Category Archives: Windows Server 2025

WSUS Retirement: Impact and Strategies for Server System Updates

With Microsoft’s announcement regarding the retirement of Windows Server Update Services (WSUS), a new chapter begins in managing updates for server systems. After almost 20 years since its release, WSUS will no longer be actively developed, creating uncertainty among IT administrators who have relied on this tool to distribute updates in enterprise environments. In this article, we will analyze the impact of this decision and possible migration strategies, with a particular focus on server systems.

What is WSUS and What Does Its Retirement Mean?

Windows Server Update Services (WSUS) has been the go-to tool for managing and distributing Microsoft product updates within enterprise networks for years. IT administrators can approve, schedule, and control the distribution of updates, deciding which devices receive them. WSUS also offers automation capabilities via PowerShell and integrates with Group Policy, making centralized management easier.

With the retirement announcement, Microsoft specified that WSUS will not be removed immediately, but it will no longer receive future developments or enhancements. The current functionality will be maintained, and Microsoft will continue to release updates through WSUS, but no new features will be introduced.

Implications for IT Administrators and Migration Strategies

The announcement has sparked doubts among IT administrators, especially regarding the continuity of support and the need to find alternative solutions. While WSUS will continue to be available in in-market versions of Windows Server, including the upcoming Windows Server 2025, it is crucial for administrators to start planning a transition to new solutions.

One important aspect to consider regarding the retirement of WSUS is its impact on Microsoft Configuration Manager. Although WSUS is being gradually retired, its deprecation will not directly impact the existing functionalities of Microsoft Configuration Manager, which will continue to use WSUS as a mechanism for managing and distributing updates. In other words, Configuration Manager will remain a viable option for organizations that rely on it to manage updates, with WSUS still serving as the distribution channel.

However, it is essential to note that even though WSUS will still be usable within Configuration Manager, Microsoft recommends planning a transition to cloud-based solutions such as Azure Update Manager to leverage new capabilities and improve the efficiency of update management in the long term. Migrating to the cloud is not only a natural evolution but also an opportunity to ensure more flexible and efficient server update management in line with modern business needs. This shift reflects the move towards a more cloud-oriented update management model, consistent with Microsoft’s strategy of simplifying Windows management through cloud-based solutions.

Azure Update Manager: A Worthy Replacement, But…

Azure Update Manager is a service that helps manage and govern updates for all machines, whether in Azure, on-premises, or on other cloud platforms connected via Azure Arc. From a single management console, it is possible to monitor update compliance for Windows and Linux servers, apply updates in real-time, or schedule them in defined maintenance windows.

With Azure Update Manager, you can:

  • Control and distribute security or critical updates to protect machines.
  • Enable periodic assessments to check for updates.
  • Use flexible patching options, such as scheduling updates in custom time windows.
  • Monitor update compliance for all machines, including hybrid or other cloud environments connected via Azure Arc.

Azure Update Manager offers several advantages, but there are some aspects to consider carefully.

Azure Update Manager respects the update source already configured on the machine, whether it is Windows Update for OS updates, Microsoft Update for product updates, or WSUS for a combination of both. In this context, WSUS can still be used in parallel with Azure Update Manager to provide additional capabilities, such as storing or caching updates locally.

The critical point concerns organizations with a large number of on-premises servers, where managing updates exclusively through Azure Update Manager requires further evaluation. The main concern is related to the bandwidth needed to download updates directly from the Internet to each server, which could saturate the network. Additionally, the micro-segmentation typical of server security policies makes it difficult to use peer-to-peer technologies such as Delivery Optimization.

Currently, if you want to explore a long-term strategy for enterprise companies and avoid this pain point, it’s necessary to evaluate solutions like Microsoft Connected Cache or explore options from other vendors.

Another relevant aspect is the cost associated with Azure Update Manager for servers managed through Azure Arc. While the service is free for systems residing in Azure, servers enabled for Azure Arc are subject to a cost of around €4.48 per server per month. However, there are cases where there are no charges for Azure Update Manager when the servers are:

  • Enabled for Extended Security Updates (ESU).
  • Managed through Defender for Servers Plan 2.
  • Hosted on Azure Stack HCI, when these machines are enabled for Azure benefits and managed via Azure Arc.

