March 2019
These features and Azure Databricks platform improvements were released in March 2019.
Note
Releases are staged. Your Azure Databricks account may not be updated until up to a week after the initial release date.
Purge deleted MLflow experiments and runs
March 26 - April 2, 2019: Version 2.94
You can now permanently purge deleted MLflow experiments and runs. See Purge workspace storage.
Manage groups from the Admin Console
March 12 - March 19, 2019: Version 2.93
Admins can now create groups using the new Groups tab in the Admin Console. Use the Groups tab to add users, add subgroups, grant members the ability to create clusters, and manage parent-child group relationships.
See Manage groups.
Notebooks automatically have associated MLflow experiment
March 12 - March 19, 2019: Version 2.93
Every notebook in an Azure Databricks Workspace now has an associated MLflow experiment. You record runs in the notebook’s experiment using MLflow tracking APIs by referring to its experiment ID or experiment name. If you use the Python API in MLflow 0.9.0 or above, MLflow automatically detects the notebook experiment when you create a run.
To view the MLflow experiment associated with a notebook, click the Experiment icon 
in the Azure Databricks notebook’s right sidebar.
See Create notebook experiment.
Lsv2 series instance types (Beta)
March 12 - March 19, 2019: Version 2.93
Azure Databricks now provides Beta support for the Lsv2 VM series for high-throughput and high-IOPS workloads.
Databricks Delta public community
March 8, 2019
With Delta Lake now GA, we have created a public community for developers to get started, discuss articles, and get help.
Note
These forums are public. Do not use them to share confidential information with Azure Databricks representatives or with other users.