Cluster Access Mode in Databricks

Recently, while working on an AutoML use case in our current project, we encountered a situation where the entire team needed to collaborate using a single cluster, rather than spinning up separate clusters for each member.

Naturally, the first question was: Why not use a standard Shared cluster?
Well, at the moment, Databricks has certain limitations with AI/ML libraries on Shared clusters — which made that option unfeasible for our use case. The only viable alternative was to use a Dedicated cluster with group access.

So, what’s next?
We brought this challenge to the Databricks team, and to our surprise, they were incredibly supportive. After our discussion, they enabled this capability in GA.
This unlocked the exact setup we needed to move forward efficiently as a team.

When working with Databricks clusters, especially in environments governed by Unity Catalog, the Access Mode of a cluster plays a critical role in determining who can access what, how securely, and with what limitations.

In this article, we’ll break down what Cluster Access Modes are, when to use each one, and how they tie into governance, performance, and team collaboration.

What is Cluster Access Mode?

Cluster Access Mode controls how users interact with a Databricks cluster — whether they have isolated environments, shared sessions, or limited permissions. This is essential…