Model serving and model metadata management are the two skills that separate the A.I. engineers above the data scientists. However there is shockingly limited tools and guides on how to do this effectively (especially compared to the effectively infinite galaxy of tutorials on LSTMs, RNNs, CNNs, and other Data Science / Machine Learning models). Kubeflow has a suite of tools that address these two areas of A.I. engineering where so few choose to tread. In this talk we'll discuss how to use Kubeflow's Artifact Store (model metadata management tool) and KFServing (Kubeflow's model serving abstraction). Users will be amazed as we quickly overview the mechanics of each piece and then dive straight into practical tips and tricks for utilizing these tools in Kubeflow.