How to isolate environments for different projects in a single mlflow server?

[HemanthVak]

I am planning to deploy MLFlow server deployed in Azure as a centralised repositories for my machine learning experiments and runs and to store events and artifacts. I would like to have different environments or isolated environments in the same workspace as Dev & Prod

[Debayan]

Hi,

Virtualenv environments support Python packages available on PyPI. When an MLflow Project specifies a Virtualenv environment, MLflow will download the specified version of Python by using 

pyenv and create an isolated environment that contains the project dependencies using 

virtualenv, activating it as the execution environment prior to running the project code.

You can specify a Virtualenv environment for your MLflow Project by including a python_env entry in your MLproject file.

Please refer: https://www.mlflow.org/docs/latest/projects.html

[Anonymous]

Hi @Hemanth Vakacharla​ 

Does @Debayan Mukherjee​  response answer your question? If yes, would you be happy to mark it as best so that other members can find the solution more quickly?

We'd love to hear from you.

Thanks!