The rapidly evolving Internet of Things (IoT) is expected to have a significant impact on the data center market, its customers, technology providers, technologies, as well as sales and marketing models. Indeed, Gartner analysts estimate the IoT will include 26 billion units installed by 2020, with IoT product and service suppliers generating incremental revenue exceeding $300 billion, mostly in services.
“IoT deployments will generate large quantities of data that need to be processed and analyzed in real time,” explained Fabrizio Biscotti, research director at Gartner. “Processing large quantities of IoT data in real time will increase as a proportion of workloads of data centers, leaving providers facing new security, capacity and analytics challenges.”
As Biscotti notes, the IoT connects remote assets – effectively providing a data stream between the asset and centralized management systems. Those assets can then be integrated into new and existing organizational processes to provide information on status, location and functionality. Meanwhile, real-time information enables more accurate understanding of status, as it enhances utilization and productivity via optimized usage and more accurate decision support. Similarly, business and data analytics offer insights into the business requirements data feed from the IoT environment, helping to predict the fluctuations of IoT-enriched data and information.
“The enormous number of devices, coupled with the sheer volume, velocity and structure of IoT data, creates challenges, particularly in the areas of security, data, storage management, servers and the data center network, as real-time business processes are at stake,” said Joe Skorupa, vice president and distinguished analyst at Gartner. “Data center managers will need to deploy more forward-looking capacity management in these areas to be able to proactively meet the business priorities associated with IoT.”
According to Skorupa, the magnitude of network connections and data associated with the IoT will accelerate a distributed data center management approach that calls for providers to offer efficient system management platforms. More specifically, massive amounts of input data will likely be generated from sources that are globally distributed.
“Transferring the entirety of that data to a single location for processing will not be technically and economically viable. The recent trend to centralize applications to reduce costs and increase security is incompatible with the IoT,” he added. “Organizations will be forced to aggregate data in multiple distributed mini data centers where initial processing can occur. Relevant data will then be forwarded to a central site for additional processing.”
As noted above, the new architecture will present operations staffs with significant challenges, as they will need to manage the entire environment as a homogeneous entity – while simultaneously monitoring and controlling individual locations. In addition, organizations will have to automate selective backups of valuable and required data. This sifting and sorting is expected to generate additional big data processing loads that will consume additional processing, storage and network resources.
“Data center operations and providers will need to deploy more forward-looking capacity management platforms that can include a data center infrastructure management (DCIM) system approach of aligning IT and operational technology (OT) standards and communications protocols to be able to proactively provide the production facility to process the IoT data points based on the priorities and the business needs,” Biscotti concluded. ”Already in the data center planning phase, throughput models derived from statistical capacity management platforms or infrastructure capacity toolkits will include business applications and associated data streams. Those comprehensive scenarios will impact design and architecture changes by moving toward virtualization, as well as cloud services. This will reduce the complexity and boost on-demand capacity to deliver reliability and business continuity.”
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