Distributed cloud has an impact on nearly every industry, fueling innovative use cases and creating a newly empowered edge primed to deliver transformative business value through new revenue streams or business models. Featured experts: Sam Doherty, World Wide Director Edge Infrastructure and Devices, Microsoft Howard Holton, Chief Technology Officer, Gigaom Edgar Haren, Senior Lead Offering Manager, Kyndryl
The global distributed cloud market size in terms of revenue was reasonably estimated at $4.4 billion in 2022 and is anticipated to rise to $11.2 billion by 2027, presenting a CAGR of 20.6% according to Markets and Markets research. While it’s still a fraction of the public cloud market size, distributed cloud is increasingly growing in popularity.
Even though the hype is relatively new, distributed cloud is actually an operational trend from the past, reemerging as new technologies reinvigorate a previously dormant model. It’s a re-imagined, better, more flexible version of the distributed systems from 50+ years ago. Distributed cloud has an impact on nearly every industry, fueling innovative use cases and creating a newly empowered edge primed to deliver transformative business value through new revenue streams or business models.
What is all the hype around distributed cloud? How can distributed cloud and edge computing benefit your industry?
Featured experts:
Sarah B. Nelson 00:02
Hello, I'm your host Sarah B. Nelson, Chief Design Officer for Kyndryl Vital and welcome back to another episode of The Progress Report. On today's episode, we're going to discuss distributed cloud and how it creates a modern operating environment for an empowered edge. We have some smart guests with us today to shed some light on how distributed cloud is shaping the digital landscape and discuss how companies can take advantage of an empowered edge to uncover innovative use cases and business models. With us today, we have Sam Doherty worldwide director edge infrastructure and devices from Microsoft. We have Howard Holton Chief Technology Officer from Gigaom and Edgard Haren, senior lead offering manager from Kyndryl. Does it feel like you're hearing a lot about distributed cloud lately? You are definitely not imagining it. In 2022, market size for distributed cloud was estimated at 4.4 billion, and is anticipated to arise to 11.2 billion by 2027. That's a fraction of the public cloud market. But it's clear that distributed cloud is on a major growth curve. So first, let's do a little grounding. Distributed cloud is a cloud computing model where resources and services are decentralized and spread across different physical locations. This could be on prem colocated, third party data centers or on your own cloud provider, or other providers centers. But ultimately, what this allows you to do is to mix and match where you run and deploy applications and components in a way that best meets your needs and the needs of your customers. Distributed Computing - it's interesting to me, it's an older operational model. It's reinvigorated by these new technologies and applications. There's lots of hype, but I'm seeing a lot of possibility. Really, the power here is the potential impact on every single industry. So many new applications, use cases, business models, revenue streams, all of these become possible. So that's what we're going to talk about today. So I want to start at the first thing that fascinates me, it's about distributed cloud, because it sounds really familiar to me. Isn't that an age old distributed model? Isn't that what that is? So let's start with you, Edgar, what's the history of distributed computing? And how has it evolved?
Edgar Haren 02:23
You know, first, let me just say, it's interesting to me to see how sometimes technologies or technical concepts can be a bit ahead of their time. And the linear evolution of these items really morphs into a long and windy road. So distributed computing emerged in the early 1970s. As organizations were looking to decouple their large, closed monolithic systems for architectures that delivered improved performance, scalability, resiliency, and even improved cost. However, distributed computing saw an ebb and flow of evolution as IT organizations, for decades, kind of shifted their strategies between centralizing and decentralizing their infrastructure. In my opinion, it took kind of three big events, to rekindle the demand for distributed computing, especially out at the edge. So with that, kind of that first big game changer was when cloud computing became pervasive, somewhere around 2012. Because only then did large cloud service providers make the strategic decision and investment to go beyond just cloud infrastructure, and delve into the vastly more complex arena platform services such as databases, or other data management offerings. This now enables organizations to deploy entire enterprise stacks to any region via virtual cloud services. The second game changer was when cloud providers then created the ability to deploy cloud services on premises addressing low latency compute requirements, and data privacy regulations. So now with those two items in place, organizations could deliver performance cloud services anywhere, including remote or Edge locations. However, the interconnectivity between cloud services, data, and management was still lacking. So unfortunately, that evolution kind of stalled again. But finally, what we saw in the last few years here was that distributed computing evolved again, and this time, you can kind of think of it as distributed computing morphing to distributed cloud, where cloud providers have delivered deep and intelligent connectivity between their services, essentially enabling a Data Fabric to ensure that data can flow seamlessly from the edge to the cloud. So these three things or three events have come together to serve as a catalyst to make the promise of distributed an edge computing a reality.
