Running Machine Learning Workloads on a Service Mesh

Explore the integration of service mesh technology with machine learning workloads in this 26-minute conference talk from the Cloud Native Computing Foundation (CNCF). Discover how a service mesh can enhance data security, resilience, and observability for machine learning services and applications. Learn about the journey of adding Istio ServiceMesh support to JupyterHub, a popular open-source tool for machine learning environments. Delve into the challenges faced, troubleshooting processes, and the benefits of using Istio for securing and operating machine learning workloads. Gain insights into combining network policies and security best practices for running workloads on Kubernetes, creating an optimal balance between operational efficiency and usability.

Introduction
Agenda
Background
What is Machine Learning
The Problem
Compliance Audit
Deployments
Conclusion