Manage Multi-tenant ML Workloads Using Istio

Explore how Istio can be integrated into multi-tenant machine learning pipelines like Kubeflow in this informative conference talk. Discover the benefits of using Istio for managing multi-tenant ML workloads on Kubernetes, including workload isolation and protection through identity, access, and API management. Learn about Istio's architectural components, challenges in multi-tenancy, and practical applications in Kubeflow. Gain insights into user access isolation through end-user authentication and authorization, as well as Istio's traffic management capabilities. Watch a demonstration and find out how to participate in this growing field of machine learning workload management on Kubernetes.

Intro
What does Istio do?
Istio Architectural Components
Multi-tenant ML Workloads
Challenges on Multi-Tenancy
Case Study: Kubeflow
User Access Isolation: End User Authentication
User Access Isolation: Authorization
Istio Traffic Management
Demo
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