Is there any limitations for the number of runs per user in each experiment in Azure ML?

Elahe Dorani 21 Reputation points
2022-06-06T15:43:51.357+00:00

I and my team members are working on a machine learning project through the Azure ML portal. We have created a specific experiment in our workspace in Azure ML and are submitting our Python script runs from our local or remote machines in this experiment.

Although I'm collaborating with my colleagues, most of the runs in this specific experiment are submitted by me.

Recently, I have faced a problem with experiment submissions. The problem is that after some number of experiments created by me, I cannot add any other runs to this experiment, but my colleagues can!!!

Unfortunately, the Azure ML portal does not show any clear error message for this problem. It continues submitting the run till a timeout exception occurs!

As a temporary solution, I've just changed the name of the experiment and I could conquer this problem.

This solution helped me to submit my run on Azure ML but it didn’t satisfy me because. We want to collect all related runs under a specific experiment. On the other hand creating multiple number of experiments for each run is overwhelming!

What I know is that there are some service limits for the number of runs in a workspace on this page. I am sure that the number of runs in our workspace has not reached to the 10 millions, because I can created new runs under new experiments dashboard. But I don’t know anything about the limitations on the number of runs in a specific experiment or even any limitations for the number of runs per users in a specific experiment. I couldn't find any clear document explaining this fact.

Is there anyone who can help me for this issue?

I have also put myquestion in StackoverFlow. I would be grateful if you could help me with this issue.

Azure Machine Learning
Azure Machine Learning
An Azure machine learning service for building and deploying models.
3,112 questions
{count} votes

Your answer

Answers can be marked as Accepted Answers by the question author, which helps users to know the answer solved the author's problem.