A Vision for Kubernetes as the Foundation for Enterprise MLOps
Learn from innovators in Kubernetes and GPU-accelerated data science
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.
Craig McLuckie
Vice President of R&D, VMware & Kubernetes Project Co-Founder, VMware
Craig is an entrepreneur and innovator in cloud and enterprise software, passionate about reducing the complexity of building and operating IT systems. He's currently a VP of R&D at VMware, leading the engineering, product management, and site reliability engineering team for Tanzu.
Craig was CEO and founder of Heptio, acquired by VMware in November 2018. Prior to this, Craig founded the Kubernetes Project, started the early growth of Google Kubernetes Engine, and conceived, bootstrapped, and chaired the Cloud Native Computing Foundation. He also served as the original product lead for Google Compute Engine.
Craig McLuckie
Vice President of R&D, VMware & Kubernetes Project Co-Founder, VMware
Chris Yang
CTO and Co-Founder, Domino Data Lab
Chris Yang is CTO and co-founder of Domino Data Lab. His focus is exploring and delivering innovative product ideas that can accelerate our customers' delivery of ML models. Before founding Domino, Chris worked at Bridgewater, one of the world’s largest hedge funds, working directly with senior research leadership to prototype and deliver their next-generation investment platform.
He holds a B.S. in computer science and a master's degree from MIT, having published papers on both computer vision and distributed databases.
Chris Yang
CTO and Co-Founder, Domino Data Lab
Chris Lamb
Vice President, GPU Computing Software Platforms, NVIDIA
Christopher runs a worldwide team building platforms for parallel high-performance computing and AI/deep learning across HPC, enterprise data center, cloud, edge/internet of things, embedded, and automotive. He works on the world's most powerful supercomputers to design the smartest self-driving cars, and everything in-between.
Chris leads the team that delivers CUDA (the world's most popular parallel programming platform), DGX systems (at the leading edge of GPU-powered computers), Saturn V (NVIDA's cloud-native supercomputing infrastructure built on DGX, NGC, which enables GPUs to be utilized at scale in every datacenter and every server), and Aerial (the worlds most powerful software-defined 5G radio stack).
Chris Lamb
Vice President, GPU Computing Software Platforms, NVIDIA
Kubernetes in Data Science
You’ll hear directly from innovators on the history of Kubernetes and why it is essential for scaling data science across the enterprise.
Foundational Decisions for Enterprise Scale
Learn how you can avoid applying an "on-prem mentality" to managing kubernetes clusters, as well as the foundational architectural decisions that must be made for enterprise-wide AI adoption.