Diana: How are organizations starting to address these challenges?
Dave: That ability to push software changes remains a challenge, as does tiering of the system. Suddenly, there are 10,000 devices, and managing a large number of dispersed devices can be incredibly complex and exhausting. It requires the ability to have dynamic tiering that leverages different technologies in different ways, with operational configuration management. More vendors will get into this space and make purpose-built tools with AI ops, configuration management, identity access management distributed encryption, and key management systems that work with edge-based systems.
Myke: I spend a lot of my time working in energy and resources with organizations like Wichita State University,9 which has a 60,000 square foot smart building on a smart grid with robotics, AI/ML, and 3D printers. Are there manufacturing use cases where the four-tier architecture is well-suited? Are there economic considerations around smart metering in power and utilities?
Satya: I have different thoughts for the manufacturing and metering use cases. To me, the potential opportunity for the edge-computing architecture is different in different cases.
The robotic factory you described is very interesting, but it is a capital-intensive investment. The robots are expensive, and each production change requires reprogramming and debugging. Therefore, each specification change comes with a certain fixed capital cost for the hardware. For each product change, there is a nontrivial cost for the software, testing, and troubleshooting. Today, the break-even point for robotics hardware may well be in hundreds of thousands, or millions, of units. Regardless, manufacturing is moving toward shorter, faster production runs—such as, producing 1,000 units quickly. At these levels, making a business case for large fixed costs gets harder.
The whole point of the robots was to reduce the people costs, but if I produce 100 widgets, it’s going to be faster and cheaper for a human with cognitive guidance to produce 100 units than to program and test those robots for such a small run. The truly unique opportunity for four-tiered edge computing (cloudlets in factories) are those situations where there is a human in the loop and the production is not multimillion-unit volumes but shorter runs, where some kind of cognitive assistance, guidance, automation to detect human error is needed.
Below a certain volume, having the sensing done by the system but leaving the actuation to the human is more cost-effective, and it aligns with the emerging desire to have short-run, highly agile manufacturing.
For the utilities and data collection, the opportunity for cloudlets and edge computing really is in the privacy space. The reason is increasing consumer concerns about how much data they’re exposing and all the inferencing that can be done with it. For example, the data collected every day by a smart water meter can reveal when your dishwasher runs. From there, it is a short step to inferring your activity, which is concerning. Edge computing, however, can alleviate some of these concerns by keeping the data in escrow at the edge, giving the consumer the opportunity to receive, for example, a more personalized experience, in exchange for detailed consumption data.
Dave: It is going to be an evolving and learning process on how to convert this to make money. The ability to keep track of the devices out there and their operations, and then to sync with software, security, and governance issues is a problem still to be solved.
To give one example, one of our major retail clients had a recommendation engine that used customers’ browser data and behavior to manage demographics targeting and determining logistics to recommend products that have a higher chance of interest. It raised sales by 25%. If they could integrate their mobile, IoT, and edge data from stores and their supply chain, they could slice and dice that data in new and different ways. The challenge right now to bringing in that data is privacy, security, and orchestration management.
Myke: We’re evaluating options, such as deploying AWS/Outposts or Azure/Stack for clients and, at this point, they may be cost prohibitive. We’re seeing some of the same challenges around 5G. I think economics shouldn’t be underestimated when you talk about edge computing.10 You can’t penalize the first few use cases with the whole cost of the infrastructure because it can scale with much smaller incremental costs to accommodate future use cases.
Dave: There has to be a business case. My client, a government contractor, is deploying AWS Outposts because their data standards forbid them from leaving top secret data at their data centers. They would pay a premium for it. Ultimately, with the right business case, edge computing can make businesses more innovative and creative and can be a disruptor. Many businesses just look at the bottom line, and they’re missing the core point and end up falling by the wayside.
Innovation: Across technology and industry
Diana: What developments are you seeing with the telecommunications and cloud providers that are shaping what is possible for this four-tier architecture model?
Satya: I think the big players, the cloud computing players, have all realized that edge computing is not just vapor; it’s real. But none of them quite knows yet how to translate that abstract concept into their edge strategies or to determine how similar their edge approach should be to the cloud.
In 2018, Microsoft announced that the intelligent edge and the intelligent cloud both would be equally important.11 They have followed through on this with the introduction of Azure Edge Zones.12 They created a brand-new profit and loss group called Azure for Operators, which is basically edge computing. So, not just Microsoft, but many corporate giants, are seeing the significance of edge computing—and they are embracing it.
Initially, Amazon started with pure serverless compute for sensing. They now have an edge and fiber play to reduce latency and improve connectivity speeds13 and continue to expand their large-scale software distribution ecosystem across the Alexa devices and skills network.
Vodafone and AWS are partnering on an innovation program for companies in the United Kingdom and Europe to incentivize the use of edge computing.14 Additionally, Amazon has announced additional edge innovations with the AWS Snow Family.15
From the viewpoint of the developer and the customer, the best scenario would be if they don’t know where the computing is taking place. If they can run an application and the edge looks exactly like the cloud, no one needs to change the workflow or software. That should be an enormous source of opportunity.