Managing your server with Software RAID is generally not too difficult. Typically and more commonly, we recommend hardware RAID (generally with a MegaCLI controller), however, if you are utilizing software RAID, it’s important to understand some fundamentals. If you are here in reference to seeing failed or missing drive(s) on
SOFTWARE The operating systems and control software you need. Control Panels We offer a wide range of both Linux and Windows supported control panels that are all built to simplify server and website management. Whether you have just a few sites to manage, a few thousand sites, or even if
For growing companies, the public cloud has long been the default for its promise of easy scaling and no hardware management. But as businesses mature, that flexibility can come at a steep price. Many organizations find they are paying a premium for elasticity they don’t use, renting infrastructure at a
The “Cloud First” strategy is no longer the default for IT infrastructure. As hyperscale public cloud bills climb and multi-tenant environments struggle with “noisy neighbor” interference, a structural shift is underway. See Evaluating Cloud vs. Dedicated Server TCO in 2026 for an in-depth look at the cost dynamics driving this change.
For nearly two decades, the economic law of the data center was simple: wait six months, and it will get cheaper. We lived in a deflationary era where Moore’s Law manifested directly in pricing—compute became denser, faster, and more accessible with every passing quarter. Welcome to 2026. The rules have
For the better part of a decade, the “Cloud First” mandate was the default strategy for nearly every CTO and VP of Engineering. The logic was simple: trade capital expenditure (CapEx) for operational expenditure (OpEx), gain infinite scalability, and outsource hardware management to the hyperscalers. But as we settle into
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Ollama Hosting on CPU Servers — No GPU Needed Pre-installed with Ollama runtime, OpenWebUI interface, and Llama 3.1 8B model. Perfect for developers, data scientists, and privacy-focused teams who want to run LLMs without cloud dependencies. Configure Server Talk to an Expert Deploy Ollama in 3 Simple Steps. 1 Choose
The rise of generative artificial intelligence (GenAI) and Large Language Models (LLMs) has created a fundamental shift in enterprise infrastructure requirements. The previous decade’s dominant model of general-purpose, multi-tenant cloud computing is often inadequate for the high-performance demands of modern AI workloads. As organizations move from pilot projects to production-grade
During the 2024 Olympics, streamers delivered over 3,800 hours of live content to millions of concurrent viewers. The technical feat behind such a broadcast is immense, yet for the end-user, the expectation is simple: instant playback, zero buffering, and pristine resolution. When buffering wheels spin, users churn. As streaming platforms
Deploying Large Language Models (LLMs) locally offers significant advantages in data privacy, cost efficiency, and performance control. However, the setup process can often be complex and resource-intensive, particularly for those looking to avoid the high costs associated with GPU hardware. Ollama simplifies this by enabling efficient LLM deployment on CPU-based