Sarah B. Nelson 05:02
And you know what I'm curious about is why is now a time that people are really becoming focused on edge. And where distributed cloud becomes really powerful? And I'm gonna throw that question to you, Howard.
Howard Holton 05:16
We need to talk about the company's appetite and availability to really leverage technology, because oftentimes as technology creators, the problem that we're trying to solve is, is in fact, an interesting technology problem. Sometimes the innovation or invention happens at a time when the market is not ready for it. And so I think part of the reason that we're starting to see this is the markets more than ready for it, the markets demanding it, the beauty of cloud kind of is the ability to do whatever I want to do right now. I can have an idea on Friday and Monday have it in production, right? And the cloud is the only way to do that; traditional procurement processes are too slow. But then what I'm doing is I still have all the standard workload challenges, and I still have all the location challenges. And when I think about what I'm really trying to do in a modern distributed customer-experience-focused, digital-experience-focused enterprise is really focus again on that experience. And so I start going, okay, cool. It's great that this thing runs, it's great that this thing works, but I want to improve performance. And the only way that I can do that is by leveraging the edge and getting the data to the customer faster, getting the the application response, faster, lowering that latency, the one thing we seem to not be able to change in everything that we do is the speed of light. Right?
Sarah B. Nelson 06:41
Yep!
Howard Holton 06:42
We didn't have is, organizations are already finding the cloud to be complex. They're already finding it to be difficult to really configure it and run it and manage it correctly. And then you layer on to that, oh, in addition to the complexity of the cloud, I now have the same application in what has suddenly become a multi cloud because of the edge. Distributed cloud is kind of traditional, hyper scalar, core cloud and edge in a somewhat seamless package that allows you to not have to learn multiple clouds within the same application. What distributed cloud is here to answer is, while customers are taking advantage of cloud and the edge, their ability to make that cohesive, has become incredibly complex. And so when we talk about the distributed cloud, we're talking about a cloud that exists in many places, many of which are focused on that user experience, in addition to the agility and availability, but have a sense of cohesion and coherency about them that the kind of multi cloud experience - when you did that before - simply did not have.
Sarah B. Nelson 07:48
The thing that's really interesting about that, I think a lot of times, we being end users unless we're aware of what's happening on the I would say like in the guts, unless we're aware of all those little things, the latencies the data, the data not arriving when you need it, or even just all the intricacies behind the scenes. That's the stuff that impacts the user experience in a way that it's not about the colors. And it's not about the interaction, it's this feeling of trust that you have with an application or not like. Is my data there? Is this car gonna drive me into a wall before it gets the information in time to tell me not to? All of those, like super gritty details of what we're doing a lot of this technology for. And you know, here's where I'm curious, Sam, is that all of this is pointing to how to organizations innovate, what do they have to do to be able to actually take advantage of the distributed cloud that the way that Howard's talking about it? How might they be doing that?
Sam Doherty 08:46
Yeah, I mean, as both Edgar and Howard said, distributed computing has a rich data history back several decades. And it's definitely gaining popularity right now. What we are seeing is companies are increasingly drawing on potential of the distributed cloud and edge due to numerous benefits that they can offer. Firstly, we see distributed cloud enables organizations to process and analyze data closer to the source, resulting in reduced latency and improved real-time decision making. Super critical for when you're looking at manufacturing environments, or you're looking at retail environments, where there's that critical decision that needs to be made around water consumption, or specifically looking at reducing your waste or your energy footprint - things that opens up the capabilities for new possibilities and unlocking new industries across the board fostering innovation and driving business growth. We're certainly seeing that as an avenue. And additionally, we also see in organizations feeling more empowered to do local data processing, enhancing privacy and improved operational efficiency, making it an attractive proposition today.
Sarah B. Nelson 09:57
Alright, so you're completely leading on to what my next question would be started pointing to it, but could either of you or any of you give me some examples of things that you're seeing in the industry? What are people doing to innovate? What are some of these newer sort of emerging use cases?
