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John Roese, Dell Technologies & Chris Wolf, VMware | theCUBE on Cloud 2021


 

>>from around the globe. It's the Cube presenting Cuban Cloud brought to you by Silicon Angle. Welcome back to the live segment of the Cuban cloud. I'm Dave, along with my co host, John Ferrier. John Rose is here. He's the global C T o Dell Technologies. John, great to see you as always, Really appreciate >>it. Absolutely good to know. >>Hey, so we're gonna talk edge, you know, the the edge, it's it's estimated. It's a multi multi trillion dollar opportunity, but it's a highly fragmented, very complex. I mean, it comprises from autonomous vehicles and windmills, even retail stores outer space. And it's so it brings in a lot of really gnarly technical issues that we want to pick your brain on. Let me start with just what to you is edge. How do you think about >>it? Yeah, I think I mean, I've been saying for a while that edges the when you reconstitute Ike back out in the real world. You know, for 10 years we've been sucking it out of the real world, taking it out of factories, you know, nobody has an email server under their desk anymore. On that was because we could put it in data centers and cloud public clouds, and you know that that's been a a good journey. And then we realized, Wait a minute, all the data actually was being created out in the real world. And a lot of the actions that have to come from that data have to happen in real time in the real world. And so we realized we actually had toe reconstitute a nightie capacity out near where the data is created, consumed and utilized. And, you know, that turns out to be smart cities, smart factories. You know, uh, we're dealing with military apparatus. What you're saying, how do you put, you know, edges in tow, warfighting theaters or first responder environments? It's really anywhere that data exists that needs to be processed and understood and acted on. That isn't in a data center. So it's kind of one of these things. Defining edge is easier to find. What it isn't. It's anywhere that you're going to have. I t capacity that isn't aggregated into a public or private cloud data center. That seems to be the answer. So >>follow. Follow that. Follow the data. And so you've got these big issue, of course, is late and see people saying, Well, some applications or some use cases like autonomous vehicles. You have to make the decision locally. Others you can you can send back. And you, Kamal, is there some kind of magic algorithm the technical people used to figure out? You know what, the right approaches? Yeah, >>the good news is math still works and way spent a lot of time thinking about why you build on edge. You know, not all things belong at the edge. Let's just get that out of the way. And so we started thinking about what does belong at the edge, and it turns out there's four things you need. You know, if you have a real time responsiveness in the full closed loop of processing data, you might want to put it in an edge. But then you have to define real time, and real time varies. You know, real time might be one millisecond. It might be 30 milliseconds. It might be 50 milliseconds. It turns out that it's 50 milliseconds. You probably could do that in a co located data center pretty far away from those devices. One millisecond you better be doing it on the device itself. And so so the Leighton see around real time processing matters. And, you know, the other reasons interesting enough to do edge actually don't have to do with real time crossing they have to do with. There's so much data being created at the edge that if you just blow it all the way across the Internet, you'll overwhelm the Internets. We have need toe pre process and post process data and control the flow across the world. The third one is the I T. O T boundary that we all know. That was the I O t. Thing that we were dealing with for a long time. And the fourth, which is the fascinating one, is it's actually a place where you might want to inject your security boundaries, because security tends to be a huge problem and connected things because they're kind of dumb and kind of simple and kind of exposed. And if you protect them on the other end of the Internet, the surface area of protecting is enormous, so there's a big shift basically move security functions to the average. I think Gardner made up a term for called Sassy. You know, it's a pretty enabled edge, but these are the four big ones. We've actually tested that for probably about a year with customers. And it turns out that, you know, seems to hold If it's one of those four things you might want to think about an edge of it isn't it probably doesn't belong in >>it. John. I want to get your thoughts on that point. The security things huge. We talked about that last time at Del Tech World when we did an interview with the Cube. But now look at what's happened. Over the past few months, we've been having a lot of investigative reporting here at Silicon angle on the notion of misinformation, not just fake news. Everyone talks about that with the election, but misinformation as a vulnerability because you have now edge devices that need to be secured. But I can send misinformation to devices. So, you know, faking news could be fake data say, Hey, Tesla, drive off the road or, you know, do this on the other thing. So you gotta have the vulnerabilities looked at and it could be everything. Data is one of them. Leighton. See secure. Is there a chip on the device? Could you share your vision on how you see that being handled? Cause it's a huge >>problem. Yeah, this is this is a big deal because, you know, what you're describing is the fact that if data is everything, the flow of data ultimately