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databricks Platform · Updated Jan 20, 2026

You can now use custom base environments for Python, Python Wheels, and…

Serverless jobs now support custom base environments defined with YAML files for Python, Python wheel, and notebook tasks.

Update Open docs ↗release note ↗
What it does

Serverless jobs now support custom base environments defined with YAML files for Python, Python wheel, and notebook tasks. For notebook tasks, you can either select a custom base environment in the job’s environment configuration or use the notebook’s own environment settings, which support both workspace environments and custom base environments. This page explains how to create and manage workspace base environments across a workspace.

Why it matters

When a workspace base environment is selected, the pre built cached environment loads quickly, reducing startup time for notebooks and jobs.

Key capabilities
--index-url https://pypi.org/simple
--index-url https://pypi.org/simple
-r "/Workspace/Shared/requirements.txt"
-r "/Workspace/Shared/requirements.txt"
my-library==6.1
my-library==6.1
/Workspace/Shared/Path/To/simplejson-3.19.3-py3-none-any.whl
/Workspace/Shared/Path/To/simplejson-3.19.3-py3-none-any.whl
Architecture
Databricks Platform → Platform
In short

Serverless jobs now support custom base environments defined with YAML files for Python, Python wheel, and notebook tasks. For notebook tasks, you can either select a custom base environment in the job’s environment configuration or use the notebook’s own…

Read the full documentation ↗
Key takeaway
Serverless jobs now support custom base environments defined with YAML files for Python, Python wheel, and notebook tasks.
2026-01-20-ad16808f Generated by the Databricks Updates Agent · browse all updates