Data centers have turned into successful business partners for a lot of companies that lack the funding to invest in their own infrastructure and optimize it for efficient energy and resource usage. Energy management software plays an important role in this entire scheme but not everyone use these tools to improve existing infrastructures.
As cost reduction turned into a huge global trend, having a look at the monthly costs to maintain a data center up and running can help identify waste. One of the biggest costs associated with all data centers is power consumption. Energy efficient systems and highly optimized infrastructures can save a lot of money and the investment tends to be covered in a relatively short period of time. Data center power management tools are often used to keep an eye over each individual asset, each rack or the entire center. This view can be used to identify which are the biggest power consumers and action plans can be developed to reduce their load.
When hundreds of servers are hosted in the same facility, it is almost impossible to keep track of all of them without proper management software. Software assisted power management for data centers can be used to identify dead servers, faulty hardware, abnormal server loads and even unused equipment. All this information can be used to reduce the energy bill of the facility and improve the uptime. When something fails, it will show immediately and action can be taken to fix the problem. At the same time, when a server is no longer used or is idle, it can be decommissioned until it might be needed back up.
Another important piece of this type of software is the reporting side. History is being kept in order to ensure a clear overview over long periods of time that can also offer a view of the improvements implemented and their impact. This data can be used to develop best-practice policies such as power allocation to increase efficiency. The reports provided by data center energy management software can also be used to gain info of power usage based on time of day which can be used to reduce power allocation during low peak times.
