Data center availability is one of the most important aspects when downtime can also quickly have a financial impact. In order to detect problems at an early stage and thus avoid downtime, the term "predictive maintenance" becomes increasingly important. In an ideal situation, predictive maintenance allows for the lowest possible maintenance frequency to avoid unscheduled reactive maintenance without incurring the cost of too much preventive maintenance.
When talking about predictive maintenance, it is usually about improving and avoiding delays in data deployment. In the data center area, the focus is more on systems and devices such as:
After all, these components are the physical basis of every data center in order to ensure trouble-free operation. The larger the data center, the more of these components there are, and also the more the need for regular maintenance increases. Evaluating data from these systems and devices enables predictive maintenance - and consequently new savings potential and improved availability. However, this predictive maintenance works with data that must first be obtained and analyzed.
In order to make predictions about unknown future events, predictive analytics is needed. This is a business analytics & information management related discipline. Organizations use techniques and modeling to analyze current data and obtain case-based predictions and forecasts. This allows data scientists to use the patterns found in historical and transactional data to identify risks and opportunities for the future.
As described above, predictive maintenance allows you to save time, energy and money, but also offers other benefits including:
Paessler PRTG Enterprise Monitor supports you with your predictive maintenance program. Designing and implementing a predictive maintenance solution can be time consuming, labor intensive and costly. If you are looking for a monitoring tool that supports you with your predictive maintenance program, contact the monitoring experts at Paessler to chat about your requirements.
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