Training large-scale AI models is far beyond the capabilities of ordinary desktops. If you plan to run LLMs, process big data, or design custom deep learning solutions, you need to know which AI server can actually handle the workload. The choice isn’t just “pick something with an RTX”—the entire platform matters: GPU, CPU, RAM, storage, cooling, and scalability.

Already trained the model? Now it’s time to move it into production—fast, stable, and without bottlenecks. This is where AI inference comes in: the phase in which your model processes live data and returns results in real time. To make this effective, you need the right hardware: an inference server capable of sustaining heavy loads, with a GPU and CPU optimized not for training but for low-latency, high-throughput inference at scale.

A server room is more than just a space for rack cabinets and blinking LEDs. It is a critical point of IT infrastructure that must operate continuously—regardless of weather, power supply, or system failure. If you want to ensure your company’s data remains secure and your equipment operates stably according to standards, every detail counts—from air conditioning, through raised flooring and emergency power, to access control and HSE documentation.

Do you have more workloads but no way to expand your hardware? Server virtualization is a method to maximize the efficiency of your existing infrastructure—without purchasing new servers, rack cabinets, or costly hardware. When properly implemented, it increases flexibility, simplifies management, shortens deployment times, and significantly reduces IT infrastructure operating costs.

Without them, nothing works as it should. A system administrator is the person behind every service, server, and application in the company – often invisible, yet indispensable. They are responsible for IT infrastructure security, performance, availability, and scalability. Beyond the purely technical role, they act as a business partner, ensuring that data remains secure, systems run without interruptions, and the organization can safely expand.

SSD or HDD – seemingly a simple question, yet the answer depends on what you aim to achieve. In data centers, where every terabyte, millisecond, and watt count, storage choice directly translates into costs, performance, and data security.

Tired of overloaded servers that can’t keep up with your company’s growth? Instead of investing in another expensive “just-in-case” machine, it’s worth considering a natively scalable solution – a compute cluster.

AI is not only models and data - it is also heat. A lot of heat. As server compute density scales up, the demand for efficient, reliable, and scalable cooling grows in lockstep.

Want to speed up your server without spending a fortune on an all-flash array? A hybrid SSD and HDD sounds like a reasonable compromise – at least on paper. In practice, hybrid drives can surprise you not only with their price, but also with their administrative requirements, scenario-dependent performance and hidden costs.

R640, T330 and M420. You probably know how Dell EMC uses letters and numbers to name its PowerEdge server models. If not, we highly recommend you to read this article to understand these naming conventions and which generation the servers belong to.