According to Gartner while 91 percent of today's data is created and processed inside centralized data centers, by 2022 about 75 percent of data will need analysis and action at the edge. 

A new report of 250 IT decision makers, including IT director/IT manager/sys admins, data center managers, application engineers, operations managers, and systems engineers reveals that it's hard enough to collect data currently, and as things continue to move to the edge and data becomes even more critical, it will only get more difficult. 

The report "The Modern Data Center: Supporting IoT Edge, and Big Data-Generated Information," was a collaboration between Intel Data Center Manager and Schneider Electric, and revealed that while edge computing presents the ability to bring data processing and storage closer to the growing number of connected devices, without the right tools, enterprises will struggle to maintain control over their vast and complex data centers, making edge computing strategies more difficult to adopt.

To learn more and dive into the findings, VMblog spoke with Jeff Klaus, General Manager of Intel Data Center Management Solutions.  

VMblog:  Were you surprised that almost half of the survey respondents said it's still a challenge to collect data?  Why is data collection so difficult for those managing data centers?

Managing power usage in any data center environment, whether on-premises, a distributed data center architecture, or a regional or micro data center facility serving the edge, can be complex.

Today, many data centers are maxed out in power capacity and poor thermal design that make obtaining insights difficult. So, I wasn't necessarily surprised when I saw that 40 percent of survey respondents indicated that it's somewhat difficult to get data from the IT, power, and cooling assets in their data center, and 7 percent of the respondents indicated that it is very difficult to do so.

With 38 percent of respondents indicating they are not using a DCIM tool, it's likely that the teams without the proper tools to help gather critical data are hamstrung. Further, the cost and complexity for these teams is going to continue rise as their decision-making process gets delayed with a lack of insight into power and thermal monitoring, data center health and energy efficiency, as well capacity planning.

VMblog:  How is edge computing impacting the data center?

Healthcare, transportation, utilities, oil and gas, retail and agriculture are just a few of the industries that will be transformed by smart systems and applications as technology evolves from a state of connected things to IoT. But these types of deployments require information processing closer to the source of the data. Instead of incurring the cost and latency of sending this information to the public cloud or an on-premise centralized data center, businesses are incorporating edge computing within their infrastructures.

Of the 87 percent of respondents that are collecting data from the IT, power, and cooling assets in their data center, 64 percent are collecting data on the edge. However, 54 percent of respondents are using one to three tools to collect data from the edge and 32 percent are using four or more.

While edge computing presents the ability to bring data processing and storage closer to the growing number of connected devices, without the right tools enterprises will struggle to maintain control over their vast and complex data centers, making edge computing strategies more difficult to adopt. Furthermore, with so many tools being used to collect data, the desire for a combined solution at the edge to scale and automate is important.

VMblog:  Can you make any predictions for next year after gathering this insight?

In 2019 the edge use case I usually see is high bandwidth, large volume applications. In fact, 50 percent of survey respondents indicated that they are looking to address this exact use case when deploying an edge solution. The next set of use cases after that are going to be moved up with 5G enabling a network for machines to talk to machines, and machines to talk to humans. We need the new networks to enable the amount of simultaneous connections all the devices will require.

Also I think we'll see existing players and new entries continue innovating edge stack infrastructure solutions, to handle the edge applications demands. So not only will you have edge application, and data choices to make, but also cloud infrastructure platforms that focus on various edge blueprints and their applications to evaluate.

About Jeff Klaus