Sovereign Cloud: Microsoft Enhances Azure Local. Customers Can Now Scale Workloads Across Thousands of Servers
Data sovereignty is no longer just a matter of where information resides. It is becoming a question of architecture. Who controls the infrastructure? Where do workloads run? Who governs policies, access, auditing, updates, AI models, and operational dependencies?
For this reason, more and more companies, including hyperscalers, have begun to offer sovereign cloud infrastructures in Europe, on which customers can securely run their workloads, even when sensitive data such as health or financial information is involved.
Among the solutions already available to customers residing in the EU is Azure Local, a reduced version of the infrastructure behind Sovereign Private Cloud, which can be installed in customer data centers. Recently, the Redmond company enhanced Azure Local, allowing its customers to scale workloads across thousands of servers.
Azure Local can now scale to thousands of servers within a single sovereign environment. Until now, Azure Local was a (very) reduced version of the Azure infrastructure, ensuring all the advantages of the cloud but installed on the customers' systems, thus guaranteeing total control over the data. With the recent announcement, Microsoft enhances the offering, providing not only local installations for specific urgent needs but also private infrastructures comparable to those of hyperscaler data centers, designed for mission-critical workloads, AI applications, and regulated environments.
The model is that of public cloud brought within the customer's perimeter. Azure Local indeed allows for the execution of workloads on an infrastructure that operates with the logic of the cloud but functions on hardware owned and managed by the customers.
The system can operate in connected environments, with intermittent connectivity, or even completely disconnected from the public cloud. In these scenarios, the application of policies, role-based access control, auditing, and compliance configurations remain local. The increase in scale will allow users to execute heavier workloads, thus overcoming the limits of previous Azure Local implementations.
As expected, artificial intelligence is at the center of Microsoft’s plans. Thanks to support for high-performance GPU infrastructures, Azure Local can execute inference and analytics workloads entirely within environments controlled by the customer. Operational data, sensitive models, access logics, and auditing remain within the organization's perimeter.
The FiberCop Case
Among the Italian customers of Azure Local is FiberCop. The operator is bringing the platform to its peripheral sites with the aim of offering cloud services and artificial intelligence capabilities closer to the territory, businesses, and the data to be processed. The point is not merely technical. If the sovereign cloud is to exit the central data center dimension, the network becomes a part of the architecture: no longer just a simple transport channel, but a computational infrastructure capable of hosting regulated workloads, AI applications, and digital services with stringent requirements for compliance and control.
"FiberCop is better positioned than any other operator in the Italian market to drive innovation and provide cloud and artificial intelligence services on a national scale. Azure Local supports our mission to lead Italy's digital future and brings Microsoft's cloud capabilities to edge workloads across the country, maintaining data sovereignty and compliance where it matters most," comments Fabio Veronese, Chief Information & Technology Officer of FiberCop.