turns into the flow of information that knowledge and wisdom and action. And if you pollute the data, if you could compromise it the most rudimentary levels by I don't know, putting bad data into a sensor or tricking the sensor which lots of people can dio or simulating a sensor, you can actually distort things like a I algorithms. You can introduce bias into them and then that's a That's a real problem. The solution to it isn't making the sensors smarter. There's this weird Catch 22 when you sense arise the world, you know you have ah, you know, finite amount of power and budget and the making sensors fatter and more complex is actually the wrong direction. So edges have materialized from that security dimension is an interesting augment to those connected things. And so imagine a world where you know your sensor is creating data and maybe have hundreds or thousands of sensors that air flowing into an edge compute layer and the edge compute layer isn't just aggregating it. It's putting context on it. It's metadata that it's adding to the system saying, Hey, that particular stream of telemetry came from this device, and I'm watching that device and Aiken score it and understand whether it's been compromised or whether it's trustworthy or whether it's a risky device and is that all flows into the metadata world the the overall understanding of not just the data itself, but where did it come from? Is it likely to be trustworthy? Should you score it higher or lower in your neural net to basically manipulate your algorithm? These kind of things were really sophisticated and powerful tools to protect against this kind of injection of false information at the sensor, but you could never do that at a sensor. You have to do it in a place that has more compute capacity and is more able to kind of enriched the data and enhance it. So that's why we think edges are important in that fourth characteristic of they aren't the security system of the sensor itself. But they're the way to make sure that there's integrity in the sense arised world before it reaches the Internet before it reaches the cloud data centers. >>So access to that metadata is access to the metadata is critical, and it's gonna be it's gonna be near real time, if not real time, right? >>Yeah, absolutely. And, you know, the important thing is, Well, I'll tell you this. You know, if you haven't figured this out by looking at cybersecurity issues, you know, compromising from the authoritative metadata is a really good compromise. If you could get that, you can manipulate things that a scale you've never imagined. Well, in this case, if the metadata is actually authoritatively controlled by the edge note the edge note is processing is determining whether or not this is trustworthy or not. Those edge nodes are not $5 parts, their servers, their higher end systems. And you can inject a lot more sophisticated security technology and you can have hardware root of trust. You can have, you know, mawr advanced. PK I in it, you can have a I engines watching the behavior of it, and again, you'd never do that in a sensor. But if you do it at the first step into the overall data pipeline, which is really where the edges materializing, you can do much more sophisticated things to the data. But you can also protect that thing at a level that you'd never be able to do to protect a smart lightbulb. A thermostat in your house? >>Uh, yes. So give us the playbook on how you see the evolution of the this mark. I'll see these air key foundational things, a distributed network and it's a you know I o t trends into industrial i o t vice versa. As a software becomes critical, what is the programming model to build the modern applications is something that I know. You guys talk to Michael Dell about this in the Cuban, everyone, your companies as well as everyone else. Its software define everything these days, right? So what is the software framework? How did people code on this? What's the application aware viewpoint on this? >>Yeah, this is, uh, that's unfortunately it's a very complex area that's got a lot of dimensions to it. Let me let me walk you through a couple of them in terms of what is the software framework for for For the edge. The first is that we have to separate edge platforms from the actual edge workload today too many of the edge dialogues or this amorphous blob of code running on an appliance. We call that an edge, and the reality is that thing is actually doing two things. It's, ah, platform of compute out in the real world and it's some kind of extension of the cloud data pipeline of the cloud Operating model. Instance, he added, A software probably is containerized code sitting on that edge platform. Our first principle about the software world is we have to separate those two things. You do not build your cloud your edge platform co mingled with the thing that runs on it. That's like building your app into the OS. That's just dumb user space. Colonel, you keep those two things separate. We have Thio start to enforce that discipline in the software model at the edges. The first principle, the second is we have to recognize that the edges are are probably best implemented in ways that don't require a lot of human intervention. You know, humans air bad when it comes to really complex distributed systems. And so what we're finding is that most of the code being pushed into production benefits from using things like kubernetes or container orchestration or even functional frameworks like, you know, the server list fast type models because those low code architectures generally our interface with via AP, eyes through CCD pipelines without a lot of human touch on it. And it turns out that, you know, those actually worked reasonably well because