>> Announcer: From theCUBE studios in Palo Alto and Boston, it's theCUBE, covering IBM Think brought to you by IBM. >> Hi, there, this is Dave Vellante. We're back at the IBM Think 2020 Digital Event Experience are socially responsible and distant. I'm here in the studios in Marlborough, our team in Palo Alto. We've been going wall to wall coverage of IBM Think, Kit Chee here is the Vice President, and general manager of Cloud and Enterprise sales at Intel. Kit, thanks for coming on. Good to see you. >> Thank you, Dave. Thank you for having me on. >> You're welcome, and Evaristus Mainsah, Mainsah is here. Mainsah, he is the general manager of the IBM Cloud Pack Ecosystem for the IBM Cloud. Evaristus, it's good to see you again. Thank you very much, I appreciate your time. >> Thank you, Dave. Thank you very much. Thanks for having me. >> You're welcome, so Kit, let me start with you. How are you guys doing? You know, there's this pandemic, never seen it before. How're things where you are? >> Yeah, so we were quite fortunate. Intel's had an epidemic leadership team. For about 15 years now, we have a team consisting of medical safety and operational professionals, and this same team has, who has navigated as across several other health issues like bad flu, Ebola, Zika and each one and one virus then navigating us at this point with this pandemic. Obviously, our top priority as it would be for IBM is protecting the health and well being of employees while keeping the business running for our customers. The company has taken the following measures to take care of it direct and indirect workforce, Dave and to ensure business continuity throughout the developing situation. They're from areas like work from home policies, keeping hourly workers home and reimbursing for daycare, elderly care, helping with WiFi policies. So that's been what we've been up to Intel's manufacturing and supply chain operations around the world world are working hard to meet demand and we are collaborating with supply pains of our customers and partners globally as well. And more recently, we have about $16 Million to support communities, from frontline health care workers and technology initiatives like online education, telemedicine and compute need to research. So that's what we've been up to date. Pretty much, you know, busy. >> You know, every society that come to you, I have to say my entire career have been in the technology business and you know, sometimes you hear negative toward the big tech but, but I got to say, just as Kit was saying, big tech has really stepped up in this crisis. IBM has been no different and, you know, tech for good and I was actually I'm really proud. How are you doing in New York City? >> Evaristus: No, thank you, Dave, for that, you know, we are, we're doing great and, and our focus has been absolutely the same, so obviously, because we provide services to clients. At a time like this, your clients need you even more, but we need to focus on our employees to make sure that their health and their safety and their well being is protected. And so we've taken this really seriously, and actually, we have two ways of doing this. One of them is just on to purpose as a, as a company, on our clients, but the other is trying to activate the ecosystem because problems of this magnitude require you to work across a broad ecosystem to, to bring forth in a solution that are long lasting, for example, we have a call for code, which where we go out and we ask developers to use their skills and open source technologies to help solve some technical problems. This year, the focus was per AVADA initiatives around computing resources, how you track the Coronavirus and other services that are provided free of charge to our clients. Let me give you a bit more color, so, so IBM recently formed the high performance computing consortium made up of the feYderal government industry and academic leaders focus on providing high performance computing to solve the COVID-19 problem. So we're currently we have 33 members, now we have 27 active products, deploying something like 400 teraflops as our petaflop 400 petaflops of compute to solve the problem. >> Well, it certainly is challenging times, but at the same time, you're both in the, in the sweet spot, which is Cloud. I've talked to a number of CIOs who have said, you know, this is really, we had a cloud strategy before but we're really accelerating our cloud strategy now and, and we see this as sort of a permanent effect. I mean, Kit, you guys, big, big on ecosystem, you, you want frankly, a level playing field, the more optionality that you can give to customers, you know, the better and Cloud is really been exploding and you guys are powering, you know, all the world's Clouds. >> We are, Dave and honestly, that's a huge responsibility that we undertake. Before the pandemic, we saw the market through the lens of four key mega trends and the experiences we are all having currently now deepens our belief in the importance of addressing these mega trends, but specifically, we see marketplace needs around key areas of cloudification of everything below point, the amount of online activities that have spiked just in the last 60 days. It's a testimony of that. Pervasive AI is the second big