Automation of device management and performance monitoring analytics are necessary to control costs of web scale data centers, especially as most organizations continually ask for their employees to do more with fewer resources.
Big Data and massive data growth are at the forefront of datacenter growth. Imagine what it takes to manage the datacenters that provide us with this information.
According to research conducted by Seagate, time consuming drive management activities represent the largest storage related pain points for datacenter managers. In addition to trying to manage potential failures of all of the disk drives, managers must monitor the performance of multiple servers as well. As indicated by Seagate, there are tremendous opportunities in cost savings if the timing of retiring disk drives can be optimized. Significant savings can also result from streamlining the management process.
While there is no such thing as a typical datacenter, for the purpose of discussion, we will assume that a typical micro-datacenter contains about 10,000 servers while a large scale data center contains on the order of 100,000 servers. In a webscale hyperconverged environment, if each server housed 15 devices (hard drives and/or flash drives), a datacenter contains anywhere from 150,000 to 1.5 million devices. That is an enormous amount of servers and devices to manage. Even if we scaled back by an order of a magnitude or two, to 50 servers and 750 drives for example, managing a data center is a daunting task.