> Option 2 - Hand it off to DevOps. The other option is to have data science produce prototypes that can be on Notebooks and then have a devops team whose job is to refactor those into an application that runs in production. This process makes things less fragile, but it is slow and very expensive.
I've never understood why this is so hard. Every time data science gives me a notebook it feels like I have been handed a function that says `doFeature()` and should just have to put it behind an endpoint called /do_feature, but it always takes forever and I'm never even able to articulate why. It feels like I am clueless at reading code but just this one particular kind of code.
I've never understood why this is so hard. Every time data science gives me a notebook it feels like I have been handed a function that says `doFeature()` and should just have to put it behind an endpoint called /do_feature, but it always takes forever and I'm never even able to articulate why. It feels like I am clueless at reading code but just this one particular kind of code.