area that we have seen and we are now resolute on investments in that area, 5G network transformation and the edge build out. Applications run the business and we know enterprise IT faces challenges when deploying applications that require data movement between Clouds and Cloud native technologies like containers and Kubernetes will be key enablers in delivering end to end data analytics, AI, machine learning and other critical workloads and Cloud environments at the edge. Pairing Intel's data centric portfolio, including Intel's obtain SSPs with Red Hat, Openshift, and IBM Cloud Paks, enterprise can now break through storage bottlenecks and have unconstrained data availability in the hybrid and multicloud environments, so we're pretty happy with the progress we're making that together with IBM. >> Yeah, Evaristus, I mean, you guys are making some big bets. I've, you know, written and discussed in my breaking analysis, I think a lot of people misunderstand IBM Cloud, Ginni Rometty arm and a bow said, hey, you know, we're after only 20% of the workloads are in cloud, we're going after the really difficult to move workloads and the hybrid workloads, that's really the fourth foundation that Arvin you know, talks about, that you and IBM has built, you know, your mainframes, you have middleware services, and in hybrid Cloud is really that fourth sort of platform that you're building out, but you're making some bets in AI. You got other services in the Cloud like, like blockchain, you know, quantum, we've been having really interesting discussions around quantum, so I wonder if you can talk a little bit about sort of where you're allocating resources, some of the big bets that, that you're making for the next decade. >> Well, thank you very much, Dave, for that. I think what we're seeing with clients is that there's increasing focus on and, and really an acceptance, that the best way to take advantage of the Cloud is through a hybrid cloud strategy, infused with data, so it's not just the Cloud itself, but actually what you need to do to data in order to make sure that you can really, truly transform yourself digitally, to enable you to, to improve your operations, and in use your data to improve the way that you work and improve the way that you serve your clients. And what we see is and you see studies out there that say that if you adopt a hybrid cloud strategy, instead of 2.5 times more effective than a public cloud only strategy, and Why is that? Well, you get thi6ngs such as you know, the opportunity to move your application, the extent to which you move your applications to the Cloud. You get things such as you know, reduction in, in, in risk, you, you get a more flexible architecture, especially if you focus on open certification, reduction and certification reduction, some of the tools that you use, and so we see clients looking at that. The other thing that's really important, especially in this moment is business agility, and resilience. Our business agility says that if my customers used to come in, now, they can't come in anymore, because we need them to stay at home, we still need to figure out a way to serve them and we write our applications quickly enough in order to serve this new client, service client in a new way. And well, if your applications haven't been modernized, even if you've moved to the Cloud, you don't have the opportunity to do that and so many clients that have made that transformation, figure out they're much more agile, they can move more easily in this environment, and we're seeing the whole for clients saying yes, I do need to move to the Cloud, but I need somebody to help improve my business agility, so that I can transform, I can change with the needs of my clients, and with the demands of competition and this leads you then to, you know, what sort of platform do you need to enable you to do this, it's something that's open, so that you can write that application once you can run it anywhere, which is why I think the IBM position with our ecosystem and Red Hat with this open container Kubernetes environment that allows you to write application once and deploy it anywhere, is really important for clients in this environment, especially, and the Cloud Paks which is developed, which I, you know, General Manager of the Cloud Pak Ecosystem, the logic of the Cloud Paks is exactly that you'll want plans and want to modernize one, write the applications that are cloud native so that they can react more quickly to market conditions, they can react more quickly to what the clients need and they, but if they do so, they're not unlocked in a specific infrastructure that keeps them away from some of the technologies that may be available in other Clouds. So we have talked about it blockchain, we've got, you know, Watson AI, AI technologies, which is available on our Cloud. We've got the weather, company assets, those are key asset for, for many, many clients, because weather influences more than we realize, so, but if you are locked in a Cloud that didn't give you access to any of those, because you hadn't written on the same platform, you know, that's not something that you you want to support. So Red Hat's platform, which is our platform, which is open, allows you to write your application