. >>Hey, welcome back everybody. Jeff, Rick here with the cube Worthen Nevada museum of art in Reno, Nevada for the Interbike show. Just happening down the street at the convention center. But we're actually at a side of it put on by Royal Dutch, a gazelle bikes, 125 year old, a bike company who is all in on electric bikes. We wanted to come in, see what's going on, really how the e-bike phenomenon is kind of intermingling with all these alternative scooters and, and all these alternative ways of getting around cities especially and, and get a feel for it. So we're excited to have a retailer who's been in the business for a long time. He's Davey oil. He is a founder a and, and cone or of GNO family. Cyclery David. Great. See you. Thanks. It's really happy to be here. Yeah. So first off, uh, just impressions of this event tonight. Um, cause I was rolling eyes. There's six or seven new bikes out here tonight. What do you think? >>It's very exciting because that was an extremely high quality brand of electric bicycle. And like you said, they have a uh, like a very long history in, in bicycle design. Right. And what they're doing now is they're, they're riding this wave of new technology that's coming through e-bikes and it's phenomenal. It's so funny cause >>some of these things I was talking about earlier, you know, so many Kickstarters, right, that have started and actually a lot of the companies have been pretty successful on the Kickstarter basis, but this is an old line company. They'd been making these things, I think I heard earlier, they're still making them at the same factory that they've been making them for 125 years. And surprisingly to me a third of this year's bike sales will be eBikes. So clearly there's something going on here. Yeah, there is that. What do you think in terms of the adoption Seattle, cause what I've heard as well is that the U S is about 10 years behind >>and Kennedy bike adoption. Yeah. I think that's probably the case in Seattle. We're very fortunate that there are a lot of factors at play that are, that are driving your bike adoption a happening a little faster than it is in some other parts of the country. But I think that all around the country and in cities and suburbs and also in rural areas, people are gonna find that adding an electric mobility to your bicycle, it takes away the barriers to cycling that so many people experienced that are totally rational. Like when I arrived at my destination, I don't want to be sweaty or I want to be able to use a bicycle, but I want to be able to carry more things or my children. Right. And when you add the mobility to your bicycle, those kind of barriers are just eliminated. You can see you're still getting exercise, but you can choose to make the bicycle ride more of what you'd expect from other forms of transportation, which is convenient and not sweaty and difficult. >>So how many of your customers aren't really bicyclists that that they're coming at this as a, as kind of a new opportunity? Maybe they just, they cycled before, but they're not kind of hardcore cyclists. You see this as the right foot. What's amazing to me is you have all these form factors, but this is a form factor that people are very familiar with and that's where I think there's a real opportunity bike that's not the same as scooters and some of these other things. Yeah, that's a really good question. Um, what we experience is that probably two thirds of our customers don't previously identified themselves as bicyclists. Um, they're probably somewhat friendly with the idea bicycles so they wouldn't have walked into a bicycle store. But what we see is that that transformation that happens to people when they adopt cycling as a, as a major part of their life and a major part of their transportation that still occurs, but it occurs all at once when they leapfrog over so many of these barriers and just have the opportunity to use a bicycle so much more than they would have otherwise. And the same thing happens to people who are already interested in cycling. People who only ride recreationally often find that with the addition of any bike into their life, they can use a bicycle for many, many, or most of their transportation needs, uh, over the course of their life. And that's profound, right. Transforms people. >>So there's a lot of special kind of characteristics of Seattle. Yeah. Obviously the weather is not great. Of course it's not great in, in Holland either. And they got a lot of bikes. They're got Hills and bridges and some nasty traffic. Not that everybody else does them, Massey traveling, but Seattle's got some crazy traffic. So you guys are seeing not only the adoption of the bikes for commuting and for fun and all those things, but you're selling a lot of cargo bikes for commercial purposes in this tight urban center. So I wonder if you can give us a little bit more color on how you're seeing the penetration in cargo bikes. Sure. >>Well, I think that cargo bikes when used for like freight purposes and delivery purposes and enterprise purposes in general, they benefit from the same things that bicyclists benefit from in urban environments in general, which is just greater mobility, freedom from the restrictions of traffic. I'm not trying to say that bicycles aren't on the road and that they don't sometimes find themselves behind a long line of stopped cars, but we have so much more flexibility in those situations and we can park safely and reasonably on a sidewalk. And so, so many things that happen, uh, that people suffer through due to congestion or alleviated when they're riding a bicycle in general. And business has experienced that when they use them for freight for sure. >>And it's not just a cargo bike, it's any cargo bikes. So now I've got the superhuman skills so I can, I can carry that load. I can replace a truck. I mean we have, we have bicycles in operation in Seattle for some, some of our customers use that. Our daily carrying 400 500 pounds of weight in there and they're traveling, you know, 60 70 miles in a day. Right. So how are you seeing the integration of the eBikes with the regular bikes, the hardcore bikers, the recreational bikers, and then of course you've got the slow move in pedestrians, right? And the, the dangerous stuff occurs when you've got all these disparity in, in, in velocity. And it's going to be interesting to see kind of how the regs kind of catch up and eventually probably, you know, discriminate. So these PO, these paths are for, you know, 20 miles or more of these paths are for, you know, 10 miles an hour or less. So how are you seeing that kind of work itself out in the streets of the city? Cause absolutely get a little rough sometimes out there. I think it has the potential to get a little rough. I think that honestly, um, yeah, >>the situation, the opportunities for conflict between pedestrians and electric bicyclists is not an issue or not any more significant than the opportunities for conflict between pedestrians and conventional bicyclists. I think that while an electric bicycle can travel up to 20 miles an hour or in some cases faster, they don't ordinarily travel that fast. That's a peak speed. Um, and so I don't really think that sidewalks are being menaced by electric bicyclists. I don't think that's really occurring, although I do think that the kind of regulations that you're talking about that classify type II bikes into types so that we can then, um, uh, empower people who have jurisdiction over different pieces of infrastructure to, um, to determine for themselves and for their users what bikes are allowed in which ones are, are, are forbidden, um, or restricted. I think that's really positive. Right? I think it's extremely important that we define what these vehicle types are because of course there are some vehicles which are more appropriate for some environments than others. >>Right. But I think the real thing is that bicyclists and III bicyclists are not the enemy of pedestrians. I think that together we're all making smart choices and we're in the safe spot. And I think that if it feels like there's too many bicycles on the sidewalk in your town, it's probably because you haven't made any room for bicyclists in the streets of your town. Right. And I think we all need to work together to make cycling a safe and viable option across all of our communities that will help congestion when we remove people from cars, we improve traffic for everybody. >>Right, right. And bikes should not be on sidewalks, period. Right. That's not really not the bike, not the bike place unless the, the street is just so, so tragic. >>I think. I think that if you're talking about it in a situational like daily life active, uh, situation, I think, um, there are a lot of conditions where bicycles are going to be on the sidewalk and there are many of them that I think are reasonable. I think it's totally reasonable to decide as a city we don't want bicycles, bicycles to primarily ride on sidewalks or when bicycles are on sidewalks. I don't think there's any city in the country that allows bicycles on sidewalks. It doesn't also stipulate as long as they're traveling safely. So if somebody has a problem with how somebody is behaving, that's still a problem either way. >>Right, right, right. So I'm just curious to get your take as, as you've seen this market evolved. Again, we've got big players involved. Bosch is doing all the, all the electronics on these bikes. Yeah. Capacity's got bigger on the battery speeds have gotten better. Dependability. Yeah. So how are you seeing kind of the evolution of the eBikes impacting the total market for bikes? Again, I can't believe that that gives out. Guys said they're going to sell a third of their bikes. Are e-bikes. Yeah. You see in the same thing in your business. >>Yeah. Well, I mean my business is focused on eBikes. Um, but what I will say is that I think that um, one of the challenges for bicycle advocacy and bicycle marketing and retail has always been a how to appeal to people who are somewhat friendly towards bicycling but aren't doing it that called interested but concerned. And it, I think it turns out that e-bikes are the key here, that we can help transform people from someone who is friendly towards bicycling to somebody who uses a bicycle as a big part of their life simply by making bicycles easier. And as you identified right now, finally, we're at a point in the development of this technology where the bikes really are reliable as a vehicle. And that's significant, right? It's not just a hobbyist activity at this point. These are, these are legitimate, uh, reliable vehicles >>in transportation. I mean, legitimate trans, it's not just your last mile vehicle anyway. >>Yeah, absolutely. I mean, at our shop at least we're talking about people who are, who have given up a car. Um, almost almost every one of our customers who's getting an electric cargo bag is doing this as part of their family transportation budget. And that includes driving less or removing a car from their life, right? And that could only work if the e-bike was at least as reliable as driving lists. And so maybe a flat tire is still a pretty annoying problem, but that should be the worst problem. Right? And I think we're finally there in terms of the quality of technology that's out >>and now it's only upward. We're like at year zero now. Right. Amazing. Even with the weather and the Hills and everything else, it's profound, man. It's really, and then it's a, it's a cultural shift, so it's just, it's just spreads across our community. Right. One person who inspires somebody else and inspires somebody else. Well, David, thanks for taking a few minutes and sharing your story. Really appreciate it. Thank you very much. All right. He's Dave young. Jeff. We are at Interbike Reno, but we're actually at the gazelle, uh, event looking at their e-bikes and they're really, really cool. Thanks for watching. Catch you next time.

>> Good afternoon, fellow cloud nerds and welcome back to AWS Reinvent 2022. We are live here from fabulous Las Vegas, Nevada. My name is Savannah Peterson, joined by Lisa Martin. So excited to be here Lisa, it's my first reinvent. >> Is it really? >> Yeah. >> I think it's only like my fourth or fifth. >> Only your fourth or fifth. >> Only. >> You're such a pro here. >> There's some serious veterans here in attendance that have been to all 11. >> I love that. >> Yeah. Wow, go them. I know, maybe we'll be at that level sooner. >> One day we will. >> Are you enjoying the show so far? >> Absolutely, it is. I cannot believe how many people are here. We've had 70,000 and we're only seeing what's at the foundation Expo Hall, not at the other hotel. So, I can only imagine. >> I mean, there's a world outside of this. >> Yes, and there's sunlight. There's actual sunlight outside of this room. >> Nobel idea. Well, Lisa, I'm very excited to be sitting here next to you and to welcome our fabulous guests, from TEKsystems, we have Brandon and Srini. Thank you so much for being here. How is the show going for you gentlemen so far? >> It's great. Lot of new insights and the customers are going to love what AWS is releasing in this reinvent. >> There is such a community here, and I love that vibe. It's similar to what we had at Cloud Native con in Detroit. So much collaboration going on. I assume most folks know a lot about TEKsystems who are watching, but just in case they don't, Brandon, give us the pitch. >> You bet. So full stack IT solutions firm, been in business for over 40 years, 80,000 global employees, really specializing in digital transformation, enterprise modernization services. We have partners in One Strategy, which is an an acquisition we made, but a well known premier partner in the Amazon partner ecosystem, as well as One North Interactive, who is our boutique brand, creative and digital strategy firm. So together, we really feel like we can bring full end-to-end solutions for digital and modernization initiatives. >> So, I saw some notes where TEKsystems are saying organizations need experienced AWS partners that are not afraid doing the dirty work of digital transformation, who really can advise and execute. Brandon, talk to us about how TEKsystems and AWS are working together to help customers on that journey which is nebulous of digital transformation. >> So, our real hallmark is the ability to scale. We partner with AWS in a lot of different ways. In fact, we just signed our strategic collaboration agreement. So, we're in the one percenter group in the whole partner network. >> Savanna: That's a pretty casual flex there. >> Not bad. >> I love that, top 1%, that no wonder you're wearing that partner pin so proud today. (speaking indistinctly) >> But we're working all the way on the advisory and working with their pro serve organization and then transforming that into large scale mass migration services, a lot of data modernization that Srini is an absolute expert in. I'm sure he can add some context too, but it's been a great partnership for many years now. >> In the keynote, Adam spent almost 52 minutes on data, right? So, it emphasizes how organizations are ready to take data to cloud and actually make meaningful insights and help their own customers come out of it by making meaningful decisions. So, we are glad to be part of this entire ecosystem. >> I love that you quantified how many minutes. >> I know. >> Talked about it, that was impressive. There's a little bit of data driven thinking going on here. >> I think so. >> Yeah. >> Well, we can't be at an event like this without talking about data for copious amounts of time, 52 minutes, has just used this morning. >> Right, absolutely. >> But every company these days has to be a data company. There's no choice to be successful, to thrive, to survive. I mean, even to thrive and grow, if it's a grocery store or your local gas station or what? You name it, that company has to be a data company. But the challenge of the data volume, the explosion in data is huge for organizations to really try to figure out and sift through what they have, where is all of it? How do we make sense of it? How do we act on it and get insights? That's a big challenge. How is TEKsystems helping customers tackle that challenge? >> Yeah, that's a great question because that's the whole fun of handling data. You need to ensure its meaning is first understood. So, we are not just dumping data into a storage place, but rather assign a meaningful context. In today's announcement, again, the data zone was unveiled to give meaning to data. And I think those are key concrete steps that we take to our customers as well with some good blueprints, methodical ways of approaching data and ultimately gaining business insights. >> And maybe I'll add just something real quick to that. The theme we're seeing and hearing a lot about is data monetization. So, technology companies have figured it out and used techniques to personalize things and get you ads, probably that you don't want half the time. But now all industries are really looking to do that. Looking at ways to open new revenue channels, looking at ways to drive a better customer experience, a better employee experience. We've got a ton of examples of that, Big Oil and Gas leveraging like well and machine data, coming in to be more efficient when they're pumping and moving commodities around. We work a lot in the medium entertainment space and so obviously, getting targeted ads to consumers during the right periods of TV or movies or et cetera. Especially with the advert on Netflix and all your streaming videos. So, it's been really interesting but we really see the future in leveraging data as one of your biggest corporate assets. >> Brilliant. >> So, I'm just curious on the ad thing, just real quick and I'll let you go, Lisa. So, do you still fall victim to falling for the advertising even though you know it's been strategically put there for you to consume in that moment? >> Most of the time. >> I mean, I think we all do. We're all, (indistinct), you're behind the curtain so to speak. >> The Amazon Truck shows up every day at my house, which is great, right? >> Hello again >> Same. >> But I think the power of it is you are giving the customer what they're looking for. >> That's it. >> And you know... >> Exactly. We have that expectation, we want it. >> 100%. >> We know that. >> Agree. >> We don't need to buy it. But technology has made it so easy to transact. That's like when developers started going to the cloud years ago, it was just, it was a swipe. It was so simple. Brandon, talk about the changes in cloud and cloud migration that TEKsystems has seen, particularly in the last couple of years as every company was rushing to go digital because they had to. >> So several years ago, we kind of pushed away that cloud first mentality to the side and we use more of a cloud smart kind of fashion, right? Does everything need to go to the cloud? No. Do applications, data, need to go to the cloud in a way that's modern and takes advantages of what the cloud can provide and all the new services that are being released this week and ongoing. So, the other thing we're seeing is initiatives that have traditionally been in the CTO, CIO organization aren't necessarily all that successful because we're seeing a complete misalignment between business goals and IT achievements, outcomes, et cetera. You can automate things, you can move it to the cloud, but if you didn't solve a core business problem or challenge, what'd you really do? >> Yeah, just to add on that, it's all about putting data and people together. And then how we can actually ensure the workforce is equally brought up to speed on these new technologies. That has been something that we have seen tremendous improvement in the last 24 months where customers are ready to take up new challenges and the end users are ready to learn something new and not just stick onto that status quo mindset. >> Where do you guys factor in to bringing in AWS in the customer's cloud journeys? What is that partnership like? >> We always first look for where the customer is in their cloud journey path and make sure we advise them with the right next steps. And AWS having its services across the spectrum makes it even easier for us to look at what business problem they're solving and then align it according to the process and technology so that at the end of the day, we want end user adoption. We don't want to build a fancy new gadget that no one uses. >> Just because you built it doesn't mean they'll come. And I think that's the classic engineering marketing dilemma as well as balance to healthy tension. I would say between both. You mentioned Srini, you mentioned workforce just a second ago. What sort of trends are you seeing in workforce development? >> Generally speaking, there are a lot of services now that can quantify your code for errors and then make sure that the code that you're pushing into production is well tested. So what we are trying to make sure is a healthy mix of trying to solve a business problem and asking the right questions. Like today, even in the keynote, it was all about how QuickSight, for example, has additional features now that tells why something happened. And that's the kind of mindset we want our end users to adopt. Not just restricting themselves to a reactive analytics, but rather ask the question why, why did it happen? Why did my sales go down? And I think those technologies and mindset shift is happening across the workforce. >> From a workforce development standpoint, we're seeing there's not enough workforce and the core skills of data, DevOps, standard cloud type work. So, we're actually an ATP advanced training partner, one of the few within the AWS network. So, we've developed programs like our Rising Talent Program that are allowing us to bring the workforce up to the skills that are necessary in this new world. So, it's a more build versus buy strategy because we're on talents real, though it may start to wane a little bit as we change the macroeconomic outlook in 2023, but it's still there. And we still believe that building those workforce and investing in your people is the right thing to do. >> It is, and I think there's a strong alignment there with AWS and their focus on that as well. I wanted to ask you, Brandon. >> Brandon: Absolutely. >> One of the things, so our boss, John Furrier, the co CEO of theCUBE, talked with Adam Selipsky just a week or maybe 10 days ago. He always gets an exclusive interview with the CEO of AWS before reinvent, and one of the things that Adam shared with him is that customers, CEOs and CIOs are not coming to Adam, to this head of AWS to talk about technology, they want to talk about transformation. He's talking about... >> The topic this year. >> Moving away from amorphous topic of digital transformation to business transformation. Are you seeing the same thing in your customer? >> 100%, and if you're not starting at the business level, these initiatives are going to fail. We see it all the time. Again, it's about that misalignment and there's no good answer to that. But digital, I think is amorphous to some degree. We play a lot with the One North partnership that I mentioned earlier, really focusing on that strategy element because consumer dollars are shrinking via inflation, via what we're heading into, and we have to create the best experience possible. We have to create an omnichannel experience to get our products or services to market. And if we're not looking at those as our core goals and we're looking at them as IT or technology challenges, we're not looking in the right place. >> Well, and businesses aren't going to be successful if they're looking at it in those siloed organizations. Data has to be democratizing and we've spent same data democratization for so long, but really, we're seeing that it has to be moving out into the lines of business because another thing Adam shared with John Furrier is that he sees and I'm curious what your thoughts are on this, the title of data analysts going away because everybody in different functions and different lines of business within an organization are going to have to be data analysts to some degree, to use data whether it's marketing, ops, sales, finance, are you seeing the same? >> That is true. I mean, at this point, we are all in the connected world, right? Every data point is connected in some form or shape to another data point. >> Savanna: There are many data points, just sitting here, yeah. >> Absolutely, so I think if you are strategizing, data needs to be right in the center of it. And then your business problems need to be addressed with reliable data. >> No, I mean, advertising, supply chain, marketing, they're all interconnected now, and we're looking at ways to bring a lot of that siloed data into one place so we can make use to it. It goes back to that monetization element of our data. >> That's a lot about context and situational awareness. We want what we want, when we want it, even before we knew we needed it then. I think I said that right. But you know, it's always more faster, quicker and then scaling things up. You see a lot of different customers across verticals, you have an absolutely massive team. Give us a sneak peek into 2023. What does the future hold? >> 2023 is again, to today's keynote, I'm bringing it back because it was a keynote filled with vision and limitless possibilities. And that's what we see. Right now, our customers, they are no longer scared to go and take the plunge into the cloud. And as Brandon said, it's all about being smart about those decisions. So, we are very excited that together with the partnership that we recently acquired and the services and the depth, along with the horizontal domain expertise, we can actually help customers make meaningful message out of their data points. And that keeps us really excited for next year. >> Love that, Brandon, what about you? >> I think the obvious one is DevOps and a focus on optimization, financially, security, et cetera, just for the changing times. The other one is, I still think that digital is going to continue to be a big push in 2023, namely making sure that experience is at its best, whether that's employee and combating the war on talent, keeping your people or opening new revenue streams, enhancing existing revenue streams. You got to keep working on that. >> We got to keep the people happy with the machines and the systems that we are building as we all know. But it's very nice, it's been a lot of human-centric focus and a lot of customer obsession here at the show. We know it's a big thing for you all, for Amazon, for pretty much everyone who sat here. Hopefully it is in general. Hopefully there's nobody who doesn't care about their community, we're not talking to them, if that's the case, we have a new challenge on theCUBE for the show, this year as we kind of prepped you for and can call it a bumper sticker, you can call it a 30 second sizzle reel. But this is sort of your Instagram moment, your TikTok, your thought of leadership highlight. What's the most important story coming out of the show? Srini, you've been quoting the keynotes very well, so, I'm going to you first on this one. >> I think overall, it's all about owning the change. In our TEKsystems culture, it's all about striving for excellence through serving others and owning the change. And so it makes me very excited that when we get that kind of keynote resonating the same message that we invite culturally, that's a big win-win for all the companies. >> It's all about the shared vision. A lot of people with similar vision in this room right now, in this room, like it's a room, it's a massive expo center, just to be clear, I'm sure everyone can see in the background. Brandon >> I would say partnership, continuing to enhance our strategic partnership with AWS, continuing to be our customers' partners in transformation. And bringing those two things together here has been a predominance of my time this week. And we'll continue throughout the week, but we're in it together with our customers and with AWS and looking forward to the future. >> Yeah, that's a beautiful note to end on there. Brandon, Srini, thank you both so much for being here with us. Fantastic to learn from your insights and to continue to emphasize on this theme of collaboration. We look forward to the next conversation with you. Thank all of you for tuning in wherever you happen to be hanging out and watching this fabulous live stream or the replay. We are here at AWS Reinvent 2022 in wonderful sunny Las Vegas, Nevada with Lisa Martin. My name is Savannah Peterson, we are theCUBE, the leading source for high tech coverage.

