I'd love to hear both of your thoughts! I'm considering durable execution and DBOS in particular and was pretty happy to see Armin's shot at this.

I'm building/architecting a system which will have to manage many business-critical operations on various schedules. Some will be daily, some bi-weekly, some quarterly, etc. Mostly batch operations and ETL, but they can't fail. I have already designed a semblance of persistent workflow in that any data ingestion and transformation is split into atomic operations whose results are persisted to blob storage and indexed in a database for cataloguing. This means that, for example, network requests can be "replayed", and data transformation can be resumed at any intermediate step. But this is enforced at the design stage, not runtime like other solutions.

My system also needs to be easily auditable and written in Python. There are many, many ways to build this (especially if you include cloud offerings) but, like Armin, I'm trying to find the simplest architecture possible so our very small team can focus on building and not maintaining.