the edges, when you look at them in production, the code actually doesn't change very often, they kind of do singular things relatively well over a period of time. And if you can make that a fully automated function by basically taking all of the human intervention away from it, and if you can program it through low code interfaces or through automated interfaces, you take a lot of the risk out of the human intervention piece of this type environment. We all know that you know most of the errors and conditions that break things are not because the technology fails it because it's because of human being touches it. So in the software paradigm, we're big fans of more modern software paradigms that have a lot less touch from human beings and a lot more automation being applied to the edge. The last thing I'll leave you with, though, is we do have a problem with some of the edge software architectures today because what happened early in the i o t world is people invented kind of new edge software platforms. And we were involved in these, you know, edge X foundry, mobile edge acts, a crane. Oh, and those were very important because they gave you a set of functions and capabilities of the edge that you kind of needed in the early days. Our long term vision, though for edge software, is that it really needs to be the same code base that we're using in data centers and public clouds. It needs to be the same cloud stack the same orchestration level, the same automation level, because what you're really doing at the edge is not something that spoke. You're taking a piece of your data pipeline and you're pushing it to the edge and the other pieces are living in private data centers and public clouds, and you like they all operate under the same framework. So we're big believers in, like pushing kubernetes orchestration all the way to the edge, pushing the same fast layer all the way to the edge. And don't create a bespoke world of the edge making an extension of the multi cloud software framework >>even though the underlying the underlying hardware might change the microprocessor, GPU might change GP or whatever it is. Uh, >>by the way, that that's a really good reason to use these modern framework because the energies compute where it's not always next 86 underneath it, programming down at the OS level and traditional languages has an awful lot of hardware dependencies. We need to separate that because we're gonna have a lot of arm. We're gonna have a lot of accelerators a lot of deep. Use a lot of other stuff out there. And so the software has to be modern and able to support header genius computer, which a lot of these new frameworks do quite well, John. >>Thanks. Thanks so much for for coming on, Really? Spending some time with us and you always a great guest to really appreciate it. >>Going to be a great stuff >>of a technical edge. Ongoing room. Dave, this is gonna be a great topic. It's a clubhouse room for us. Well, technical edge section every time. Really. Thanks >>again, Jon. Jon Rose. Okay, so now we're gonna We're gonna move to the second part of our of our technical edge discussion. Chris Wolf is here. He leads the advanced architecture group at VM Ware. And that really means So Chris's looks >>at I >>think it's three years out is kind of his time. Arise. And so, you know, advanced architecture, Er and yeah. So really excited to have you here. Chris, can you hear us? >>Okay. Uh, >>can Great. Right. Great to see you again. >>Great >>to see you. Thanks for coming on. Really appreciate it. >>So >>we're talking about the edge you're talking about the things that you see way set it up is a multi trillion dollar opportunity. It's It's defined all over the place. Uh, Joey joke. It's Could be a windmill. You know, it could be a retail store. It could be something in outer space. Its's It's it's, you know, whatever is defined A factory, a military installation, etcetera. How do you look at the edge. And And how do you think about the technical evolution? >>Yeah, I think it is. It was interesting listening to John, and I would say we're very well aligned there. You know, we also would see the edge is really the place where data is created, processed and are consumed. And I think what's interesting here is that you have a number off challenges in that edges are different. So, like John was talking about kubernetes. And there's there's multiple different kubernetes open source projects that are trying to address thes different edge use cases, whether it's K three s or Cubbage or open your it or super edge. And I mean the list goes on and on, and the reason that you see this conflict of projects is multiple reasons. You have a platform that's not really designed to supported computing, which kubernetes is designed for data center infrastructure. Uh, first on then you have these different environments where you have some edge sites that have connectivity to the cloud, and you have some websites that just simply don't write whether it's an oil rig or a cruise ship. You have all these different use cases, so What we're seeing is you can't just say this is our edge platform and, you know, go consume it because it won't work. You actually have to have multiple flavors of your edge platform and decide. You know what? You should time first. From a market perspective, I >>was gonna ask you great to have you on. We've had many chest on the Cube during when we actually would go to events and be on the credit. But we appreciate you coming into our virtual editorial event will be doing more of these things is our software will be put in the work to do kind of a clubhouse model. We get these talks going and make them really valuable. But this one is important because one of the things that's come up all day and