Hybrid Cloud Machine Learning on Kubernetes with Azure Arc. 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.
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. That’s an “evergreen” database service (for SQL Server or PostgresDB) with the continuous updates, automation and elasticity of a cloud service, just on your own hardware or your infrastructure in other clouds.
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.
Our original Kubernetes tool list was so popular that we've curated another great list of tools to help you improve your functionality with the platform.
In a series of blog posts, I am planning to write down my experiences of training, deploying and managing models and running pipelines with Azure Machine Learning Service.
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