serverless…

Read the full documentation ↗
Key takeaway
The ability to use a job environment in serverless notebook tasks is now generally available, allowing you to use the notebook's environment or select a specific job environment.
2025-11-05-serverless-notebook-tasks-can-now-use-jobs-environment Generated by the Databricks Updates Agent · browse all updates