It depends. Give you an example: We have an expensive reporting workflow that needs considerable resources, but usually only once a month. Two ways to do this cost effectively: Scale down containers to zero, meaning several minutes of response time if you do need it ad-hoc sometime. At least as complex to configure. OR you fit it to AWS SAM. The latter has proven to be a good match for us. I solved the debugging story by keeping lambda functions AWS agnostic and wrapping them i a Flask debug server - will respond exactly the same but it is all local in a single process.
I’m the head of product for Temporal. You should check us out, have to self host (MIT) right now but we are working on a cloud. You can safely write code that blocks for years. No more job queues.
I suppose you mean temporal.io, but just FYI, the first google result for me was https://github.com/RTradeLtd/Temporal which is far but not far enough to be “obviously unrelated”.
You might want to give a link next time to avoid ambiguity.