Conclusion

The retirement of WSUS will bring significant changes in the long term for IT administrators, especially in large environments with a high number of servers. While WSUS will continue to be available, companies should start considering long-term strategies to ensure efficient and secure update management. Azure Update Manager is a viable alternative but requires careful analysis of the economic and operational implications of this change.

For those interested in a more comprehensive approach in terms of security and centralized management, combining Azure Update Manager with Defender for Cloud (Plan 2) offers an interesting solution. This combination not only allows for update management but also provides advanced features for server system protection, ensuring a higher level of security.

In conclusion, although WSUS will remain available for a few more years, Microsoft’s direction is clear: the future of update management is moving towards the cloud, and organizations must prepare to face this transition in a strategic and proactive manner.

Windows Server 2025 vs. Azure Stack HCI: Who Wins the Virtualization Challenge?

Recently, the virtualization landscape has seen significant changes, pushing companies to evaluate new solutions for their IT environments. Specifically, the acquisition of VMware by Broadcom has raised concerns among many customers, leading them to explore alternatives for their virtualization infrastructures. In this context, Windows Server 2025 and Azure Stack HCI emerge as two key options offered by Microsoft. Both play a fundamental role in cloud and on-premises architectures, but they cater to very different needs and contexts. In this article, we will delve into the differences between these two platforms, highlighting their strengths and use cases to understand how they fit into the adoption of new virtualization and hybrid cloud solutions.

Background: The Evolution from Traditional Infrastructure to Hyper-Converged Infrastructure (HCI)

Before the widespread adoption of hyper-converged infrastructure (HCI), virtualization was often implemented through a three-tier infrastructure, consisting of servers, switches, and SAN (Storage Area Network). The SAN represented the shared storage to which servers accessed via protocols such as iSCSI or Fibre Channel. This approach enabled and still enables the management of workloads across multiple hosts, ensuring redundancy and high availability through advanced failover and resilience mechanisms.

With the introduction of hyper-converged solutions, such as Azure Stack HCI—Microsoft’s solution for implementing a hyper-converged infrastructure—the management paradigm and architecture radically change: storage, networking, and computing are integrated into a single software-defined platform, eliminating the need for many dedicated hardware components.

Figure 1 – “Three Tier” Infrastructure vs Hyper-Converged Infrastructure (HCI)

This allows for greater simplicity in management, reduced costs associated with hardware, rack space, and cooling, and more flexibility in deployment.

Windows Server 2025: The Operating System for All Needs

Windows Server 2025 represents the latest evolution of Microsoft’s proven server operating system. This new version is designed to be a versatile, general-purpose platform, aimed at meeting the needs of businesses of any size. Windows Server 2025 continues to support a wide range of workloads, from traditional services like Active Directory and SQL Server to advanced virtualization scenarios with Hyper-V.

Some of the key innovations and features of Windows Server 2025 include:

  • Virtualization enhancements: Hyper-V has been further enhanced to support advanced features like GPU partitioning and optimized performance for virtual machines (VMs). This makes it ideal for companies heavily dependent on virtualization and needing to manage high-intensity workloads.
  • Storage Spaces Direct (S2D): This feature allows the creation of distributed storage clusters, transforming local disks into shared, highly available storage pools, with a strong focus on performance and resilience.
  • Hybrid cloud support: Although primarily designed for on-premises environments, Windows Server 2025 offers strong integration with Azure Arc, enabling hybrid and centralized management of both local and cloud resources. This feature opens up new scenarios, where on-premises resources can be managed directly from the Azure portal.
  • Flexible licensing: Windows Server continues to offer adaptable licensing models to meet business needs. In fact, Microsoft plans to sell Windows Server 2025 not only through traditional perpetual licenses but also through a pay-as-you-go subscription option.