once and deploy it anyways, particularly our customers in this particular environment together with the data pieces that come on top of that, so that you can scale, scale, because, you know, you've got six people, but you need 600 of them. How do you scale them or they can use data and AI in it? >> Okay, this must be music to your ears, this whole notion of you know, multicloud because, you know, Intel's pervasive and so, because the more Clouds that are out there, the better for you, better for your customers, as I said before, the more optionality. Can you6 talk a little bit about the rela6tionship today between IBM and Intel because it's obviously evolved over the years, PC, servers, you know, other collaboration, nearly the Cloud is, you know, the latest 6and probably the most rel6evant, you know, part of your, your collaboration, but, but talk more about what that's like you guys are doing together that's, that'6s interesting and relevant. >> You know, IBM and Intel have had a very rich history of collaboration starting with the invention of the PC. So for those of us who may take a PC for granted, that was an invention over 40 years ago, between the two companies, all the way to optimizing leadership, IBM software like BB2 to run the best on Intel's data center products today, right? But what's more germane today is the Red Hat piece of the study and how that plays into a partnership with IBM going forward, Intel was one of Red Hat's earliest investors back in 1998, again, something that most people may not realize that we were in early investment with Red Hat. And we've been a longtime pioneer of open source. In fact, Levin Shenoy, Intel's Executive Vice President of Data Platforms Group was part of COBOL Commies pick up a Red Hat summit just last week, you should definitely go listen to that session, but in summary, together Intel and Red Hat have made commercial open source viable and enterprise and worldwide competing globally. Basically, now we've65 used by nearly every vertical and horizontal industr6y. We are bringing our customers choice, scalability and speed of innovation for key technologies today, such as security, Telco, NFV, and containers, or even at ease and most recently Red Hat Openshift. We're very excited to see IBM Cloud Packs, for example, standardized on top of Openshift as that builds the foundation for IBM chapter two, and allows for Intel's value to scale to the Cloud packs and ultimately IBM customers. Intel began partnering with IBM on what is now called Pax over two years ago and we 6are committed to that success and scaling that, try ecosystem, hardware partners, ISVs and our channel. >> Yeah, so theCUBE by the way, covered Red Hat summit last week, Steve Minima and I did a detailed analysis. It was awesome, like if we do say so ourselves, but awesome in the sense of, it allowed us to really sort of unpack what's going on at Red Hat and what's happening at IBM. Evaristus, so I want to come back to you on this Cloud Pack, you got, it's, it's the kind of brand that you guys have, you got Cloud Packs all over the place, you got Cloud Packs for applications, data, integration, automation, multicloud management, what do we need to know about Cloud pack? What are the relevant components there? >> Evaristus: I think the key components is so this is think of this as you know, software that is designed that is Cloud native is designed for specific core use cases and it's built on Red Hat Enterprise Linux with Red Hat Openshift container Kubernetes environment, and then on top of that, so you get a set of common services that look right across all of them and then on top of that, you've got specific both open source and IBM software that deals with specific plant situations. So if you're dealing with applications, for example, the open source and IBM software would be the run times that you need to write and, and to blow applications to have setups. If you're dealing with data, then you've got Cloud Pack to data. The foundation is still Red Hat Enterprise Linux sitting on top of with Red Hat Openshift container Kubernetes environment sitting on top of that providing you with a set of common services and then you'll get a combination of IBM zone open, so IBM software as well as open source will have third party software that sits on top of that, as well as all of our AI infrastructure that sits on top of that and machine learning, to enable you to do everything that you need to do, data to get insights updates, you've got automation to speed up and to enable us to do work more efficiently, more effectively, to make your smart workers better, to make management easier, to help management manage work and processes, and then you've got multicloud management that allows you to see from a single pane, all of your applications that you've deployed in the different Cloud, because the idea here, of course, is that not all sitting in the same Cloud. Some of it is on prem, some of it is in other Cloud, and you want to be able to see and deploy applications across all of those. And then you've got the Cloud Pack to security, which has a combination of third party offerings, as well as ISV offerings, as well as AI offerings. Again, the structure is the same, REL, Red Hat Openshift and then you've