>> 10, nine, eight, (clears throat) four, three. >> Good afternoon, fellow cloud nerds and welcome back to AWS Reinvent 2022. We are live here from fabulous Las Vegas, Nevada. My name is Savannah Peterson, joined by Lisa Martin. So excited to be here Lisa, it's my first reinvent. >> Is it really? >> Yeah. >> I think it's only like my fourth or fifth. >> Only your fourth or fifth. >> Only. >> You're such a pro here. >> There's some serious veterans here in attendance that have been to all 11. >> I love that. >> Yeah. Wow, go them. I know, maybe we'll be at that level sooner. >> One day we will. >> Are you enjoying the show so far? >> Absolutely, it is. I cannot believe how many people are here. We've had 70,000 and we're only seeing what's at the foundation Expo Hall, not at the other hotel. So, I can only imagine. >> I mean, there's a world outside of this. >> Yes, and there's sunlight. There's actual sunlight outside of this room. >> Nobel idea. Well, Lisa, I'm very excited to be sitting here next to you and to welcome our fabulous guests, from TEKsystems, we have Brandon and Srini. Thank you so much for being here. How is the show going for you gentlemen so far? >> It's great. Lot of new insights and the customers are going to love what AWS is releasing in this reinvent. >> There is such a community here, and I love that vibe. It's similar to what we had at Cloud Native con in Detroit. So much collaboration going on. I assume most folks know a lot about TEKsystems who are watching, but just in case they don't, Brandon, give us the pitch. >> You bet. So full stack IT solutions firm, been in business for over 40 years, 80,000 global employees, really specializing in digital transformation, enterprise modernization services. We have partners in One Strategy, which is an an acquisition we made, but a well known premier partner in the Amazon partner ecosystem, as well as One North Interactive, who is our boutique brand, creative and digital strategy firm. So together, we really feel like we can bring full end-to-end solutions for digital and modernization initiatives. >> So, I saw some notes where TEKsystems are saying organizations need experienced AWS partners that are not afraid doing the dirty work of digital transformation, who really can advise and execute. Brandon, talk to us about how TEKsystems and AWS are working together to help customers on that journey which is nebulous of digital transformation. >> So, our real hallmark is the ability to scale. We partner with AWS in a lot of different ways. In fact, we just signed our strategic collaboration agreement. So, we're in the one percenter group in the whole partner network. >> Savanna: That's a pretty casual flex there. >> Not bad. >> I love that, top 1%, that no wonder you're wearing that partner pin so proud today. (speaking indistinctly) >> But we're working all the way on the advisory and working with their pro serve organization and then transforming that into large scale mass migration services, a lot of data modernization that Srini is an absolute expert in. I'm sure he can add some context too, but it's been a great partnership for many years now. >> In the keynote, Adam spent almost 52 minutes on data, right? So, it emphasizes how organizations are ready to take data to cloud and actually make meaningful insights and help their own customers come out of it by making meaningful decisions. So, we are glad to be part of this entire ecosystem. >> I love that you quantified how many minutes. >> I know. >> Talked about it, that was impressive. There's a little bit of data driven thinking going on here. >> I think so. >> Yeah. >> Well, we can't be at an event like this without talking about data for copious amounts of time, 52 minutes, has just used this morning. >> Right, absolutely. >> But every company these days has to be a data company. There's no choice to be successful, to thrive, to survive. I mean, even to thrive and grow, if it's a grocery store or your local gas station or what? You name it, that company has to be a data company. But the challenge of the data volume, the explosion in data is huge for organizations to really try to figure out and sift through what they have, where is all of it? How do we make sense of it? How do we act on it and get insights? That's a big challenge. How is TEKsystems helping customers tackle that challenge? >> Yeah, that's a great question because that's the whole fun of handling data. You need to ensure its meaning is first understood. So, we are not just dumping data into a storage place, but rather assign a meaningful context. In today's announcement, again, the data zone was unveiled to give meaning to data. And I think those are key concrete steps that we take to our customers as well with some good blueprints, methodical ways of approaching data and ultimately gaining business insights. >> And maybe I'll add just something real quick to that. The theme we're seeing and hearing a lot about is data monetization. So, technology companies have figured it out and used techniques to personalize things and get you ads, probably that you don't want half the time. But now all industries are really looking to do that. Looking at ways to open new revenue channels, looking at ways to drive a better customer experience, a better employee experience. We've got a ton of examples of that, Big Oil and Gas leveraging like well and machine data, coming in to be more efficient when they're pumping and moving commodities around. We work a lot in the medium entertainment space and so obviously, getting targeted ads to consumers during the right periods of TV or movies or et cetera. Especially with the advert on Netflix and all your streaming videos. So, it's been really interesting but we really see the future in leveraging data as one of your biggest corporate assets. >> Brilliant. >> So, I'm just curious on the ad thing, just real quick and I'll let you go, Lisa. So, do you still fall victim to falling for the advertising even though you know it's been strategically put there for you to consume in that moment? >> Most of the time. >> I mean, I think we all do. We're all, (indistinct), you're behind the curtain so to speak. >> The Amazon Truck shows up every day at my house, which is great, right? >> Hello again >> Same. >> But I think the power of it is you are giving the customer what they're looking for. >> That's it. >> And you know... >> Exactly. We have that expectation, we want it. >> 100%. >> We know that. >> Agree. >> We don't need to buy it. But technology has made it so easy to transact. That's like when developers started going to the cloud years ago, it was just, it was a swipe. It was so simple. Brandon, talk about the changes in cloud and cloud migration that TEKsystems has seen, particularly in the last couple of years as every company was rushing to go digital because they had to. >> So several years ago, we kind of pushed away that cloud first mentality to the side and we use more of a cloud smart kind of fashion, right? Does everything need to go to the cloud? No. Do applications, data, need to go to the cloud in a way that's modern and takes advantages of what the cloud can provide and all the new services that are being released this week and ongoing. So, the other thing we're seeing is initiatives that have traditionally been in the CTO, CIO organization aren't necessarily all that successful because we're seeing a complete misalignment between business goals and IT achievements, outcomes, et cetera. You can automate things, you can move it to the cloud, but if you didn't solve a core business problem or challenge, what'd you really do? >> Yeah, just to add on that, it's all about putting data and people together. And then how we can actually ensure the workforce is equally brought up to speed on these new technologies. That has been something that we have seen tremendous improvement in the last 24 months where customers are ready to take up new challenges and the end users are ready to learn something new and not just stick onto that status quo mindset. >> Where do you guys factor in to bringing in AWS in the customer's cloud journeys? What is that partnership like? >> We always first look for where the customer is in their cloud journey path and make sure we advise them with the right next steps. And AWS having its services across the spectrum makes it even easier for us to look at what business problem they're solving and then align it according to the process and technology so that at the end of the day, we want end user adoption. We don't want to build a fancy new gadget that no one uses. >> Just because you built it doesn't mean they'll come. And I think that's the classic engineering marketing dilemma as well as balance to healthy tension. I would say between both. You mentioned Srini, you mentioned workforce just a second ago. What sort of trends are you seeing in workforce development? >> Generally speaking, there are a lot of services now that can quantify your code for errors and then make sure that the code that you're pushing into production is well tested. So what we are trying to make sure is a healthy mix of trying to solve a business problem and asking the right questions. Like today, even in the keynote, it was all about how QuickSight, for example, has additional features now that tells why something happened. And that's the kind of mindset we want our end users to adopt. Not just restricting themselves to a reactive analytics, but rather ask the question why, why did it happen? Why did my sales go down? And I think those technologies and mindset shift is happening across the workforce. >> From a workforce development standpoint, we're seeing there's not enough workforce and the core skills of data, DevOps, standard cloud type work. So, we're actually an ATP advanced training partner, one of the few within the AWS network. So, we've developed programs like our Rising Talent Program that are allowing us to bring the workforce up to the skills that are necessary in this new world. So, it's a more build versus buy strategy because we're on talents real, though it may start to wane a little bit as we change the macroeconomic outlook in 2023, but it's still there. And we still believe that building those workforce and investing in your people is the right thing to do. >> It is, and I think there's a strong alignment there with AWS and their focus on that as well. I wanted to ask you, Brandon. >> Brandon: Absolutely. >> One of the things, so our boss, John Furrier, the co CEO of theCUBE, talked with Adam Selipsky just a week or maybe 10 days ago. He always gets an exclusive interview with the CEO of AWS before reinvent, and one of the things that Adam shared with him is that customers, CEOs and CIOs are not coming to Adam, to this head of AWS to talk about technology, they want to talk about transformation. He's talking about... >> The topic this year. >> Moving away from amorphous topic of digital transformation to business transformation. Are you seeing the same thing in your customer? >> 100%, and if you're not starting at the business level, these initiatives are going to fail. We see it all the time. Again, it's about that misalignment and there's no good answer to that. But digital, I think is amorphous to some degree. We play a lot with the One North partnership that I mentioned earlier, really focusing on that strategy element because consumer dollars are shrinking via inflation, via what we're heading into, and we have to create the best experience possible. We have to create an omnichannel experience to get our products or services to market. And if we're not looking at those as our core goals and we're looking at them as IT or technology challenges, we're not looking in the right place. >> Well, and businesses aren't going to be successful if they're looking at it in those siloed organizations. Data has to be democratizing and we've spent same data democratization for so long, but really, we're seeing that it has to be moving out into the lines of business because another thing Adam shared with John Furrier is that he sees and I'm curious what your thoughts are on this, the title of data analysts going away because everybody in different functions and different lines of business within an organization are going to have to be data analysts to some degree, to use data whether it's marketing, ops, sales, finance, are you seeing the same? >> That is true. I mean, at this point, we are all in the connected world, right? Every data point is connected in some form or shape to another data point. >> Savanna: There are many data points, just sitting here, yeah. >> Absolutely, so I think if you are strategizing, data needs to be right in the center of it. And then your business problems need to be addressed with reliable data. >> No, I mean, advertising, supply chain, marketing, they're all interconnected now, and we're looking at ways to bring a lot of that siloed data into one place so we can make use to it. It goes back to that monetization element of our data. >> That's a lot about context and situational awareness. We want what we want, when we want it, even before we knew we needed it then. I think I said that right. But you know, it's always more faster, quicker and then scaling things up. You see a lot of different customers across verticals, you have an absolutely massive team. Give us a sneak peek into 2023. What does the future hold? >> 2023 is again, to today's keynote, I'm bringing it back because it was a keynote filled with vision and limitless possibilities. And that's what we see. Right now, our customers, they are no longer scared to go and take the plunge into the cloud. And as Brandon said, it's all about being smart about those decisions. So, we are very excited that together with the partnership that we recently acquired and the services and the depth, along with the horizontal domain expertise, we can actually help customers make meaningful message out of their data points. And that keeps us really excited for next year. >> Love that, Brandon, what about you? >> I think the obvious one is DevOps and a focus on optimization, financially, security, et cetera, just for the changing times. The other one is, I still think that digital is going to continue to be a big push in 2023, namely making sure that experience is at its best, whether that's employee and combating the war on talent, keeping your people or opening new revenue streams, enhancing existing revenue streams. You got to keep working on that. >> We got to keep the people happy with the machines and the systems that we are building as we all know. But it's very nice, it's been a lot of human-centric focus and a lot of customer obsession here at the show. We know it's a big thing for you all, for Amazon, for pretty much everyone who sat here. Hopefully it is in general. Hopefully there's nobody who doesn't care about their community, we're not talking to them, if that's the case, we have a new challenge on theCUBE for the show, this year as we kind of prepped you for and can call it a bumper sticker, you can call it a 30 second sizzle reel. But this is sort of your Instagram moment, your TikTok, your thought of leadership highlight. What's the most important story coming out of the show? Srini, you've been quoting the keynotes very well, so, I'm going to you first on this one. >> I think overall, it's all about owning the change. In our TEKsystems culture, it's all about striving for excellence through serving others and owning the change. And so it makes me very excited that when we get that kind of keynote resonating the same message that we invite culturally, that's a big win-win for all the companies. >> It's all about the shared vision. A lot of people with similar vision in this room right now, in this room, like it's a room, it's a massive expo center, just to be clear, I'm sure everyone can see in the background. Brandon >> I would say partnership, continuing to enhance our strategic partnership with AWS, continuing to be our customers' partners in transformation. And bringing those two things together here has been a predominance of my time this week. And we'll continue throughout the week, but we're in it together with our customers and with AWS and looking forward to the future. >> Yeah, that's a beautiful note to end on there. Brandon, Srini, thank you both so much for being here with us. Fantastic to learn from your insights and to continue to emphasize on this theme of collaboration. We look forward to the next conversation with you. Thank all of you for tuning in wherever you happen to be hanging out and watching this fabulous live stream or the replay. We are here at AWS Reinvent 2022 in wonderful sunny Las Vegas, Nevada with Lisa Martin. My name is Savannah Peterson, we are theCUBE, the leading source for high tech coverage.

>> The rapid rise of ransomware attacks has added yet another challenge that business technology executives have to worry about these days, cloud storage, immutability, and air gaps have become a must have arrows in the quiver of organization's data protection strategies. But the important reality that practitioners have embraced is data protection, it can't be an afterthought or a bolt on it, has to be designed into the operational workflow of technology systems. The problem is, oftentimes, data protection is complicated with a variety of different products, services, software components, and storage formats, this is why object storage is moving to the forefront of data protection use cases because it's simpler and less expensive. The put data get data syntax has always been alluring, but object storage, historically, was seen as this low-cost niche solution that couldn't offer the performance required for demanding workloads, forcing customers to make hard tradeoffs between cost and performance. That has changed, the ascendancy of cloud storage generally in the S3 format specifically has catapulted object storage to become a first class citizen in a mainstream technology. Moreover, innovative companies have invested to bring object storage performance to parity with other storage formats, but cloud costs are often a barrier for many companies as the monthly cloud bill and egress fees in particular steadily climb. Welcome to Secure Storage Hot Takes, my name is Dave Vellante, and I'll be your host of the program today, where we introduce our community to Wasabi, a company that is purpose-built to solve this specific problem with what it claims to be the most cost effective and secure solution on the market. We have three segments today to dig into these issues, first up is David Friend, the well known entrepreneur who co-founded Carbonite and now Wasabi will then dig into the product with Drew Schlussel of Wasabi, and then we'll bring in the customer perspective with Kevin Warenda of the Hotchkiss School, let's get right into it. We're here with David Friend, the President and CEO and Co-founder of Wasabi, the hot storage company, David, welcome to theCUBE. >> Thanks Dave, nice to be here. >> Great to have you, so look, you hit a home run with Carbonite back when building a unicorn was a lot more rare than it has been in the last few years, why did you start Wasabi? >> Well, when I was still CEO of Wasabi, my genius co-founder Jeff Flowers and our chief architect came to me and said, you know, when we started this company, a state of the art disk drive was probably 500 gigabytes and now we're looking at eight terabyte, 16 terabyte, 20 terabyte, even 100 terabyte drives coming down the road and, you know, sooner or later the old architectures that were designed around these much smaller disk drives is going to run out of steam because, even though the capacities are getting bigger and bigger, the speed with which you can get data on and off of a hard drive isn't really changing all that much. And Jeff foresaw a day when the architectures sort of legacy storage like Amazon S3 and so forth was going to become very inefficient and slow. And so he came up with a new, highly parallelized architecture, and he said, I want to go off and see if I can make this work. So I said, you know, good luck go to it and they went off and spent about a year and a half in the lab, designing and testing this new storage architecture and when they got it working, I looked at the economics of this and I said, holy cow, we can sell cloud storage for a fraction of the price of Amazon, still make very good gross margins and it will be faster. So this is a whole new generation of object storage that you guys have invented. So I recruited a new CEO for Carbonite and left to found Wasabi because the market for cloud storage is almost infinite. You know, when you look at all the world's data, you know, IDC has these crazy numbers, 120 zetabytes or something like that and if you look at that as you know, the potential market size during that data, we're talking trillions of dollars, not billions and so I said, look, this is a great opportunity, if you look back 10 years, all the world's data was on-prem, if you look forward 10 years, most people agree that most of the world's data is going to live in the cloud, we're at the beginning of this migration, we've got an opportunity here to build an enormous company. >> That's very exciting. I mean, you've always been a trend spotter, and I want to get your perspectives on data protection and how it's changed. It's obviously on people's minds with all the ransomware attacks and security breaches, but thinking about your experiences and past observations, what's changed in data protection and what's driving the current very high interest in the topic? >> Well, I think, you know, from a data protection standpoint, immutability, the equivalent of the old worm tapes, but applied to cloud storage is, you know, become core to the backup strategies and disaster recovery strategies for most companies. And if you look at our partners who make backup software like Veeam, Convo, Veritas, Arcserve, and so forth, most of them are really taking advantage of mutable cloud storage as a way to protect customer data, customers backups from ransomware. So the ransomware guys are pretty clever and they, you know, they discovered early on that if someone could do a full restore from their backups, they're never going to pay a ransom. So, once they penetrate your system, they get pretty good at sort of watching how you do your backups and before they encrypt your primary data, they figure out some way to destroy or encrypt your backups as well, so that you can't do a full restore from your backups. And that's where immutability comes in. You know, in the old days you, you wrote what was called a worm tape, you know, write once read many, and those could not be overwritten or modified once they were written. And so we said, let's come up with an equivalent of that for the cloud, and it's very tricky software, you know, it involves all kinds of encryption algorithms and blockchain and this kind of stuff but, you know, the net result is if you store your backups in immutable buckets, in a product like Wasabi, you can't alter it or delete it for some period of time, so you could put a timer on it, say a year or six months or something like that, once that data is written, you know, there's no way you can go in and change it, modify it, or anything like that, including even Wasabi's engineers. >> So, David, I want to ask you about data sovereignty. It's obviously a big deal, I mean, especially for companies with the presence overseas, but what's really is any digital business these days, how should companies think about approaching data sovereignty? Is it just large firms that should be worried about this? Or should everybody be concerned? What's your point of view? >> Well, all around the world countries are imposing data sovereignty laws and if you're in the storage business, like we are, if you don't have physical data storage in-country, you're probably not going to get most of the business. You know, since Christmas we've built data centers in Toronto, London, Frankfurt, Paris, Sydney, Singapore, and I've probably forgotten one or two, but the reason we do that is twofold; one is, you know, if you're closer to the customer, you're going to get better response time, lower latency, and that's just a speed of light issue. But the bigger issue is, if you've got financial data, if you have healthcare data, if you have data relating to security, like surveillance videos, and things of that sort, most countries are saying that data has to be stored in-country, so, you can't send it across borders to some other place. And if your business operates in multiple countries, you know, dealing with data sovereignty is going to become an increasingly important problem. >> So in May of 2018, that's when the fines associated with violating GDPR went into effect and GDPR was like this main spring of privacy and data protection laws and we've seen it spawn other public policy things like the CCPA and think it continues to evolve, we see judgments in Europe against big tech and this tech lash that's in the news in the U.S. and the elimination of third party cookies, what does this all mean for data protection in the 2020s? >> Well, you know, every region and every country, you know, has their own idea about privacy, about security, about the use of even the use of metadata surrounding, you know, customer data and things of this sort. So, you know, it's getting to be increasingly complicated because GDPR, for example, imposes different standards from the kind of privacy standards that we have here in the U.S., Canada has a somewhat different set of data sovereignty issues and privacy issues so it's getting to be an increasingly complex, you know, mosaic of rules and regulations around the world and this makes it even more difficult for enterprises to run their own, you know, infrastructure because companies like Wasabi, where we have physical data centers in all kinds of different markets around the world and we've already dealt with the business of how to meet the requirements of GDPR and how to meet the requirements of some of the countries in Asia and so forth, you know, rather than an enterprise doing that just for themselves, if you running your applications or keeping your data in the cloud, you know, now a company like Wasabi with, you know, 34,000 customers, we can go to all the trouble of meeting these local requirements on behalf of our entire customer base and that's a lot more efficient and a lot more cost effective than if each individual country has to go deal with the local regulatory authorities. >> Yeah, it's compliance by design, not by chance. Okay, let's zoom out for the final question, David, thinking about the discussion that we've had around ransomware and data protection and regulations, what does it mean for a business's operational strategy and how do you think organizations will need to adapt in the coming years? >> Well, you know, I think there are a lot of forces driving companies to the cloud and, you know, and I do believe that if you come back five or 10 years from now, you're going to see majority of the world's data is going to be living in the cloud and I think storage, data storage is going to be a commodity much like electricity or bandwidth, and it's going to be done right, it will comply with the local regulations, it'll be fast, it'll be local, and there will be no strategic advantage that I can think of for somebody to stand up and run their own storage, especially considering the cost differential, you know, the most analysts think that the full, all in costs of running your own storage is in the 20 to 40 terabytes per month range, whereas, you know, if you migrate your data to the cloud, like Wasabi, you're talking probably $6 a month and so I think people are learning how to deal with the idea of an architecture that involves storing your data in the cloud, as opposed to, you know, storing your data locally. >> Wow, that's like a six X more expensive in the clouds, more than six X, all right, thank you, David,-- >> In addition to which, you know, just finding the people to babysit this kind of equipment has become nearly impossible today. >> Well, and with a focus on digital business, you don't want to be wasting your time with that kind of heavy lifting. David, thanks so much for coming in theCUBE, a great Boston entrepreneur, we've followed your career for a long time and looking forward to the future. >> Thank you. >> Okay, in a moment, Drew Schlussel will join me and we're going to dig more into product, you're watching theCUBE, the leader in enterprise and emerging tech coverage, keep it right there. ♪ Whoa ♪ ♪ Brenda in sales got an email ♪ ♪ Click here for a trip to Bombay ♪ ♪ It's not even called Bombay anymore ♪ ♪ But you clicked it anyway ♪ ♪ And now our data's been held hostage ♪ ♪ And now we're on sinking ship ♪ ♪ And a hacker's in our system ♪ ♪ Just 'cause Brenda wanted a trip ♪ ♪ She clicked on something stupid ♪ ♪ And our data's out of our control ♪ ♪ Into the hands of a hacker's ♪ ♪ And he's a giant asshole. ♪ ♪ He encrypted it in his basement ♪ ♪ He wants a million bucks for the key ♪ ♪ And I'm pretty sure he's 15 ♪ ♪ And still going through puberty ♪ ♪ I know you didn't mean to do us wrong ♪ ♪ But now I'm dealing with this all week long ♪ ♪ To make you all aware ♪ ♪ Of all this ransomware ♪ ♪ That is why I'm singing you this song ♪ ♪ C'mon ♪ ♪ Take it from me ♪ ♪ The director of IT ♪ ♪ Don't click on that email from a prince Nairobi ♪ ♪ 'Cuz he's not really a prince ♪ ♪ Now our data's locked up on our screen ♪ ♪ Controlled by a kid who's just fifteen ♪ ♪ And he's using our money to buy a Ferrari ♪ (gentle music) >> Joining me now is Drew Schlussel, who is the Senior Director of Product Marketing at Wasabi, hey Drew, good to see you again, thanks for coming back in theCUBE. >> Dave, great to be here, great to see you. >> All right, let's get into it. You know, Drew, prior to the pandemic, Zero Trust, just like kind of like digital transformation was sort of a buzzword and now it's become a real thing, almost a mandate, what's Wasabi's take on Zero Trust. >> So, absolutely right, it's been around a while and now people are paying attention, Wasabi's take is Zero Trust is a good thing. You know, there are too many places, right, where the bad guys are getting in. And, you know, I think of Zero Trust as kind of smashing laziness, right? It takes a little work, it takes some planning, but you know, done properly and using the right technologies, using the right vendors, the rewards are, of course tremendous, right? You can put to rest the fears of ransomware and having your systems compromised. >> Well, and we're going to talk about this, but there's a lot of process and thinking involved and, you know, design and your Zero Trust and you don't want to be wasting time messing with infrastructure, so we're going to talk about that, there's a lot of discussion in the industry, Drew, about immutability and air gaps, I'd like you to share Wasabi's point of view on these topics, how do you approach it and what makes Wasabi different? >> So, in terms of air gap and immutability, right, the beautiful thing about object storage, which is what we do all the time is that it makes it that much easier, right, to have a secure immutable copy of your data someplace that's easy to access and doesn't cost you an arm and a leg to get your data back. You know, we're working with some of the best, you know, partners in the industry, you know, we're working with folks like, you know, Veeam, Commvault, Arc, Marquee, MSP360, all folks who understand that you need to have multiple copies of your data, you need to have a copy stored offsite, and that copy needs to be immutable and we can talk a little bit about what immutability is and what it really means. >> You know, I wonder if you could talk a little bit more about Wasabi's solution because, sometimes people don't understand, you actually are a cloud, you're not building on other