The secret formula for MLOps success

"I was a happy data scientist until we decided it was time for deploying our models." It is common among many DS/ML teams that when the time for productionizing the model comes, they are caught off guard due to poor planning. Of course, thinking solely about the end is far from enough, the stages beforehand are equally as important. To reach the end of any endeavor we need to be strategic, the same applies for succeeding with MLOps. One such strategy is to take on a less challenging problem or part of it in the beginning and find the easiest way it can be solved.