got the software that enables you to manage all aspects of security and to deal with incidents when, when they arise. So that gives you data applications and then there's integration, as every time you start writing an application, you need to integrate, you need to access data security from someplace, you need to bring two pipes together for them to communicate and we use a Cloud Pack for integration to allow us to do that. You can open up API's and expose those API so others writing application and gain access to those API's. And again, this idea of resilience, this idea of agility, so you can make changes and you can adapt data things about it. So that's what the Cloud Pack provides for you and Intel has been an absolutely fantastic partner for us. One of the things that we do with Intel, of course, is to, to work on the reference architectures to help our certification program for our hardware OEMs so that we can scale that process, get many more OEMs adopt and be ready for the Cloud Packs and then we work with them on some of the ISV partners and then right up front. >> Got it, let's talk about the edge. Kity, you mentioned 5G. I mean it's a really exciting time, (laughs) You got windmills, you got autonomous vehicles, you got factories, you got to ship, you know, shipping containers. I mean, everything's getting instrumented, data everywhere and so I'm interested in, let's start with Intel's point of view on the edge, how that's going to evolve, you know what it means to Cloud. >> You know, Dave, it's, its definitely the future and we're excited to partner with IBM here. In addition to enterprise edge, the communication service providers think of the Telcos and take advantage of running standardized open software at the Telco edge, enabling a range of new workloads via scalable services, something that, you know, didn't happen in the past, right? Earlier this year, Intel announced a new C on second generation, scalable, atom based processes targeting the 5G radio access network, so this is a new area for us, in terms of investments going to 5G ran by deploying these new technologies, with Cloud native platforms like Red Hat Openshift and IBM Cloud Packs, comm service providers can now make full use of their network investments and bring new services such as Artificial Intelligence, augmented reality, virtual reality and gaming to the market. We've only touched the surface as it comes to 5G and Telco but IBM Red Hat and Intel compute together that I would say, you know, this space is super, super interesting, as more developed with just getting started. >> Evaristus, what do you think this means for Cloud and how that will evolve? Is this sort of a new Cloud that will form at the edge? Obviously, a lot of data is going to stay at the edge, probably new architectures are going to emerge and again, to me, it's all about data, you can create more data, push more data back to the Cloud, so you can model it. Some of the data is going to have to be done in real time at the edge, but it just really extends the network to new horizons. >> Evaristus: It does exactly that, Dave and we think of it and which is why I thought it will impact the same, right? You wouldn't be surprised to see that the platform is based on open containers and that Kubernetes is container environment provided by Red Hat and so whether your data ends up living at the edge or your data lives in a private data center, or it lives in some public Cloud, and how it flows between all of them. We want to make it easy for our clients to be able to do that. So this is very exciting for us. We just announced IBM Edge Application Manager that allows you to basically deploy and manage applications at endpoints of all these devices. So we're not talking about 2030, we're talking about thousands or hundreds of thousands. And in fact, we're working with, we're getting divided Intel's device onboarding, which will enable us to use that because you can get that and you can onboard devices very, very easily at scale, which if you get that combined with IBM Edge Application Manager, then it helps you onboard the devices and it helps you divide both central devices. So we think this is really important. We see lots of work that moving on the edge devices, many of these devices and endpoints now have sufficient compute to be able to run them, but right now, if they are IoT devices, the data has been transferred to hundreds of miles away to some data center to be processed and enormous pass and then only 1% of that actually is useful, right? 