influencing cutting-edge computing
While cutting-edge computing will continue to proliferate across all industries in 2020, growth challenges will continue to emerge as organizations learn what types of implementations can achieve the best results and how to leverage data to drive digital transformation. For me, I see three areas where we will see greater clarity and confidence in high-end computing.
Security at the edge
For a while, people worried about safety at the edge. At
Stratus, we make sure you can't use the same security technology you use in the
data center and apply it to the perimeter. The main difference is in the large
number of connected devices, and each one represents a potential vulnerability.
RELATED: Implementing a Border Security Strategy
By 2020, end-user security requirements will become more
specific due to the work of industry consortia or end users defining specific
requirements. Security criteria are likely to vary widely from industry to
industry: for example, finance companies have different cutting-edge computing needs and goals than wastewater treatment plants. Companies must create
security controls based on what data is collected, where it is usedand who needs
access to it. For example, a peripheral device might not need a persistent
cloud connection and might be configured to initiate a connection only when
certain data needs to be transferred.
IT and OT
Another ongoing discussion of peripherals focuses on how IT
and OT teams interact with each other and who is responsible for the various
aspects of edge deployments. I believe that in 2020, IT and OT will begin to
collaborate more effectively as they gain a better understanding of each team
member's role and clarify the paths from swimming to cutting-edge computing. As
responsibilities become clearer, the organization as a whole adapts to both
structure and budget support. There are many benefits to this technique,
including improving the customer experience through predictive analytics.
OEM manufacturers
Finally, I believe OEMs will add more intelligence to their
machines, given the lack of highly trained technicians in the field. It's
amazing to see the level of interest from people who build very intelligent
machines. They will add features like predictive maintenance, resilience and
increased autonomy.
Machines will make better use of the data they exchange with
software solutions such as handling complex events. This will reduce the need
for supervisory intervention and will be the first step in further adapting
machine processes. And it drives the full cycle of these smart machines,
helping with what I mentioned earlier about IT and OT and how they work
together, integrating technology into one machine, reducing complexity but
producing data that affects business results.