#dedicated-servers

#dedicated-servers

The UK has about 1.59GW of currently installed datacentre capacity at just under 190 sites. If we add existing capacity to that which is planned to complete by 2030 and which has planning consent, we get 4.9GW.

AI Armor provides dynamic runtime security and relies on a central policy engine in the Universal Management Suite (UMS) to meet compliance requirements, ensuring that organizations can manage their security effectively.

"For healthcare, government, and contact center environments, reducing risk at the endpoint is essential. By aligning IGEL's immutable endpoint OS and Adaptive Secure Desktop™ with Windows 365 and Microsoft Azure Virtual Desktop, these reference architectures give organizations clear guidance for delivering secured and resilient digital workspaces."

[EHS] is actually a profit centre in the company," he says. "I know people tend to think it isn't. Compared to some other hats that I've worn, sustainability is usually not a cost centre.

As businesses contend with ever-increasing data volumes and performance-intensive applications such as AI model training, AI inferencing and high-performance computing, they need infrastructure that delivers speed, scalability and efficiency without added complexity.

Ring the bells, sound the trumpet, the Linux 6.19 kernel has arrived. Linus Torvalds announced that "6.19 is out as expected -- just as the US prepares to come to a complete standstill later today, watching the latest batch of televised commercials." Because while the big news in Linux circles might be a new Linux release, Torvalds recognizes that for many people, the "big news [was] some random sporting event." American football, what can you do?

An observability control plane isn't just a dashboard. It's the operational authority system. It defines alert rules, routing, ownership, escalation policy, and notification endpoints. When that layer is wrong, the impact is immediate. The wrong team gets paged. The right team never hears about the incident. Your service level indicators look clean while production burns.

A North American manufacturer spent most of 2024 and early 2025 doing what many innovative enterprises did: aggressively standardizing on the public cloud by using data lakes, analytics, CI/CD, and even a good chunk of ERP integration. The board liked the narrative because it sounded like simplification, and simplification sounded like savings. Then generative AI arrived, not as a lab toy but as a mandate. "Put copilots everywhere," leadership said. "Start with maintenance, then procurement, then the call center, then engineering change orders."

Lenovo has announced a new series of enterprise servers and solutions specifically designed for AI inferencing workloads. These consist of three different ThinkSystem and ThinkEdge servers. "Enterprises today need AI that can turn massive amounts of data into insight the moment it's created," said Ashley Gorakhpurwalla, President of Lenovo Infrastructure Solutions Group. "With Lenovo's new inferencing-optimized infrastructure, we are giving customers that real-time advantage."

This new reality is forcing organizations to undertake careful assessments before making platform decisions for AI. The days when IT leaders could simply sign off on wholesale cloud migrations, confident it was always the most strategic choice, are over. In the age of AI, the optimal approach is usually hybrid. Having openly championed this hybrid path even when it was unpopular, I welcome the growing acceptance of these ideas among decision-makers and industry analysts.

I've had several incarnations of the self-hosted home lab for decades. At one point, I had a small server farm of various machines that were either too old to serve as desktops or that people simply no longer wanted. I'd grab those machines, install Linux on them, and use them for various server purposes. Here are two questions you should ask yourself:

The main advantage of going the Multi-Cloud way is that organizations can "put their eggs in different baskets" and be more versatile in their approach to how they do things. For example, they can mix it up and opt for a cloud-based Platform-as-a-Service (PaaS) solution when it comes to the database, while going the Software-as-a-Service (SaaS) route for their application endeavors.