99% of it gets thrown away. Some of that actually has data residency requirements, so you may not be able to move the data to process, so why wouldn't you just process the data where the data is created around your analytics where the data is spread, or you have situations that are disconnected as well. So you can't actually do that. You don't want to stop this still in the supermarket, because there's, you lost connectivity with your data center and so the importance of being able to work offline and IBM Edge Application Manager actually allows you so it's tournament so you can do all of this without using lots of people because it's a process that is all sort or automated, but you can work whether you're connected or you're disconnected, and then you get replication when you get really, really powerful for. >> All right, I think the developer model is going to be really interesting here. There's so many new use cases and applications. Of course, Intel's always had a very strong developer ecosystem. You know, IBM understands the importance of developers. Guys, we've got to wrap up, but I wonder if you could each, maybe start with Kit. Give us your sense as to where you want to see this, this partnership go, what can we expect over the next, you know, two to five years and beyond? >> I think it's just the area of, you know, 5G, and how that plays out in terms of edge build out that we just touched on. I think that's a really interesting space, what Evaristus has said is spot on, you know, the processing, and the analytics at the edge is still fairly nascent today and that's growing. So that's one area, building out the Cloud for the different enterprise applications is the other one and obviously, it's going to be a hybrid world. It's not just a public Cloud world on prem world. So the whole hybrid build out What I call hybrid to DoD zero, it's a policy and so the, the work that both of us need to do IBM and Intel will be critical to ensure that, you know, enterprise IT, it has solutions across the hybrid sector. >> Great. Evaristus, give us the last word, bring us home. >> Evaristus: And I would agree with that as well, Kit. I will say this work that you do around the Intel's market ready solutions, right, where we can bring our ecosystem together to do even more on Edge, some of these use cases, this work that we're doing around blockchain, which I think you know, again, another important piece of work and, and I think what we really need to do is to focus on helping clients because many of them are working through those early cases right now, identify use cases that work and without commitment to open standards, using exactly the same standard across like what you've got on your open retail initiative, which we're going to do, I think is going to be really important to help you out scale, but I wanted to just add one more thing, Dave, if you if you permit me. >> Yeah. >> Evaristus: In this COVID era, one of the things that we've been able to do for customers, which has been really helpful, is providing free technology for 90 days to enable them to work in an offline situation to work away from the office. One example, for example, is the just the ability to transfer files and bandwidth, new bandwidth is an issue because the parents and the kids are all working from home, we have a protocol, IBM Aspera, which will make available customers for 90 days at no cost. You don't need to give us your credit card, just log on and use it to improve the way that you work. So your bandwidth feels as if you are in the office. We have what's an assistant that is now helping clients in more than 18 countries that keep the same thing, basically providing COVID information. So those are all available. There's a slew of offerings that we have. We just want listeners to know that they can go on the IBM website and they can gain those offerings they can deploy and use them now. >> That's huge. I knew about the 90 day program, I didn't realize a sparrow was part of that and that's really important because you're like, Okay, how am I going to get this file there? And so thank you for, for sharing that and guys, great conversation. You know, hopefully next year, we could be face to face even if we still have to be socially distant, but it was really a pleasure having you on. Thanks so much. Stay safe, and good stuff. I appreciate it. >> Evaristus: Thank you very much, Dave. Thank you, Kit. Thank you. >> Thank you, thank you. >> All right, and thank you for watching everybody. This is Dave Volante for theCUBE, our wall to wall coverage of the IBM Think 2020 Digital Event Experience. We'll be right back right after this short break. (upbeat music)

>>Yeah, >>from the Cube Studios in Palo Alto and Boston. It's the Cube covering IBM. Think brought to you by IBM. >>Welcome back, everybody. This is Dave Vellante of the Cube, and you're watching our continuous coverage of the IBM think Digital 2020 experience. And we're really pleased to have Rob High here. He's not only an IBM fellow bodies. He runs the vice president CTO of the IBM Edge Computing Initiative. Rob, thanks so much for coming on the Cube. Good to see you. Which we're face to face, but yeah, that time to be safe and healthy, I guess. And did so edge obviously hot topic. Everybody has this sort of point of view would be interested in how IBM looks at edge. You define it and what your thoughts are on. It's evolution. >>Yeah, well, you know, there's ah really kind of two fairly distinct ways of thinking about the edge of the telcos. Our, ah, you know, they're creating edge capabilities in their own network facilities. We call that the network edge on the other side of the edge they that I think matters a lot to our enterprise businesses is there's remote on premise locations where they actually perform the work that they do, where the majority of people are, where the data that actually gets created is first formed and where the actions that they need to operate on are being taken. That is a lot of