Manage Multi-tenant ML Workloads Using Istio

With rapid growth of machine learning workloads deployed on Kubernetes, it is becoming a popular demand to offer a multi-tenant pipeline to manage machine learning workloads that facilitates different …

With rapid growth of machine learning workloads deployed on Kubernetes, it is becoming a popular demand to offer a multi-tenant pipeline to manage machine learning workloads that facilitates different data scientists to collect data, train and serve models on kubernetes. Come learn how Istio can be integrated into a multi-tenant machine learning pipeline like Kubeflow to provide isolation and protection of workloads deployed for different users through sufficient identity, access, and api management