Many data scientists want to operationalize their models. If you don't work at a hip startup with a killer dev ops team, then you are likely at a big enterpris

Many data scientists want to operationalize their models. If you don't work at a hip startup with a killer dev ops team, then you are likely at a big enterprise shop where relying on anyone else to handle your infrastructure for you is a great way to have 90% of your work never see the light of day. I use Docker daily for my needs. It ensures that I can easily prototype a scalable set of services on my local machine, and then deploy it to a multi-node environment on AWS, Gcloud, or our on-prem infrastructure. Good luck developing a Redis-backed ML app without Docker when it comes time for deployment. You'll get it done, but it'll be a lot slower and more difficult than if you had used Docker or containers of some sort. Edit: Make sure to check out Yhat. https://www.yhat.com/ https://www.yhat.com/