interest, because if we can move work workloads, Iot workloads to where that data is being created, where those actions are being taken Uh, not only can we dramatically reduce the late and see to those decisions, uh, but we can also ensure continuous operations and the failed in the presence of perhaps network failures. We can manage the growth of increasing demand for network bandwidth as Maura born data gets created and we can optimize the efficiency of both the business operations as well as the I t operations before that. So for us edge computing at the end of the day is about movie work where the data and the actions are being taken >>well, so this work from home, you know, gives a result of this pandemic is kind of creating a new stresses on networks and people are putting, you know, pouring money actually into beefing up that infrastructure is sort of an extension of what we used to think about edge. But I wonder if you could talk about some of the industries and the use cases that you guys we are seeing and notwithstanding, though assay that >>work from home pivot. Yeah, absolutely. So I mean, look, we have seen ah, the need for placing workloads close to where it is being created and where actions have been picking in virtually every industry, the ones that are probably easier for us to think about and more common in terms of our mindset. Our is manufacturing. If you think about all the things that go on in a factory floor that need to be able to perform analytic in, uh, in the equipment and the processes that are performing in the affection for, If you think, for example, production quality. Uh, you know, if you've got a machine that's putting out parts and maybe it's welding seams on metal boxes, uh, you know, you want to be able to look at the quality of that seem at the moment that is being performed, so that if there are any problems, you can remediate that immediately rather than having that box move on down the line and find that you know the quality issues they were created earlier on now have exacerbated in other ways. Um, you know, so quality, productive quality. Ah, inspection production optimization in our world of Covic Cover 19 and worker safety and getting workers back to work and ensuring that you know people wearing the masks and are exercising social distancing. This is on the factory floor. Worker Insight is another major use case that we're seeing surface of lake with a lot of interest in using whether that's infrared cameras or Bluetooth beacons or infrared cameras. Any variety of devices that could be employed in the work area to help ensure that factories are operating efficiently, that workers are safe. Ah, and whether that's in a factor situation or even in an office situation or e a r in a warehouse or distribution center. And all these scenarios the the utility, the edge computing to bring to those use cases is tremendous. >>And a lot of these devices are unattended or infrequently attended. I always use the windmill example. Um, you know, you don't want to have to do a truck roll to figure out you know what the dynamics are going on, that at the windmill s, so I can instrument that. But what about the management of those devices you know from an autonomous standpoint? And and are you? What are you doing? Or are you doing anything in the autonomous managed space? >>Yeah. In fact, that's really kind of key here, because when you think about the scale, the diversity and the dynamic dynamism of equipment in these environments And as you point out, Dave, you know the lack of I t resource lack of skills on the factory floor, or even in the retail store or hotel or distribution center or any of these environments. The situation is very similar. You can't simply manage getting the right workloads to the right place at the right time. In sort of the traditional approach is, you have to really think about another autonomous approach to management and, you know, let the system the side for you. What software needs to be placed out there? Which software to put their If it's an analytic algorithm, what models to be associated with that software and getting to the right place at the right place at the right Time is a key Part of what we do in this thing that we call IBM Edge application manager is that product that we're really kind of bringing to market right now in the context of edge computing that facilitates this idea of autonomous management. >>You know, I wonder if you could comment Robb on just sort of the approach that you're taking with regard to providing products and services. I mean, we've seen a lot of, uh, situations where people are just essentially packing, packaging traditional, you know, compute and storage devices and sort of throwing it over the fence at the edge. Uh, and saying, Hey, here's our edge computing solution and another saying there's not a place for that. Maybe that will help flatten the network and, you know, provide Ah, gateway for storing on maybe processing information. But it seems to us that that that a bottoms up approach is going to be more appropriate. In other words, you've got engineers, you know who really understand operations, technology, people, maybe a new breed of developers emerging. How do you see the evolution you know of products and