people's public clouds and this storage is the one use case where it actually makes sense to do that, tell us a little bit more about Wasabi's approach and your solution. >> Yeah, I appreciate that, so there's definitely some misconception, we are our own cloud storage service, we don't run on top of anybody else, right, it's our systems, it's our software deployed globally and we interoperate because we adhere to the S3 standard, we interoperate with practically hundreds of applications, primarily in this case, right, we're talking about backup and recovery applications and it's such a simple process, right? I mean, just about everybody who's anybody in this business protecting data has the ability now to access cloud storage and so we've made it really simple, in many cases, you'll see Wasabi as you know, listed in the primary set of available vendors and, you know, put in your private keys, make sure that your account is locked down properly using, let's say multifactor authentication, and you've got a great place to store copies of your data securely. >> I mean, we just heard from David Friend, if I did my math right, he was talking about, you know, 1/6 the cost per terabyte per month, maybe even a little better than that, how are you able to achieve such attractive economics? >> Yeah, so, you know, I can't remember how to translate my fractions into percentages, but I think we talk a lot about being 80%, right, less expensive than the hyperscalers. And you know, we talked about this at Vermont, right? There's some secret sauce there and you know, we take a different approach to how we utilize the raw capacity to the effective capacity and the fact is we're also not having to run, you know, a few hundred other services, right? We do storage, plain and simple, all day, all the time, so we don't have to worry about overhead to support, you know, up and coming other services that are perhaps, you know, going to be a loss leader, right? Customers love it, right, they see the fact that their data is growing 40, 80% year over year, they know they need to have some place to keep it secure, and, you know, folks are flocking to us in droves, in fact, we're seeing a tremendous amount of migration actually right now, multiple petabytes being brought to Wasabi because folks have figured out that they can't afford to keep going with their current hyperscaler vendor. >> And immutability is a feature of your product, right? What the feature called? Can you double-click on that a little bit? >> Yeah, absolutely. So, the term in S3 is Object Lock and what that means is your application will write an object to cloud storage, and it will define a retention period, let's say a week. And for that period, that object is immutable, untouchable, cannot be altered in any way, shape, or form, the application can't change it, the system administration can't change it, Wasabi can't change it, okay, it is truly carved in stone. And this is something that it's been around for a while, but you're seeing a huge uptick, right, in adoption and support for that feature by all the major vendors and I named off a few earlier and the best part is that with immutability comes some sense of, well, it comes with not just a sense of security, it is security. Right, when you have data that cannot be altered by anybody, even if the bad guys compromise your account, they steal your credentials, right, they can't take away the data and that's a beautiful thing, a beautiful, beautiful thing. >> And you look like an S3 bucket, is that right? >> Yeah, I mean, we're fully compatible with the S3 API, so if you're using S3 API based applications today, it's a very simple matter of just kind of redirecting where you want to store your data, beautiful thing about backup and recovery, right, that's probably the simplest application, simple being a relative term, as far as lift and shift, right? Because that just means for your next full, right, point that at Wasabi, retain your other fulls, you know, for whatever 30, 60, 90 days, and then once you've kind of made that transition from vine to vine, you know, you're often running with Wasabi. >> I talked to my open about the allure of object storage historically, you know, the simplicity of the get put syntax, but what about performance? Are you able to deliver performance that's comparable to other storage formats? >> Oh yeah, absolutely, and we've got the performance numbers on the site to back that up, but I forgot to answer something earlier, right, you said that immutability is a feature and I want to make it very clear that it is a feature but it's an API request. Okay, so when you're talking about gets and puts and so forth, you know, the comment you made earlier about being 80% more cost effective or 80% less expensive, you know, that API call, right, is typically something that the other folks charge for, right, and I think we used the metaphor earlier about the refrigerator, but I'll use a different metaphor today, right? You can think of cloud storage as a magical coffee cup, right? It gets as big as you want to store as much coffee as you want and the coffee's always warm, right? And when you want to take a sip, there's no charge, you want to, you know, pop the lid and see how much coffee is in there, no charge, and that's an important thing, because when you're talking about millions or billions of objects, and you want to get a list of those objects, or you want to get the status of the immutable settings for those objects, anywhere else it's going to cost you money to look at your data, with Wasabi, no additional charge and that's part of the thing that sets us apart. >> Excellent, so thank you for that. So, you mentioned some partners before, how do partners fit into the Wasabi story? Where do you stop? Where do they pick up? You know, what do they bring? Can you give us maybe, a paint a picture for us example, or two? >> Sure, so, again, we just do storage, right, that is our sole purpose in life is to, you know, to safely and securely store our customer's data. And so they're working with their application vendors, whether it's, you know, active archive, backup and recovery, IOT, surveillance, media and entertainment workflows, right, those systems already know how to manage the data, manage the metadata, they just need some place to keep the data that is being worked on, being stored and so forth. Right, so just like, you know, plugging in a flash drive on your laptop, right, you literally can plug in Wasabi as long as your applications support the API, getting started is incredibly easy, right, we offer a 30-day trial, one terabyte, and most folks find that within, you know, probably a few hours of their POC, right, it's giving them everything they need in terms of performance, in terms of accessibility, in terms of sovereignty, I'm guessing you talked to, you know, Dave Friend earlier about data sovereignty, right? We're global company, right, so there's got to be probably, you know, wherever you are in the world some place that will satisfy your sovereignty requirements, as well as your compliance requirements. >> Yeah, we did talk about sovereignty, Drew, this is really, what's interesting to me, I'm a bit of a industry historian, when I look back to the early days of cloud, I remember the large storage companies, you know, their CEOs would say, we're going to have an answer for the cloud and they would go out, and for instance, I know one bought competitor of Carbonite, and then couldn't figure out what to do with it, they couldn't figure out how to compete with the cloud in part, because they were afraid it was going to cannibalize their existing business, I think another part is because they just didn't have that imagination to develop an architecture that in a business model that could scale to see that you guys have done that is I love it because it brings competition, it brings innovation and it helps lower clients cost and solve really nagging problems. Like, you know, ransomware, of mutability and recovery, I'll give you the last word, Drew. >> Yeah, you're absolutely right. You know, the on-prem vendors, they're not going to go away anytime soon, right, there's always going to be a need for, you know, incredibly low latency, high bandwidth, you know, but, you know, not all data's hot all the time and by hot, I mean, you know, extremely hot, you know, let's take, you know, real time analytics for, maybe facial recognition, right, that requires sub-millisecond type of processing. But once you've done that work, right, you want to store that data for a long, long time, and you're going to want to also tap back into it later, so, you know, other folks are telling you that, you know, you can go to these like, you know, cold glacial type of tiered storage, yeah, don't believe the hype, you're still going to pay way more for that than you would with just a Wasabi-like hot cloud storage system. And, you know, we don't compete with our partners, right? We compliment, you know, what they're bringing to market in terms of the software vendors, in terms of the hardware vendors, right, we're a beautiful component for that hybrid cloud architecture. And I think folks are gravitating towards that, I think the cloud is kind of hitting a new gear if you will, in terms of adoption and recognition for the security that they can achieve with it. >> All right, Drew, thank you for that, definitely we see the momentum, in a moment, Drew and I will be back to get the customer perspective with Kevin Warenda, who's the Director of Information technology services at The Hotchkiss School, keep it right there. >> Hey, I'm Nate, and we wrote this song about ransomware to educate people, people like Brenda. >> Oh, God, I'm so sorry. We know you are, but Brenda, you're not alone, this hasn't just happened to you. >> No! ♪ Colonial Oil Pipeline had a guy ♪ ♪ who didn't change his password ♪ ♪ That sucks ♪ ♪ His password leaked, the data was breached ♪ ♪ And it cost his company 4 million bucks ♪ ♪ A fake update was sent to people ♪ ♪ Working for the meat company JBS ♪ ♪ That's pretty clever ♪ ♪ Instead of getting new features, they got hacked ♪ ♪ And had to pay the largest crypto ransom ever ♪ ♪ And 20 billion dollars, billion with a b ♪ ♪ Have been paid by companies in healthcare ♪ ♪ If you wonder buy your premium keeps going ♪ ♪ Up, up, up, up, up ♪ ♪ Now you're aware ♪ ♪ And now the hackers they are gettin' cocky ♪ ♪ When they lock your data ♪ ♪ You know, it has gotten so bad ♪ ♪ That they demand all of your money and it gets worse ♪ ♪ They go and the trouble with the Facebook ad ♪ ♪ Next time, something seems too good to be true ♪ ♪ Like a free trip to Asia! ♪ ♪ Just check first and I'll help before you ♪ ♪ Think before you click ♪ ♪ Don't get fooled by this ♪ ♪ Who isn't old enough to drive to school ♪ ♪ Take it from me, the director of IT ♪ ♪ Don't click on that email from a prince in Nairobi ♪ ♪ Because he's not really a prince ♪ ♪ Now our data's locked up on our screen ♪ ♪ Controlled by a kid who's just fifteen ♪ ♪ And he's using our money to buy a Ferrari ♪ >> It's a pretty sweet car. ♪ A kid without facial hair, who lives with his mom ♪ ♪ To learn more about this go to wasabi.com ♪ >> Hey, don't do that. ♪ Cause if we had Wasabi's immutability ♪ >> You going to ruin this for me! ♪ This fifteen-year-old wouldn't have on me ♪ (gentle music) >> Drew and I are pleased to welcome Kevin Warenda, who's the Director of Information Technology Services at The Hotchkiss School, a very prestigious and well respected boarding school in the beautiful Northwest corner of Connecticut, hello, Kevin. >> Hello, it's nice to be here, thanks for having me. >> Yeah, you bet. Hey, tell us a little bit more about The Hotchkiss School and your role. >> Sure, The Hotchkiss School is an independent boarding school, grades nine through 12, as you said, very prestigious and in an absolutely beautiful location on the deepest freshwater lake in Connecticut, we have 500 acre main campus and a 200 acre farm down the street. My role as the Director of Information Technology Services, essentially to oversee all of the technology that supports the school operations, academics, sports, everything we do on campus. >> Yeah, and you've had a very strong history in the educational field, you know, from that lens, what's the unique, you know, or if not unique, but the pressing security challenge that's top of mind for you? >> I think that it's clear that educational institutions are a target these days, especially for ransomware. We have a lot of data that can be used by threat actors and schools are often underfunded in the area of IT security, IT in general sometimes, so, I think threat actors often see us as easy targets or at least worthwhile to try to get into. >> Because specifically you are potentially spread thin, underfunded, you got students, you got teachers, so there really are some, are there any specific data privacy concerns as well around student privacy or regulations that you can speak to? >> Certainly, because of the fact that we're an independent boarding school, we operate things like even a health center, so, data privacy regulations across the board in terms of just student data rights and FERPA, some of our students are under 18, so, data privacy laws such as COPPA apply, HIPAA can apply, we have PCI regulations with many of our financial transactions, whether it be fundraising through alumni development, or even just accepting the revenue for tuition so, it's a unique place to be, again, we operate very much like a college would, right, we have all the trappings of a private college in terms of all the operations we do and that's what I love most about working in education is that it's all the industries combined in many ways. >> Very cool. So let's talk about some of the defense strategies from a practitioner point of view, then I want to bring in Drew to the conversation so what are the best practice and the right strategies from your standpoint of defending your data? >> Well, we take a defense in-depth approach, so we layer multiple technologies on top of each other to make sure that no single failure is a key to getting beyond those defenses, we also keep it simple, you know, I think there's some core things that all organizations need to do these days in including, you know, vulnerability scanning, patching , using multifactor authentication, and having really excellent backups in case something does happen. >> Drew, are you seeing any similar patterns across other industries or customers? I mean, I know we're talking about some uniqueness in the education market, but what can we learn from other adjacent industries? >> Yeah, you know, Kevin is spot on and I love hearing what he's doing, going back to our prior conversation about Zero Trust, right, that defense in-depth approach is beautifully aligned, right, with the Zero Trust approach, especially things like multifactor authentication, always shocked at how few folks are applying that very, very simple technology and across the board, right? I mean, Kevin is referring to, you know, financial industry, healthcare industry, even, you know, the security and police, right, they need to make sure that the data that they're keeping, evidence, right, is secure and immutable, right, because that's evidence. >> Well, Kevin, paint a picture for us, if you would. So, you were primarily on-prem looking at potentially, you know, using more cloud, you were a VMware shop, but tell us, paint a picture of your environment, kind of the applications that you support and the kind of, I want to get to the before and the after Wasabi, but start with kind of where you came from. >> Sure, well, I came to The Hotchkiss School about seven years ago and I had come most recently from public K12 and municipal, so again, not a lot of funding for IT in general, security, or infrastructure in general, so Nutanix was actually a hyperconverged solution that I implemented at my previous position. So when I came to Hotchkiss and found mostly on-prem workloads, everything from the student information system to the card access system that students would use, financial systems, they were almost all on premise, but there were some new SaaS solutions coming in play, we had also taken some time to do some business continuity, planning, you know, in the event of some kind of issue, I don't think we were thinking about the pandemic at the time, but certainly it helped prepare us for that, so, as different workloads were moved off to hosted or cloud-based, we didn't really need as much of the on-premise compute and storage as we had, and it was time to retire that cluster. And so I brought the experience I had with Nutanix with me, and we consolidated all that into a hyper-converged platform, running Nutanix AHV, which allowed us to get rid of all the cost of the VMware licensing as well and it is an easier platform to manage, especially for small IT shops like ours. >> Yeah, AHV is the Acropolis hypervisor and so you migrated off of VMware avoiding the VTax avoidance, that's a common theme among Nutanix customers and now, did you consider moving into AWS? You know, what was the catalyst to consider Wasabi as part of your defense strategy? >> We were looking at cloud storage options and they were just all so expensive, especially in egress fees to get data back out, Wasabi became across our desks and it was such a low barrier to entry to sign up for a trial and get, you know, terabyte for a month and then it was, you know, $6 a month for terabyte. After that, I said, we can try this out in a very low stakes way to see how this works for us. And there was a couple things we were trying to solve at the time, it wasn't just a place to put backup, but we also needed a place to have some files that might serve to some degree as a content delivery network, you know, some of our software applications that are deployed through our mobile device management needed a place that was accessible on the internet that they could be stored as well. So we were testing it for a couple different scenarios and it worked great, you know, performance wise, fast, security wise, it has all the features of S3 compliance that works with Nutanix and anyone who's familiar with S3 permissions can apply them very easily and then there was no egress fees, we can pull data down, put data up at will, and it's not costing as any extra, which is excellent because especially in education, we need fixed costs, we need to know what we're going to spend over a year before we spend it and not be hit with, you know, bills for egress or because our workload or our data storage footprint grew tremendously, we need that, we can't have the variability that the cloud providers would give us. >> So Kevin, you explained you're hypersensitive about security and privacy for obvious reasons that we discussed, were you concerned about doing business with a company with a funny name? Was it the trial that got you through that knothole? How did you address those concerns as an IT practitioner? >> Yeah, anytime we adopt anything, we go through a risk review. So we did our homework and we checked the funny name really means nothing, there's lots of companies with funny names, I think we don't go based on the name necessarily, but we did go based on the history, understanding, you know, who started the company, where it came from, and really looking into the technology and understanding that the value proposition, the ability to provide that lower cost is based specifically on the technology in which it lays down data. So, having a legitimate, reasonable, you know, excuse as to why it's cheap, we weren't thinking, well, you know, you get what you pay for, it may be less expensive than alternatives, but it's not cheap, you know, it's reliable, and that was really our concern. So we did our homework for sure before even starting the trial, but then the trial certainly confirmed everything that we had learned. >> Yeah, thank you for that. Drew, explain the whole egress charge, we hear a lot about that, what do people need to know? >> First of all, it's not a funny name, it's a memorable name, Dave, just like theCUBE, let's be very clear about that, second of all, egress charges, so, you know, other storage providers charge you for every API call, right? Every get, every put, every list, everything, okay, it's part of their process, it's part of how they make money, it's part of how they cover the cost of all their other services, we don't do that. And I think, you know, as Kevin has pointed out, right, that's a huge differentiator because you're talking about a significant amount of money above and beyond what is the list price. In fact, I would tell you that most of the other storage providers, hyperscalers, you know, their list price, first of all, is, you know, far exceeding anything else in the industry, especially what we offer and then, right, their additional cost, the egress costs, the API requests can be two, three, 400% more on top of what you're paying per terabyte. >> So, you used a little coffee analogy earlier in our conversation, so here's what I'm imagining, like I have a lot of stuff, right? And I had to clear up my bar and I put some stuff in storage, you know, right down the street and I pay them monthly, I can't imagine having to pay them to go get my stuff, that's kind of the same thing here. >> Oh, that's a great metaphor, right? That storage locker, right? You know, can you imagine every time you want to open the door to that storage locker and look inside having to pay a fee? >> No, that would be annoying. >> Or, every time you pull into the yard and you want to put something in that storage locker, you have to pay an access fee to get to the yard, you have to pay a door opening fee, right, and then if you want to look and get an inventory of everything in there, you have to pay, and it's ridiculous, it's your data, it's your storage, it's your locker, you've already paid the annual fee, probably, 'cause they gave you a discount on that, so why shouldn't you have unfettered access to your data? That's what Wasabi does and I think as Kevin pointed out, right, that's what sets us completely apart from everybody else. >> Okay, good, that's helpful, it helps us understand how Wasabi's different. Kevin, I'm always interested when I talk to practitioners like yourself in learning what you do, you know, outside of the technology, what are you doing in terms of educating your community and making them more cyber aware? Do you have training for students and faculty to learn about security and ransomware protection, for example? >> Yes, cyber security awareness training is definitely one of the required things everyone should be doing in their organizations. And we do have a program that we use and we try to make it fun and engaging too, right, this is often the checking the box kind of activity, insurance companies require it, but we want to make it something that people want to do and want to engage with so, even last year, I think we did one around the holidays and kind of pointed out the kinds of scams they may expect in their personal life about, you know, shipping of orders and time for the holidays and things like that, so it wasn't just about protecting our school data, it's about the fact that, you know, protecting their information is something do in all aspects of your life, especially now that the folks are working hybrid often working from home with equipment from the school, the stakes are much higher and people have a lot of our data at home and so knowing how to protect that is important, so we definitely run those programs in a way that we want to be engaging and fun and memorable so that when they do encounter those things, especially email threats, they know how to handle them. >> So when you say fun, it's like you come up with an example that we can laugh at until, of course, we click on that bad link, but I'm sure you can come up with a lot of interesting and engaging examples, is that what you're talking about, about having fun? >> Yeah, I mean, sometimes they are kind of choose your own adventure type stories, you know, they stop as they run, so they're telling a story and they stop and you have to answer questions along the way to keep going, so, you're not just watching a video, you're engaged with the story of the topic, yeah, and that's what I think is memorable about it, but it's also, that's what makes it fun, you're not just watching some talking head saying, you know, to avoid shortened URLs or to check, to make sure you know the sender of the email, no, you're engaged in a real life scenario story that you're kind of following and making choices along the way and finding out was that the right choice to make or maybe not? So, that's where I think the learning comes in. >> Excellent. Okay, gentlemen, thanks so much, appreciate your time, Kevin, Drew, awesome having you in theCUBE. >> My pleasure, thank you. >> Yeah, great to be here, thanks. >> Okay, in a moment, I'll give you some closing thoughts on the changing world of data protection and the evolution of cloud object storage, you're watching theCUBE, the leader in high tech enterprise coverage. >> Announcer: Some things just don't make sense, like showing up a little too early for the big game. >> How early are we? >> Couple months. Popcorn? >> Announcer: On and off season, the Red Sox cover their bases with affordable, best in class cloud storage. >> These are pretty good seats. >> Hey, have you guys seen the line from the bathroom? >> Announcer: Wasabi Hot Cloud Storage, it just makes sense. >> You don't think they make these in left hand, do you? >> We learned today how a serial entrepreneur, along with his co-founder saw the opportunity to tap into the virtually limitless scale of the cloud and dramatically reduce the cost of storing data while at the same time, protecting against ransomware attacks and other data exposures with simple, fast storage, immutability, air gaps, and solid operational processes, let's not forget about that, okay? People and processes are critical and if you can point your people at more strategic initiatives and tasks rather than wrestling with infrastructure, you can accelerate your process redesign and support of digital transformations. Now, if you want to learn more about immutability and Object Block, click on the Wasabi resource button on this page, or go to wasabi.com/objectblock. Thanks for watching Secure Storage Hot Takes made possible by Wasabi. This is Dave Vellante for theCUBE, the leader in enterprise and emerging tech coverage, well, see you next time. (gentle upbeat music)

(contemplative upbeat music) >> Hello and welcome to this CUBE Conversation. I'm John Furrier, your host of theCUBE, here in Palo Alto, California. Got a great topic on expanding capabilities for urgent computing. Dan Stanzione, he's Executive Director of TACC, the Texas Advanced Computing Center, and Rajesh Pohani, VP of PowerEdge, HPC Core Compute at Dell Technologies. Gentlemen, welcome to this CUBE Conversation. >> Thanks, John. >> Thanks, John, good to be here. >> Rajesh, you got a lot of computing in PowerEdge, HPC, Core Computing. I mean, I get a sense that you love compute, so we'll jump right into it. And of course, I got to love TACC, Texas Advanced Computing Center. I can imagine a lot of stuff going on there. Let's start with TACC. What is the Texas Advanced Computing Center? Tell us a little bit about that. >> Yeah, we're part of the University of Texas at Austin here, and we build large-scale supercomputers, data systems, AI systems, to support open science research. And we're mainly funded by the National Science Foundation, so we support research projects in all fields of science, all around the country and around the world. Actually, several thousand projects at the moment. >> But tied to the university, got a lot of gear, got a lot of compute, got a lot of cool stuff going on. What's the coolest thing you got going on right now? >> Well, for me, it's always the next machine, but I think science-wise, it's the machines we have. We just finished deploying Lonestar6, which is our latest supercomputer, in conjunction with Dell. A little over 600 nodes of those PowerEdge servers that Rajesh builds for us. Which makes more than 20,000 that we've had here over the years, of those boxes. But that one just went into production. We're designing new systems for a few years from now, where we'll be even larger. Our Frontera system was top five in the world two years ago, just fell out of the top 10. So we've got to fix that and build the new top-10 system sometime soon. We always have a ton going on in large-scale computing. >> Well, I want to get to the Lonestar6 in a minute, on the next talk track, but... What are some of the areas that you guys are working on that are making an impact? Take us through, and we talked before we came on camera about, obviously, the academic affiliation, but also there's a real societal impact of the work you're doing. What are some of the key areas that the TACC is making an impact? >> So there's really a huge range from new microprocessors, new materials design, photovoltaics, climate modeling, basic science and astrophysics, and quantum mechanics, and things like that. But I think the nearest-term impacts that people see are what we call urgent computing, which is one of the drivers around Lonestar and some other recent expansions that we've done. And that's things like, there's a hurricane coming, exactly where is it going to land? Can we refine the area where there's going to be either high winds or storm surge? Can we assess the damage from digital imagery afterwards? Can we direct first responders in the optimal routes? Similarly for earthquakes, and a lot recently, as you might imagine, around COVID. In 2020, we moved almost a third of our resources to doing COVID work, full-time. >> Rajesh, I want to get your thoughts on this, because Dave Vellante and I have been talking about this on theCUBE recently, a lot. Obviously, people see what cloud's, going on with the cloud technology, but compute and on-premises, private cloud's been growing. If you look at the hyperscale on-premises and the edge, if you include that in, you're seeing a lot more user consumption on-premises, and now, with 5G, you got edge, you mentioned first responders, Dan. This is now pointing to a new architectural shift. As the VP of PowerEdge and HPC and Core Compute, you got to look at this and go, "Hmm." If Compute's going to be everywhere, and in locations, you got to have that compute. How does that all work together? And how do you do advanced computing, when you have these urgent needs, as well as real-time in a new architecture? >> Yeah, John, I mean, it's a pretty interesting time when you think about some of the changing dynamics and how customers are utilizing Compute in the compute needs in the industry. Seeing a couple of big trends. One, the distribution of Compute outside of the data center, 5G is really accelerating that, and then you're generating so much data, whether what you do with it, the insights that come out of it, that we're seeing more and more push to AI, ML, inside the data center. Dan mentioned what he's doing at TACC with computational analysis and some of the work that they're doing. So what you're seeing is, now, this push that data in the data center and what you do with it, while data is being created out at the edge. And it's actually this interesting dichotomy that we're beginning to see. Dan mentioned some of the work that they're doing in medical and on COVID research. Even at Dell, we're making cycles available for COVID research using our Zenith cluster, that's located in our HPC and AI Innovation Lab. And we continue to partner with organizations like TACC and others on research activities to continue to learn about the virus, how it mutates, and then how you treat it. So if you think about all the things, and data that's getting created, you're seeing that