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In Azure AI | Machine Learning Studio on 'Code and environment for inferencing' and 'Select environment type' Issue

Timothy Moore 20 Reputation points
2025-08-10T21:15:01.0866667+00:00

I am trying to add a Custom environment and scoring script in Azure AI | Machine Learning Studio here when i get to the Code + environment tabUser's image

I add the script that Copilot helped me create I change the environment to 'Custom environment' I select the environment that Copilot helped me create.

User's image

i click next. when i get to the Review sections it still says

Environment

Scoring script and environment are auto generated

when i go back to the 'Code + Environment' tab. the environment has change back to 'Curated environment' even though i had selected Custom environment as you can see in the print screen above. My Scoring script is still there but the Environment type keeps changing back

User's image

I have tried everything i and Copilot could think of to get it to save and nothing works.

How do i get this to work?

Azure Machine Learning
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Accepted answer
  1. Sina Salam 22,576 Reputation points Volunteer Moderator
    2025-08-11T08:57:24.9+00:00

    Hello Timothy Moore,

    Welcome to the Microsoft Q&A and thank you for posting your questions here.

    I understand that your Azure AI / Machine Learning Studio is having issue on 'Code and environment for inferencing' and 'Select environment type'.

    This is a known issue in the Azure AI | Machine Learning Studio. As of today the review step still says, "Scoring script and environment are auto generated." However, in my opinion and as best practices. I recommend that you register and use a workspace environment and deploy via CLI/SDK does avoid the Studio UI bug and will make deployments use your custom environment consistently. Use the below suggested links as alternative workaround to work manually or use CLI:

    1. Manage and register custom environments in Azure ML - https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-environments-in-studio
    2. Manage environments with the CLI & YAML - https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-environments-v2?view=azureml-api-2
    3. Deploy models with a registered custom environment (CLI v2) - https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-online-endpoints?view=azureml-api-2
    4. Azure ML environments concept page - https://learn.microsoft.com/en-us/azure/machine-learning/concept-environments?view=azureml-api-2

    I hope this is helpful! Do not hesitate to let me know if you have any other questions or clarifications.

    Please don't forget to close up the thread here by upvoting and accept it as an answer if it is helpful.

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