The great IIoT cloud myth
Author : Jason Andersen, VP of Business Line Management, Stratus
30 July 2018
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Mention the Industrial Internet of Things (IIoT) and, for many people, the same image will come to mind: a lot of small, inexpensive devices pushing data up to the cloud. In fact, some major vendors of cloud computing solutions have aggressively pushed this vision. But for the enterprises at the forefront of the IIoT revolution, this cloud-centric vision is shifting. Jason Andersen, VP of Business Line Management, Stratus Technologies explains.
They are discovering that there are certain types of real-time computing that happen at the edge that you simply cannot – or do not want to – push up to cloud. That may be due to security concerns, latency issues or a variety of other reasons.
Given the sheer volume of data generated at the edge and the speed with which it needs to be made available to other systems or to analytics, the connectivity to the cloud just isn’t robust enough for many of these newer situations. The reality is that edge computing is better suited to handle certain use cases, such as data collection, real-time data processing for decision support and most SCADA functions, whereas the cloud can be utilised for non-real-time workloads like post-processing corporate analytics.
A good way to illustrate the edge and cloud playing their most appropriate roles would be with a driverless car scenario. Imagine being in a driverless car going 80mph, when a car from another lane begins to swerve towards you. The round trip of data to and from the cloud would be too slow for the car to react, resulting in a collision. Edge computing, on the other hand, can provide real-time information, allowing the car to take immediate action to avoid the crash. Metrics collected from the car could then be periodically sent to the data centre or cloud, where they can be used for analytics that support planning and maintenance in the future.
Generation 1 vs. Generation 2
There’s actually an interesting cultural divide at the core of this issue. Talk to the operational technology (OT) teams who have been managing automation systems for years – they understand what needs to happen at the edge and what doesn’t. That’s where they live. But go talk to the people pushing cloud-based IIoT implementations and they are a different breed. They are usually large enterprise IT professionals. They preach the same approach to industrial automation that they do for enterprise IT deployments: send it to the cloud and all will be well. However, those ideas belong more to “Generation 1” IoT thinking, which is all about cloud. “Generation 2” IoT thinking, which focuses on the hybridisation of cloud and edge, is beginning to gain popularity as enterprises realise the benefits of both edge and cloud, and how to pick the right tool for the job given the situation and computing needs.
There’s also a cost issue at stake. One engineer I spoke to recently estimated that about 15 percent of the data generated on the plant floor needs to go to the cloud to make it immediately available to other systems. What about the other 85 percent? That data must be aggregated and filtered to tease out the valuable bits. But if you push it all up to the cloud, you have to pay for all that capacity.
What does this mean for industrial enterprises considering their IIoT strategy? Simply that you need to carefully evaluate your workloads to determine what can safely go to the cloud, and which are better off staying at the edge. The success of your IIoT investments will depend on getting that right.
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