Scalability and Performance with Windows Server 2025

One of the standout aspects of Windows Server 2025 is its focus on scalability. With support for up to 240 terabytes of memory and 248 virtual processors per virtual machine, this platform is designed to handle extremely intensive workloads, such as artificial intelligence and big data processing. Additionally, optimization for NVMe storage ensures a performance improvement of up to 70% compared to previous versions, positioning Windows Server 2025 as an excellent choice for businesses needing high-speed storage.

Another significant innovation is support for AD-less clustering, designed for edge scenarios where traditional Active Directory (AD) management might not be practical. This is particularly useful for companies operating in decentralized environments, such as remote industrial sites or branch offices.

Azure Stack HCI: The Hyper-Converged Virtualization Platform

Unlike Windows Server, Azure Stack HCI is not a general-purpose operating system. It is a platform specifically designed for virtualization and containerization environments. Azure Stack HCI combines compute, networking, and storage in a software-defined solution, offering simplified on-premises workload management with strong Azure cloud integration. It is an ideal solution for organizations seeking a scalable HCI infrastructure that can be managed through the Azure portal.

Key features of Azure Stack HCI include:

  • Focus on virtualization: Azure Stack HCI is optimized to run virtual machines and containers, without offering traditional server roles like Active Directory or file servers. This makes it a solution focused on specific workloads, such as managing virtualization and containerization environments through Hyper-V and Kubernetes.
  • Advanced cloud integration: Azure Stack HCI integrates seamlessly with Azure services, enabling the management of both on-premises and cloud resources through a single interface. This hybrid capability simplifies tasks such as provisioning, monitoring, and governance of resources in geographically distributed environments.
  • Security: Azure Stack HCI implements over 100 predefined security best practices.
  • Costs and licensing: Azure Stack HCI adopts a subscription-based licensing model, ensuring constant updates and security patches. While this approach makes costs more predictable, it may be less advantageous for smaller setups compared to the traditional Windows Server licensing model.

When to Choose Windows Server 2025?

Windows Server 2025 is a versatile and reliable choice for a wide range of IT scenarios, thanks to its general-purpose nature. However, to determine whether this platform is suitable for a specific organization, it is important to evaluate technical, economic, and operational requirements. Situations where Windows Server 2025 might be the ideal solution include:

  • On-premises-focused workloads: If an organization needs to keep most of its workloads on-premises with minimal cloud integration, Windows Server 2025 is the best choice.
  • Limited budget: If the company is not ready to invest in subscription-based solutions, the traditional Windows Server licensing model might be more cost-effective.
  • Hardware compatibility: If the goal is to reuse existing hardware, Windows Server offers greater flexibility in terms of compatibility.

When to Choose Azure Stack HCI?

Azure Stack HCI stands out for its strong cloud integration and ability to provide a modern hyper-converged infrastructure. While not a general-purpose operating system, its architecture makes it particularly suited to specific needs related to virtualization and containerized workloads. Situations where Azure Stack HCI emerges as the optimal choice include:

  • Hybrid cloud environments: If a company has already adopted a hybrid cloud strategy, Azure Stack HCI offers integrated management with the Azure portal, simplifying the control of resources in distributed environments.
  • Resilience and disaster recovery: Thanks to support for stretched clusters across multiple geographic locations, Azure Stack HCI provides greater resilience and advanced disaster recovery options.
  • Infrastructure modernization: If you are looking to modernize infrastructure by adopting hyper-converged technologies and close cloud integration, Azure Stack HCI is the perfect solution to support the transition.

Conclusions

Windows Server 2025 and Azure Stack HCI are robust and powerful platforms, but designed for different needs. Windows Server 2025 is perfect for organizations needing a general-purpose platform with a strong on-premises presence and some hybrid cloud capabilities. Azure Stack HCI, on the other hand, is the ideal choice for companies looking to fully embrace hybrid cloud with simplified management and strong Azure integration.

The choice between the two will depend on the specific requirements of the organization, budget, and long-term goals. It’s not about deciding which is the “better” virtualization platform, but which better meets the company’s operational and strategic needs.