distribution and it's really leading to some really cool innovations going forward. >> Yeah, I want to get to that COVID research, but first, you mentioned a few words I want to get out there. You mentioned Lonestar6. Okay, so first, what is Lonestar6, then we'll get into the system aspect of it. Take us through what that definition is, what is Lonestar6? >> Well, as Dan mentioned, Lonestar6 is a Dell technology system that we developed with TACC, it's located at the University of Texas at Austin. It consists of more than 800 Dell PowerEdge 6525 servers that are powered with 3rd Generation AMD EPYC processors. And just to give you an example of the scale of this cluster, it could perform roughly three quadrillion operations per second. That's three petaFLOPS, and to match what Lonestar6 can compute in one second, a person would have to do one calculation every second for a hundred million years. So it's quite a good-size system, and quite a powerful one as well. >> Dan, what's the role that the system plays, you've got petaFLOPS, what, three petaFLOPS, you mentioned? That's a lot of FLOPS! So obviously urgent computing, what's cranking through the system there? Take us through, what's it like? >> Sure, well, there there's a mix of workloads on it, and on all our systems. So there's the urgent computing work, right? Fast turnaround, near real-time, whether it's COVID research, or doing... Project now where we bring in MRI data and are doing sort of patient-specific dosing for radiation treatments and chemotherapy, tailored to your tumor, instead of just the sort of general for people your size. That all requires sort of real-time turnaround. There's a lot AI research going on now, we're incorporating AI in traditional science and engineering research. And that uses an awful lot of data, but also consumes a huge amount of cycles in training those models. And then there's all of our traditional, simulation-based workloads and materials and digital twins for aircraft and aircraft design, and more efficient combustion in more efficient photovoltaic materials, or photovoltaic materials without using as much lead, and things like that. And I'm sure I'm missing dozens of other topics, 'cause, like I said, that one really runs every field of science. We've really focused the Lonestar line of systems, and this is obviously the sixth one we built, around our sort of Texas-centric users. It's the UT Austin users, and then with contributions from Texas A&M , and Texas Tech and the University of Texas system, MD Anderson Healthcare Center, the University of North Texas. So users all around the state, and every research problem that you might imagine, those are into. We're just ramping up a project in disaster information systems, that's looking at the probabilities of flooding in coastal Texas and doing... Can we make building code changes to mitigate impact? Do we have to change the standard foundation heights for new construction, to mitigate the increasing storm surges from these sort of slow storms that sit there and rain, like hurricanes didn't used to, but seem to be doing more and more. All those problems will run on Lonestar, and on all the systems to come, yeah. >> It's interesting, you mentioned urgent computing, I love that term because it could be an event, it could be some slow kind of brewing event like that rain example you mentioned. It could also be, obviously, with the healthcare, and you mentioned COVID earlier. These are urgent, societal challenges, and having that available, the processing capability, the compute, the data. You mentioned digital twins. I can imagine all this new goodness coming from that. Compare that, where we were 10 years ago. I mean, just from a mind-blowing standpoint, you have, have come so far, take us through, try to give a context to the level of where we are now, to do this kind of work, and where we were years ago. Can you give us a feel for that? >> Sure, there's a lot of ways to look at that, and how the technology's changed, how we operate around those things, and then sort of what our capabilities are. I think one of the big, first, urgent computing things for us, where we sort of realized we had to adapt to this model of computing was about 15 years ago with the big BP Gulf Oil spill. And suddenly, we were dumping thousands of processors of load to figure out where that oil spill was going to go, and how to do mitigation, and what the potential impacts were, and where you need to put your containment, and things like that. And it was, well, at that point we thought of it as sort of a rare event. There was another one, that I think was the first real urgent computing one, where the space shuttle was in orbit, and they knew something had hit it during takeoff. And we were modeling, along with NASA and a bunch of supercomputers around the world, the heat shield and could they make reentry safely? You have until they come back to get that problem done, you don't have months or years to really investigate that. And so, what we've sort of learned through some of those, the Japanese tsunami was another one, there have been so many over the years, is that one, these sort of disasters are all the time, right? One thing or another, right? If we're not doing hurricanes, we're doing wildfires and drought threat, if it's not COVID. We got good and ready for COVID through SARS and through the swine flu and through HIV work, and things like that. So it's that we can do the computing very fast, but you need to know how to do the work, right? So we've spent a lot of time, not only being able to deliver the computing quickly, but having the data in place, and having the code in place, and having people who know the methods who know how to use big computers, right? That's been a lot of what the COVID Consortium, the White House COVID Consortium, has been about over the last few years. And we're actually trying to modify that nationally into a strategic computing reserve, where we're ready to go after these problems, where we've run drills, right? And if there's a, there's a train that derails, and there's a chemical spill, and it's near a major city, we have the tools and the data in place to do wind modeling, and we have the terrain ready to go. And all those sorts of things that you need to have to be ready. So we've really sort of changed our sort of preparedness and operational model around urgent computing in the last 10 years. Also, just the way we scheduled the system, the ability to sort of segregate between these long-running workflows for things that are really important, like we displaced a lot of cancer research to do COVID research. And cancer's still important, but it's less likely that we're going to make an impact in the next two months, right? So we have to shuffle how we operate things and then just, having all that additional capacity. And I think one of the things that's really changed in the models is our ability to use AI, to sort of adroitly steer our simulations, or prune the space when we're searching parameters for simulations. So we have the operational changes, the system changes, and then things like adding AI on the scientific side, since we have the capacity to do that kind of things now, all feed into our sort of preparedness for this kind of stuff. >> Dan, you got me sold, I want to come work with you. Come on, can I join the team over there? It sounds exciting. >> Come on down! We always need good folks around here, so. (laughs) >> Rajesh, when I- >> Almost 200 now, and we're always growing. >> Rajesh, when I hear the stories about kind of the evolution, kind of where the state of the art is, you almost see the innovation trajectory, right? The growth and the learning, adding machine learning only extends out more capabilities. But also, Dan's kind of pointing out this kind of response, rapid compute engine, that they could actually deploy with learnings, and then software, so is this a model where anyone can call up and get some cycles to, say, power an autonomous vehicle, or, hey, I want to point the machinery and the cycles at something? Is the service, do you guys see this going that direction, or... Because this sounds really, really good. >> Yeah, I mean, one thing that Dan talked about was, it's not just the compute, it's also having the right algorithms, the software, the code, right? The ability to learn. So I think when those are set up, yeah. I mean, the ability to digitally simulate in any number of industries and areas, advances the pace of innovation, reduces the time to market of whatever a customer is trying to do or research, or even vaccines or other healthcare things. If you can reduce that time through the leverage of compute on doing digital simulations, it just makes things better for society or for whatever it is that we're trying to do, in a particular industry. >> I think the idea of instrumenting stuff is here forever, and also simulations, whether it's digital twins, and doing these kinds of real-time models. Isn't really much of a guess, so I think this is a huge, historic moment. But you guys are pushing the envelope here, at University of Texas and at TACC. It's not just research, you guys got real examples. So where do you guys see this going next? I see space, big compute areas that might need some data to be cranked out. You got cybersecurity, you got healthcare, you mentioned oil spill, you got oil and gas, I mean, you got industry, you got climate change. I mean, there's so much to tackle. What's next? >> Absolutely, and I think, the appetite for computing cycles isn't going anywhere, right? And it's only going to, it's going to grow without bound, essentially. And AI, while in some ways it reduces the amount of computing we do, it's also brought this whole new domain of modeling to a bunch of fields that weren't traditionally computational, right? We used to just do engineering, physics, chemistry, were all super computational, but then we got into genome sequencers and imaging and a whole bunch of data, and that made biology computational. And with AI, now we're making things like the behavior of human society and things, computational problems, right? So there's this sort of growing amount of workload that is, in one way or another, computational, and getting bigger and bigger. So that's going to keep on growing. I think the trick is not only going to be growing the computation, but growing the software and the people along with it, because we have amazing capabilities that we can bring to bear. We don't have enough people to hit all of them at once. And so, that's probably going to be the next frontier in growing out both our AI and simulation capability, is the human element of it. >> It's interesting, when you think about society, right? If the things become too predictable, what does a democracy even look like? If you know the election's going to be over two years from now in the United States, or you look at these major, major waves >> Human companies don't know. >> of innovation, you say, "Hmm." So it's democracy, AI, maybe there's an algorithm for checking up on the AI 'cause biases... So, again, there's so many use cases that just come out of this. It's incredible. >> Yeah, and bias in AI is something that we worry about and we work on, and on task forces where we're working on that particular problem, because the AI is going to take... Is based on... Especially when you look at a deep learning model, it's 100% a product of the data you show it, right? So if you show it a biased data set, it's going to have biased results. And it's not anything intrinsic about the computer or the personality, the AI, it's just data mining, right? In essence, right, it's learning from data. And if you show it all images of one particular outcome, it's going to assume that's always the outcome, right? It just has no choice, but to see that. So how we deal with bias, how do we deal with confirmation, right? I mean, in addition, you have to recognize, if you haven't, if it gets data it's never seen before, how do you know it's not wrong, right? So there's about data quality and quality assurance and quality checking around AI. And that's where, especially in scientific research, we use what's starting to be called things like physics-informed or physics-constrained AI, where the neural net that you're using to design an aircraft still has to follow basic physical laws in its output, right? Or if you're doing some materials or astrophysics, you still have to obey conservation of mass, right? So I can't say, well, if you just apply negative mass on this other side and positive mass on this side, everything works out right for stable flight. 'Cause we can't do negative mass, right? So you have to constrain it in the real world. So this notion of how we bring in the laws of physics and constrain your AI to what's possible is also a big part of the sort of AI research going forward. >> You know, Dan, you just, to me just encapsulate the science that's still out there, that's needed. Computer science, social science, material science, kind of all converging right now. >> Yeah, engineering, yeah, >> Engineering, science, >> slipstreams, >> it's all there, >> physics, yeah, mmhmm. >> it's not just code. And, Rajesh, data. You mentioned data, the more data you have, the better the AI. We have a world what's going from silos to open control planes. We have to get to a world. This is a cultural shift we're seeing, what's your thoughts? >> Well, it is, in that, the ability to drive predictive analysis based on the data is going to drive different behaviors, right? Different social behaviors for cultural impacts. But I think the point that Dan made about bias, right, it's only as good as the code that's written and the way that the data is actually brought into the system. So making sure that that is done in a way that generates the right kind of outcome, that allows you to use that in a predictive manner, becomes critically important. If it is biased, you're going to lose credibility in a lot of that analysis that comes out of it. So I think that becomes critically important, but overall, I mean, if you think about the way compute is, it's becoming pervasive. It's not just in selected industries as damage, and it's now applying to everything that you do, right? Whether it is getting you more tailored recommendations for your purchasing, right? You have better options that way. You don't have to sift through a lot of different ideas that, as you scroll online. It's tailoring now to some of your habits and what you're looking for. So that becomes an incredible time-saver for people to be able to get what they want in a way that they want it. And then you look at the way it impacts other industries and development innovation, and it just continues to scale and scale and scale. >> Well, I think the work that you guys are doing together is scratching the surface of the future, which is digital business. It's about data, it's about out all these new things. It's about advanced computing meets the right algorithms for the right purpose. And it's a really amazing operation you guys got over there. Dan, great to hear the stories. It's very provocative, very enticing to just want to jump in and hang out. But I got to do theCUBE day job here, but congratulations on success. Rajesh, great to see you and thanks for coming on theCUBE. >> Thanks for having us, John. >> Okay. >> Thanks very much. >> Great conversation around urgent computing, as computing becomes so much more important, bigger problems and opportunities are around the corner. And this is theCUBE, we're documenting it all here. I'm John Furrier, your host. Thanks for watching. (contemplative music)

(bright music) >> Welcome back to AWS re:Invent. You're watching theCUBE. And we're here with Steve Mullaney, who is the president and CEO of Aviatrix. Steve, I got to tell ya, great to see you man. >> We started the whole pandemic, last show we did was with you guys. >> Steve: Don't say we started, we didn't start it. (steve chuckles) >> Right, we kicked it off (all cross talking) >> It's going to be great. >> Our virtual coverage, that hybrid coverage that we did, how ironic? >> Steve: Yeah, was as the world was shutting down. >> So, great to see you face to face. >> Steve: Great to see you too. >> Wow, so you're two years in? >> Steve: Two and a half years yeah. >> Started, the company was standing start $2 billion valuation, raised a bunch of dough. >> Steve: Yeah. >> That's good, you got to feel good about that. >> We were 38 people, two and a half years ago, we're now 400. We had a couple million in ARR, we're now going to be over a 100 million next year, next calendar year, so significant growth. We just raised $200 million, three months ago at a $2 billion valuation. Now have 550 customers, 54 of them are fortune 500, when I started two and a half years ago, we didn't have any fortune 500s, we had probably about a 100 customers. So, massive growth, big growth (indistinct). >> Awesome, I got to ask you, I love to ask CEO's, entrepreneurs, how did you know when to scale? >> You just know it, when you see it. (indistinct) Yeah, there's no formula, you just know it and what you look for is that point where you say, okay, we've now proven the model and until you do that you minimize things and we actually just went through this. We had 12 sales teams, four months ago, we now have 50. 50, five zero and it's that step function as a company, you don't want to linearly grow 'cause you want to hold until you say, it's happening. And then once you say it's happening, okay, the dogs are eating the dog food, this is good then you flip the other way, and then you say, let's grow as fast as we possibly can and that's kind of the mode we're in right now. >> Okay, You've... >> You just know it when you see it. >> Other piece of that is how fast do you scale? And now you're sort of doing that step function as your going. >> Steve: We are going as fast as we possibly can. >> Wow, that's awesome, congratulations and I know you've got to long way to go. So okay, let's talk about the big trends that you're seeing that Aviatrix has taken advantage of, maybe explain a little bit about what you guys do. >> Yeah. So we are, what I like to call Multi- Cloud Native Networking and Network Security. So, if you think of... >> David: What is multicloud native? You got to explain that. >> I got to to explain that. Here's what's happened, it's happening and what I mean by it's happening is, enterprises at two and a half years ago, this is why I joined Aviatrix, all decided for the first time, we mean it now, we are going into Cloud 'cause before that they were just mouthing it. And they said, "We're going into the Cloud." And oh by the way, I knew two and a half years ago of course it was going to be multicloud, 'cause enterprises run workloads where they run best. That's what they do, it's sometimes it's AWS, sometimes it's ads or sometimes it's Google, it's of course going to be multicloud. And so from an enterprise perspective, they love the DevOps, they love the simplicity, the automation, the infrastructure is code, the Terraform, that Cloud operational model, because this is a business transformation, moving to Cloud is not a technology transformation it's the business. It's the CEO saying we are digitizing we have an existential threat to the survival of our company, I want to grow a market share, I want to be more competitive, we're doing this, stop laying across the tracks technology people, will run you over, we're doing this. And so when they do that as an enterprise, I'm BNY Mellon, I'm United Airlines, you name it, your favorite enterprise. I need the visibility and control from a networking and network security perspective like I used to have on-prem. Now I'm not going to do it in the horrible complex operational model the Cisco 1994 data center, do not bring that crap into my wonderful Cloud, so that ain't happening but, all I get from the Native constructs, I don't get enough of that visibility and control, it's a little bit of a black box, I don't get that. So where do I get the best of the Cloud from an operational model, but yet with the visibility and control that I need, that I used to have on-prem from networking network security, that's Aviatrix. And that's where people find us and so from a networking and network security, so that's why I call it multicloud Native because what we do is, create a layer basically an abstraction layer above all the different Clouds, we create one architecture for networking and network security with advanced services not basic services that run on AWS, Azure, Google, Oracle, Ali Cloud, Top Secret Clouds, GovClouds, you name it. And now the customer has one architecture, which is what enterprises want, I want one network, I want one network security architecture, not AWS Native, Azure Native, Google Native. >> David: Right. >> We leverage those native constructs, abstract it, and then provide a single common architecture with demand services, irrespective of what Cloud you're on. >> Dave, I've been saying this for a couple of years now, that Cloud Native... >> Does that make sense Dave? >> Absolutely. >> That abstraction layer, right? And I said, "The guys who do this, who figure this out are going to make a lot of dough." >> Yeah. >> Snowflakes obviously doing it. >> Yeah. >> You guys are doing it, it's the future. >> Yeah. >> And it's really an obvious construct when you look back at the world of call it Legacy IT for a moment... >> Steve: Yeah. >> Because did we have different networks to hookup different things in a data center? >> No, one network. >> One network of course. I don't care if the physical stack comes from Dell, HP or IBM. >> Steve: That's right, I want an attraction layer above that, yeah. >> Exactly. >> So the other thing that happens is, everybody and you'll understand this from being at Oracle, everybody wants to forget about the network. Network security, it's down in the bowels, it's like plumbing, electricity, it's just, it has to be there but people want to forget about it and so you see Datadog, you see Snowflake, you see HashiCorp going IPO in early December. Guess what? That next layer underneath that, I call it the horsemen of the multicloud infrastructure is networking and network security, that's going to be Aviatrix. >> Well, you guys make some announcements recently in that space, every company is a security company but you're really deep into it. >> Well, that's the interesting thing about it. So I said multicloud Native Networking and Network Security, it's integrated, so guess where network security is going to be done in the Cloud? In the network. >> David: Network. >> Yeah in the network. >> What a strange concept but guess what on-prem it's not, you deflect traffic to this thing called a firewall. Well, why was that? I was at Synoptics, I was at Cisco 'cause we didn't care about network security, so that's why firewall companies existed. >> Dave: Right. >> It should be integrated into the infrastructure. So now in the Cloud, your security posture is way worse than it was on-prem. You're connected to the internet by default so guess what? You want your network to do network security, so we announced two things in security; one, we're now a security competency partner for AWS, they do not give that out lightly. We were networks competency four years ago, we're now network security competency. One of the few that are both, they don't do that, that took us nine months of working with them to get there. And they only do that for the people that really are delivering value. And then what we just announced what we call, 'ThreatIQ with ThreatGuard.' So again, built into the network because we are the network, we understand the traffic, we're the control plane and the data plane, we see all traffic. We integrate into the network, we subscribe to threat databases, public databases, where we see what are the malicious IPS. If we have any traffic anywhere in your overall, and this is multicloud, not just AWS, every single Cloud, if we see that malicious traffic going some into IP guess what? It's probably BIT Mining, Bitcoin, crypto mining, it's probably some sort of data ex filtration. It could be some tour thing that you're connected to, whatever it is, you should not have traffic going. And so we do two things we alert and we show you where that all is and then with ThreatGuard, we actually will do a firewall rule right at that gateway, at that point that it's going out and immediately gone. >> You'll take the action. >> We'll take the action. >> Okay. >> And so every single customer, Dave and David, that we've shown this new capability to, it lights up like a Christmas tree. >> Yeah al bet. Okay, but now you've made some controversial statements... >> Steve: Which time? >> Okay, so you said Cisco, I think VMware... >> Dave: He's writing them down. >> I know but I can back it up. >> I think you said the risk, Cisco, VMware and Arista, they're not even in the Cloud conversation now. Arista, Jayshree Ullal is a business hero of mine, so I don't want to... >> Steve: Yeah, mine too. >> I don't want to interrogate her, she's awesome. >> Steve: Yeah. >> But what do you mean by that? Because can't Cisco come at this from their networking perspective and security and bring that in? What do you mean by they're not in the Cloud conversation? >> They're not in the conversation. >> David: Okay, defend that. >> And the reason is they were about four years ago. So when you're four years ago, you're moving into the Cloud, what's the first thing you do? I'm going to grab my CSR and I'm going to try to jam it in the Cloud. Guess what? The CSR doesn't even know it's in the Cloud, it's looking for ports, right? And so what happens is the operational model is horrendous, so all the Cloud people, it just is like oil and water, so they go, oh, that was horrendous. So no one's doing that, so what happens in the Cloud is they realize the number one thing is the Cloud operational model. I need that simplicity, I have to be a single Terraform provider, infrastructure is code. Where do I put my box with my wires? That's what the on-prem hardware people think. >> David: The selling ports your saying? >> The selling boxes. >> David: Yeah. >> And so they'll say, "Oh, we got us software version of it, it runs as a VM, it has no idea it's in the Cloud." It is not Cloud Native, I call that Cloud naive, they don't understand so then the model doesn't work. And so then they say, "Okay, I'm not going to do that." Then the only other thing they can do, is they look at the Cloud providers themselves and they say, "All right, I'm going to use Native constructs, what do you got?" And what happens basically is the Cloud providers say, "Well, we do everything and anything you'll ever need and networking and network security." And the customers, "Oh my God, it's fantastic." Then they try to use it and what they realize is you get very basic level services, and you get no visibility and control because they're a black box, you don't get to go in. How about troubleshooting, Packet Captures, simple things? How about security controls, performance traffic engineering, performance controls, visibility nothing, right? And so then they go, "Oh shit, I'm an enterprise, I'm not just some DevOps Danny three years ago, who was just spinning up workloads and didn't care about security." No, that was the Cloud three years ago. This is now United, BNY, Nike. This is like elite of elite. So when my VC was here, he said, "It's happening." That's what he meant, it's happening. Meaning enterprises, the dogs are eating the dog food and they need visibility and control, they cannot get it from the Cloud providers. >> It's happening in early days Dave. >> So Steve, we're going to stipulate that you can't jam this stuff into Cloud, but those dinosaurs are real and they're there. Explain how you... >> Steve: Well you called them dinosaurs not me but they're roaming the earth and they're going to run out of food pretty soon. (all laughing) The comet hit the earth. >> Hey, they're going to go down fighting. (all laughing) >> But the dinosaurs didn't all die the day after the comet hit the earth... >> Steve: That's right. >> They took awhile. >> Steve: They took a while. >> So, how are you going to saddle them up? That's the question because you're... >> Steve: It's over there walking dead, I don't need to do anything. >> Is it the captain Kirk to con, let them die. >> Steve: Yeah. >> Because you're in the Cloud, you're multicloud... >> Steve: Yeah. >> That's great, but 80% of my IT still on-prem and I still have Cisco switches. Isn't that just not your market or? >> When IBM and DEC did we have to do anything with IBM and DEC in the 90s, early 90s, when we created BC client server, IP architectures? No, they weren't in the conversation. >> David: Yeah. >> So, we dint compete with them, just like whatever they do on-prem, keep doing it, I wish you the best. >> But you need to integrate with them and play with them. >> Steve: No. >> Not at all? >> No, no we integrate, here is the thing that's going to happen, so to the on-prem people, it's all point of reference. They look at Cloud as off-prem, I'm going to take my operational model on-prem and I'm going to push it into the Cloud. And if I push it into multiple Clouds, they're going to call that multicloud, see we are multicloud. You're pushing your operational model into the Cloud. What's happening is Cloud has won, it won two and a half years ago with every enterprise. It's like a rock in the water. And what's going to happen is that operational model is moving out to the edge, it's moving to the branch, it's moving to the data center and it's moving into edge computing. That's what's happening... >> So outpost, so I put an outpost in my data center... >> Outpost looks like... >> Is that Aviatrix? >> Absolutely, we're going to get dragged with that... >> Dave: Okay, alright. >> Because we're the networking and network security provider, and as the company pushes out, that operational model is going to move out, not the existing on-prem OT, IT branch office then pushing in. And so, what's happening is you're coming at it from the wrong perspective. And this wave is just going to push over and so I'm just following behind this wave of AWS and Azure and Google. >> Here's the thing, you can do this and you don't have a bunch of legacy deductible debt... >> Steve: Yeah. >> So you can be Cloud Native, multicloud native, I think you called it? >> Steve: Yeah, yeah. >> I love it, you're building castles on the sand. >> Steve: Yeah. >> Jerry Chen's thing. >> Steve: Yeah. >> Now, the thing is, today's executives, they're not as naive as Ken Olsen, UNIX as, "Snake oil," who would need a PC, so they're not in denial. >> They're probably not in denial, yeah. >> Right, and so they have some resources, so the problem is they can't move as fast as you can. So, you're going to do really well. >> Steve: Yeah. >> I think they'll eventually get there Steve, but you're going to be, I don't know how many, four or five years ahead, that's a nice lead. >> That's a bet I'll take any day. >> David: Then what you don't think they'll ever get there? >> No, 10 years. (steve laughing) >> Okay, but they're not going out of business. >> No, I didn't say that. >> I know you didn't. >> What they're doing, I wish them all the best. >> Because a lot of their customers move... >> I don't compete with them. >> Yeah. We were out of time. >> Yeah. >> What did you mean by AWS is like Sandals? You mean like cool like Sandals? >> Steve: Oh, no, no, no. I don't want to... >> You mean like the vacation place? >> Have you ever been to Sandals? >> I never done it. What do you mean by that? >> There coming, there coming. Which version of sandals (indistinct)? (people cross talking) >> This is for an enterprise by the way, and look, Sandals is great for a lot of people but if you're a Cloud provider, you have to provide the common set of services for the masses because you need to make money. And oh, by the way, when you go to Sandals, go try it, like get a bottle of wine, they say, "We got red wine or white wine?" "Oh, great, what kind of red wine?" "No, red wine and it's in a box." And they hope that you won't know the difference. The problem is some people in enterprises want Four Seasons, so they want to be able to swipe the card and get a good bottle of wine. And so that's the thing with the Cloud, but the Cloud can't offer up a 200 bottle of wine to everybody. My mom loves box wine, so give her box wine. Where ISBs like us come in, is great but complimentary to the Cloud provider for that person who wants that nice bottle of wine because if AWS had to provide all this level of functionality for everybody, their instant sizes would be too big, >> Too much cost for that. (people cross talking) You're right on. And as long as you can innovate fast and stay ahead of that and keep adding value... >> Well, here's the thing, they're not going to do it for multicloud either though. >> David: I wouldn't trust them to do it with multicloud. >> No. >> David: I wouldn't. >> No enterprise would and I don't think they would ever do it anyway. >> That makes sense. Steve, we've got to go man. You're awesome, love to have you on theCUBE, come back anytime. >> Awesome, thank you. >> All right, keep it right there everybody. You're watching theCUBE, the leader in enterprise tech coverage. (bright music)