we kind of introduced earlier to come back every time is the standardization openness of how open source is going to extend out this this interoperability kind of vibe. And then the second theme is and we were kind of like the U S side stack come throwback to the old days. Uh, talk about Cooper days is that next layer, but then also what is going to be the programming model for modern applications? Okay, with the edge being obviously a key part of it. What's your take on that vision? Because that's a complex area certain a lot of a lot of software to be written, still to come, some stuff that need to be written today as well. So what's your view on How do you programs on the edge? >>Yeah, it's a It's a great question, John and I would say, with Cove it We have seen some examples of organizations that have been successful when they had already built an edge for the expectation of change. So when you have a truly software to find edge, you can make some of these rapid pivots quite quickly, you know. Example was Vanderbilt University had to put 1000 hospital beds in a parking garage, and they needed dynamic network and security to be able to accommodate that. You know, we had a lab testing company that had to roll out 400 testing sites in a matter of weeks. So when you can start tohave first and foremost, think about the edge as being our edge. Agility is being defined as you know, what is the speed of software? How quickly can I push updates? How quickly can I transform my application posture or my security posture in lieu of these types of events is super important. Now, if then if we walk that back, you know, to your point on open source, you know, we see open source is really, uh you know, the key enabler for driving edge innovation and driving in I S V ecosystem around that edge Innovation. You know, we mentioned kubernetes, but there's other really important projects that we're already seeing strong traction in the edge. You know, projects such as edge X foundry is seeing significant growth in China. That is, the core ejects foundry was about giving you ah, pass for some of your I o T aps and services. Another one that's quite interesting is the open source faith project in the Linux Foundation. And fate is really addressing a melody edge through a Federated M L model, which we think is the going to be the long term dominant model for localized machine learning training as we continue to see massive scale out to these edge sites, >>right? So I wonder if you could You could pick up on that. I mean, in in thinking about ai influencing at the edge. Um, how do you see that? That evolving? Uh, maybe You know what, Z? Maybe you could We could double click on the architecture that you guys see. Uh, progressing. >>Yeah, Yeah. Right now we're doing some really good work. A zai mentioned with the Fate project. We're one of the key contributors to the project. Today. We see that you need to expand the breath of contributors to these types of projects. For starters, uh, some of these, what we've seen is sometimes the early momentum starts in China because there is a lot of innovation associated with the edge there, and now it starts to be pulled a bit further West. So when you look at Federated Learning, we do believe that the emergence of five g I's not doesn't really help you to centralized data. It really creates the more opportunity to create, put more data and more places. So that's, you know, that's the first challenge that you have. But then when you look at Federated learning in general, I'd say there's two challenges that we still have to overcome organizations that have very sophisticated data. Science practices are really well versed here, and I'd say they're at the forefront of some of these innovations. But that's 1% of enterprises today. We have to start looking at about solutions for the 99% of enterprises. And I'd say even VM Ware partners such as Microsoft Azure Cognitive Services as an example. They've been addressing ML for the 99%. I say That's a That's a positive development. When you look in the open source community, it's one thing to build a platform, right? Look, we love to talk about platforms. That's the easy part. But it's the APS that run on that platform in the services that run on that platform that drive adoption. So the work that we're incubating in the VM, or CTO office is not just about building platforms, but it's about building the applications that are needed by say that 99% of enterprises to drive that adoption. >>So if you if you carry that through that, I infer from that Chris that the developers are ultimately gonna kind of win the edge or define the edge Um, How do you see that From their >>perspective? Yeah, >>I think its way. I like to look at this. I like to call a pragmatic Dev ops where the winning formula is actually giving the developer the core services that they need using the native tools and the native AP eyes that they prefer and that is predominantly open source. It would some cloud services as they start to come to the edge as well. But then, beyond that, there's no reason that I t operations can't have the tools that they prefer to use. A swell. So we see this coming together of two worlds where I t operations has to think even for differently about edge computing, where it's not enough to assume that I t has full control of all of these different devices and sensors and things that exists at the edge. It doesn't happen. Often times it's the lines of business that air directly. Deploying these types of infrastructure solutions or application services is a better phrase and connecting them to the networks at the edge. So what does this mean From a nightie operations perspective? We need tohave, dynamic discovery capabilities and more policy