Enabling auto-shutdown of idle computes in Machine Learning causes shutdowns during active jobs

Question

We have enabled the preview feature “Configure auto-shutdown for idle compute instances” in Azure Machine Learning.   I set this to, for example, 60 minutes for a given compute instance in the “Schedules” tab when navigating to the compute instance.  When I do this it appears to be shutting down 60 minutes after the compute was started, independent of if any jobs were started or are currently running.

Is there another way this setting should be enabled so that it allows any jobs to complete, and then shuts down after the period of inactivity?

Answer 1

Did you use the feature "Idle Shutdown"?

https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-manage-compute-instance?tabs=python#enable-idle-shutdown-preview

As per the documentation, a compute instance is considered inactive if the below conditions are met:

• No active Jupyter Kernel sessions (which translates to no Notebooks usage via Jupyter, JupyterLab or Interactive notebooks)
  

• No active Jupyter terminal sessions
  

• No active AzureML runs or experiments
  

• No SSH connections
  

• No VS code connections; you must close your VS Code connection for your compute instance to be considered inactive. Sessions are auto-terminated if VS code detects no activity for 3 hours.
  

Answer 2

Use only lowercase characters for your compute instance name.
I know it sounds stupid but we had the same issue and the support suggested that "using the naming convention with multiple lower and upper case characters sometimes cause backend querying errors".