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A growing number of companies are putting more emphasis on edge computing. According to a report by AT&T Cybersecurity, 75% of security leaders are planning, deploying, or have fully deployed an edge use case. This is largely attributed to the technology’s ability to save bandwidth, speed up response times, and enable data processing with fewer restrictions. In fact, the Study on the state of the periphery of the Linux Foundation predicts that by 2028, enterprises will make more extensive use of edge computing.
Speaking at VentureBeat’s Transform 2022 virtual conference, David Shacochis, VP of Enterprise Product Strategy at Lumenmoderate one round table to talk about how edge computing is transforming the use cases and strategies of some of the industry’s true giants, across hardware, software and service providers.
The discussion also featured Shacochis’ colleague Chip Swisher, who leads the Internet of Things (IoT) practice for Lumen; Rick Lievano, CTO for the global telecommunications industry at Microsoft; and Dan O’Brien, CEO of HTC Vive.
Cycles of technological evolution
Shacochis said computing power has gone through evolutionary cycles that oscillate between centralized and distributed models. Looking through periods of technological achievement, Shacochis said steam power enabled mass production industries, while electrical distribution fueled the modern industrial economy that brought about the dawn of the power of computation in microprocessing. This, he said, led to this day and what is called the Fourth Industrial Revolution.
He further noted that the dawn of the mainframe is the original dawn of computing power, distributed to client server models, then aggregated to the cloud and bringing all business logic back into more centralized postures.
“We are now seeing this explosion of all the different sources of data, different ways of processing that data, different types of sensor actuator cycles that can really add a lot of value to customer experience and efficiency. industry,” Shacochis said. “All of these different types of business outcomes from the many different ways to leverage the advantage. So with these industry cycles happening over decades, IT cycles happening over even shorter periods of years, we really led to this exciting time in the industry.
The fourth industrial revolution
Examining the Fourth Industrial Revolution era from a hardware perspective, O’Brien said HTC started out as an original design manufacturing (ODM) company. He said HTC makes motherboards and chipsets for other companies and other products and PCs, using immersive silicon. He added that the company moved very quickly to application-specific integrated circuit (ASIC) chips and GPUs that evolved into smartphone technology.
O’Brien noted that “many people don’t realize that was the dawn of what we see in extended reality today. [XR] world, building these new types of immersive products. It actually evolved from a lot of chipsets and evolved so much from smartphones. What’s in modern virtual reality [VR] Headsets and Displays is a smartphone panel that was fueled by the need to have superior visual quality and fidelity inside a smartphone.
“We now see where we need even more processing power,” he continued, “We need even more visual quality and performance inside VR headsets for an XR headset. and augmented reality [AR] kind of solutions. We see this increase in demand and overall performance needs. Additional products require big PCs and GPUs to make it all work. Now we are transferring all of this to a cloud environment. »
He added that there is now also artificial intelligence (AI) and machine learning (ML) that will optimize processes for all virtual content and interactions.
Additionally, Lievano said the cloud really has changed everything and the edge is an extension of the cloud. He noted that there’s a lot of talk at Microsoft about this notion of the smart cloud and smart edge, which he says is a way to deliver applications across the entire computing canvas to where they’re needed.
“As a developer, you like to think you can build an app once,” Lievano said. “You want to use the latest technologies, which are currently cloud-native principles, and you want to be able to deploy them anywhere, whether it’s a public cloud in the sky or an edge location. So this vision that we have of the intelligent cloud and the intelligent edge is very much dependent on our telecommunications partners because, ultimately, they provide that connectivity – the connective tissue needed to make this vision a reality. But the cloud must connect to the edge. And without telecom operators like Lumen, there is no smart advantage. »
According to Lievano, this is different from moving from mainframe to client server, where each mainframe and cloud server had their own unique developed models that had their own governance. Cloud-native capabilities are the same whether available in Azure or in the cloud, he said.
He also noted that at the edge you may have a subset of these cloud capabilities due to scale, but the programming model, devops model, management portals, management interfaces, and APIs are All The same. He also said that advertising is becoming another cloud region a developer can deploy their apps to, and that’s a huge difference between a mainframe and a client-server.
“Again, as a developer, I’m amazed at the progress and tooling, especially over the past few years,” Lievano said. “AI, for example, has had an incredible influence not only on the apps we create as developers, but also on the apps we write and how we develop those apps. So the cloud gives you unlimited computing capabilities [that are] really close at hand. Again, scale isn’t an issue, but features like serverless computing, for example, allow you to take your applications to the next level. In science, you will be able to build and deploy complex applications using microservices.
From the perspective of solution and service providers, Shacochis said the cloud and some of its tools make some things easier, but opportunities and customer expectations make things more complex. However, Swisher, talking about his specialty around IoT, said while some say IoT is a new concept, in fact, it has been around for over 20 years. It’s a concept that explains the ability to pull data from machines and devices and perform certain operations with it, Swisher said.
“I experienced the wave of what I call IoT 2.0, where you can be held in a factory, a localized production line control machine that was doing the processing there locally,” Swisher noted. “Then we saw the advent of cloud migration, and different siled cloud providers providing centralized end-to-end solutions in this space. Now we’re really seeing the need for integration on IoT 2.0, where we’re starting to see cross use cases, having data from multiple different IoT infrastructures and IoT paradigms and being able to bring all of that data together in a single view .
Swisher added that machine learning is the next evolution to have complete visibility into everything happening in the city, factory, warehouse and distribution to bring the data together.
He noted that IoT 2.0 “creates new challenges both from the point of view of computing and network and service integration, where it is necessary to calculate even closer to these aspects, because by building all those things together, we really need the ability to make that happen even more in real time so that we can scale based on our needs The concept of using in-place computing, you know, computing in a metropolitan or near-periphery capacity, as well as in the cloud, and being able to have everyone there to collect all these pieces and be able to move around, compute around these different places has really become critical.
Don’t miss the full discussion how edge computing is transforming the use cases and strategies of some of the industry’s true giants, across hardware, software and service providers.
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