CONNECTIVITY METHODS USED IN ETHERNET NETWORKS

Low-loss energy storage battery cabinets used in operator backbone networks

Low-loss energy storage battery cabinets used in operator backbone networks

Featuring lithium-ion batteries, integrated thermal management, and smart BMS technology, these cabinets are perfect for grid-tied, off-grid, and microgrid applications. Explore reliable, and IEC-compliant energy storage systems designed for renewable integration, peak. Purpose-built for critical backup and AI compute loads, they provide 10–15 years of reliable performance in a smaller footprint than VRLA batteries. Let's talk about something that keeps network operators up at night: keeping the lights on at remote telecom base stations.

Read More
Commonly Used Optical Cables in Distribution Networks

Commonly Used Optical Cables in Distribution Networks

A fiber optic cable is a transmission medium that uses strands of glass or plastic fibers to carry data as pulses of light. It offers high bandwidth, low signal loss, and resistance to electromagnetic interference (EMI), making it ideal for modern high-speed networks. The fibers are loosely bundled within the buffer tubes, which are filled with a gel-like compound.

Read More
Size parameters for edge data centers used in local area networks

Size parameters for edge data centers used in local area networks

According to a recent JLL article, edge data centers have smaller capacities, between 500 kilowatts to 2 megawatts (versus the typical 80 MW capacity of most hyperscale centers). This proximity reduces latency from 50-100 milliseconds down to single digits, which matters for applications where every millisecond of. 5 billion in 2024 from $4 billion in 2017, thanks to the potential for these smaller, locally located data centers to reduce latency, overcome intermittent connections and store and compute data close to the end user. Edge data center location planning with Atlas gives edge network operators the spatial planning environment that distributed compute deployment requires — connecting application requirements, user geography, and infrastructure availability into network designs that meet latency targets within. There are two types of Edge datacenters (Metro and Mobile), which are typically the size of a shipping container, are placed at the base of cell towers, and provide substantial support to IoT (Internet of Things) and the autonomous vehicle segment to increase processing capability and enhance.

Read More
How large a cable tray should be used for a 10 square millimeter cable

How large a cable tray should be used for a 10 square millimeter cable

A 10 or 12-foot cable tray is usually used for both of these installation types. In practice, cable tray dimensions are a system of interrelated measurements —width, depth, length, and material thickness—that directly affect cable fill compliance, heat dissipation, structural loading, and long-term expandability. Standard electrical cable tray dimensions for width typically range from 50 millimeters to 1000 millimeters in metric systems, or from 6 inches to 36 inches in imperial measurements. This calculator determines if your tray meets industry standards (typically 30-50% fill for alternating single-layer or 40-50% for random arrangement).

Read More
Which graphics cards are used in AI servers

Which graphics cards are used in AI servers

The RTX 4070, 4070 Ti, and 5070 offer balanced performance for mid-range AI tasks such as fine-tuning and image generation. Your GPU choice will determine your development experience, from training speed and model size limitations to deployment costs. A clear, simple 2025 guide to picking the right NVIDIA GPU for AI: it maps budgets and workloads to sensible choices-from entry cards (RTX 4060 Ti / 5060) for small experiments, through mid-range (4070/4070 Ti/5070) and bigger models on 4080/5080, up to 4090/5090 for heavy inference-while. NVIDIA provides a range of GPUs (graphics processing units) specifically designed to accelerate artificial intelligence (AI) workloads, including the A100, H100, H200, and newer Blackwell-based platforms such as the B200. Whether you're training deep neural networks, running inference on large datasets, or experimenting with. GPU servers speed up the parallel computation required for Deep Learning, large-scale matrix operations and the training of complicated Neural Networks. The best graphics card for AI is the NVIDIA RTX 4090 with its 24GB GDDR6X memory and fourth-generation tensor cores, delivering up to 4.

Read More

Get In Touch

Connect With Us

📱

Poland (Sales & Engineering HQ)

+48 22 538 72 19

📍

Headquarters & Manufacturing

ul. Postępu 14, 02-676 Warszawa, Poland