Design Goals

HyperCloud is a highly integrated, turn-key hardware and software solution for building private clouds.

The design and implementation of HyperCloud is governed by seven key principles, outlined below.

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Freedom wherever possible

With its foundation of integrated hardware and software that prioritizes highly performant interoperability at every level, HyperCloud's deployment is a set of fixed, easy-to-replicate steps. This consistency simplifies the initial steps for getting HyperCloud running - but this doesn't mean restriction and lock-in for what you can do with it. HyperCloud aims to provide freedom to the operator wherever possible, combining the best aspects of a turn-key solution and a DIY approach.

Simplicity and elegance

Building and operating a private cloud should be a simple, straightforward, and well-documented process.

Scalability and resilience

The cloud should function equally well, whether it is built on minimal quarter-rack deployments to dozens of racks. It needs to offer enough resilience that operators feel comfortable committing to quality SLAs (Service Level Agreements) for their tenants and stakeholders.

Sustainability

The data center landscape is changing rapidly, and strict regulation is being introduced around power usage efficiency and the approach to cooling and power consumption. We manufacture appliances that assist our customers on their journey to net zero emissions, optimizing for efficient operation and cooling.

Turn-key appliance

We provide a mature and exemplary cloud, delivered as a turn-key appliance. Building and deploying a private cloud should be as easy as installing a home WiFi router. It should be easy to deploy and service from thousands of miles away - both in the rack and at the edge.

Integrated and supported

Every facet of the cloud solution stack required should be provided by HyperCloud, and the whole stack should be fully supported, ideally by a single vendor.

Scalability

Deliver a cloud solution that our customers will be able to operate efficiently at massive scale.