Azure Machine Learning Networking (Hands-on)

This video explains and shows you how to deploy networking end to end for Azure Machine Learning for securing your ML environment access. For Azure machine learning behind the virtual network, it will explain how to get access to your workspace using:
1) Jumpbox VM ( Azure BAstion)
2) Point to site VPN
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The example code utilized in the video:
techcommunity.microsoft.com/t...
Point to Site VPN:
docs.microsoft.com/en-us/azur...
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#AzureMachineLearning #Networking#AzureMLNetworking #ComputeCluster#Azure #AI #ML #MachineLearning #AzureVirtualNetwork #VirtualNetwork #AzureFirewall #AzurePrivateEndpoints

[@victorsaraiva9487]

wow! so much content presented and very well presented. Thanks for all the hard work and sharing your experience

[@mcdonamw]

This has been very helpful. Thank you.

[@s.sasisekhar4608]

Awesome content 🎉❤

[@pulsorion]

Top!

[@dhulabrothers4552]

I've a question here. I'm setting up the similar environment for one our client but the only difference is they're using hub and spoke architecture in that the firewall is in hub and separate spokes are created for azure ML and VM workstations, we have vnet peering enabled with all of the hub and spoke vnets. When it comes to FW rules what exactly we have to configure so that we will be able to connect azure ML services with VM. The rules we were thinking of have FQDN names of private endpoint DNS zones for each service like keyvault, acr, azureML to TCP 443 ports. Will that enough to handle the connection from VM?

[@TumBBBu]

Any sources to apply a Hub-Spoke topology with Machine Learning (so that machine learning is in its own spoke with own virtual network, not inside the hub?