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Our Design Emphasis

We design Data Centres to optimise high-availability, efficiency, flexibility and simplicity based on your needs and contraints

Data Centre designs are judged by their ability to provide continuous operations for the networking, computing and application services they support.  Data Centre availability is affected by both planned (scheduled maintenance) and unplanned (failures) events.  To maximize availability, the impact from each of these must be minimized and/or eliminated.
A Data Centre achieves high-availability by implementing a fully redundant, fault-tolerant, and concurrently maintainable IT and support infrastructure architecture in which all possible hardware failures are predictable and deterministic.
A Data Centre must support fast and seamless growth, and deployment of new services without a major overhaul of its infrastructure, and without a major disruption to its operation. A Data Centre designed for flexibility can adapt to changing business conditions and thereby the demands put upon its function.
Another key component in achieving flexibility is scalability.  Scalability is the design concept of proactively planning for changing requirements.  A Data Centre that is scalable has the capacity to sustain rapid growth in performance, the number of devices that it can host, and the quality of services offered.
Like many old adages, the one about, ‘keeping it simple,’ is true, most especially for Data Centres.  The major benefits of simplifying a Data Centre design are:
– Reduced chance of failures due to human error (the most common cause of down time)
– Reduced cost of implementation, and
– Interactive and intuitive systems monitoring, manageability, and maintainability.
“GREEN” stands at the core of our designs. We believe that achieving the best optimization of performance and energy efficiency is the core responsibility of a Data Centre designer.
“Green” is accomplished in the Data Centre design by specifying technologies as per specific Data Centre requirements, and by finding the optimum balance between required redundancy in devices and over-provisioning, and maximizing the “spend when you need” approach.