and automation that can allow the developers to have the velocity they want but still have that consistency of security, agility, networking and all of the other hard stuff that somebody has to solve. And you can have the best of both worlds here. >>So if Amazon turned the data center into an A P I and then the traditional, you know, vendors sort of caught up or catching up and trying to do in the same premise is the edge one big happy I Is it coming from the cloud? Is it coming from the on Prem World? How do you see that evolving? >>Yes, that's the question and races on. Yeah, but it doesn't. It doesn't have to be exclusive in one way or another. The VM Ware perspective is that, you know, we can have a consistent platform for open source, a consistent platform for cloud services. And I think the key here is this. If you look at the partnerships we've been driving, you know, we've on boarded Amazon rds onto our platform. We announced the tech preview of Azure Arc sequel database as a service on our platform as well. In addition, toe everything we're doing with open source. So the way that we're looking at this is you don't wanna make a bet on an edge appliance with one cloud provider. Because what happens if you have a business partner that says I am a line to Google or on the line to AWS? So I want to use this open source. Our philosophy is to virtualized the edge so that software can dictate, you know, organizations velocity at the end of the day. >>Yeah. So, Chris, you come on, you're you're an analyst at Gartner. You know us. Everything is a zero sum game, but it's but But life is not like that, right? I mean, there's so much of an incremental opportunity, especially at the edge. I mean, the numbers are mind boggling when when you look at it, >>I I agree wholeheartedly. And I think you're seeing a maturity in the vendor landscape to where we know we can't solve all the problems ourselves and nobody can. So we have to partner, and we have to to your earlier point on a P. I s. We have to build external interfaces in tow, our platforms to make it very easy for customers have choice around ice vendors, partners and so on. >>So, Chris, I gotta ask you since you run the advanced technology group in charge of what's going on there, will there be a ship and focus on mawr ships at the edge with that girl singer going over to intel? Um, good to see Oh, shit, so to speak. Um, all kidding aside, but, you know, patch leaving big news around bm where I saw some of your tweets and you laid out there was a nice tribute, pat, but that's gonna be cool. That's gonna be a didn't tell. Maybe it's more more advanced stuff there. >>Yeah, I think >>for people pats staying on the VMRO board and to me it's it's really think about it. I mean, Pat was part of the team that brought us the X 86 right and to come back to Intel as the CEO. It's really the perfect book end to his career. So we're really sad to see him go. Can't blame him. Of course it's it's a It's a nice chapter for Pat, so totally understand that. And we prior to pack going to Intel, we announced major partnerships within video last year, where we've been doing a lot of work with >>arm. So >>thio us again. We see all of this is opportunity, and a lot of the advanced development projects were running right now in the CTO office is about expanding that ecosystem in terms of how vendors can participate, whether you're running an application on arm, whether it's running on X 86 or whatever, it's running on what comes next, including a variety of hardware accelerators. >>So is it really? Is that really irrelevant to you? I mean, you heard John Rose talk about that because it's all containerized is it is. It is a technologies. Is it truly irrelevant? What processor is underneath? And what underlying hardware architectures there are? >>No, it's not. You know it's funny, right? Because we always want to say these things like, Well, it's just a commodity, but it's not. You didn't then be asking the hardware vendors Thio pack up their balls and go home because there's just nothing nothing left to do, and we're seeing actually quite the opposite where there's this emergence and variety of so many hardware accelerators. So even from an innovation perspective, for us. We're looking at ways to increase the velocity by which organizations can take advantage of these different specialized hardware components, because that's that's going to continue to be a race. But the real key is to make it seamless that an application could take advantage of these benefits without having to go out and buy all of this different hardware on a per application basis. >>But if you do make bets, you can optimize for that architecture, true or not, I mean, our estimate is that the you know the number of wafer is coming out of arm based, you know, platforms is 10 x x 86. And so it appears that, you know, from a cost standpoint, that's that's got some real hard decisions to make. Or maybe maybe they're easy decisions, I don't know. But so you have to make bets, Do you not as a technologist and try to optimize for one of those architectures, even though you have to hedge those bets? >>Yeah, >>we do. It really boils down to use cases and seeing, you know, what do you need for a particular use case like, you know, you mentioned arm, you know, There's a lot of arm out at the edge and on smaller form factor devices. Not so much in the traditional enterprise data center today. So our bets and a lot of the focus there has been on those types of devices. And again, it's it's really the It's about timing, right? The customer demand versus when we need to make a particular move from an innovation >>perspective. It's my final question for you as we wrap up our day here with Great Cuban Cloud Day. What