Microsoft today announced new capabilities for its Azure Arc service (opens in new tab) that will make it useful for what it hopes are a wide number of various cloud computing (opens in new tab) use cases.
Azure Arc allows users to manage their servers and Kubernetes clusters (opens in new tab) across on-premises, multi-cloud, and edge devices, as well as with other cloud platforms such as Google Cloud and AWS (opens in new tab).
“Customers tell us a key challenge with hybrid and multicloud adoption is managing and securing their IT environments while building and running cloud-native applications,” wrote Arpan Shah General Manager, Microsoft Azure (opens in new tab) to highlight the importance of Azure Arc.
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More data services
Azure data services were one of the first sets of services that users could run on any Kubernetes environment via Azure Arc, Shah noted as he revealed the new functionalities.
Based on feedback from customers such as KPMG, Ford, Ferguson, and SKF, the Azure Arc enabled data services has been enhanced to include Azure Machine Learning as well.
“By using Azure Arc to extend machine learning (ML) capabilities to hybrid and multicloud environments, customers can train ML models directly where the data lives using their existing infrastructure investments. This reduces data movement while meeting security and compliance requirements,” explains Shah.
Along with this, Microsoft also announced the general availability of Azure Arc enabled Kubernetes as its Spring Ignite event got underway today.
Microsoft already collaborates with several popular Kubernetes distributions including RedHat OpenShift, Canonical’s Charmed Kubernetes, and Rancher Kubernetes Engine (RKE) to ensure they integrate with Azure Arc. Shah also announced that VMware Tanzu and Nutanix Karbon are joining the list of supported Kubernetes distributions.
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