#azure-kubernetes-service

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#ray-distributed-computing #gpu-resource-management #multi-region-deployment #ml-infrastructure #ray #anyscale
DevOps
fromInfoQ
16 hours ago

Running Ray at Scale on AKS

Microsoft and Anyscale provide guidance for running managed Ray service on Azure Kubernetes Service, addressing GPU capacity limits, ML storage challenges, and credential expiry issues through multi-cluster, multi-region deployment strategies.
Artificial intelligence
fromInfoWorld
3 months ago

Running managed Ray on Azure Kubernetes Service

Anyscale's managed Ray on Azure Kubernetes Service enables building, training, and running large-scale PyTorch ML models without managing distributed infrastructure.
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