>>live from Orlando, Florida It's the cue covering Microsoft Ignite Brought to you by Cohee City. Welcome >>back, everyone to the cubes Live coverage of Microsoft IC night here at the Orange County Convention Center in Orlando, Florida I'm your host, Rebecca Night, along with my co host Stew Minutemen were joined by Parham Cologne. He is the chief product officer at you. I path. Thank you so much for coming on the Cube. >>Thank you so much for >>coming back on the cute. >>Thank you. >>So I I was just a u IE path with you in Vegas a couple of weeks ago and the U AI Path tagline is a robot for every employee Microsoft tagline is employing empowering every employee to be a technologist, empowering citizen developers. Does it strike you that do the two missions are are similar in their way? >>That's that's absolutely right. I think we have so much in common their companies together on I think we're working very closely together and not just our technology, but also in what we're trying to achieve, which is to make people achieve more in amplifying human achievement is a core mission of our company and very excited that Microsoft so shares the same emission. >>Yeah, it really does connect with Mace onto this morning. Talked about that 61% of job openings for developers air outside the tech sector. And of course, you AI path is really trying to help. But this is productivity overall, with everything you're doing, >>absolutely, and productivity's where we focus our technology primarily on. In fact, a lot of focus is around. How do we actually get people to do more with less time so they can have more time to do the things that they could do with the creative parts of their time, as opposed to doing a Monday in part? So, yeah, productivity's is really important to us. The company. That's what we think about every day. >>Could you bring us inside the relationship with Microsoft and you? I passed? >>Yeah, so we're deeply partner that Microsoft's and today one we've most of our technology is built on Microsoft's stack on dot net miran. Our databases all run on sequel server or cloud service runs on Microsoft Azure. So we are very deeply partner to be health Microsoft Bill. A lot of a I service is around document extraction. The forms recognize her with one of the first customers that we work together with Microsoft and Chevron on so very deep partnership with Microsoft. Okay, >>so let me ask you a question. Actually, as a customer of Microsoft, you know what? Why, why everything built on Microsoft from, you know, the dot net through the infrastructure of the service. What, what? Why did you bypass choose Microsoft? >>I think it made a lot of sense. Microsoft's focus on productivity Microsoft's focus on enabling developers do stuff quickly on it also helped a lot of the founders, myself included, came through with Microsoft to be a lot of experience with Microsoft's. I think part of that helped as well. >>Does it help or hurt when you are then pitching your service? Is that that it is that it is a much more Microsoft focused company, >>So I think we've grown over the years to actually have a much broader ecosystem, so we have more than 500 partners now we work with Google. Google is a customer, it's an investor. It's also very deep partner. A lot of very I service is we're welding on it with Google were be partnered with AWS as well. So I think we're working with all the way our customers are today. But I think we're still have a very close relationship with Microsoft, given our agitated given where we started. >>Yeah, I actually I I went to the passport event last year and had not realized how deep that connection was with Microsoft. I see you. I path across all the clouds. So there's a little mention of our p A. That this morning in the keynote theme, the power automate solution coming out from Microsoft. Of course, everyone seems tohave an R p A. Out there, you know all the big software houses out there. Tell us what this means in the marketplace. >>Yes, Listen, our P a is a very fast growing market. Is the fastest growing enterprise category today, And when you grow so fast, it's good for the business but also attracts attention, I think getting somebody like Microsoft to sort of say that we're in it as well. Only help sort of solidify the foundation, solidify the category and brings a lot more, you know, credibility to this category. So I think we're excited to have Microsoft here as well. >>And in terms of a CZ, you were saying to companies that are very much focused on workplace productivity, employee collaboration, and being able to be more creative with the time that you have. How much is that cultural alignment? How much does that help your partnership? >>I think it helps a partnership a lot. So you know, when we, for example, of when you meet with the office team, they think deeply about helping people do more with last time. You know, we think about the same things as well. So if you notice some of the newer products that we've launched our very deeply integrated into office, in fact to do a lot of inspiration from products like Excel to be able to say business people that are able to, you know, do some very sophisticated, complex business models and excel should be able to do similar stuff with their products as well. So we continue to work with Microsoft and across collaboration across the steams, anything in general, our message. We have a close relationship with Microsoft, So when Microsoft bring this into opportunities and it closes, it actually retired Dakota for Microsoft Sellers as well. So I think all of that alignment really helps. >>I would love to hear you know what? What? Joint customers. You know what brings customers to you? I path at a show here. What? What are some of the key drivers for their discussions that you're having this week? >>Yeah. I mean, we've got you know, through through the years, we've got over 5000 customers that work with us large enterprises in a very large banks to companies like Chevron. Chevron in particular, is one of those customers. You know, that's a very, very deep customer of Microsoft, but also a very strong customer of ours and a specific use case at my at Chevron. Chevron wanted to extract data from their oil field service reports. They were getting more than 1000 oil. Regular reports coming in every day with about 300 pages for average. For report on. Somebody had to manly go in and physically read those reports. Put him into that s a P system so that you could predict if there was a pretty prevent amendments appear that was acquired, you know, working together with Microsoft, we were able to take service that Microsoft was building an A. I called forums recognize ER and take it to pre bid on Alfa with customers so that Chevron is now able to have all of those reports read by you. I path robots and automatically punch it into, you know, the SNP preventive maintenance applications so that you can actually ship the engineer on side before you know that something happened to the old Greg. So I think that's a pretty cool a scenario. >>Another's another similarity between AI Path and you, AI Path and Microsoft is this customer obsession. And this is something that you talked a lot about at your path forward. This spending time with customers, learning how they would use our p A and then also thinking, thinking ahead of them and in terms of how they could use our p A. How do you work with customers and Microsoft together in partnership in terms of how do you find out exactly what their needs are and the joint solutions you could provide? >>Yeah, and then that's a really good question. Microsoft has been very obsessed with, you know, driving customer obsession and all parts of the organization we culturally have a really deep obsession about working closely with customers. And I think so that Microsoft has empty sea, meet the customer sessions around around the world on We were close living Microsoft to make sure that our technology can be showcased by Microsoft people in those empty see sessions so that when customers come in, they able to not only see Microsoft technology, but also our technology. And if they're interested, then our sales teams work elaborately together to make sure we can, you know, have a joint session than planning and working with customers. >>So I had a chat earlier this year with your CMO Bobbi Patrick talking about how a I and r p a go together. You on the product? So will I. I be able to allow our p A to get into more complex configuration, give us where we are and you know what? What's what's new in that space? >>Yeah, No, absolutely. So like the first wave of our p A was all about taking sort of structured processes, you know, deluding data from excel sheets, reading data for maybe eyes and be able to process it in different systems now in the humans don't always work with that. 10% of what >>we do >>on a daily basis, a structure, data right, spreadsheets and stuff, 90% of what we d'oh reading spread shades, extracting information from papers responding Thio. You know Chad conversations. All of that unstructured information can now be processed by AI algorithms to be able to extract the intent off the chat conversation to be to extract the data. That's in that unstructured document that we just received to be able to use computer vision to detect what is on the computer screen so that you're able to detect that control, whether rendered the browser or renders in a window start to application of that. So I brings the possibility to automate a lot more complex processes within the organization, you know, mimicking sort of MME. Or human like behavior. So the robots are not just doing the numbers and structured data but be able to process unstructured information. It's >>well, well, the way I help it all, trying to understand, what can I automate? >>Absolutely. And that's the other piece off being able to use process, understanding capability. So what we've done is we've built capability that's able to follow human activity logs and how people are using systems, but also how the databases air getting updated by different applications and be able to mind that information to understand how work is getting done and the enterprise and be able to understand what are the scenarios and possibilities for automating mawr business processes that's hold onto the key benefits of how a I and process mining can be can be applied to the context of the R P. A. >>There's so many product announcements today. On the main stage is an 87 page book that we that we were sent from the Microsoft calms team. What is it? What's the most exciting things you've seen here today? >>I think I'm really excited about some of the innovation that Microsoft is doing in the analytic stock to be able to report on the, you know, the data warehouse, but also big data together and one stack. I think that's really powerful. That is something that our customers have have be very interested in, because robots process structure log, but also in structure logs. I'm also excited about some of the eye investments that Microsoft is making, I think some of the eye capabilities and are really coming to practical use. A lot of companies tuck Brody I For a long time. We've applied a I practically in our technology, but I think a lot more technology is now available for us to be used in our products. >>Okay, parm. There's a recent acquisition process. Gold was. The company could tell us a little bit about that. What what? What are the plans for that >>absolutely process Goal is a company that's basically all in Germany and nine home and in bed. Ireland. On this is the company that was focused on process, understanding of process. Mining's essentially, what they had was that connectors a different line of business applications and be able to sit and study logs of how work was getting done over long periods of time. So what happened is if you went to a line of business owner and he asked them, What is your process for procure to pay look like, in order to cash look like chances out, they'll draw you a straight line. That's a haze with the processes, However, when you look at how work is getting done, it's typically not a straight line. And depending on how many variations you're looking at, you can get up to, like, you know, 15 or 20 different variations, the same process being done. So what process gold does is identifies. What are the different ways in which processes air getting done? Identify where the bottlenecks exist in the process, right? How long is the step one? How long is the time? But we step two and step three, right? Is that taking 25% of what the total time is? And is there a way to optimize that process by eliminating that bottleneck? And once you've optimized the process, it also gives you the ability to go automate that optimized process right? You don't want to automate a process that is sub optimal. You want to go understand the process, see how work is getting done, optimized the bottlenecks and eliminate the bottlenecks, optimize the process and then go out of made that and process go. It really helps us sort of cater to that need, which is go automate. You know, the best possible way to optimize the process >>in terms of Microsoft's use of things like a I and ML And now we have not really talked a lot about ML here. I mean, it was mentioned on the main stage, but not a lot. How? What? What do you think the future holds in terms of Microsoft in the next 5 to 10 years? >>Yeah. I mean, I think I see Microsoft investing a lot in data and really being able Thio get all kinds of data because ML is useful only after it's able to reason over tons of data. And Microsoft is in a rightfully investing and the data repositories in stores so that it has the ability to store that data to process that data. And once that's got the data on the data assets over it, then it's able to go Korea the algorithms that can reason over data on and create that stuff. And I think that's really exciting because Microsoft has a lot of the horsepower to be able to not only store that data process that data efficiently said can be used in machine learning. And I >>hope our um thank you so much for coming on the Cube. It was a pleasure talking to you. >>Thank you. Pleasure to have you here. Thank you very much. >>I'm Rebecca Knight. First to minimum. Stay tuned for more of the cubes. Live coverage of Microsoft ignite.

>> live from San Francisco, California. It's the key. You covering the IBM chief Data officer? Someone brought to you by IBM. >> We're back at the IBM CDO conference. Fisherman's Worf Worf in San Francisco. You're watching the Cube, the leader in life tech coverage. My name is David Dante. Glenn Finches. Here's the global leader of Big Data Analytics and IBM, and we're pleased to have Mark Clare. He's the head of data enablement at AstraZeneca. Gentlemen, welcome to the Cube. Thanks for coming on my mark. I'm gonna start with this head of data Data Enablement. That's a title that I've never heard before. And I've heard many thousands of titles in the Cube. What is that all about? >> Well, I think it's the credit goes to some of the executives at AstraZeneca when they recruited me. I've been a cheap date officer. Several the major financial institutions, both in the U. S. And in Europe. Um, AstraZeneca wanted to focus on how we actually enable our business is our science areas in our business is so it's not unlike a traditional CDO role, but we focus a lot more on what the enabling functions or processes would be >> So it sounds like driving business value is really the me and then throw. Sorry. >> I've always looked at this role in three functions value, risk and cost. So I think that in any CDO role, you have to look at all three. I think the you'd slide it if you didn't. This one with the title. Obviously, we're looking at quite a bit at the value we will drive across the the firm on how to leverage our date in a different way. >> I love that because you can quantify all three. All right, Glenn. So you're the host of this event. So awesome. I love that little presentation that you gave. So for those you didn't see it, you gave us pay stubs and then you gave us a website and said, Take a picture of the paste up, uploaded, and then you showed how you're working with your clients. Toe. Actually digitize that and compress all kinds of things. Time to mortgage origination. Time to decision. So explain that a little bit. And what's that? What's the tech behind that? And how are people using it? You know, >> for three decades, we've had this OCR technology where you take a piece of paper, you tell the machine what's on the paper. What longitudinal Enter the coordinates are and you feed it into the hope and pray to God that it isn't in there wrong. The form didn't change anything like that. That's what that's way. We've lived for three decades with cognitive and a I, but I read things like the human eye reads things. And so you put the page in and the machine comes back and says, Hey, is this invoice number? Hey, is this so security number? That's how you train it as compared to saying, Here's what it So we use this cognitive digitization capability to grab data that's locked in documents, and then you bring it back to the process so that you can digitally re imagine the process. Now there's been a lot of use of robotics and things like that. I'm kind of taken existing processes, and I'm making them incrementally. Better write This says look, you now have the data of the process. You can re imagine it. However, in fact, the CEO of our client ADP said, Look, I want you to make me a Netflix, not a blood Urbach Blockbuster, right? So So it's a mind shift right to say we'll use this data will read it with a I will digitally re imagine the process. And it usually cuts like 70 or 80% of the cycle time, 50 to 75% of the cost. I mean, it's it's pretty groundbreaking when you see it. >> So markets ahead of data neighborhood. You hear something like that and you're not. You're not myopically focused on one little use case. You're taking a big picture of you doing strategies and trying to develop a broader business cases for the organization. But when you see an example like that and many examples out there, I'm sure the light bulbs go off. So >> I wrote probably 10 years cases down while >> Glenn was talking about you. You do get tactical, Okay, but but But where do you start when you're trying to solve these problems? >> Well, I look att, Glenn's example, And about five and 1/2 years ago, Glenn was one I went to had gone to a global financial service, firms on obviously having scale across dozens of countries, and I had one simple request. Thio Glenn's team as well as a number of other technology companies. I want cognitive intelligence for on data in Just because the process is we've had done for 20 years just wouldn't scale not not its speed across many different languages and cultures. And I now look five and 1/2 years later, and we have beginning of, I would say technology opportunities. When I asked Glenn that question, he was probably the only one that didn't think I had horns coming out of my head, that I was crazy. I mean, some of the leading technology firms thought I was crazy asking for cognitive data management capabilities, and we are five and 1/2 years later and we're seeing a I applied not just on the front end of analytics, but back in the back end of the data management processes themselves started automate. So So I look, you know, there's a concept now coming out day tops on date offices. You think of what Dev Ops is. It's bringing within our data management processes. It's bringing cognitive capabilities to every process step, And what level of automation can we do? Because the, you know, for typical data science experiment 80 to 90% of that work Estate engineering. If I can automate that, then through a date office process, then I could get to incite much faster, but not in scale it and scale a lot more opportunities and have to manually do it. So I I look at presentations and I think, you know, in every aspect of our business, where we clear could we apply >> what you talk about date engineering? You talk about data scientist spending his or her time just cleaning the wrangling data, All the all the not fun stuff exactly plugging in cables back in the infrastructure date. >> You're seeing horror stories right now. I heard from a major academic institution. A client came to them and their data scientists. They had spent several years building. We're spending 99% of their time trying to cleanse and prep data. They were spend 90% cleansing and prepping, and of the remaining 10% 90% of that fixing it where they fix it wrong and the first time so they had 1% of their job doing their job. So this is a huge opportunity. You can start automating more of that and actually refocusing data science on data >> science. So you've been a chief data officer number of financial institutions. You've got this kind of cool title now, which touches on some of the things a CDO might do and your technical. We got a technical background. So when you look a lot of the what Ginny Rometty calls incumbents, call them incumbent Disruptors two years ago at Ivy and think they've got data that has been hardened, you know, in all these projects and use cases and it's locked and people talk about the silos, part of your role is to figure out Okay, how do we get that data out? Leverage. It put it at the core. Is that is that fair? >> Well, and I'm gonna stay away from the word core cause to make core Kenan for kind of legacy processes of building a single repositories single warehouse, which is very time consuming. So I think I can I leave it where it is, but find a wayto to unify it. >> Not physically, exactly what I say. Corny, but actually the court, that's what we need >> to think about is how to do this logically and cream or of Ah unification approach that has speed and agility with it versus the old physical approaches, which took time. And resource is >> so That's a that's a computer science problem that people have been trying to solve for years. Decentralized, distributed, dark detectors, right? And why is it that we're now able Thio Tap your I think it's >> a perfect storm of a I of Cloud, the cloud native of Io ti, because when you think of I o. T, it's a I ot to be successful fabric that can connect millions of devices or millions of sensors. So you'd be paired those three with the investment big data brought in the last seven or eight years and big data to me. Initially, when I started talking to companies in the Valley 10 years ago, the early days of, um, apparatus, what I saw or companies and I could get almost any of the digital companies in the valley they were not. They were using technology to be more agile. They were finding agile data science. Before we call the data signs the map produce and Hadoop, we're just and after almost not an afterthought. But it was just a mechanism to facilitate agility and speed. And so if you look at how we built out all the way up today and all the convergence of all these new technologies, it's a perfect storm to actually innovate differently. >> Well, what was profound about my producing in the dupe? It was like leave the data where it is and shipped five megabytes a code two upended by the data and that you bring up a good point. We've now, we spent 10 years leveraging that at a much lower cost. And you've got the cloud now for scale. And now machine intelligence comes in that you can apply in the data causes. Bob Pityana once told me, Data's plentiful insights aren't Amen to that. So Okay, so this is really interesting discussion. You guys have known each other for a couple of couple of decades. How do you work together toe to solve problems Where what is that conversation like, Do >> you want to start that? >> So, um, first of all, we've never worked together on solving small problems, not commodity problems. We would usually tackle something that someone would say would not be possible. So normally Mark is a change agent wherever he goes. And so he usually goes to a place that wants to fix something or change something in an abnormally short amount of time for an abnormally small amount of money. Right? So what's strange is that we always find that space together. Mark is very judicious about using us as a service is firm toe help accelerate those things. But then also, we build in a plan to transition us away in transition, in him into full ownership. Right. But we usually work together to jump start one of these wicked, hard, wicked, cool things that nobody else >> was. People hate you. At first. They love you. I would end the one >> institution and on I said, OK, we're going to a four step plan. I'm gonna bring the consultants in day one while we find Thailand internally and recruit talent External. That's kind of phases one and two in parallel. And then we're gonna train our talent as we find them, and and Glenn's team will knowledge transfer, and by face for where, Rayna. And you know, that's a model I've done successfully in several organizations. People can. I hated it first because they're not doing it themselves, but they may not have the experience and the skills, and I think as soon as you show your staff you're willing to invest in them and give them the time and exposure. The conversation changes, but it's always a little awkward. At first, I've run heavy attrition, and some organizations at first build the organizations. But the one instance that Glen was referring to, we came in there and they had a 4 1 1 2 1 12 to 15 year plan and the C I O. Looked at me, he says. I'll give you two years. I'm a bad negotiator. I got three years out of it and I got a business case approved by the CEO a week later. It was a significant size business case in five minutes. I didn't have to go back a second or third time, but we said We're gonna do it in three years. Here's how we're gonna scale an organization. We scaled more than 1000 person organization in three years of talent, but we did it in a planned way and in that particular organization, probably a year and 1/2 in, I had a global map of every data and analytics role I need and I could tell you were in the US they set and with what competitors earning what industry and where in India they set and in what industry And when we needed them. We went out and recruited, but it's time to build that. But you know, in any really period, I've worked because I've done this 20 plus years. The talent changes. The location changes someone, but it's always been a challenge to find him. >> I guess it's good to have a deadline. I guess you did not take the chief data officer role in your current position. Explain that. What's what. What's your point of view on on that role and how it's evolved and how it's maybe being used in ways that don't I >> mean, I think that a CDO, um on during the early days, there wasn't a definition of a matter of fact. Every time I get a recruiter, call me all. We have a great CDO row for first time I first thing I asked him, How would you define what you mean by CDO? Because I've never seen it defined the same way into cos it's just that way But I think that the CDO, regardless of institutions, responsibility end in to make sure there's an Indian framework from strategy execution, including all of the governance and compliance components, and that you have ownership of each piece in the organization. CDO most companies doesn't own all of that, but I think they have a responsibility and too many organizations that hasn't occurred. So you always find gaps and each organization somewhere between risk costs and value, in terms of how how they're, how the how the organization's driving data and in my current role. Like I said, I wanted to focus. We want the focus to really be on how we're enabling, and I may be enabling from a risk and compliance standpoint, Justus greatly as I'm enabling a gross perspective on the business or or cost management and cost reductions. We have been successful in several programs for self funding data programs for multi gears. By finding and costs, I've gone in tow several organizations that it had a decade of merger after merger and Data's afterthought in almost any merger. I mean, there's a Data Silas section session tomorrow. It'd be interesting to sit through that because I've found that data data is the afterthought in a lot of mergers. But yet I knew of one large health care company. They've made data core to all of their acquisitions, and they was one the first places they consolidated. And they grew faster by acquisition than any of their competitors. So I think there's a There's a way to do it correctly. But in most companies you go in, you'll find all kinds of legacy silos on duplication, and those are opportunities to, uh, to find really reduce costs and self fund. All the improvements, all the strategic programs you wanted, >> a number inferring from the Indian in the data roll overlaps or maybe better than gaps and data is that thread between cost risk. And it is >> it is. And I've been lucky in my career. I've report toe CEOs. I reported to see Yellows, and I've reported to CEO, so I've I've kind of reported in three different ways, and each of those executives really looked at it a little bit differently. Value obviously is in a CEO's office, you know, compliance. Maurizio owes office and costs was more in the c i o domain, but you know, we had to build a program looking >> at all three. >> You know, I think this topic, though, that we were just talking about how these rules are evolving. I think it's it's natural, because were about 5 2.0. to 7 years into the evolution of the CDO, it might be time for a CDO Um, and you see Maur CEOs moving away from pure policy and compliance Tomb or value enablement. It's a really hard change, and that's why you're starting to Seymour turnover of some of the studios because people who are really good CEOs at policy and risk and things like that might not be the best enablers, right? So I think it's pretty natural evolution. >> Great discussion, guys. We've got to leave it there, They say. Data is the new oil date is more valuable than oil because you could use data to reduce costs to reduce risk. The same data right toe to drive revenue, and you can't put a gallon of oil in your car and a quart of oil in the car quarter in your house of data. We think it's even more valuable. Gentlemen, thank you so much for coming on the cues. Thanks so much. Lot of fun. Thanks. Keep right, everybody. We'll be back with our next guest. You're watching the Cube from IBM CDO 2019 right back.