is the most important stories in in the cloud tech world, edge and or cloud? And you think people should be paying attention to that will matter most of them over the next few years. >>Wow, that's a huge question. How much time do we have? Not not enough. A >>architect. Architectural things. They gotta focus on a lot of people looking at this cove it saying I got to come out with a growth strategy obvious and clear, obvious things to see Cloud >>Yeah, yeah, let me let me break it down this way. I think the most important thing that people have to focus on >>is deciding How >>do they when they build architectures. What does the reliance on cloud services Native Cloud Services so far more proprietary services versus open source technologies such as kubernetes and the SV ecosystem around kubernetes. You know, one is an investment in flexibility and control, lots of management and for your intellectual property, right where Maybe I'm building this application in the cloud today. But tomorrow I have to run it out at the edge. Or I do an acquisition that I just wasn't expecting, or I just simply don't know. Sure way. Sure hope that cova doesn't come around again or something like it, right as we get past this and navigate this today. But architect ng for the expectation of change is really important and having flexibility of round your intellectual property, including flexibility to be able to deploy and run on different clouds, especially as you build up your different partnerships. That's really key. So building a discipline to say you know what >>this is >>database as a service, it's never going to define who I am is a business. It's something I have to do is an I T organization. I'm consuming that from the cloud This part of the application sacked that defines who I am is a business. My active team is building this with kubernetes. And I'm gonna maintain more flexibility around that intellectual property. The strategic discipline to operate this way among many of >>enterprise customers >>just hasn't gotten there yet. But I think that's going to be a key inflection point as we start to see. You know, these hybrid architectures continue to mature. >>Hey, Chris. Great stuff, man. Really appreciate you coming on the cube and participate in the Cuban cloud. Thank you for your perspectives. >>Great. Thank you very much. Always a pleasure >>to see you. >>Thank you, everybody for watching this ends the Cuban Cloud Day. Volonte and John Furry. All these sessions gonna be available on demand. All the write ups will hit silicon angle calm. So check that out. We'll have links to this site up there and really appreciate you know, you attending our our first virtual editorial >>event again? >>There's day Volonte for John Ferrier in the entire Cube and Cuba and Cloud Team >>Q 3 65. Thanks >>for watching. Mhm

Published Date : Jan 22 2021

SUMMARY :

John, great to see you as always, Really appreciate Hey, so we're gonna talk edge, you know, the the edge, it's it's estimated. And a lot of the actions that have to come from that data have to happen in real time in the real world. Others you can you can send back. And the fourth, which is the fascinating one, is it's actually a place where you might want to inject your security drive off the road or, you know, do this on the other thing. information at the sensor, but you could never do that at a sensor. And, you know, the important thing is, Well, I'll tell you this. So give us the playbook on how you see the evolution of the this mark. of functions and capabilities of the edge that you kind of needed in the early days. GPU might change GP or whatever it is. And so the software has to Spending some time with us and you always a great It's a clubhouse room for us. move to the second part of our of our technical edge discussion. So really excited to have you here. Great to see you again. to see you. How do you look at the edge. And I mean the list goes on and on, and the reason that you see this conflict of projects is But we appreciate you coming into our virtual editorial event if then if we walk that back, you know, to your point on open source, you know, we see open source is really, click on the architecture that you guys see. So that's, you know, that's the first challenge that you have. And you can have the best of both worlds here. If you look at the partnerships we've been driving, you know, we've on boarded Amazon rds I mean, the numbers are mind boggling when when can't solve all the problems ourselves and nobody can. all kidding aside, but, you know, patch leaving big news around bm where I It's really the perfect book end to his career. So in the CTO office is about expanding that ecosystem in terms of how vendors can I mean, you heard John Rose talk about that But the real key is to make it seamless that an application could take advantage of I mean, our estimate is that the you know the number of wafer is coming out of arm based, It really boils down to use cases and seeing, you know, what do you need for a particular use case And you think people should be paying attention to that will matter most of them How much time do we have? They gotta focus on a lot of people looking at this cove it saying I got to come I think the most important thing that people have to focus on So building a discipline to say you know I'm consuming that from the cloud This part of the application sacked that defines who I am is a business. But I think that's going to be a key inflection point as we start to see. Really appreciate you coming on the cube and participate in the Cuban Thank you very much. We'll have links to this site up there and really appreciate you know, you attending our our first for watching.

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