Azure Kubernetes Service#

This guide offers recommended configurations and settings unique to Azure Kubernetes Service (AKS). These should be used to augment the generic requirements offered on our primary requirements page.

Instance types#

  • Minimum: Standard_D8s_v4

  • Recommended: Standard_D16s_v4

Storage#

Unfortunately, we have found that Azure’s built-in, managed Network File System (NFS) service, Azure Files NFS, does not provide an acceptable performance level for use with Data Science & AI Workbench. We have not yet had the opportunity to evaluate Azure NetApp Files.

For this reason, Anaconda recommends creating a separate Virtual Machine for hosting NFS storage. Follow the recommendations offered in this document, with these Azure-specific recommendations:

  • The Standard_D4s_v3 machine type is suitable for this purpose.

  • Azure tightly couples disk size and IOPS performance. Anaconda recommends a minimum disk size of 1 TiB to ensure good performance.

Note

This server can be the administration server as well.

Network#

Azure offers two different networking options for AKS clusters. Both approaches are compatible with Workbench, so the determination depends upon your larger networking needs.

Note

AKS uses a LoadBalancer which by default sets TCP idle timeouts to 4 minutes, and enables TCP resets. This may affect any user workload that depends on a continuous TCP connection.

GPUs#

Please see this Azure guide for adding GPU resources to your AKS cluster.

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