live from Las Vegas it's the cube covering AWS reinvent 2018 brought to you by Amazon Web Services Intel and their ecosystem partners welcome back everyone to the cubes live coverage of AWS reinvent here at the Venetian in Las Vegas I'm your host Rebecca night along with my co-host Dave Volante Rebecca we work together this week and I'm excited for our next guest he is an esteemed cube alum Harish Venkat vice president global sales enablement and marketing at Veritas technologies welcome back to the Q thank you very much thank you see you Gary good to see you David so you've been to this is not your first rodeo you know many AWS reinvents what are you hearing what what are you hearing on the ground from your customers what trends are you seeing what most excites you yeah first of all that's great to be part of reinvent you know love the buzz here it's very electrifying and we're very happy about our partnership with AWS and we're very happy about the sponsorship for reinvent as well if there are any skeptics out there who's still thinking cloud is still a fashion statement they really need to reassess their statement because proud is in full effect for both computer and storage the other trend that I'm seeing is globalization is in full effect ideas are flowing swiftly and freely through the borders and then when you think about technology technology is very exciting the global GDP is what about 79 trillion IT spend about four trillion but it's interesting to see the four trillion sort of fueling the growth for the 79 trillion I also think AI machine learning deep learning all of this is going to reshape not only the software industry but I think it's going to reshape the way we live our lives and the last thing I'll say is data hands down as the new currency for enterprise right exactly we keep hearing this data is the new oil data is the it is the currency it's even more valuable I got our take on this okay so I can take a quarter oil and/or a gallon oil I can put it in my house or I can put it in my car I can't do both with that same resource data it doesn't follow the laws of scarcity I can use that same data from multiple use cases so by premises it's more valuable than oil what do you think I think the versatility of data is not the same as oil oil has very limited purpose and I think it's important and we are all dependent on it but data is so meaningful the amount of insights you can get it provides you a competitive edge in the industry it is unbeatable so yeah oil not say mono reefs I've had the pleasure of doing a couple of Veritas solution days yes I did Veritas vision last year you guys have broken that up into multiple cities this year I did New York and Chicago just at ease with the last 30 to 45 days yeah had some great conversations with customers some Veritas execs the conversation was obviously heavy kool-aid injection of Veritas technology your roadmap your vision really really detailed stuff obviously a cloud was a piece of that the conversations here I'm sure a much more cloud oriented now can you talk about the discussions that you're having the focus that you have on cloud generally in AWS specifically yeah sure look I mean data is growing year over year and and customers are still trying to figure out how to manage the data how am I going to work out the economics of this by leveraging cloud and this is not an easy equation to solve by no means and this is where Veritas and cloud service providers like AWS are really taking the market leadership role and then figuring out how do we leverage the entire data landscape if you will so before you even think of cloud the first thing you want to know is where does my data reside and what type of data do I have so Veritas is able to provide that visibility of data classification of data we provide immense amount of deduplication ratio which helps with the economics of this ratio this equation so I think we provide an end to solution from visibility classification deduplication even helping new application and data to the cloud and the partnership with AWS is really enabling customers to solve that conundrum that you're talking so I want to double click on this you know so as a as a as a person who understands backup and recovery deeply as a working for a company that's that's their business and of course you're extending beyond backup and I understand that but you know snapshots replication that's not backup in recovery so when I see something like outpost outpost is this on Prem infrastructure appliance that AWS is bringing as part of its hybrid strategy I want to know how is that gonna be protected now of course they'll talk about the way in which they protect it but a company like yours has a different philosophy your recovery is everything the whole data management approach how do you guys think about data management and data protection you know beyond snapshots or beyond just replication can you explain that yeah so I think the best way to explain that would be to talk about a customer use case great and while several customers come to mind I want to talk about see IMC I think it's a perfect embodiment of all the business use cases that we've been discussing so far ok see IMC is China International Marine container and they've been in business since 1980 you know employ about 51,000 based out of Shenzhen in in in China and they started their digital transformation in 2017 and what they're trying to do is really achieve three things one move all of their business application to the cloud starting with their strategic ERP in this case it was s AP and s AP Hana and the other thing is because they've been around since 1980s a lot of their processes are outdated it's very manual and they had a lot of dependency on tape as part of their backup and recovery so they want to modernize but they want to modernize that piece of it and then the last thing is they wanted a state-of-the-art disaster recovery which is also required by the local compliance laws in China where it doesn't matter where your business application is running they needed a copy of data on Prem so they evaluated all the different vendors market and clearly they chose Veritas as well as AWS to solve that business problem why why did they choose you guys yeah so you know obviously Veritas is number one in data protection 15 years in a row we got more than 50 thousand customers 96 percent of Fortune 100 trust their data with us but more importantly I think it's the partnership with AWS that really helped solve this problem and let me tell you how they did it I think that's important so the first thing they did is they launched an instance of net backup in AWS you know gone are the days where you're completely dependent on purpose-built appliance people are switching over to virtual appliance and they were able to do that by the partnership with Veritas and AWS so an instance in AWS leveraging s3 for the immediate server two days after the data they moved on s3 data over to s3 ia and eventually to glacier you know obviously Andy Jessee has been talking quite a bit in terms of increased throughput from s3 to glacier which is going to help this cause and then when you when you think about how customers are dealing with the transition to the cloud not everyone's ever going to move there all of their application to the cloud it's going to be a journey with time but what that creates in a customer environment is you got critical data in the cloud critical data on prem and they're looking at one data protection solution for both on prem and cloud and this is where Veritas net back really comes and that backup really comes in well I want to ask a little bit about that journey because as you said they don't have everything in the cloud so how has Veritas and any available AWS this sort of three-way partnership how are you how does that work I mean our user hand-holding them are you is it a co-creative process can you can you riff on that a little bit yeah sure so you know just like any of their lines we start off with the technical alliance we want to make sure that whatever use case that we're going to the market and all of those use cases are really coming from customers we understand customer challenges we work with different companies and cloud service providers in this case AWS to make sure that the solution that we take to the market is complete there's absolutely no hiccups we got professional services to help them to mitigate the risk factors and to considerations that most customers are thinking about one is costs another one is performance and thanks to net backup a IR or auto image replicator you know we are able to take a 2/3 of the network bandwidth out so you can achieve all of that performance with one third the network we got incredible deduplication ratio the storage cost as a result as 50 times less than what you would get and so back to the to consideration factor performance and cost we're able to do that in collaboration with AWS so I wonder we could talk about multi cloud or poly cloud as we sometimes call it so you can infer from listening to AWS that it really is better off having a one cloud strategy but as we know oh you say you talk to customers there's no one customer cloud strategy the customers are made up of there's like the government there's multiple constituencies in the company and shadow IT and so there's multi clouds you don't care whether it's one cloud a moment about you're there to protect it but I'm interested in what years you're seeing so what are you seeing and how are you because we we know it's not more than it's more than just one it's not just on Prem in one cloud how are you approaching that problem talk about customers and what their kind of roadmap looks like in their strategic plans and where you fit yeah so back to your point I don't think we'll ever see just one cloud the dependency on just one cloud is not happening we're seeing multiple clouds we're seeing hybrid clouds obviously you know Azure stack is coming up with their own version and so is AWS and in a customer's environment you are seeing that now there's also talks about are we going to see cloud to cloud movement cloud to cloud disaster recovery I am not seeing that at all I think the economics of cloud to cloud move over our failover is just too expensive so I think we're still seeing physical to cloud cloud back to physical and then one physical to another cloud I don't see a whole lot of cloud movement so where Veritas really comes in as our ability to provide that disaster recovery both from physical to physical protect your data in the same assured way on Prem as well as the cloud allowing you to leverage the cloud as a disaster recovery mechanism in fact I was having breakfast with Bell media this morning and they have two sides in Canada that they're using disaster recovery and they're wanting to leverage cloud and he's super excited about net backup eight one two cloud catalyst you know ability to leverage cloud as the disaster recovery and with our VRP was just Veritas resiliency platform to achieve that so a culmination of all of that hopefully answers their question absolutely and I think that's right on you had referenced earlier in your commentary Harish that you see some major changes coming for the software industry and we were we were talking to Jerry Chen the other day from Greylock in a really sharp former VMware now he's you know VC so he sees a lot of stuff and he put forth the premise that everything's changing in software development as a software company I wonder if you could you could comment that Amazon is essentially giving all these this tooling to create new software apps but as a software player how do you guys look at that how are you modernizing you know your platform and what do you see is the outcome yeah so you know it's interesting you talked about VSD in New York obviously and I spoke about it and when I talked about two things over there which was really ease of use and simplicity and and that's really where the customers are gravitating we have to make sure that any platform in the software industry has the 3.click to value mantra built in you can't be having the green screens anymore so Veritas has taken the same approach we're really looking at ease of use and simplicity and three clicks to value so that's a big trend you know I talked about AI and machine learning and deep learning you know gone are the days where everyone is reacting to something now it's all predictive analytics how do I garner more information so we're building AI and machine learning into our platform where if there's an outage we're going to tell you beforehand some of the reasons before or beforehand into some of the reasons behind it and that way you can address it and not be a subject to a reactive catastrophe so I think those are two big things that I'm seeing in the software-defined storage and the second thing is just an overall ecosystem right so it's not just about standalone value but how do you collaborate with the rest of the software providers to build a bigger and better solutions as an example our relationship with AWS is speaking very highly of that we're solving bigger and better problems as a result of this we just announced our alliance with pure storage with their data hub architecture we're able to do you know data protection with IOT s which is again another trend in the marketplace where we can share protect and collaborate with pure data as well well let's talk with the edge in terms of data protection for the edge how'd how does the edge IOT how does that affect customers data protection strategies and what's Veritas is angle there yeah so you know I mentioned this in in Microsoft ignite because Satya had mentioned this in his keynote saying that the edge computing there's a lot of proliferation around that and it's not just a compute fact because a lot of data has been generated in that too so how do you make sense of all of that data how do you which ones do you protect which ones do discard so Veritas has that solution which allows you to sift through all of that data figure out which one's important classify that and then help you provide data protection for the edge computing I'm thinking about yesterday's keynote with Andy Jesse a dizzying number of announcements of new products and services new innovations and it's and this is really de rigueur at an AWS reinvent is this is this pace sustainable I mean this this constant innovation I mean is that sustainable what are you you know it's interesting you asked me that question because it's the same concept of is Moore's lot going to be sustainable right so far we're seeing that it is and as a result you're seeing all these madness around innovation you know driverless cars and you know journey to the another planet in a I and and ml and full effect and all of this is going to reshape our future so far I'm not seeing any signs of slowing down as long as Moore's law is going to keep up with its multiplier effect I think we'll see better better lifestyle and more and more innovation just the amount of patents that we're seeing with new startups it's just off the charts so I'm a big proponent of innovation and I think this will this will continue going on well I think if I could comment I think Moore's Law in many ways was was one-dimensional I mean you had the doubling of you know performance every 18 months whatever it is now you have this multi-dimensional innovation combination Moore's Law fine but you've got data you've got machine intelligence applied to that data and you've got the cloud at scale so this you have this combinatorial effect that has multiplicative effects on innovation so that our argument is the curve is actually bending you know into a nonlinear and it's mind-boggling there's big pace of innovation you certainly see that here from from Amazon it seems to be accelerating and it's it's underscored by the number of announcements that this company is making others trying to keep pace them forcing their customers to keep pace it's him it actually feels like it's it's speeding up not decelerating without a doubt and I think it depends on the type of company you're talking about if you're a startup company you know and have any of the legacy things that you're talking about you're spending all of your IT spent on innovation you look at a classy IT spend equation 85% of it just to keep the lights on and less than 10% on innovation I think that is mind-boggling to me and that's why some of these new startups are constantly challenging you know fortune 500 companies whose lifespan used to be 65 years but now at 16 years and it's constantly getting down because of this effect as well and I think that's a great point if if you're stuck in that 85% technical debt world and you don't allocate enough for innovation yeah it's it's going to be problematic and so what we see is customers looking at it as a portfolio we got run the business we have grow the business we have transformed the business we're going to deliberately allocate cash to each of those and hopefully bet on the right things yeah not a doubt I mean look at the at the end of it as a result of all these different phenomenons that we're talking about it is good for consumers because they're looking at more and more options better technology and those sort of fierce competition is always good for everyone as consumers as well as enterprise great well Harish thank you so much for coming on the cables my pleasure I'm Rebekah night for DES Volante we will have more of the cubes the live coverage of AWS re-invent coming up in just a little bit [Music]

>> Narrator: From Chicago, it's theCUBE. Covering Veritas Vision Solution Day, 2018. Brought to you by Veritas. >> Welcome back to Chicago everybody, you're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante, we're here covering the Veritas Vision Solution Day. Veritas last year had a big tent event thay thousands and thousands of customers. They decided this year to go out to the customers. Like us, we go out to the events, we extract the signal from the noise. Jeff Kroth is here, he's the manager of data management and analytics at Softchoice, which is a Veritas partner. Welcome to theCube, thanks for coming on, Jeff. >> Thanks for having me. >> So tell me more about Softchoice, what's your sort of niche and differentiation in the market? >> Sure, so Softchoice is about a two billion dollar North American IT Solution proivder, we're actually the number three Global Midmarket Managed Service provider. We provide the breadth and coverage across a variety of vendors, helping our customers modernize their IT infrastructure. >> So Midmarket is unique, you know, it's not big enough to have like thousands of people do it, data protection for example, they're Generalists, typically, IT Generalists, they're not small, not like the CEO doing the back up. So talk a little bit about the unique aspects of Midmarket from your perspective. >> Well I think some of the things that we bring to the bare Midmarker is helping customers who don't have that deep IT staff with our technology mentorship, with our skills transfer that we provide our customers, we have a managed service that we provide which really helps our customers do more with what they have. >> So data protection is one of the hottest topics going here at VMworld in August, and for the last two years it's been probably one of the hottest topics. That along with Cloud and obviously the AWS partnership with VMWare. Why is data protection so hot right now? What are the factors? >> I would say data protection and data management is hot. It actually comes back to the underlying data behind it, they say, Gardener says data is the new gold and the new natural resource. Well if you don't have your data protected, available, and modernized, you can't leverage things like data analytics to get the most out of your data. Our customers, we see, customers use data as a competitive advantage. Go back look at Blockbuster and Netflix, they weren't able to take advantage of their data and understand that, so really to me data protection is the foundation and building block to grow into an analytics environment where you're really taking advantage of the underlying data for that competitive advantage. >> And I want to do a little tangent here, cause when you hear things like, "data is the new oil, its the new gold," it's actually, in our view, even more valuable, and here's why. Oil, you can put a quart of oil in your car or in your house, but you can't put the same quart in both. Data, using the Netflix example, you can use the same data in a variety of different ways. So in some regards, it's even more valuable. So I guess the bottom line here is digital transformation, which is real, is all about how you use data and that has direct implications on how you protect data, doesn't it? >> It does. >> And so, the other thing is Cloud. You hear a lot of talk about Cloud, and Multicloud, and we're moving into this world of more distributed data. What kind of challenges does that present for customers? >> I mean we are a big Microsoft partner and have a big partnership with Azure, you know, helping our customers on that Cloud journey I think is an important part. One of the things and one of the trends that we're finding is ensuring that you're monerizing your current data platform as you do that data migration to the Cloud. One of the things we see is customers really struggle with cost containment as they make that Cloud migration. So being able to understand what the data is and ensuring that you're only moving the right amount of data and the right workloads to the Cloud to keep costs down, I think is one of the important things, one of the things we're helping our customers, making sure they're getting real value out of the Cloud and doing that cost containment. >> We heard this morning Joe T was talking about some Cloud repatriation and you definitely are seeing it he gave an example of a large company in Dubai who said, "we're going all in on Cloud," and they went all in on Cloud and said, "wow, this is really expensive." Make sense, right? Renting is often times more expensive than owning. So I look at that as, you know, those that have had to repatriate, a lot of that is poor planning so how do you help your customers plan which work loads should be in the Cloud and follow those laws of economics, and physics, and governance, you know the law of the land, how do you help them? >> So it's really a couple of things, we have a couple of assessments that we use to help customers understand their existing workloads and what makes sense to move to the Cloud and what makes sense to keep on premise. So that's an assessment that Softchoice offers. The other thing is aligning to Veritas's 360 data management strategy is really getting a deeper understanding of what that data is that you have so you're aligning the right costs associated with that data to decide what you move to the Cloud and what stays on prem and I think that's a big thing, it's really understanding what that data is and aligning it to what needs to be moved. >> We talked to senior leaders in IT and business, they tell us that if you got to move to the Cloud you really want to change the operating model, that's where you're going to get the biggest bang for the buck. What does that mean in terms of data protection? If you're going to go digital, go Cloud, change your operating model, that's going to have implications on data protection, isn't it? And what do you see as the-- >> It is, and what I think we're seeing in Softchoice as a whole, you know we are a big proponent of the Cloud, what I think we see that, you really don't think that customers are going to go fully Cloud. It's really taking that hybrid approach and aligning what applications make sense to go to the Cloud, what applications make sense to stay on prem. So really having that full view of your environment so you can make intelligent decisions on what to move to the Cloud and what to keep on prem, aligning to the usage of that data. >> Now what about your partnership with Veritas? You kind of exclusive Veritas, you work with other back up vendors? Maybe talk about that a little bit and then what do you see as Veritas's strengths and what's on their to-do list? >> Yeah, so we're a Veritas Gold Partner both in the US and in Canada. We're not an exclusive to Veritas, we like to take a very agnostic approach and really help customers understand what their environment looks like and what makes sense for them. Veritas is a key player as part of our data management strategy and going down the road of our analytics strategy, helping customers really understand the value of their data. You can't get into the analytics world unless your data is in the right place so, again we like to take an agnostic approach but Veritas does align very well from a data management strategy for Softchoice. >> Why, why is that? Is that their stack, they've just been around longer, they focus a lot on governance, and I heard things like categorization, throwing out Federal rules of civil procedure today, that's a long history, so why, what's so special? >> I would say it's the overall breadth of their portfolio, it's helping customers back up to Cloud, back up for the Cloud, it's helping customers do things like DR and replication. It's really getting that full 360 view, you know one of the things we're big on is things like Infomap and Data Insights and really helping customers really understand what the underlying data is, associating the cost with that, so as they move workloads to the Cloud they get a full understanding of what they're moving so they're just not blindly moving things to the Cloud, helping keep costs down. Again, when customers, like as in the example we saw earlier today, a lot of customers think that Cloud is a logical strategy for them but over time they see that it increases cost. So it's really about aligning the right sizing of your environment, moving the right applications, the right data to the Cloud and using that as part of your overall strategy. We really see customers really taking a hybrid approach, it's not ever going to be fully public Cloud, it's not going to be fully private Cloud, it's going to be a combination. >> So we're going to ask you about the competitive landscape cause you are sort of Switzerland here, even though got an affinity, it seems, to Veritas, but you've seen a lot of VC money move into the space, you're seeing a lot of specialists emerge, you've seen some startups come after the Incumbents like Veritas, certainly you know Commvault's another, IBM's another, of course DELL EMC, add those guys up they probably have three quarters on the market place so of course the startups are going to come after them. And they're got shiny new toys and probably developing in Cloud Native and probably talking all the right language. But how do you squint through the hype from the marketing side and sort of help customers figure out how they're going to have the greatest business impact? >> I mean I think that's a good point. I think we're seeing a lot of small niche players that are born in the Cloud or have this shiny new marketing collatoral that they're going to market with and I think what's important for us is making sure our customers understand a full road map on what they're trying to do. So, we do see a lot of upstarts that are going after some of the Veritas, the IBM, the DELL EMC businesses, the world. But it's really making sure you're not taking a point solution and trying to go forward with that, it's understanding Portfolio, like Veritas's that has that depth and breadth and really has that history and background. You know, Veritas has been doing this forever and they really know their stuff. >> Yeah, so we've stressed that platforms are important to pay attention to, you know an API based platform is going to beat a product every time and have some legs. It might be it might have other implications in terms of complexities, but it can drive your business forward as opposed to your point, being a point product. And I'm curious as to your thoughts, particularly as it relates to analytics, which is in your title. For years people have looked at back up as just insurance, people that are trying to get more out of it. But how are people using the corpus of back up data and analytics use cases, why the affinity between data protection and analytics? >> I think data protection and data management are kind of clumped into one category. If you don't have a modernized IT infrastructure and you don't have a good data management strategy, it's impossible, you know poor data in, poor data out. You can't make intelligent analytics decisions or have that data for your analytics team if the information isn't there and accessible and good data. So it's really having a very keen data management strategy enabling your analytics users to have the right data to make the right decisions, cause if you don't have the right data you can't make the right decisions, and no analytics tool can go in and make informed decisions based off bad data. So data management is definitely part of the overall analytic strategy cause it's really the first step. >> And why the, in the back up corpuses, because you've got visibility on that data and it's the logical-- >> Sure. >> The logical one place, even if it's virtual, to actually be able to do those analytics, right? >> Exactly. >> Okay, and then I'll give you the last word. Thing's that your learning here today at the Vision Event, customers obviously Chicago, big customer center, you're based in Atlanta another big customer center. We were just in New York a few weeks ago meeting some pretty senior level folks. What are you learning here, what's the conversation like? >> I think the one key thing that I've taken out is that really customers aren't going full Cloud. It's you know, I think I saw a stat and 92% of customers are taking a hybrid approach and leveraging a really full data management policy to be able to handle on prem, to be able to handle private Cloud, public Cloud, and the combination. Really having that tool set to give you visualizations across an entire hybrid IT infrastructure I think it important. And that's really one of the key takeaways. >> We would agree, we've talked for quite some time now, years actually how organizations can't just shove data into the Cloud, they can't just put their business up into the public Cloud, rather they need to move the Cloud operating model to their business. it's very clearly, that's the trend, you're seeing so many signs of that. AWS and VMware partnering up. You certainly saw Google do that and this summer with Istio on prem, Microsoft obviously with Azure Stack, huge presence in hybrid Cloud. So those predictions are coming true. Jeff thanks very much for coming to theCUBE, great to see you. >> Yep, thanks for having me. >> Oh you're very welcome. Alright, keep it right there everybody, this is Dave Vellante, we'll be back from Veritas Vision Day in Chicago at the Palmer House Hotel, you're watching theCube. (soft techno music)

- [Announcer] Live, from New York, it's theCUBE. Covering theCUBE New York City 2018. Brought to you by SiliconANGLE Media, and its ecosystem partners. - Hello everyone, welcome back to CUBE NYC. This is a CUBE special presentation of something that we've done now for the past couple of years. IBM has sponsored an influencer panel on some of the hottest topics in the industry, and of course, there's no hotter topic right now than AI. So, we've got nine of the top influencers in the AI space, and we're in Hell's Kitchen, and it's going to get hot in here. (laughing) And these guys, we're going to cover the gamut. So, first of all, folks, thanks so much for joining us today, really, as John said earlier, we love the collaboration with you all, and we'll definitely see you on social after the fact. I'm Dave Vellante, with my cohost for this session, Peter Burris, and again, thank you to IBM for sponsoring this and organizing this. IBM has a big event down here, in conjunction with Strata, called Change the Game, Winning with AI. We run theCUBE NYC, we've been here all week. So, here's the format. I'm going to kick it off, and then we'll see where it goes. So, I'm going to introduce each of the panelists, and then ask you guys to answer a question, I'm sorry, first, tell us a little bit about yourself, briefly, and then answer one of the following questions. Two big themes that have come up this week. One has been, because this is our ninth year covering what used to be Hadoop World, which kind of morphed into big data. Question is, AI, big data, same wine, new bottle? Or is it really substantive, and driving business value? So, that's one question to ponder. The other one is, you've heard the term, the phrase, data is the new oil. Is data really the new oil? Wonder what you think about that? Okay, so, Chris Penn, let's start with you. Chris is cofounder of Trust Insight, long time CUBE alum, and friend. Thanks for coming on. Tell us a little bit about yourself, and then pick one of those questions. - Sure, we're a data science consulting firm. We're an IBM business partner. When it comes to "data is the new oil," I love that expression because it's completely accurate. Crude oil is useless, you have to extract it out of the ground, refine it, and then bring it to distribution. Data is the same way, where you have to have developers and data architects get the data out. You need data scientists and tools, like Watson Studio, to refine it, and then you need to put it into production, and that's where marketing technologists, technologists, business analytics folks, and tools like Watson Machine Learning help bring the data and make it useful. - Okay, great, thank you. Tony Flath is a tech and media consultant, focus on cloud and cyber security, welcome. - Thank you. - Tell us a little bit about yourself and your thoughts on one of those questions. - Sure thing, well, thanks so much for having us on this show, really appreciate it. My background is in cloud, cyber security, and certainly in emerging tech with artificial intelligence. Certainly touched it from a cyber security play, how you can use machine learning, machine control, for better controlling security across the gamut. But I'll touch on your question about wine, is it a new bottle, new wine? Where does this come from, from artificial intelligence? And I really see it as a whole new wine that is coming along. When you look at emerging technology, and you look at all the deep learning that's happening, it's going just beyond being able to machine learn and know what's happening, it's making some meaning to that data. And things are being done with that data, from robotics, from automation, from all kinds of different things, where we're at a point in society where data, our technology is getting beyond us. Prior to this, it's always been command and control. You control data from a keyboard. Well, this is passing us. So, my passion and perspective on this is, the humanization of it, of IT. How do you ensure that people are in that process, right? - Excellent, and we're going to come back and talk about that. - Thanks so much. - Carla Gentry, @DataNerd? Great to see you live, as opposed to just in the ether on Twitter. Data scientist, and owner of Analytical Solution. Welcome, your thoughts? - Thank you for having us. Mine is, is data the new oil? And I'd like to rephrase that is, data equals human lives. So, with all the other artificial intelligence and everything that's going on, and all the algorithms and models that's being created, we have to think about things being biased, being fair, and understand that this data has impacts on people's lives. - Great. Steve Ardire, my paisan. - Paisan. - AI startup adviser, welcome, thanks for coming to theCUBE. - Thanks Dave. So, uh, my first career was geology, and I view AI as the new oil, but data is the new oil, but AI is the refinery. I've used that many times before. In fact, really, I've moved from just AI to augmented intelligence. So, augmented intelligence is really the way forward. This was a presentation I gave at IBM Think last spring, has almost 100,000 impressions right now, and the fundamental reason why is machines can attend to vastly more information than humans, but you still need humans in the loop, and we can talk about what they're bringing in terms of common sense reasoning, because big data does the who, what, when, and where, but not the why, and why is really the Holy Grail for causal analysis and reasoning. - Excellent, Bob Hayes, Business Over Broadway, welcome, great to see you again. - Thanks for having me. So, my background is in psychology, industrial psychology, and I'm interested in things like customer experience, data science, machine learning, so forth. And I'll answer the question around big data versus AI. And I think there's other terms we could talk about, big data, data science, machine learning, AI. And to me, it's kind of all the same. It's always been about analytics, and getting value from your data, big, small, what have you. And there's subtle differences among those terms. Machine learning is just about making a prediction, and knowing if things are classified correctly. Data science is more about understanding why things work, and understanding maybe the ethics behind it, what variables are predicting that outcome. But still, it's all the same thing, it's all about using data in a way that we can get value from that, as a society, in residences. - Excellent, thank you. Theo Lau, founder of Unconventional Ventures. What's your story? - Yeah, so, my background is driving technology innovation. So, together with my partner, what our work does is we work with organizations to try to help them leverage technology to drive systematic financial wellness. We connect founders, startup founders, with funders, we help them get money in the ecosystem. We also work with them to look at, how do we leverage emerging technology to do something good for the society. So, very much on point to what Bob was saying about. So when I look at AI, it is not new, right, it's been around for quite a while. But what's different is the amount of technological power that we have allow us to do so much more than what we were able to do before. And so, what my mantra is, great ideas can come from anywhere in the society, but it's our job to be able to leverage technology to shine a spotlight on people who can use this to do something different, to help seniors in our country to do better in their financial planning. - Okay, so, in your mind, it's not just a same wine, new bottle, it's more substantive than that. - [Theo] It's more substantive, it's a much better bottle. - Karen Lopez, senior project manager for Architect InfoAdvisors, welcome. - Thank you. So, I'm DataChick on twitter, and so that kind of tells my focus is that I'm here, I also call myself a data evangelist, and that means I'm there at organizations helping stand up for the data, because to me, that's the proxy for standing up for the people, and the places and the events that that data describes. That means I have a focus on security, data privacy and protection as well. And I'm going to kind of combine your two questions about whether data is the new wine bottle, I think is the combination. Oh, see, now I'm talking about alcohol. (laughing) But anyway, you know, all analogies are imperfect, so whether we say it's the new wine, or, you know, same wine, or whether it's oil, is that the analogy's good for both of them, but unlike oil, the amount of data's just growing like crazy, and the oil, we know at some point, I kind of doubt that we're going to hit peak data where we have not enough data, like we're going to do with oil. But that says to me that, how did we get here with big data, with machine learning and AI? And from my point of view, as someone who's been focused on data for 35 years, we have hit this perfect storm of open source technologies, cloud architectures and cloud services, data innovation, that if we didn't have those, we wouldn't be talking about large machine learning and deep learning-type things. So, because we have all these things coming together at the same time, we're now at explosions of data, which means we also have to protect them, and protect the people from doing harm with data, we need to do data for good things, and all of that. - Great, definite differences, we're not running out of data, data's like the terrible tribbles. (laughing) - Yes, but it's very cuddly, data is. - Yeah, cuddly data. Mark Lynd, founder of Relevant Track? - That's right. - I like the name. What's your story? - Well, thank you, and it actually plays into what my interest is. It's mainly around AI in enterprise operations and cyber security. You know, these teams that are in enterprise operations both, it can be sales, marketing, all the way through the organization, as well as cyber security, they're often under-sourced. And they need, what Steve pointed out, they need augmented intelligence, they need to take AI, the big data, all the information they have, and make use of that in a way where they're able to, even though they're under-sourced, make some use and some value for the organization, you know, make better use of the resources they have to grow and support the strategic goals of the organization. And oftentimes, when you get to budgeting, it doesn't really align, you know, you're short people, you're short time, but the data continues to grow, as Karen pointed out. So, when