It depends on how complex your configuration is, but if config elements are all that will change between versions (i.e. not the code itself) then you could consider using parameter overrides.

A ClearML Task can have a number of "hyperparameters" attached to it. But once that task is cloned and in draft mode, one can EDIT these parameters and change them. If then the task is queued, the new parameters will be injected into the code itself.

A pipeline is no different, it can have pipeline parameters that are accessible in the code. When cloning the pipeline using the TaskScheduler you can easily override these parameters 🙂

References: https://clear.ml/docs/latest/docs/pipelines/pipelines_sdk_tasks#pipeline-parameters
https://youtu.be/MX3BrXnaULs?t=162