services and architectures at >>the edge? Yeah, so First of all, let me say IBM is taking a really pretty broad approach to edge computing we have. What I just described is IBM Edge Application Manager, which is the if you will the platform or the infrastructure on which we can manage the appointment of workloads out to the edge. But then add to that we do have a whole variety of edge and Nevil enabled applications that are being created are global service of practices and our AI applications business all are creating, um, variations of their product specific to address and exploit edge computing and to bring that advantage to the business. And of course, then we also have global services Consulting, which is a set of skilled resource, is who know we understand the transformations that business need to go through when they went, take advantage of edge computing and how to think about that in the context of both their journey to the cloud as well as now in this case, the edge. But also then how to go about implementing and delivering that, uh and then firmly further managing that now you know, coupled out then with at the end of the day you're also going to need the equipment, the devices, whether that is an intelligent automobile or other vehicle, whether that is an appellate, a robot or a camera, Um, or if those things are not intelligent. But you want to bring intelligence to them that how you augment that with servers and other forms of cluster computing that resides resident with the device. All of those are going to require participation from a very broad ecosystem. So we've been working with partners of whether that is vendors who create hardware and enabling that hardware in certifying that hardware to work with our management infrastructure or whether those are people who bring higher order services to the table that provide support for, let's, say, data cashing and facilitating the creation of applications, or whether those are device manufacturers that are embedding compute in their device equipment. All of that is part of our partnership ecosystem, Um, and then finally, you know, I need to emphasize that, you know, the world that we operate in is so vast and so large. There are so many edge devices in the marketplace, and that's growing so rapidly, and so many participants in that likewise There are a lot of other contributors to this ecosystem that we call edge computing. And so for all of those reasons, we have grounded IBM education manager on open source. We created an open source project called Open Rise, and we've been developing that, actually now, for about 4.5 years just recently, the Linux Foundation has adopted Stage one adoption of Open arising as part of its Lennox Foundation edge LF edge, uh, Reg X Foundry project. And so we think this is key to building out, Um, a ecosystem of partners who want to both contribute as well consumed value and create ecosystems around this common idea of how we manage the edge. >>Yeah, I'm glad you brought up the ecosystem, and it's too big for any one company toe to go it alone. But I want to tap your brain on just sort of architectures. And there's so many diverse use cases, you know, we don't necessarily see one uber architecture emerging, but there are some characteristics that we think are important at the edge you mentioned sort of real time or near real time. In many cases, it has to be real time you think about autonomous vehicles? Um, yeah. A lot of the data today is analog, and maybe it doesn't have to be digitized, but much of it will be, um, it's not all gonna be sent back to the cloud. It may not all have to be persisted. So we've envisioned this sort of purpose built, you know, architecture for certain use cases that can support real time. That maybe have, you know, arm based processors. Ah, or other alternative processors there that can do real time analytics at the edge and maybe sending portions of the data back. How do you see the architectures evolving from a technologist? >>Well, so certainly one of the things that we see at the edge is a tremendous premium being placed on things like energy consumption. So architectures they're able to operate efficiently with less power is ah is certainly an advantage to any of those architectures that are being brought aboard. Um, clearly, you know x 86 is a dominant architecture in any information technology endeavor. More specifically at the edge. We're seeing the emergence of lot of arm based architecture chips out there. In fact, I would guess that the majority of the edge devices today are not being created with, um, arm architectures, but it's the you know, but some of this is about the underlying architecture of the compute. But also then the augmentation of that compute the the compute Thea the CP use with other types of processing units. Whether those GPS, of course, we're seeing, you know, a number of deep use being created that are designed to be low power consuming, um, and have a tremendous amount of utility at the edge. There are alternate processing units, architectures that have been designed specifically for AI model based analytics. Uh, things like TP use and infuse and and, uh, and set around, which are very purpose built for certain kinds of intellect. And we think that those are