Machine learning promises to address many of the challenges faced by network security analysts; however, there are still many obstacles that prevent widespread adoption of machine learning within security operations centers (SOC). The first major challenge is one of trust as discussed in our previous post. The second major set of challenges is around the complexity of deploying machine learning in a production environment. Once a machine-learning model has been trained and validated in the lab, there is often an equal if not larger effort required to deploy that model in a repeatable, production environment.\Transitioning Data science typically operates using an iterative batch process.