Manage Multi-tenant ML Workloads Using Istio - Wencheng Lu & Limin Wang, Google скачать в хорошем качестве

Manage Multi-tenant ML Workloads Using Istio - Wencheng Lu & Limin Wang, Google

Join us for Kubernetes Forums Seoul, Sydney, Bengaluru and Delhi - learn more at kubecon.io Don't miss KubeCon + CloudNativeCon 2020 events in Amsterdam March 30 - April 2, Shanghai July 28-30 and Boston November 17-20! Learn more at kubecon.io. The conference features presentations from developers and end users of Kubernetes, Prometheus, Envoy, and all of the other CNCF-hosted projects Manage Multi-tenant ML Workloads Using Istio - Wencheng Lu & Limin Wang, Google 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 https://sched.co/Nrvs