New-Tech Europe Magazine | Feb 2017

Solving Power Capacity Challenges with Software Defined Power

Mark Adams, CUI Inc.

Understanding the data center ‘power challenge’ The demand for Cloud data services continues apace as businesses and individual consumers become ever more reliant on remotely stored data that can be accessed over the Internet from almost anywhere. In addition, Cisco has estimated that the emergence of the Internet of Things will result in some 50 billion “things” connected to the Internet by 2020 as a myriad of sensors and controls enable smart homes, offices, factories, etc. Combined with more established applications, this is forecast to require a daily network capacity in excess of a zettabyte (1021 bytes) as early as 2018. Servicing this demand and scaling up the capacity of networks and data centers is inevitably challenging, especially as customer requirements can turn on rapidly. While the IT

are only powered when there is sufficient supply capacity. In this way the system can respond to peak demand while managing other tasks to spread the power load. In much the same way that Software Defined Data Centers allow self- serviced users to deploy services and workloads in seconds, this approach to Software Defined Power® unlocks the underutilized power capacity available within existing systems. This allows a data center’s server processing and storage capacity to expand without increasing power supply capacity and achieves considerable capital expenditure savings by not overprovisioning power. Furthermore, the use of battery storage to provide peak shaving and load leveling can also enable UPS functionality within a data center or server rack to protect it from power outage.

Running out of power is a constant concern for the operators of data centers and similar IT and communications infrastructure. The fight for footprint optimization while boosting processing and storage capabilities is a never-ending battle. However, the inefficiencies and underutilization of current power supply infrastructures that are designed to meet peak demand can now be avoided using a combination of hardware and software to even out supply loading and optimize the available capacity. This intelligent use of available power can be realized with software tools that profile usage and recognize priority tasks. Utility power can then be supplemented with battery storage to supply peak demand using power stored during low utilization periods. Similarly, low-priority workloads can be assigned to server racks that

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