Retry pipeline and/or task on failure

I use the Python SDK to develop ML pipelines for Azure ML.

How do I get my PythonScriptStep tasks or the encompassing Pipeline object to simply rerun upon failure?
I reckon it's pretty common for pipelines to temporarily break upon temporary network, storage, etc. issues so a simple rerun / retry seems pretty basic for task orchestration frameworks to provide (see e.g. Apache Airflow).

I've spent a fair amount of time going over the documentation for Azure ML and I just can't figure out how to get "retry upon failure" behaviour.

The closest there is is the continue_on_step_failure pipeline / task parameter which doesn't really do what's needed.

Any advice please?

I've tried finding a solution on SO over here - a proposed solution uses external tools which just adds more overhead:

https://stackoverflow.com/questions/68647922/azure-machine-learning-pipeline-how-to-retry-upon-failure

Comece pela documentação do Azure ML Python SDK sobre PythonScriptStep, Pipeline e continue_on_step_failure e, em seguida, compare a proposta vinculada do Stack Overflow. Nenhum arquivo do repositório ou teste é identificado; o trabalho estaria concluído com um comportamento de retry claramente suportado ou com um notebook mínimo reproduzível e etapas de validação que esclareçam a alteração solicitada.

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