MLOps FMEA: A Proactive & Structured Approach to Mitigate Failures and Ensure Success for Machine Learning Operations

Abstract

Machine learning applications have seen an exponential rise in prevalence across many different industries including healthcare, banking, manufacturing, and defense. While there is a lot of potential for machine learning applications, successful development and productionization is not assured. To prevent failures and ensure success, a Machine Learning Operations (MLOps) Failure Modes and Effects Analysis (FMEA) is proposed as a proactive structured approach for risk identification and mitigation.