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:
- The history of Kubernetes, and why it has risen to prominence in IT infrastructure management.
- Challenges in scaling data science, and foundational architectural decisions.
- How virtualized, containerized data science workloads set the foundation for AI adoption in the enterprise.