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Traditional Data Centers Must Adapt If They Are To Survive

Posted on February 25, 2019 by Jessica Ciesla

Since their inception, data centers seem to have been in a near constant state of evolution. As we approach the end of another decade, the next evolution cycle is nearing, and with it, traditional data centers must grapple with emerging technologies, environmental concerns, and ever-increasing costs. In fact, a recent Gartner study revealed that traditional data centers will turn to Artificial Intelligence (AI) and machine learning to combat the array of challenges that are looming. To support this claim, the study further suggested that approximately 30 percent of traditional data centers will fail to implement machine learning solutions, which will result in their failure by the year 2020.

The above statement might seem like it caters to a pessimistic's dark and gloomy mentality; but the reality is quite the opposite. Each day there is a surge in the amount of data that is used by traditional data centers throughout the globe. As these surges increase, traditional data centers will eventually become too bogged down to produce efficient outputs. Instead of going the way of the dinosaurs, traditional data centers can instead drive operational efficiencies and lower costs by choosing to implement the right monitoring technologies in tandem with machine learning solutions.

Enjoy The Numerous Benefits Of Server Optimization In Traditional Data Centers

One of the potential downfalls of the traditional data center is its physical servers and storage equipment. The latter entities must be properly maintained, which is not only a time consuming but a potentially expensive task. Fortunately, AI-based predictive analysis can be used by data center managers to more effectively distribute workloads across the various servers. Through the proper workload distribution, servers can not only operate at higher efficiencies, but data center loads will be easier to predict and subsequently manage. When data center managers can more readily track server performance, network congestion, and disk utilization, they will be able to optimize server storage systems to reduce risks, lower costs, and effectively increase efficiencies.

Machine Learning Coupled With PX Intelligent Rack PDUs Leads To Intelligent Monitoring

Machine learning has the unique capability of helping IT professionals more efficiently complete their daily IT monitoring tasks. By incorporating copious amounts of data, machine learning solutions can more accurately predict when a machine is close to failing.

An intelligent rack PDU provides power monitoring at the PDU and individual outlet level. It is also systematically designed to provide user defined threshold alerts. These alerts ensure that data center mangers can effectively monitor the entire data center from either an off-site or on-site location. Whether a device needs to be powered on or off, or an environmental sensor is triggered by overheating, intelligent PDUs coupled with machine learning solutions can help data center managers more effectively manage the entire data center in real-time.

The Bottom Line: Machine Learning Can Only Be Embraced With The Right Data Center Tools

If data center managers want to enjoy greater financial benefits and higher operating efficiencies, then machine learning and AI must be carefully balanced with the right data center tools. In this vein, if the statistics from the latest Gartner study come to fruition, then data center managers should carefully watch the machine learning space as they seek to identify new ways to improve traditional data centers. In addition to machine learning solutions, intelligent PDUs offer the insights needed to balance power usage, save energy, avoid server crashes, and assist with the proper allocation of resources. In short, by accurately identifying opportunities to grow, analyzing risks, and implementing technological solutions that increase operational efficiencies, traditional data centers will successfully ride out the next evolution cycle.

To learn more about how machine learning, AI, and power monitoring solutions can be effectively leveraged within traditional data centers, check out our website here

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