Manage Multi-tenant ML Workloads Using Istio - Wencheng Lu & Limin Wang, Google
Автор: CNCF [Cloud Native Computing Foundation]
Загружено: 2019-07-05
Просмотров: 262
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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
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