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

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

HemanthVak — Thu, 22 Sep 2022 16:44:30 GMT

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

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

Anonymous — Thu, 13 Oct 2022 09:47:18 GMT

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!

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

Debayan — Fri, 23 Sep 2022 08:21:19 GMT

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