you take those together, using AI to augment, provided augmented intelligence, to help them get through that data, make real tangible decisions based on information versus just raw data, especially around cyber security, which is a big hit right now, is really a great place to be, and there's a lot of stuff going on, and a lot of exciting stuff in that area. - Great, thank you. Kevin L. Jackson, author and founder of GovCloud. GovCloud, that's big. - Yeah, GovCloud Network. Thank you very much for having me on the show. Up and working on cloud computing, initially in the federal government, with the intelligence community, as they adopted cloud computing for a lot of the nation's major missions. And what has happened is now I'm working a lot with commercial organizations and with the security of that data. And I'm going to sort of, on your questions, piggyback on Karen. There was a time when you would get a couple of bottles of wine, and they would come in, and you would savor that wine, and sip it, and it would take a few days to get through it, and you would enjoy it. The problem now is that you don't get a couple of bottles of wine into your house, you get two or three tankers of data. So, it's not that it's a new wine, you're just getting a lot of it. And the infrastructures that you need, before you could have a couple of computers, and a couple of people, now you need cloud, you need automated infrastructures, you need huge capabilities, and artificial intelligence and AI, it's what we can use as the tool on top of these huge infrastructures to drink that, you know. - Fire hose of wine. - Fire hose of wine. (laughs) - Everybody's having a good time. - Everybody's having a great time. (laughs) - Yeah, things are booming right now. Excellent, well, thank you all for those intros. Peter, I want to ask you a question. So, I heard there's some similarities and some definite differences with regard to data being the new oil. You have a perspective on this, and I wonder if you could inject it into the conversation. - Sure, so, the perspective that we take in a lot of conversations, a lot of folks here in theCUBE, what we've learned, and I'll kind of answer both questions a little bit. First off, on the question of data as the new oil, we definitely think that data is the new asset that business is going to be built on, in fact, our perspective is that there really is a difference between business and digital business, and that difference is data as an asset. And if you want to understand data transformation, you understand the degree to which businesses reinstitutionalizing work, reorganizing its people, reestablishing its mission around what you can do with data as an asset. The difference between data and oil is that oil still follows the economics of scarcity. Data is one of those things, you can copy it, you can share it, you can easily corrupt it, you can mess it up, you can do all kinds of awful things with it if you're not careful. And it's that core fundamental proposition that as an asset, when we think about cyber security, we think, in many respects, that is the approach to how we can go about privatizing data so that we can predict who's actually going to be able to appropriate returns on it. So, it's a good analogy, but as you said, it's not entirely perfect, but it's not perfect in a really fundamental way. It's not following the laws of scarcity, and that has an enormous effect. - In other words, I could put oil in my car, or I could put oil in my house, but I can't put the same oil in both. - Can't put it in both places. And now, the issue of the wine, I think it's, we think that it is, in fact, it is a new wine, and very simple abstraction, or generalization we come up with is the issue of agency. That analytics has historically not taken on agency, it hasn't acted on behalf of the brand. AI is going to act on behalf of the brand. Now, you're going to need both of them, you can't separate them. - A lot of implications there in terms of bias. - Absolutely. - In terms of privacy. You have a thought, here, Chris? - Well, the scarcity is our compute power, and our ability for us to process it. I mean, it's the same as oil, there's a ton of oil under the ground, right, we can't get to it as efficiently, or without severe environmental consequences to use it. Yeah, when you use it, it's transformed, but our scarcity is compute power, and our ability to use it intelligently. - Or even when you find it. I have data, I can apply it to six different applications, I have oil, I can apply it to one, and that's going to matter in how we think about work. - But one thing I'd like to add, sort of, you're talking about data as an asset. The issue we're having right now is we're trying to learn how to manage that asset. Artificial intelligence is a way of managing that asset, and that's important if you're going to use and leverage big data. - Yeah, but see, everybody's talking about the quantity, the quantity, it's not always the quantity. You know, we can have just oodles and oodles of data, but if it's not clean data, if it's not alphanumeric data, which is what's needed for machine learning. So, having lots of data is great, but you have to think about the signal versus the noise. So, sometimes you get so much data, you're looking at over-fitting, sometimes you get so much data, you're looking at biases within the data. So, it's not the amount of data, it's the, now that we have all of this data, making sure that we look at relevant data, to make sure we look at clean data. - One more thought, and we have a lot to cover, I want to get inside your big brain. - I was just thinking about it from a cyber security perspective, one of my customers, they were looking at the data that just comes from the perimeter, your firewalls, routers, all of that, and then not even looking internally, just the perimeter alone, and the amount of data being pulled off of those. And then trying to correlate that data so it makes some type of business sense, or they can determine if there's incidents that may happen, and take a predictive action, or threats that might be there because they haven't taken a certain action prior, it's overwhelming to them. So, having AI now, to be able to go through the logs to look at, and there's so many different types of data that come to those logs, but being able to pull that information, as well as looking at end points, and all that, and people's houses, which are an extension of the network oftentimes, it's an amazing amount of data, and they're only looking at a small portion today because they know, there's not enough resources, there's not enough trained people to do all that work. So, AI is doing a wonderful way of doing that. And some of the tools now are starting to mature and be sophisticated enough where they provide that augmented intelligence that Steve talked about earlier. - So, it's complicated. There's infrastructure, there's security, there's a lot of software, there's skills, and on and on. At IBM Think this year, Ginni Rometty talked about, there were a couple of themes, one was augmented intelligence, that was something that was clear. She also talked a lot about privacy, and you own your data, etc. One of the things that struck me was her discussion about incumbent disruptors. So, if you look at the top five companies, roughly, Facebook with fake news has dropped down a little bit, but top five companies in terms of market cap in the US. They're data companies, all right. Apple just hit a trillion, Amazon, Google, etc. How do those incumbents close the gap? Is that concept of incumbent disruptors actually something that is being put into practice? I mean, you guys work with a lot of practitioners. How are they going to close that gap with the data haves, meaning data at their core of their business, versus the data have-nots, it's not that they don't have a lot of data, but it's in silos, it's hard to get to? - Yeah, I got one more thing, so, you know, these companies, and whoever's going to be big next is, you have a digital persona, whether you want it or not. So, if you live in a farm out in the middle of Oklahoma, you still have a digital persona, people are collecting data on you, they're putting profiles of you, and the big companies know about you, and people that first interact with you, they're going to know that you have this digital persona. Personal AI, when AI from these companies could be used simply and easily, from a personal deal, to fill in those gaps, and to have a digital persona that supports your family, your growth, both personal and professional growth, and those type of things, there's a lot of applications for AI on a personal, enterprise, even small business, that have not been done yet, but the data is being collected now. So, you talk about the oil, the oil is being built right now, lots, and lots, and lots of it. It's the applications to use that, and turn that into something personally, professionally, educationally, powerful, that's what's missing. But it's coming. - Thank you, so, I'll add to that, and in answer to your question you raised. So, one example we always used in banking is, if you look at the big banks, right, and then you look at from a consumer perspective, and there's a lot of talk about Amazon being a bank. But the thing is, Amazon doesn't need to be a bank, they provide banking services, from a consumer perspective they don't really care if you're a bank or you're not a bank, but what's different between Amazon and some of the banks is that Amazon, like you say, has a lot of data, and they know how to make use of the data to offer something as relevant that consumers want. Whereas banks, they have a lot of data, but they're all silos, right. So, it's not just a matter of whether or not you have the data, it's also, can you actually access it and make something useful out of it so that you can create something that consumers want? Because otherwise, you're just a pipe. - Totally agree, like, when you look at it from a perspective of, there's a lot of terms out there, digital transformation is thrown out so much, right, and go to cloud, and you migrate to cloud, and you're going to take everything over, but really, when you look at it, and you both touched on it, it's the economics. You have to look at the data from an economics perspective, and how do you make some kind of way to take this data meaningful to your customers, that's going to work effectively for them, that they're going to drive? So, when you look at the big, big cloud providers, I think the push in things that's going to happen in the next few years is there's just going to be a bigger migration to public cloud. So then, between those, they have to differentiate themselves. Obvious is artificial intelligence, in a way that makes it easy to aggregate data from across platforms, to aggregate data from multi-cloud, effectively. To use that data in a meaningful way that's going to drive, not only better decisions for your business, and better outcomes, but drives our opportunities for customers, drives opportunities for employees and how they work. We're at a really interesting point in technology where we get to tell technology what to do. It's going beyond us, it's no longer what we're telling it to do, it's going to go beyond us. So, how we effectively manage that is going to be where we see that data flow, and those big five or big four, really take that to the next level. - Now, one of the things that Ginni Rometty said was, I forget the exact step, but it was like, 80% of the data, is not searchable. Kind of implying that it's sitting somewhere behind a firewall, presumably on somebody's premises. So, it was kind of interesting. You're talking about, certainly, a lot of momentum for public cloud, but at the same time, a lot of data is going to stay where it is. - Yeah, we're assuming that a lot of this data is just sitting there, available and ready, and we look at the desperate, or disparate kind of database situation, where you have 29 databases, and two of them have unique quantifiers that tie together, and the rest of them don't. So, there's nothing that you can do with that data. So, artificial intelligence is just that, it's artificial intelligence, so, they know, that's machine learning, that's natural language, that's classification, there's a lot of different parts of that that are moving, but we also have to have IT, good data infrastructure, master data management, compliance, there's so many moving parts to this, that it's not just about the data anymore. - I want to ask Steve to chime in here, go ahead. - Yeah, so, we also have to change the mentality that it's not just enterprise data. There's data on the web, the biggest thing is Internet of Things, the amount of sensor data will make the current data look like chump change. So, data is moving faster, okay. And this is where the sophistication of machine learning needs to kick in, going from just mostly supervised-learning today, to unsupervised learning. And in order to really get into, as I said, big data, and credible AI does the who, what, where, when, and how, but not the why. And this is really the Holy Grail to crack, and it's actually under a new moniker, it's called explainable AI, because it moves beyond just correlation into root cause analysis. Once we have that, then you have the means to be able to tap into augmented intelligence, where humans are working with the machines. - Karen, please. - Yeah, so, one of the things, like what Carla was saying, and what a lot of us had said, I like to think of the advent of ML technologies and AI are going to help me as a data architect to love my data better, right? So, that includes protecting it, but also, when you say that 80% of the data is unsearchable, it's not just an access problem, it's that no one knows what it was, what the sovereignty was, what the metadata was, what the quality was, or why there's huge anomalies in it. So, my favorite story about this is, in the 1980s, about, I forget the exact number, but like, 8 million children disappeared out of the US in April, at April 15th. And that was when the IRS enacted a rule that, in order to have a dependent, a deduction for a dependent on your tax returns, they had to have a valid social security number, and people who had accidentally miscounted their children and over-claimed them, (laughter) over the years them, stopped doing that. Well, some days it does feel like you have eight children running around. (laughter) - Agreed. - When, when that rule came about, literally, and they're not all children, because they're dependents, but literally millions of children disappeared off the face of the earth in April, but if you were doing analytics, or AI and ML, and you don't know that this anomaly happened, I can imagine in a hundred years, someone is saying some catastrophic event happened in April, 1983. (laughter) And what caused that, was it healthcare? Was it a meteor? Was it the clown attacking them? - That's where I was going. - Right. So, those are really important things that I want to use AI and ML to help me, not only document and capture that stuff, but to provide that information to the people, the data scientists and the analysts that are using the data. - Great story, thank you. Bob, you got a thought? You got the mic, go, jump in here. - Well, yeah, I do have a thought, actually. I was talking about, what Karen was talking about. I think it's really important that, not only that we understand AI, and machine learning, and data science, but that the regular folks and companies understand that, at the basic level. Because those are the people who will ask the questions, or who know what questions to ask of the data. And if they don't have the tools, and the knowledge of how to get access to that data, or even how to pose a question, then that data is going to be less valuable, I think, to companies. And the more that everybody knows about data, even people in congress. Remember when Zuckerberg talked about? (laughter) - That was scary. - How do you make money? It's like, we all know this. But, we need to educate the masses on just basic data analytics. - We could have an hour-long panel on that. - Yeah, absolutely. - Peter, you and I were talking about, we had a couple of questions, sort of, how far can we take artificial intelligence? How far should we? You know, so that brings in to the conversation of ethics, and bias, why don't you pick it up? - Yeah, so, one of the crucial things that we all are implying is that, at some point in time, AI is going to become a feature of the operations of our homes, our businesses. And as these technologies get more powerful, and they diffuse, and know about how to use them, diffuses more broadly, and you put more options into the hands of more people, the question slowly starts to turn from can we do it, to should we do it? And, one of the issues that I introduce is that I think the difference between big data and AI, specifically, is this notion of agency. The AI will act on behalf of, perhaps you, or it will act on behalf of your business. And that conversation is not being had, today. It's being had in arguments between Elon Musk and Mark Zuckerberg, which pretty quickly get pretty boring. (laughing) At the end of the day, the real question is, should this machine, whether in concert with others, or not, be acting on behalf of me, on behalf of my business, or, and when I say on behalf of me, I'm also talking about privacy. Because Facebook is acting on behalf of me, it's not just what's going on in my home. So, the question of, can it be done? A lot of things can be done, and an increasing number of things will be able to be done. We got to start having a conversation about should it be done? - So, humans exhibit tribal behavior, they exhibit bias. Their machine's going to pick that up, go ahead, please. - Yeah, one thing that sort of tag onto agency of artificial intelligence. Every industry, every business is now about identifying information and data sources, and their appropriate sinks, and learning how to draw value out of connecting the sources with the sinks. Artificial intelligence enables you to identify those sources and sinks, and when it gets agency, it will be able to make decisions on your behalf about what data is good, what data means, and who it should be. - What actions are good. - Well, what actions are good. - And what data was used to make those actions. - Absolutely. - And was that the right data, and is there bias of data? And all the way down, all the turtles down. - So, all this, the data pedigree will be driven by the agency of artificial intelligence, and this is a big issue. - It's really fundamental to understand and educate people on, there are four fundamental types of bias, so there's, in machine learning, there's intentional bias, "Hey, we're going to make "the algorithm generate a certain outcome "regardless of what the data says." There's the source of the data itself, historical data that's trained on the models built on flawed data, the model will behave in a flawed way. There's target source, which is, for example, we know that if you pull data from a certain social network, that network itself has an inherent bias. No matter how representative you try to make the data, it's still going to have flaws in it. Or, if you pull healthcare data about, for example, African-Americans from the US healthcare system, because of societal biases, that data will always be flawed. And then there's tool bias, there's limitations to what the tools can do, and so we will intentionally exclude some kinds of data, or not use it because we don't know how to, our tools are not able to, and if we don't teach people what those biases are, they won't know to look for them, and I know. - Yeah, it's like, one of the things that we were talking about before, I mean, artificial intelligence is not going to just create itself, it's lines of code, it's input, and it spits out output. So, if it learns from these learning sets, we don't want AI to become another buzzword. We don't want everybody to be an "AR guru" that has no idea what AI is. It takes months, and months, and months for these machines to learn. These learning sets are so very important, because that input is how this machine, think of it as your child, and that's basically the way artificial intelligence is learning, like your child. You're feeding it these learning sets, and then eventually it will make its own decisions. So, we know from some of us having children that you teach them the best that you can, but then later on, when they're doing their own thing, they're really, it's like a little myna bird, they've heard everything that you've said. (laughing) Not only the things that you said to them directly, but the things that you said indirectly. - Well, there are some very good AI researchers that might disagree with that metaphor, exactly. (laughing) But, having said that, what I think is very interesting about this conversation is that this notion of bias, one of the things that fascinates me about where AI goes, are we going to find a situation where tribalism more deeply infects business? Because we know that human beings do not seek out the best information, they seek out information that reinforces their beliefs. And that happens in business today. My line of business versus your line of business, engineering versus sales, that happens today, but it happens at a planning level, and when we start talking about AI, we have to put the appropriate dampers, understand the biases, so that we don't end up with deep tribalism inside of business. Because AI could have the deleterious effect that it actually starts ripping apart organizations. - Well, input is data, and then the output is, could be a lot of things. - Could be a lot of things. - And that's where I said data equals human lives. So that we look at the case in New York where the penal system was using this artificial intelligence to make choices on people that were released from prison, and they saw that that was a miserable failure, because that people that release actually re-offended, some committed murder and other things. So, I mean, it's, it's more than what anybody really thinks. It's not just, oh, well, we'll just train the machines, and a couple of weeks later they're good, we never have to touch them again. These things have to be continuously tweaked. So, just because you built an algorithm or a model doesn't mean you're done. You got to go back later, and continue to tweak these models. - Mark, you got the mic. - Yeah, no, I think one thing we've talked a lot about the data that's collected, but what about the data that's not collected? Incomplete profiles, incomplete datasets, that's a form of bias, and sometimes that's the worst. Because they'll fill that in, right, and then you can get some bias, but there's also a real issue for that around cyber security. Logs are not always complete, things are not always done, and when things are doing that, people make assumptions based on what they've collected, not what they didn't collect. So, when they're looking at this, and they're using the AI on it, that's only on the data collected, not on that that wasn't collected. So, if something is down for a little while, and no data's collected off that, the assumption is, well, it was down, or it was impacted, or there was a breach, or whatever, it could be any of those. So, you got to, there's still this human need, there's still the need for humans to look at the data and realize that there is the bias in there, there is, we're just looking at what data was collected, and you're going to have to make your own thoughts around that, and assumptions on how to actually use that data before you go make those decisions that can impact lots of people, at a human level, enterprise's profitability, things like that. And too often, people think of AI, when it comes out of there, that's the word. Well, it's not the word. - Can I ask a question about this? - Please. - Does that mean that we shouldn't act? - It does not. - Okay. - So, where's the fine line? - Yeah, I think. - Going back to this notion of can we do it, or should we do it? Should we act? - Yeah, I think you should do it, but you should use it for what it is. It's augmenting, it's helping you, assisting you to make a valued or good decision. And hopefully it's a better decision than you would've made without it. - I think it's great, I think also, your answer's right too, that you have to iterate faster, and faster, and faster, and discover sources of information, or sources of data that you're not currently using, and, that's why this thing starts getting really important. - I think you touch on a really good point about, should you or shouldn't you? You look at Google, and you look at the data that they've been using, and some of that out there, from a digital twin perspective, is not being approved, or not authorized, and even once they've made changes, it's still floating around out there. Where do you know where it is? So, there's this dilemma of, how do you have a digital twin that you want to have, and is going to work for you, and is going to do things for you to make your life easier, to do these things, mundane tasks, whatever? But how do you also control it to do things you don't want it to do? - Ad-based business models are inherently evil. (laughing) - Well, there's incentives to appropriate our data, and so, are things like blockchain potentially going to give users the ability to control their data? We'll see. - No, I, I'm sorry, but that's actually a really important point. The idea of consensus algorithms, whether it's blockchain or not, blockchain includes games, and something along those lines, whether it's Byzantine fault tolerance, or whether it's Paxos, consensus-based algorithms are going to be really, really important. Parts of this conversation, because the data's going to be more distributed, and you're going to have more elements participating in it. And so, something that allows, especially in the machine-to-machine world, which is a lot of what we're talking about right here, you may not have blockchain, because there's no need for a sense of incentive, which is what blockchain can help provide. - And there's no middleman. - And, well, all right, but there's really, the thing that makes blockchain so powerful is it liberates new classes of applications. But for a lot of the stuff that we're talking about, you can use a very powerful consensus algorithm without having a game side, and do some really amazing things at scale. - So, looking at blockchain, that's a great thing to bring up, right. I think what's inherently wrong with the way we do things today, and the whole overall design of technology, whether it be on-prem, or off-prem, is both the lock and key is behind the same wall. Whether that wall is in a cloud, or behind a firewall. So, really, when there is an audit, or when there is a forensics, it always comes down to a sysadmin, or something else, and the system administrator will have the finger pointed at them, because it all resides, you can edit it, you can augment it, or you can do things with it that you can't really determine. Now, take, as an example, blockchain, where you've got really the source of truth. Now you can take and have the lock in one place, and the key in another place. So that's certainly going to be interesting to see how that unfolds. - So, one of the things, it's good that, we've hit a lot of buzzwords, right now, right? (laughing) AI, and ML, block. - Bingo. - We got the blockchain bingo, yeah, yeah. So, one of the things is, you also brought up, I mean, ethics and everything, and one of the things that I've noticed over the last year or so is that, as I attend briefings or demos, everyone is now claiming that their product is AI or ML-enabled, or blockchain-enabled. And when you try to get answers to the questions, what you really find out is that some things are being pushed as, because they have if-then statements somewhere in their code, and therefore that's artificial intelligence or machine learning. - [Peter] At least it's not "go-to." (laughing) - Yeah, you're that experienced as well. (laughing) So, I mean, this is part of the thing you try to do as a practitioner, as an analyst, as an influencer, is trying to, you know, the hype of it all. And recently, I attended one where they said they use blockchain, and I couldn't figure it out, and it turns out they use GUIDs to identify things, and that's not blockchain, it's an identifier. (laughing) So, one of the ethics things that I think we, as an enterprise community, have to deal with, is the over-promising of AI, and ML, and deep learning, and recognition. It's not, I don't really consider it visual recognition services if they just look for red pixels. I mean, that's not quite the same thing. Yet, this is also making things much harder for your average CIO, or worse, CFO, to understand whether they're getting any value from these technologies. - Old bottle. - Old bottle, right. - And I wonder if the data companies, like that you talked about, or the top five, I'm more concerned about their nearly, or actual $1 trillion valuations having an impact on their ability of other companies to disrupt or enter into the field more so than their data technologies. Again, we're coming to another perfect storm of the companies that have data as their asset, even though it's still not on their financial statements, which is another indicator whether it's really an asset, is that, do we need to think about the terms of AI, about whose hands it's in, and who's, like, once one large trillion-dollar company decides that you are not a profitable company, how many other companies are going to buy that data and make that decision about you? - Well, and for the first time in business history, I think, this is true, we're seeing, because of digital, because it's data, you're seeing tech companies traverse industries, get into, whether it's content, or music, or publishing, or groceries, and that's powerful, and that's awful scary. - If you're a manger, one of the things your ownership is asking you to do is to reduce asset specificities, so that their capital could be applied to more productive uses. Data reduces asset specificities. It brings into question the whole notion of vertical industry. You're absolutely right. But you know, one quick question I got for you, playing off of this is, again, it goes back to this notion of can we do it, and should we do it? I find it interesting, if you look at those top five, all data companies, but all of them are very different business models, or they can classify the two different business models. Apple is transactional, Microsoft is transactional, Google is ad-based, Facebook is ad-based, before the fake news stuff. Amazon's kind of playing it both sides. - Yeah, they're kind of all on a collision course though, aren't they? - But, well, that's what's going to be interesting. I think, at some point in time, the "can we do it, should we do it" question is, brands are going to be identified by whether or not they have gone through that process of thinking about, should we do it, and say no. Apple is clearly, for example, incorporating that into their brand. - Well, Silicon Valley, broadly defined, if I include Seattle, and maybe Armlock, not so much IBM. But they've got a dual disruption agenda, they've always disrupted horizontal tech. Now they're disrupting vertical industries. - I was actually just going to pick up on what she was talking about, we were talking about buzzword, right. So, one we haven't heard yet is voice. Voice is another big buzzword right now, when you couple that with IoT and AI, here you go, bingo, do I got three points? (laughing) Voice recognition, voice technology, so all of the smart speakers, if you think about that in the world, there are 7,000 languages being spoken, but yet if you look at Google Home, you look at Siri, you look at any of the devices, I would challenge you, it would have a lot of problem understanding my accent, and even when my British accent creeps out, or it would have trouble understanding seniors, because the way they talk, it's very different than a typical 25-year-old person living in Silicon Valley, right. So, how do we solve that, especially going forward? We're seeing voice technology is going to be so more prominent in our homes, we're going to have it in the cars, we have it in the kitchen, it does everything, it listens to everything that we are talking about, not talking about, and records it. And to your point, is it going to start making decisions on our behalf, but then my question is, how much does it actually understand us? - So, I just want one short story. Siri can't translate a word that I ask it to translate into French, because my phone's set to Canadian English, and that's not supported. So I live in a bilingual French English country, and it can't translate. - But what this is really bringing up is if you look at society, and culture, what's legal, what's ethical, changes across the years. What was right 200 years ago is not right now, and what was right 50 years ago is not right now. - It changes across countries. - It changes across countries, it changes across regions. So, what does this mean when our AI has agency? How do we make ethical AI if we don't even know how to manage the change of what's right and what's wrong in human society? - One of the most important questions we have to worry about, right? - Absolutely. - But it also says one more thing, just before we go on. It also says that the issue of economies of scale, in the cloud. - Yes. - Are going to be strongly impacted, not just by how big you can build your data centers, but some of those regulatory issues that are going to influence strongly what constitutes good experience, good law, good acting on my behalf, agency. - And one thing that's underappreciated in the marketplace right now is the impact of data sovereignty, if you get back to data, countries are now recognizing the importance of managing that data, and they're implementing data sovereignty rules. Everyone talks about California issuing a new law that's aligned with GDPR, and you know what that meant. There are 30 other states in the United States alone that are modifying their laws to address this issue. - Steve. - So, um, so, we got a number of years, no matter what Ray Kurzweil says, until we get to artificial general intelligence. - The singularity's not so near? (laughing) - You know that he's changed the date over the last 10 years. - I did know it. - Quite a bit. And I don't even prognosticate where it's going to be. But really, where we're at right now, I keep coming back to, is that's why augmented intelligence is really going to be the new rage, humans working with machines. One of the hot topics, and the reason I chose to speak about it is, is the future of work. I don't care if you're a millennial, mid-career, or a baby boomer, people are paranoid. As machines get smarter, if your job is routine cognitive, yes, you have a higher propensity to be automated. So, this really shifts a number of things. A, you have to be a lifelong learner, you've got to learn new skillsets. And the dynamics are changing fast. Now, this is also a great equalizer for emerging startups, and even in SMBs. As the AI improves, they can become more nimble. So back to your point regarding colossal trillion dollar, wait a second, there's going to be quite a sea change going on right now, and regarding demographics, in 2020, millennials take over as the majority of the workforce, by 2025 it's 75%. - Great news. (laughing) - As a baby boomer, I try my damnedest to stay relevant. - Yeah, surround yourself with millennials is the takeaway there. - Or retire. (laughs) - Not yet. - One thing I think, this goes back to what Karen was saying, if you want a basic standard to put around the stuff, look at the old ISO 38500 framework. Business strategy, technology strategy. You have risk, compliance, change management, operations, and most importantly, the balance sheet in the financials. AI and what Tony was saying, digital transformation, if it's of meaning, it belongs on a balance sheet, and should factor into how you value your company. All the cyber security, and all of the compliance, and all of the regulation, is all stuff, this framework exists, so look it up, and every time you start some kind of new machine learning project, or data sense project, say, have we checked the box on each of these standards that's within this machine? And if you haven't, maybe slow down and do your homework. - To see a day when data is going to be valued on the balance sheet. - It is. - It's already valued as part of the current, but it's good will. - Certainly market value, as we were just talking about. - Well, we're talking about all of the companies that have opted in, right. There's tens of thousands of small businesses just in this region alone that are opt-out. They're small family businesses, or businesses that really aren't even technology-aware. But data's being collected about them, it's being on Yelp, they're being rated, they're being reviewed, the success to their business is out of their hands. And I think what's really going to be interesting is, you look at the big data, you look at AI, you look at things like that, blockchain may even be a potential for some of that, because of mutability, but it's when all of those businesses, when the technology becomes a cost, it's cost-prohibitive now, for a lot of them, or they just don't want to do it, and they're proudly opt-out. In fact, we talked about that last night at dinner. But when they opt-in, the company that can do that, and can reach out to them in a way that is economically feasible, and bring them back in, where they control their data, where they control their information, and they do it in such a way where it helps them build their business, and it may be a generational business that's been passed on. Those kind of things are going to make a big impact, not only on the cloud, but the data being stored in the cloud, the AI, the applications that you talked about earlier, we talked about that. And that's where this bias, and some of these other things are going to have a tremendous impact if they're not dealt with now, at least ethically. - Well, I feel like we just got started, we're out of time. Time for a couple more comments, and then officially we have to wrap up. - Yeah, I had one thing to say, I mean, really, Henry Ford, and the creation of the automobile, back in the early 1900s, changed everything, because now we're no longer stuck in the country, we can get away from our parents, we can date without grandma and grandpa setting on the porch with us. (laughing) We can take long trips, so now we're looked at, we've sprawled out, we're not all living in the country anymore, and it changed America. So, AI has that same capabilities, it will automate mundane routine tasks that nobody wanted to do anyway. So, a lot of that will change things, but it's not going to be any different than the way things changed in the early 1900s. - It's like you were saying, constant reinvention. - I think that's a great point, let me make one observation on that. Every period of significant industrial change was preceded by the formation, a period of formation of new assets that nobody knew what to do with. Whether it was, what do we do, you know, industrial manufacturing, it was row houses with long shafts tied to an engine that was coal-fired, and drove a bunch of looms. Same thing, railroads, large factories for Henry Ford, before he figured out how to do an information-based notion of mass production. This is the period of asset formation for the next generation of social structures. - Those ship-makers are going to be all over these cars, I mean, you're going to have augmented reality right there, on your windshield. - Karen, bring it home. Give us the drop-the-mic moment. (laughing) - No pressure. - Your AV guys are not happy with that. So, I think the, it all comes down to, it's a people problem, a challenge, let's say that. The whole AI ML thing, people, it's a legal compliance thing. Enterprises are going to struggle with trying to meet five billion different types of compliance rules around data and its uses, about enforcement, because ROI is going to make risk of incarceration as well as return on investment, and we'll have to manage both of those. I think businesses are struggling with a lot of this complexity, and you just opened a whole bunch of questions that we didn't really have solid, "Oh, you can fix it by doing this." So, it's important that we think of this new world of data focus, data-driven, everything like that, is that the entire IT and business community needs to realize that focusing on data means we have to change how we do things and how we think about it, but we also have some of the same old challenges there. - Well, I have a feeling we're going to be talking about this for quite some time. What a great way to wrap up CUBE NYC here, our third day of activities down here at 37 Pillars, or Mercantile 37. Thank you all so much for joining us today. - Thank you. - Really, wonderful insights, really appreciate it, now, all this content is going to be available on theCUBE.net. We are exposing our video cloud, and our video search engine, so you'll be able to search our entire corpus of data. I can't wait to start searching and clipping up this session. Again, thank you so much, and thank you for watching. We'll see you next time.