Sam Doherty 10:14
We’re certainly seeing exciting innovation happening in industries like fast food retailers, or even in mining and manufacturing. One of the largest fast food retailers, globally, operates a processing and is focused on customer satisfaction. And some of the things that they really looking at doing is reducing customer waste. Also putting the power in a user's hands for making that intellectual decision making, but feeling that they are in control. So for example, if you go into a fast food retailer, and there's this kiosk, you can go in, and you can say, at a visual, I want a, I want B, and I want C and that automatically then does calculation for preparation stations and maximizes efficiency. But it also reduces huge amount of bottlenecks in your production lead times and the way that you would produce. And then when you look at mining and manufacturing, I'll share a really great example in Africa, one of the big mines had nearly 18% fatality rates, in accidents, in transportation, and collapsing of mining shafts. And with collaboration with this particular mining company, these fascinating IoT sensors were placed strategically in critical areas to collect real-time data insights, leading to a life-saving initiative. During the analysis, it was discovered that reality actually to collapse of mind shops, were not solely caused by natural occurrences but rather failure in equipment, which is known as - I don't know if you've ever heard of it, and I had to learn with myself - a trench strut. And, it's actually an architectural structural component, that useful support or bracing, of a mineshaft. And in there's a little tiny button, and it actually resulted within doing a bunch of analytics, they came to realize that that little particular pin that was holding that component in place failed, and actually reduced significant number of fatalities. So technology is at the tip of our fingers that processes data, real time can give us a lifesaving insight and make those decisions at the point in time and not wait until a much later stage.
Sarah B. Nelson 12:34
These things are about getting the data there in real time and having the decisions made really in a snap of my fingers, but really super quick. I mean, how different is that from what's been happening? And, what are the consequences, though, of not having the data that way? Or what is the delta between what it used to be like and what it's like now?
Edgar Haren 12:54
I think it goes to a concept that's been around for quite some time called "data capital," which states that inherently data has a monetary value in it. And, we've seen industry data that shows that there is hundreds of billions of dollar advantage for companies that can become data driven, and turn insights into actions or activity. So then it brings up a new concept that we call "data gravity," which essentially says that as a mass of data becomes large, it starts to pool, other peripheral items, such as business logic, applications, and even infrastructure. So then it comes down to, if we go back to business capital, or data capital, what are three things that companies want to do either independently or as a collective and so the first one is grow top line revenue. The second one is to reduce operational costs and improve profitability. And the third is to disrupt the market. So to your point, your question is, well, what's the other side of it? What's the negative if companies don't start really capturing their data and enabling an empowered edge? Well, the other side of it is they have a severe competitive disadvantage, and their competition is going to create hard advantages that are going to be difficult to overcome in time. So let's take for instance the healthcare industry. The healthcare industry is the fastest vertical in terms of data creation and data volume. Lamentably 97% of healthcare data goes unprocess because it's unstructured. So the healthcare industry is primed for disruption. So then you might say, well, what can hospitals do at the edge to improve patient lifecycle and outcomes? Well, the first thing they can do is to build a strong data pipeline from the edge where they're ingesting all this unstructured and structured data. So taking that unstructured data from medical devices, combining it with their structured data from electronic medical records, so that they can extract insights, improve cross patients symptomology analysis, or even better evaluation of the efficacy of new treatments. So those are some examples for healthcare. If we pivot to manufacturing, the importance kind of shifts from top-line growth to operational efficiencies. So we've seen examples of, there's a large airplane manufacturer, and they've deployed augmented reality for maintenance and repair armar in the industry. And they saw upwards of 30% improvement in the acceleration of service and about a 90% improvement in surface quality or reducing human error by having this virtual dashboard that could help service the planes. And so then, if you build a connected factory, what that then does is, companies can deploy containerized manufacturing software of applications to improve performance and reduce costs. They can deploy artificial intelligence, which is imperative for robotic processing automation. There's the gamification of factories, so bringing in a digital twins environment, kind of like the Minority Report where you've got this virtual heads up display and the changes you make onto that virtual factory floor, then emulated down on the actual factory floor. And then there's other kinds of elements like deploying smart cameras, for fault detection, so a camera that can go around the body of a car to look for faults, or fissures. And then lastly, retail. Retail is the third fastest vertical in terms of data creation and ingestion. And here, the focus is again, shifting to now, top-line growth. So one of the
really cool use cases we've seen is augmented reality, in retail stores, like for smart fitting rooms, there's a retailer here in Texas that's deployed that and seen about a 30% increase in sales and shopping basket, because what it does is it allows people to walk into a fitting room, they can bring in a blue shirt, put that on, and then they'll show them what it looks like in red or green, it will highlight other accessories, maybe you should look at these pants or the shoes etc. So it helps reduce waste of people walking in with an armful of clothes, that they just leave in the fitting room. But it also helps increase the shopping basket because it highlights other items that other shoppers may potentially use, right? And most importantly, also is that, again, I can't emphasize this enough, but the data pipeline, making sure they're getting data from all of their stores, in order to get a 360 degree view of their customer. So they can then continually improve and personalize promotions in the shopping experience.
