Too Long; Didn't Read
Machine Learning(ML) world is that it takes a lot longer to deploy ML models to production than to develop it. Modern software requires a variety of crucial properties such as on-demand scaling and high availability. It might take a lot of effort and time to correctly deploy models into productions. Let’s discuss some different options you have when it comes to deploying ML models. Models can be easily wrapped into specially designed servers such as NVIDIA Triton or Tensorflow. The most direct way to deploy anything is to rent a VM, wrap a model into some kind of server and leave it running.