How will enterprises consistently adopt IoT and edge computing technologies?

The IoT and edge computing space is one that will continue to evolve, but organizations may be struggling now with finding the right way to address it. What the edge means to most organizations doesn’t always translate to an individual organization. The same goes for IoT systems, which I’ve always advocated that organizations will find their best way and have an “aha” moment.

The piece of good news is that the how isn’t as daunting as it may seem. I say that because some familiar faces are in place to make this seem much more reasonable than how face value may be perceived. VMware and Microsoft, among others, are making significant investments in this space that will pave the way for specific business systems to be easy to implement. This will allow each organization to find its way with brands that already have an established relationship in place.

VMware Pulse IoT Center and Azure IoT Edge are two technologies that can make this transition start to make sense. Consider as IoT devices grow in popularity — it will be natural that there may be storage and networking considerations that will need to be rethought. Businesses will see IoT devices start to become more integrated and modern options in systems used — for example, machinery, autonomous vehicles, smart buildings, appliances and more — that will pose an IoT conundrum: Where what used to be a forklift is now a multi-terabyte a day data generating system. And the location has 25 of them. And your organization has 12 distribution centers. You can quickly see storage, bandwidth and compute needs will make this seem to be a tricky tradeoff between smarter devices and unwanted network and storage problems. That example was a forklift. The next example could be a tractor-trailer, an air-conditioning unit or scores of other examples.

Looking at consistent adoption for edge and IoT, organizations need to use key technologies to do the business-benefit-inducing work at the edge. Take the forklift example. If analytics can be performed on the device, wouldn’t that make sense to interpret the data there, at the source? Let the analytics be set in the cloud or central management, but do the hard work close to the data. Aggregating the results is the most important part, and organizations can manage that relatively smaller amount of data in a much more scalable fashion.

Many of IoT and edge use cases today are around photo and video surveillance, but these are just a start. Organizations will have plenty of options for more complete systems, and when multiple systems are in place, the management and scale will become more important than ever.

A safe bet from IT practices of the past is to use key platform partners for the technology services to drive your business; IoT and edge are no different. Just finding the right place to start is the most important step.

Still not sure? Azure IoT can even walk organizations through a few questions to help them get started in the right direction.

What do you look for in an IoT and edge deployment today? Are platforms from established brands part of your requirements? Share your comments below.

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