starting to surface and become increasingly important. And then on the flip side of this is both the memory storage in network architectures which are sort of exotically different. But at least in terms of capacity, um have quite variability. Specifically, five G, though, is emerging and five g. While it's not necessarily the same computing, there is a lot of symbolism between edge and five G and the kinds of use cases that five G envisions are very similar to those that we've been talking about in the edge world as well. >>Rob, I want to ask you about sort of this notion of program ability at the edge. I mean, we've seen the success of infrastructure as code. Um, how do you see program ability occurring at the edge in terms of fostering innovation and maybe new developer bottles or maybe existing developer models at the edge? Yeah, >>we found a lot of utility in sort of leveraging what we now think of as cloud computing or cloud computing models. Uh, you know, the idea of continue ization extends itself very easily into the edge. Whether that is running a container in a docker runtime, let's say on an edge device which is, you know, resource constrained and purpose built and needs to focus on sort of a very small footprint or even edge clusters edge servers where we might be running a cluster of containers using our kubernetes platform called open shift. Um, you know the course of practices of continuous integration, continuous delivery. What we write a Otherwise think of his Dev ops. Ah, and, of course, the benefits they continue. Realization brings to the idea of component architectures. Three. Idea of loose coupling. The separation of concerns, the ability to mix and match different service implementations to be opposed. Your application are all ideas that were matured in the cloud world but have a lot of utility in the edge world. Now we actually call it edge native programming. But you can think of that as being mostly cloud native programming, with a further extension that there are certain things you have to be aware of what you're building for the edge. You have to recognize that resource is air limited. Unlike the cloud where we have this notion of infinite resource, you don't have that at the edge. Find and constrained resources. Be worried about, you know, Layton sees and the fact that there is a network that separates the different services and that network can be and reliable. It can introduce his own forms of Layton sees it, maybe bandwidth constrained and those air issues that you now have to factor into your thinking as you build out the logic of your application components. But I think by building on the cloud native programming about me paradigm. You know, we get to exercise sort of all of the skills that have been developing and maturing in the cloud world. Now, for the edge >>that makes sense. My last question is around security. I mean, I've often sort of tongue in cheek said, you know, building a moat around the castle doesn't work anymore. The queen i e. The data has left the castle. She's everywhere. So what about the security model? I mean, I feel like the edge is moving so fast you feel confident or what gives you confidence >>that we can secure the edge. You know, the edges does introduce some very interesting and challenging concerns with respect to security because, frankly, the compute is out there in the wild. You know, you've got computers in the store you've got, you know, people walking around the kiosks you have in the manufacturing site, you know, workers that are, you know, in the midst of all of this compute capability and so the attack surface is substantially bigger. And that's been a big focus for us, is how to the only way validate in 30 of the software that was But it also takes advantage of one of the key characters with edge computing to bring to the table, which is, if you think about it. You know, when you've got personal and private information being entered into quote system, the more often you move that personal private data around, and certainly the more that you move it to a central location and aggregate that with other data, the more of a target becomes more vulnerable, exposed that data becomes and by using edge computing, which moves the workloads out to the edge where that did has been created in some sense, you can process on it there and then move it back. They need central location, you don't have to aggregate it. And that actually in itself is a counterbalance of all of the other issues that we also describe about security by essentially not moving the personal privacy and in protecting by keeping it exactly where it began. >>You know, Rob, this is an exciting topic. Is a huge opportunity for IBM and Ginny in and talk about the trillion dollar opportunity and hybrid cloud and the Edge is a multi $1,000,000,000 opportunity for IBM and, uh So you just got to go get her done. But I really appreciate you coming on the Cube and sharing your insights. That awesome topic in the best interest of the David. Yeah. Thank you. Thank you for the thank you. Stay safe and thank you for watching everybody. This is Dave Volante for the Cube. This is our coverage of IBM. Think 2020 the digital. Think >>we'll be right back after this short break? >>Yeah, yeah, yeah, yeah.