It seems you have a specific workflow in mind, but I'm not sure I follow it. Can you give a specific example ?

Absolutely. So, let's say a DS tags a model in ClearML with "release candidate". It'd be great to have that trigger a number of processes, each with their own retry logic:

• A fairness/bias evaluation, potentially as a task in ClearML itself. This would load the model and run some sample datasets through it. The
• Pipeline to prepare for deployment. Trigger a GitHub Actions pipeline that downloads the model weights and builds them into a docker image together with FastAPI or BentoML code. The build could fail and it'd be nice to have retries/dead letter queue for that.
• An approval process: Add a line item in our internal frontend application which shows models that are meant to be reviewed. The logic for this submission lives in AWS lambda. It'd be good for this to have retries/dead letter queue in case our Lambda function fails.
• Documentation: execute a Lambda function that generates a report about this model in Notion. Our lambda that makes the Notion API calls may fail, so this could do to have retries/dead letter queue.