Sarah B. Nelson 18:15
My head is spinning around the possibilities for, again, the human experience, Ialways come back to this, one of my personal missions is to sort of have technology disappear to some degree. We are working to bring technology to people, not people to technology. And that's exactly what I'm hearing you all talk about, which is what's got me super excited is that there's all of these different ways that it's being used to just kind of slip into what people are doing. This is where I've kind of got I've gotten to with this, Sam, these are some like amazing, innovative ideas. But how could a company get started? Where would you even start?
Sam Doherty 18:55
Yeah, regardless of the size of the organization or industry, I think getting started at a distributed edge can be overwhelming, complicated, but as well, as exciting. You know, Howard said it in the beginning, you have an idea on Saturday, and you want to implement that on Monday. And this is actually the radical fast-paced momentum that we're seeing and how fast technology has evolved. But I think getting started begins in understanding the specific business needs and use cases that you're looking to solve for. I think the number one question is, what problem am I trying to solve for? It can be overwhelming with all the different products and solutions that are out there, it can be cost overwhelming for any organization. So it's good that you have a trusted partner or a trusted provider that you could help you make the informed decisions that you need, that can really help you tailor your requirements and the guidance of the things that you're looking to achieve. And then ultimately, taking a strategic approach will help organizations size and embark on their distributed cloud and edge computing journey.
Edgar Haren 20:05
One of the big challenges organizations have is that you have an evangelist who wants to do something new and creative, but oftentimes, they have to get executive buy in. And so it's better to get a small success that you can take to your executive sponsor and present that versus trying to do something really game changing, and then it falters. And now you have to overcome that internally. And usually, that can set things back significantly. Organizations have to kind of change their culture and be open to bring in these folks in to put their shared expertise in order to really move the ball forward in a succinct fashion. Otherwise, if they try to go at it alone, certainly there can be some pitfalls there that can really derail their strategy and goals.
Sam Doherty 20:56
And be super costly, right?
Edgar Haren 20:59
Yeah, exactly. Right. Exactly. Exactly.
Sarah B. Nelson 21:02
So this is my burning question for you now is for companies that want to leverage distributed cloud, what does progress look like?
Sam Doherty 21:11
Working with a partner like Kyndryl or Microsoft, you have a vast range of experience across multiple industries, it is not just one particular industry that you're focused at. There's multiple industries that you touch, and your experience in each of those could complement any customer's desired end state. And it just takes a partner like Kyndryl to bring those components together, and really see it flourish and realize a vision of a customer. I think, to your point is don't boil the ocean. What are the tools that we have today? And what are the tools that we need for the future?
Edgar Haren 21:51
Every company in the near future is going to be a software company. So I think there's some evolutions that are happening, that can be transformative with distributed cloud, whether you're a agriculture company, and you want to become an ag tech one of the great use cases I saw in a past life was there was a agriculture hardware manufacturer and their, their hardware, sales of tractors and other equipment were starting to decline, because they were being kind of cut out by direct from abroad, hardware providers, and they just couldn't compete on cost. So what they did was they built a data platform. And now all of the farmers that came in had this dashboard. And their equipment were all connected via sensors, so their irrigation systems would send the dashboard and note and say, hey, the fields are over watered or underwatered. They are reusing predictive analytics, it helped double their sales after they launched this platform, because they evolved from a hardware farming manufacturer to an ag tech.
Sarah B. Nelson 22:05
So I would argue that what they're then creating, what you're creating is this experience ecosystem. So technology, it's all the like the omni channel touchpoints of that, again, an ecosystem that wraps around in an invisible way, the needs of the Combine driver. And so you've got this experience ecosystem that you can now create, because of this technology that is going to offer like a really deep value. If you're interested in doing this for your own business, the really important starting point is to really think about proof of concept about how you can make to learn about how this technology and applications will work for your organization. So scope it small, make tests, engage other people in sort of learning how you can use this technology, and how it works with your business, ground all of that in, again, what your business needs, who your business is impacting. And I think there's just an enormous amount of potential to really transform your business but also transforms so many things in our universe.
Sarah B. Nelson 23:34
Thank you. That's the end of the episode today. We'll be back in two weeks for another episode. So come join us. Make sure to subscribe, share this with your colleagues, and we'll talk with you next time. So thank you all very much.
Sam Doherty 23:45
Thank you for having us.
Edgar Haren 23:46
Thank you guys.