(upbeat electronic music) >> Narrator: Live from San Francisco, it's The Cube, covering Red Hat Summit 2018. Brought to you by Red Hat. >> Hey, welcome back, everyone. We are here live, The Cube in San Francisco, Moscone West for the Red Hat Summit 2018 exclusive coverage. I'm John Furrier, the cohost of The Cube. I'm here with my cohost, John Troyer, who is the co-founder of Tech Reckoning, an advisory and community development firm. Our next guest is Jonathan Donaldson, Technical Director, Office of the CTO, Google Cloud. Former Cube Alumni. Formerly was Intel, been on before, now at Google Cloud for almost two years. Welcome back, good to see you. >> Good to see you too, it's great to be back. >> So, had a great time last week with the Google Cloud folks at KubeCon in Denmark. Kubernetes, rocking the world. Really, when I hear the word de facto standard and abstraction layers, I start to get, my bells go off, let me look at that. Some interesting stuff. You guys have been part of that from the beginning, with the CNCF, Google, Intel, among others. Really created a movement, congratulations. >> Yeah, thank you. It really comes down to the fact that we've been running containers for almost a dozen years. Four billion a week, we launch and collapse. And we know that at some point, as Docker and containers really started to take over the new way of developing things, that everyone is going to run into that scalability wall that we had run into years and years and years ago. And so Craig and the team at Google, again, I wasn't at Google at this time, but they had a really, let's take what we know from internally here and let's take those patterns and let's put them out there for the world to use, and that became Kubernetes. And so I think that's really the massive growth there, is that people are like, "Wow, you've solved a problem, "but not from a science project. "It's actually from something "that's been running for a decade." >> Internally, that's called bore. That's tools that Google used, that their SRE cyber lab engineers used to massively provision manage. And they're all software engineers, so it's not like they're operators. They're all Google engineers. But I want to take a minute, if you can, to explain. 'Cause you're new to Google Cloud. You're in the industry, you've been around, you helped form the CNCF, which is the Cloud Native Foundation. You know cloud, you know tech. Google's changed a lot, and Google Cloud specifically has a narrative of, they're one big cloud and they have an application called Google stuff and enterprises are different. You've been there now for almost a year or more. >> Jonathan: Little over a year, yeah. >> What's Google Cloud like right now? Break the myths down around Google Cloud. What's the current status? I know personally, a lot of cloud DNA is coming in from the industry. They've been hiring, making some great progress. Take a minute to explain the Google Cloud. >> Yeah, so it's really interesting. So again, it comes back from where you started from. So Google itself started from a scale consumer SAS type of business. And so that, they understood really well. And we still understand, obviously, uptime and scalability really, really well. And I would say if you backtrack several years ago, as the enterprise really started to look at public clouds and Google Cloud itself started to spin up, that was probably not, they probably didn't understand exactly all of the things that an enterprise would need. Really, at that point in time, no one cloud understood any of the enterprise specifically. And so what they did is they started hiring in people like myself and others that are in the group that I'm in. They're former CIOs of large enterprise companies or former VPs of engineering, and really our job in the Office of the CTO for Google Cloud is to help with the product teams, to help them build the products that enterprises need to be able to use the public cloud. And then also work with some of those top enterprise customers to help them adopt those technologies. And so I think now that if you look at Google Cloud, they understand enterprise really, really well, certainly from the product and the technology perspective. And I think it's just going to get better. >> I interviewed Jennifer Lynn, I had a one-on-one with her. I didn't publish it, it was more of a briefing. She runs Product Management, all on security side. >> Jonathan: Yeah, she's fantastic. >> So she's checking the boxes. So the table stakes are set for Google. I know you got to do some basic things to catch up to get in the cloud. But also you have partnerships. Google Next is coming up, The Cube will be there. Red Hat's a partner. Talk about that relationship with Red Hat and partners. So you're very partner-centric with Google Cloud. >> Jonathan: We are. >> And that's important in the enterprise, but so what-- >> Well, there tends to be two main ares that we focus on, from what we consider the right way to do cloud. One of them is open source. So having, which again, aligns perfectly with Red Hat, is putting the technologies that we want customers to use and that we think customers should use in open source. Kubernetes is an example, there's Istio and others that we've put out that are examples of those. A lot of the open source projects that we all take for granted today were started from white papers that we had put out at one point in time, explaining how we did those things. Red Hat, from a partner perspective, I think that that follows along. We think that the way that customers are going to consume these technologies, certainly enterprise customers are, through those partners that they know and trust. And so having a good, flourishing ecosystem of partners that surround Google Cloud is absolutely key to what we do. >> And they love multicloud too. >> They love multicloud. >> Can't go wrong with it. >> And we do too. The idea is that we want customers to come to Google Cloud and stay there because they want to stay there, because they like us for who we are and for what we offer them, not because they're locked into a specific service or technology. And things like Kubernetes, things like containers, being open sourced allows them to take their tool chains all the way from their laptop to their own cloud inside their own data center to any cloud provider they want. And we think hopefully they'll naturally gravitate towards us over time. >> One of the things I like about the cloud is that there's a flywheel, if you will, of expertise. Like I look at Amazon, for instance. They're getting a lot of metadata of the kinds of workloads that are on their cloud, so they can learn from that and turn that into an advantage for them, or not, or for their customers, and how they could do that. That's their business decision. Google has a lot of flywheel action going on. A lot of Android devices connected in the Google system. You have a lot of services that you can bring to bear in the cloud. How are you guys looking at, say, from a security standpoint alone, that would be a very valuable service to have. I can tap into all the security goodness of Google around what spear phishing is out there, things of that nature. So are you guys thinking like that, in terms of services for customers? How does that play out? >> So where we, we're very consistent on what we consider is, privacy is number one for our customers, whether they're consumer customers or whether they're enterprise customers. Where we would use data, you had mentioned a lot of things, but where we would use some data across customer bases are typically for security things, so where we would see some sort of security impact or an attack or something like that that started to impact many customers. And we would then aggregate that information. It's not really customer information. It's just like you said, metadata, themes, or trends. >> John Furrier: You're not monetizing it. >> Yeah, we're not monetizing it, but we're actually using it to protect customers. But when a customer actually uses Google Cloud, that instance is their hermetically sealed environment. In fact, I think we just came out recently with even the transparency aspects of it, where it's almost like the two key type of access, for if our engineers have to help the customer with a troubleshooting ticket, that ticket actually has to be opened. That kind of unlocks one door. The customer has to say, "Yes," that unlocks the other door. And then they can go in there and help the customer do things to solve whatever the problem is. And each one of those is transparently and permanently logged. And then the customer can, at any point in time, go in and see those things. So we are taking customer privacy from an enterprise perspective-- >> And you guys are also a whole building from Google proper, like it's a completely different campus. So that's important to note. >> It is. And a lot of it just chains on from Google proper itself. If you understood just how crazy and fanatical they are about keeping things inside and secret and proprietary. Not proprietary, but not allowing that customer data out, even on the consumer side, it would give a whole-- >> Well, you got to amplify that, I understand. But what I also see, a good side of that, which is there's a lot of resources you're bringing to bear or learnings. >> Yeah, absolutely. >> The SRE concept, for instance, is to me, really powerful, because Google had to build that out themselves. This is now a paradigm, we're seeing a cloud scale here, with the Cloud Native market bringing in all-new capabilities at scale. Horizontally scalable, fully synchronous, microservices architecture. This future is a complete game-changer on functionality at the different scale points. So there's no longer the operator's room, provisioning storage here. >> And this is what we've been doing for years and years and years. That's how all of Google itself, that's how search and ads and Gmail and everything runs, in containers all orchestrated by Borg, which is our version of Kubernetes. And so we're really just bringing those leanings into the Google Cloud, or learnings into Google Cloud and to our customers. >> Jonathan, machine learning and AI have been the big topic this week on OpenShift. Obviously that's a big strength of Google Cloud as well. Can you drill down on that story, and talk about what Google Cloud is bringing on, and machine learning on OpenShift in general? Give us a little picture of what's running. >> Yeah, so I think they showed some of the service broker stuff. And I think, did they show some of the Kubeflow stuff, which is taking some machine learning and Kubernetes underneath OpenShift. I think those are very, very interesting for people that want to start getting into using AutoML, which is kind of roll-your-own machine learning, or even the voice or vision APIs to enhance their products. And I think that those are going to be keys. Easing the adoption of those, making them really, really easy to consume, is what's going to drive the significant ramp on using those types of technologies. >> One of the key touchpoints here has been the fact that this stuff is real-world and production-ready. The fact that the enterprise architecture now rolling out apps within days or weeks. One of those things that's now real is ML. And even in the opening keynote, they talked about using a little bit of it to optimize the scheduling and what sessions were in which rooms. As you talk to enterprises, it does seem like this stuff is being baked into real enterprise apps today. Can you talk a little bit about that? >> Sure, so I certainly can't give any specific examples, because what I think what you're saying is that a lot of enterprises or a lot of companies are looking at that like, "Oh, this is our new secret sauce." It always used to be like they had some interesting feature before, that a competitor would have to keep up with or catch up with. But I think they're looking at machine learning as a way to enhance that customer experience, so that it's a much more intimate experience. It feels much more tailored to whomever is using their product. And I think that you're seeing a lot of those types of things that people are starting to bake into their products. We've, again, this is one of these things where we've been using machine learning for almost 10 years inside Google. Things like for Gmail, even in the early days, like spam filtering, something just mundane like that. Or we even used it, turned it on in our data centers, 'cause it does a really good job of lowering the PUE, which is the power efficiency in data centers. And those are very mundane things. But we have a lot of experience with that. And we're exposing that through these products. And we're starting to see people, customers gravitate to grab onto those. Instead of having to hard code something that is a one to many kind of thing, I may get it right or I may have to tweak it over time, but I'm still kind of generalizing what the use cases are that my customers want to see, once they turn on machine learning inside their applications, it feels much more tailored to the customer's use cases. >> Machine learning as a service seems to be a big hot button that's coming out. How are you guys looking at the technical direction from the cloud within the enterprise? 'Cause you have three classes of enterprise. You have the early adopters, the power, front, cutting-edge. Then you have the fast followers, then you have everybody else. The everybody else and fast followers, they know about Kubernetes, some might not even, "What is Kubernetes?" So you have kind of-- >> Jonathan: "What containers?" >> A level of progress where people are. How are you guys looking at addressing those three areas, because you could blow them away with TensorFlow as a service. "Whoa, wowee, I'm just trying to get my storage LUNs "moving to a cloud operation system." There's different parts of this journey. Is there a technical direction that addresses these? What are you guys doing? >> So typically we'll work with those customers to help them chart the path through all those things, and making it easy for them to use and consume. Machine learning is still, unless you are a stats major or you're a math major, a lot of the algorithms and understanding linear algebra and things like that are still very complex topics. But then again, so is networking and BGP and things like OSPF back a few years ago. So technology always evolves, and the thing that you can do is you can just help pull people along the continuum there, by making it easy for them to use and to provide a lot of education. And so we work with customers on all ends of the spectrum. Even if it's just like, "How do I modernize my applications, "or how do I even just put them into the cloud?" We have teams that can help do that or can educate on that. If there are customers that are like, "I really want to go do something special "with maybe refactoring my applications. "I really want to get the Cloud Native experience." We help with that. And those customers that say, "I really want to find out this machine learning thing. "How can I actually make that an impactful portion of my company's portfolio?" We can certainly help with that. And there's no one, and typically you'll find in any large enterprise, because there'll be some people on each one of those camps. >> Yeah, and they'll also want to put their toe in the water here and there. The question I have for you guys is you got a lot of goodness going on. You're not trying to match Amazon speed for speed, feature for feature, you guys are picking your shots. That is core to Google, that's clear. Is there a use case or a set of building blocks that are highly adopted with you guys now, in that as Google gets out there and gets some penetration in the enterprise, what's the use, what are the key things you see with successes for you guys, out of the gate? Is there a basic building? Amazon's got EC2 and S3. What are you guys seeing as the core building blocks of Google Cloud, from a product standpoint, that's getting the most traction today? >> So I think we're seeing the same types of building blocks that the other cloud providers are, I think. Some of the differences is we look at security differently, because of, again, where we grew up. We do things like live migration of virtual machines, if you're using virtual machines, because we've had to do that internally. So I think there are some differences on just even some of the basic block and tackling type of things. But I do think that if you look at just moving to the cloud, in and of itself is not enough. That's a stepping stone. We truly believe that artificial intelligence and machine learning, Cloud Native style of applications, containers, things like service meshes, those things that reduce the operational burdens and improve the rate of new feature introduction, as well as the machine learning things, I think that that's what people tend to come to Google for. And we think that that's a lot of what people are going to stay with us for. >> I overheard a quote I want to get your reaction to. I wrote it down, it says, "I need to get away from VPNs and firewalls. "I need user and application layer security "with un-phishable access, otherwise I'm never safe." So this is kind of a user perspective or customer perspective. Also with cloud there's no perimeters, so you got phishing problems. Spear phishing's one big problem. Security, you mentioned that. And then another quote I had was, "Kubernetes is about running frameworks, "and it's about changing the way "applications are going to be built over time." That's where, I think, SRE and Istio is very interesting, and Kubeflow. This is a modern architecture for-- >> There's even KubeVirt out there, where you can run a VM inside a container, which is actually what we do internally too. So there's a lot of different ways to slice and dice. >> Yeah, how relevant is that, those concepts? Because are you hearing that as well on the customers? 'Cause that's pain point, but also the new modern software development's future way to do things. So there's pain point, I need some aspirin for that. And then I need some growth with the new applications being built and hiring talent. Is that consistent with how you guys see it? >> So which one should I tackle? So you're talking about. >> John Furrier: VPN, do the VPNs first. >> The VPNs first, okay. >> John Furrier: That's my favorite one. >> So one of the most, kind of to give you the backstory, so one of the most interesting things when I came to Google, having come from other large enterprise vendors before this, was there's no VPNs. We don't even have it on our laptop. They have this thing called BeyondCorp, which is essentially now productized as the Identity-Aware Proxy. Which is, it actually takes, we trust no one or nothing with anything. It's not the walled garden style of approach of firewall-type VPN security. What we do is, based upon the resource you're going to request access for, and are you on a trusted machine? So on one that corporate has given you? And do you have two-factor authentication that corporate, not only your, so what you have and what you know. And so they take all of those things into awareness. Is this the laptop that's registered to you? Do you have your two-factor authentication? Have you authenticated to it and it's a trusted platform? Boom, then I can gain access to the resources. But they will also look for things like if all of a sudden you were sitting here and I'm in San Francisco, but something from some country in Asia pops up with my credentials on it, they're going to slam the door shut, going, "There's no way that you can be in two places at one time." And so that's what the Identity-Aware Proxy or BeyondCorp does, kind of in a nutshell. And so we use that everywhere, internally, externally. And so that's one of the ways that we do security differently is without VPNs. And that's actually in front of a lot of the GCP technologies today, that you can actually leverage that. So I would say we take-- >> Just rethinking security. >> It's rethinking security, again, based upon a long history. And not only that, but what we use internally, from our corporate perspective. And now to get to the second question, yeah. >> Istio, Kubeflow, is more of the way software gets run. One quote from one of the ex-Googlers who left Google then went out to another company, she goes, she was blown away, "This is the way you people ship software?" Like she was a fish out of water. She was like, "Oh my god, where's Borg?" "We do Waterfall." So there's a new approach that opens doors between these, and people expect. That's this notion of Kubeflow and orchestration. So that's kind of a modern, it requires training and commitment. That's the upside. Fix the aspirin, so Identity Proxy, cool. Future of software development architecture. >> I think one of the strong things that you're going to see in software development is I think the days of people running it differently in development, and then sandbox and testing, QA, and then in prod, are over. They want to basically have that same experience, no matter where they are. They want to not have to do the crossing your fingers if it, remember, now it gets reddited or you got slash-dotted way back in the past and things would collapse. Those days of people being able to put up with those types of issues are over. And so I think that you're going to continue to see the development and the style of microservices, containers, orchestrated by something that can do auto scaling and healing, like Kubernetes. You're going to see them then start to use that base layer to add new capabilities on top, which is where we see Kubeflow, which is like, hey, how can I go put scalable machine learning on top of containers and on top of Kubernetes? And you even see, like I said, you see people saying, "Well, I don't really want to run "two different data planes and do the inception model. "If I can lay down a base layer "of Kubernetes and containers, then I can run "bare metal workloads against the bare metal. "If I need to launch a virtual machine, "I'll just launch that inside the container." And that's what KubeVirt's doing. So we're seeing a lot of this very interesting stuff pop. >> John Furrier: Yeah, creativity. >> Creativity. >> Great, talk about your role in the Office of the CTO. I know we got a couple of minutes left. I want to get out there, what is the role of the CTO? Bryan Stevens, formerly a Red Hat executive. >> Yeah, Bryan's our CTO. He used to run a big chunk of the engineering for Google Cloud, absolutely. >> And so what is the office's charter? You mentioned some CIOs, former CIOs are in there. Is it the think tank? Is it the command and control ivory tower? What's the role of the office? >> So I think a couple of years ago, Diane Greene and Bryan Stevens and other executives decided if we want to really understand what the enterprise needs from us, from a cloud perspective, we really need to have some people that have walked in those shoes, and they can't just be Diane or can't just be Bryan, who also had a big breadth of experience there. But two people can't do that for every customer for every product. And so they instituted the Office of the CTO. They tapped Will Grannis, again, had been in Boeing before, been in the military, and so tapped him to build this thing. And they went and they looked for people that had experience. