How to deploy ML models in production? Have been learning Machine Learning concepts and doing hands-on past few months. Now got a bit different doubt than implementation of code. 

This is regarding measures to be considered while deploying in a Prod environment, say something like "A newbie's checklist to ML production" example - 


Are Feedback loops always considered?
Is cross-validation done in final prod model or only during train/test the model?
How the auto-suggestion in Amazon or any ecommerce website works? - Meaning does the model get trained on every page load or already pre-trained and just predicts (suggests) based on user selections?


I know the questions are too general and newbie, but will help many to understand the concepts relating to real-world. Please advise. 

Let me know for any further information and I will be happy to furnish/respond.
I got some pointers (below links) to my doubts. Hope it helps other future readers as well.


https://www.quora.com/How-do-you-take-a-machine-learning-model-to-production/answer/H%C3%A5kon-Hapnes-Strand
https://www.quora.com/Do-most-machine-learning-algorithms-run-in-batch-or-do-they-run-every-time-they-get-a-new-bit-of-data/answer/H%C3%A5kon-Hapnes-Strand


Will keep updating this space as and when I get some good answer(s) regarding this.