Kubernetes, an open-source container orchestration system, is becoming the consensus API for infrastructure for IT professionals. For data scientists, the once-onerous task of environment and package management is made tremendously easier by containers. And Kubernetes brings a whole new set of benefits for data scientists, including making models portable and reproducible, handling bursty compute requirements of AI workfloads, and future-proofing infrastructure. In this panel discussion moderated by Chris Yang, CTO and co-founder of Domino Data Lab, Craig McLuckie, VP of R&D at VMware and Kubernetes Project co-founder, and Chris Lamb, vice president of GPU computing platforms at NVIDIA, will discuss challenges in scaling data science — and how virtualized, containerized data science workloads set the foundation for AI adoption in the enterprise.