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Web & Server Infrastructure

Cloud & HostingSolutions

Web hosting, managed VPS, dedicated servers and GPU hosting for AI models — plan limits spelled out upfront, support that answers during business hours.

Incident — gpu-node-01 · Dhaka

Resolved automatically
  1. Traffic spike detected — 3.2x normal load

  2. Second GPU node brought online

  3. Requests rebalanced across both nodes

  4. Alert closed — no action needed

0

Requests dropped

40s

Time to scale

41ms

p50 inference

Handled while you slept

Hosting and Servers Sized to Your Workload

The right tier follows from two things: how much traffic the workload actually pulls, and whether any rule requires hardware that isn't shared with other customers. A small brochure site tolerates the occasional slowdown that comes with shared web hosting. A VPS sets aside a fixed slice of CPU and memory for one account, which is enough for most business applications and online stores. A dedicated server matters when a compliance rule calls for unshared hardware, or when load is heavy enough, often enough, to need it. A GPU server is for one job only: running an AI model directly, not calling one through an API. The single most common hosting expense is a tier bigger than any of that requires.

Frequently Asked Questions

Shared web hosting and domain registration, managed VPS, dedicated servers, and GPU hosting for AI workloads — each sized to what the account actually needs, not sold as a single default package.

A VPS guarantees a fixed share of CPU and memory on hardware split between several customers, at a price below a full machine. A dedicated server hands over the entire box — nothing shared with anyone else — which is what a compliance requirement for unshared hardware is asking for.

Support answers during business hours, and every plan states its resource limits upfront in the plan itself, not buried in a terms page found later.

Match it to the workload. A small site runs fine on shared hosting, where occasional slowdowns are part of the deal. A VPS reserves CPU and memory for one account and covers most business applications and online stores. A dedicated server is for a compliance rule requiring unshared hardware, or for load heavy enough to justify it. GPU servers exist for one purpose: running an AI model directly.

Yes — a dedicated GPU allocation for models run in-house, at a flat monthly cost, with the card assigned to one account only, not shared and not billed per token.

Not sure which one you need?

Describe the problem rather than the product. A short call is usually enough to tell you which of these fits — or that none of them does.

Book a Free Consultation