The Importance of GPUs in the Field of Artificial Intelligence and the Innovations Introduced in Windows Server 2025

The evolution of technologies related to artificial intelligence (AI) has led to an increasing demand for computing power, essential for managing the training, learning, and inferencing of machine learning and deep learning models. In this context, GPUs (Graphics Processing Units) have established themselves as fundamental components, thanks to their ability to perform large-scale parallel computations extremely efficiently. With the upcoming releases of Windows Server 2025 and Azure Stack HCI 24H2, Microsoft introduces significant innovations that enable companies to fully harness the potential of GPUs not only in AI but beyond. These advanced new features simplify hardware resource management and provide an optimized platform for developing and deploying AI solutions on a large scale. In this article, we will explore the importance of GPUs in the AI ecosystem and analyze how the new versions of Windows Server 2025 further enhance these capabilities, transforming how companies tackle the challenges and opportunities presented by AI.

Computing Power and GPU Optimization for Deep Learning on Virtual Infrastructures

Deep learning, an advanced branch of artificial intelligence that leverages deep artificial neural networks, requires a vast amount of computing power to function effectively. Training these models involves processing large volumes of data through multiple layers of interconnected nodes, each performing complex mathematical operations. While traditional CPUs are highly powerful in sequential data processing, they are not optimized to handle a large number of parallel operations, as required by deep learning models.

In this context, GPUs (Graphics Processing Units) are particularly well-suited due to their ability to execute thousands of operations simultaneously. This makes GPUs ideal for training deep learning models, especially complex ones like convolutional neural networks (CNNs), which are widely used in image recognition. For example, training a CNN on a large dataset could take weeks on a CPU, while with the help of a GPU, the time required can be drastically reduced to just days or even hours, depending on the model’s complexity and the dataset’s size.

With the imminent release of Windows Server 2025 and Azure Stack HCI 24H2, Microsoft will offer its customers the ability to allocate an entire GPU’s capacity to a virtual machine (VM), which can run both Linux and Windows Server operating systems within a fault-tolerant cluster, thanks to Discrete Device Assignment (DDA) technology. This means that critical AI workloads for businesses can be reliably executed on a VM within a cluster, ensuring that, in the event of an unexpected failure or planned migration, the VM can be restarted on another node in the cluster using the GPU available on that node.

Microsoft recommends working closely with OEM (Original Equipment Manufacturer) partners and independent GPU hardware manufacturers (IHV) to plan, order, and configure the necessary systems to support the desired workloads with the right configurations and software. Additionally, if GPU acceleration via DDA is desired, it is advisable to consult with OEM and IHV partners to obtain a list of GPUs compatible with DDA. To ensure the best possible performance, Microsoft also suggests creating a homogeneous configuration for GPUs across all servers in the cluster. A homogeneous configuration implies installing the same GPU model and configuring the same number of partitions on all GPUs in the cluster’s servers. For example, in a cluster consisting of two servers each with one or more GPUs, all GPUs should be of the same model, brand, and size, and the number of partitions on each GPU should be identical.

Scalability and Flexibility of GPUs in AI Computing Architectures

In addition to their extraordinary computational speed, GPUs also offer significant advantages in terms of scalability, a crucial factor in modern AI computing architectures. Often, the datasets used to train AI models are so vast that they exceed the computational capabilities of a single processor. In these cases, GPUs allow the workload to be distributed across multiple computing units, ensuring high operational efficiency and enabling the simultaneous processing of enormous amounts of data.

Another critical aspect of GPUs is their flexibility in handling a variety of workloads, ranging from real-time inference, used for example in speech recognition applications, to the training of complex models that require weeks of intensive computation. This versatility makes GPUs an indispensable tool not only for advanced research centers but also for commercial applications that require high performance on a large scale.

