Wednesday, November 20 • 3:20pm - 3:55pm
Kubeflow: Multi-Tenant, Self-Serve, Accelerated Platform for Practitioners - Kam Kasravi, Intel & Kunming Qu, Google

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The kubeflow platform provides a self-serve multi-tenant platform on k8s for ML developers. Users can train their models using accelerated hardware in an isolated environment. Jobs can be configured and triggered from a notebook with no devops involvement. We leverage optimized libraries such as Intel® DAAL, Intel® MKL-DNN now included in tensorflow 1.14.+. Models can be monitored using Application CR deployed with kubeflow. All attendees can join the demo, create their own workspace and try out features. Attendees will walk away understanding how to run multi-tenancy on Kubernetes with kubeflow.

Self-serve multi-tenant workplace
Workspace owners can share / revoke access
System admin can reset access policy & resource quota per workspace
Multi-tenancy service is transparent to other apps.
A UI is available to simplify user experience.

avatar for Kunming Qu

Kunming Qu

Software Engineer, Google
Kunming Qu is a software engineer at Google working on Kubeflow project, a k8s based platform to help developers and enterprises deploy and use ML cloud-natively everywhere. He's been focusing on Kubeflow deployment experience; Identity-Aware integration; multi-tenancy cluster; enabling... Read More →
avatar for Kam Kasravi

Kam Kasravi

Senior Software Engineer, Intel
Kam works at Intel and is an early contributor to kubeflow. His focus has been on multi-tenancy, the kfctl/kustomize cli, device/hardware integration and application CR composition. Kam speaking history includes Scala conferences and a number of Kubernetes/Kubeflow related user meetings... Read More →

Wednesday November 20, 2019 3:20pm - 3:55pm
Room 17AB - San Diego Convention Center Mezzanine Level