So I've got an Azure Machine Learning pipeline here that consists of a number of `PythonScriptStep` tasks - pretty basic really.

Some of these script steps fail intermittently due to network issues or somesuch - really nothing unexpected. The solution here is always to simply trigger a rerun of the failed experiment in the browser interface of Azure Machine Learning studio.

Despite my best efforts I haven't been able to figure out how to set a retry parameter either on the script step objects, the pipeline object, or any other AZ ML-related object.
This is a common pattern in pipelines of any sort: Task fails once - retry a couple of times before deciding it actually fails.

Does anyone have pointers for me please?

Edit: One helpful user suggested an external solution to this which requires an Azure Logic App that listens to ML pipeline events and re-triggers failed pipelines via an HTTP request. While this solution may work for some it just takes you down another rabbit hole of setting up, debugging, and maintaining another external component. I'm looking for a simple "retry upon task failure" option that (IMO) must be baked into the Azure ML pipeline framework and is hopefully just poorly documented.