GPU Partitioning: Maximizing Efficiency and Resource Utilization

One of the most significant innovations in the field of GPUs is the concept of GPU Partitioning, which is the ability to divide a single GPU into multiple virtual partitions, each of which can be dedicated to different workloads. This technique is crucial for optimizing GPU resources, as it maximizes operational efficiency while minimizing waste. In the context of artificial intelligence, where computational requirements can vary significantly depending on the models used, GPU Partitioning offers the flexibility to dynamically allocate portions of the GPU to various tasks, such as training machine learning models, real-time inference, or other parallel operations. This approach is particularly advantageous in data centers, as it allows multiple users or applications to share the same GPU resources without compromising overall system performance.

The introduction of GPU Partitioning not only improves the flexibility and scalability of computing infrastructures but also helps reduce operational costs by avoiding the need to purchase additional hardware when not strictly necessary. Additionally, this technology promotes a more balanced use of resources, preventing situations of GPU overload or underutilization, contributing to more sustainable and efficient management of AI-related operations.

With the release of Windows Server 2025 Datacenter, Microsoft has integrated and enhanced support for GPU Partitioning, allowing customers to divide a supported GPU into multiple partitions and assign them to different virtual machines (VMs) within a fault-tolerant cluster. This means that multiple VMs can share a single physical GPU, with each receiving an isolated portion of the GPU’s capabilities. For example, in the retail and manufacturing sectors, customers can perform inferences at the edge using GPU support to obtain rapid results from machine learning models, results that can be used before the data is sent to the cloud for further analysis or continuous improvement of ML models.

GPU Partitioning utilizes the Single Root IO Virtualization (SR-IOV) interface, which provides a hardware-based security boundary and ensures predictable performance for each VM. Each VM can only access the GPU resources dedicated to it, with secure hardware partitioning preventing unauthorized access by other VMs.

Another significant development concerns live migration capability for VMs using GPU Partitioning. This allows customers to balance critical workloads across various cluster nodes and perform hardware maintenance or software updates without interrupting VM operations. During a planned or unplanned migration, the VMs can be restarted on different nodes within the cluster, using available GPU partitions on those nodes.

Finally, Microsoft has made the Windows Administration Center (WAC) available to configure, use, and manage VMs that leverage virtualized GPUs, both in standalone configurations and in failover clusters. The WAC centralizes the management of virtualized GPUs, significantly simplifying administrative complexity.

Innovations and Future Prospects

The future of GPUs in artificial intelligence looks extremely promising. With the increasing complexity of AI models and the growing demand for solutions capable of leveraging real-time AI, the parallel computing power offered by GPUs will become increasingly essential. In particular, their ability to perform a large number of simultaneous operations on vast datasets makes them an indispensable component in cloud solutions.

The significant innovations in GPUs, supported by the upcoming releases of Windows Server 2025 and Azure Stack HCI 24H2, are the result of ongoing and close collaboration between Microsoft and NVIDIA. Microsoft Azure handles some of the world’s largest workloads, pushing CPU and memory capabilities to the limit to process enormous volumes of data in distributed environments. With the expansion of AI and machine learning, GPUs have become a key component of cloud solutions as well, thanks to their extraordinary ability to perform large-scale parallel operations. Windows Server 2025 will bring many benefits to the GPU sector as well, further enhancing features related to storage, networking, and the scalability of computing infrastructures.

Conclusions

The importance of GPUs in the field of artificial intelligence is set to grow exponentially, thanks to their ability to process large volumes of data in parallel with efficiency and speed. The innovations introduced in Windows Server 2025 and Azure Stack HCI 24H2 represent a significant step toward optimizing computing infrastructures, providing companies with advanced tools to manage and fully exploit GPU resources. These developments not only enhance the computing power necessary for AI but also introduce greater flexibility and scalability, essential for addressing future challenges. With the adoption of technologies like GPU Partitioning and support for live VM migration, Microsoft demonstrates its leadership in providing solutions that not only improve performance but also enhance the reliability and sustainability of AI-related business operations. The future prospects see GPUs playing an increasingly crucial role, not only in data centers but also in edge and cloud applications, ensuring that technological innovation continues to drive the evolution of AI across all sectors.

Useful References