Hybrid Cloud Machine Learning on Kubernetes with Azure Arc - The New Stack

Azure Arc is Microsoft's hybrid solution for getting the simplicity and value of cloud services on any infrastructure, by putting a representation of that infrastructure in Azure so the automation, monitoring and policy tools that work in the cloud can manage it too. Arc started with servers, VMs, Kubernetes and SQL Server databases -- an on-premises equivalent of IaaS -- and moved on to bring cloud PaaS services to the infrastructure you manage with Arc, starting with putting Azure Data Services on Kubernetes containers. The next Azure service to come to Arc is machine learning, which you can now use to run training locally on the data in the databases you're managing with Arc. That could be data in a different cloud that you don't want to copy to Azure, incurring data egress costs and latency, data you want to keep in your own data center for regulatory reasons, or data you want to process at the edge so you can act on it immediately. Arc-enabled Machine Learning will be useful at the edge for workloads like predictive maintenance, monitoring assets in the field for failure or analyzing activity in retail locations, where you don't have the connectivity or bandwidth to use cloud services.