Data Center Automation With AIM

Data Center Automation With AIM

Key Performance Indicators (KPIs) can help improve data center management in the areas of monitoring, analyzing and optimizing the infrastructure as well as offering specific services.

Thomas Wellinger is global Market Manager of Data Centers for R&M.

A data center is an ever-growing organism, interwoven at many levels and with an infrastructure that is difficult to see. Once installed, the entire structure needs to remain in place for many years. Under these conditions, data center managers need to deal with constant demand for new services and today’s tremendous growth of data volume. This constantly requires smart decisions regarding the infrastructure. In order to make these decisions adequately, data center managers must be able to revise all of their data centers’ operations and processes. This requires complete transparency, right down to the level of the inventory. This is also referred to as asset-level visibility or network visibility.

KPIs for Data Center Efficiency

Besides transparency, we need to take several critical key performance indicators (KPIs) into account. These provide information which is vital to achieving the desired efficiency. These indicators can help improve data center management in the areas of monitoring, analyzing and optimizing the infrastructure as well as offering specific services. These KPIs include PUE (power usage efficiency), total energy costs and delivery costs (price/kWh) but also the time required for the documentation and average delivery time. Once these indicators are related to increased efficiency, the time required for the delivery of infrastructures and services may be reduced. This result will surely result in greater internal and external customer satisfaction . Two further indicators are indispensable, as they clearly lead to higher data center reliability: accuracy of the documentation and the average mean time to repair (MTTR). Documentation accuracy depends on the number of data points which have been correctly recorded and are up to date.

Several further indicators refer to increasing infrastructure efficiency and density. Stranded or unused capacities can be easily identified by analyzing the relationship between rackspace and limiting factors such as restrictions at the power supply. Space efficiency is the result of utilized floor and rack area per area unit. By additionally examining the personnel requirement, the total cost of ownership (TCO) can be improved correspondingly.

Reliability and Transparency for Data Center Management

Automated infrastructure management (AIM) not only supports each of the aforementioned KPIs, but offers another great advantage: various operational aspects of data center management become more reliable and transparent. In today’s world, many interdependent aspects of data center operation are outsourced to (multiple) third party companies. Company A might be in charge of network operation, for example, while company B may be responsible for MACs.

Until relatively recently, if something went wrong, you could speak to someone from your own organization to find out what happened and resolve the issue. What’s more, the entire legal responsibility for any occurrence that had an impact would be clearly defined.

What happens if everything is outsourced, however? If you have no way of recording and tracking the individual tasks, what happens if something goes wrong? Each party will simply blame the others and in the end, data center management might be held accountable.

Approaches to Data Center Management

For data center infrastructures in particular, the potential to improve on planning, forecasting, creating inventories and MAC processes, for example, is enormous. A smarter approach will also lead to a highly standardized service catalog and constantly high reliability and data integrity of documented actions. This is especially important for highly regulated industries such as the financial, pharmaceutical or chemical sectors.

Improving visibility is the essential first step in moving towards infrastructure management maturity. With visibility in place, proactive planning based on predictions and forecasts can begin, eventually moving towards KPI-driven data center management.

Deciding which type of AIM system best suits your needs, and ensuring your hardware, software and processes support this can be very complicated. Make sure you have a clear overview of your goals and requirements before specifying and selecting a solution. Once installed, the scope for quick fixes and changes can be limited. Of course, when in doubt, don’t hesitate to consult experts in this area.

Opinions expressed in the article above do not necessarily reflect the opinions of Data Center Knowledge and Penton.

Industry Perspectives is a content channel at Data Center Knowledge highlighting thought leadership in the data center arena. See our guidelines and submission process for information on participating. View previously published Industry Perspectives in our Knowledge Library.
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