Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA

Skyler Thomas
Engineer, MapR

Skyler Thomas is an engineer at MapR, where he is designing Kubernetes-based infrastructure to deliver machine learning and big data applications at scale. Previously, Skyler was chief architect for WebSphere user experience at IBM, where he worked with more than a hundred customers to deliver extreme-scaled applications in the healthcare, financial services, and retail industries.

Sessions

5:10pm–5:50pm Wednesday, March 27, 2019
Persistent storage for machine learning in KubeFlow
Data Engineering & Architecture
 Location: 2008
Secondary topics:  AI and Data technologies in the cloud, Model lifecycle management, Storage
Skyler Thomas (MapR), Terry He (MapR Technologies)
Average rating: ****.
(4.75, 4 ratings)
KubeFlow separates compute and storage to provide the ability to deploy best-of-breed open source systems for machine learning to any cluster running Kubernetes, whether on-premises or in the cloud. Skyler Thomas and Terry He explore the problems of state and storage and explain how distributed persistent storage can logically extend the compute flexibility provided by KubeFlow. Read more.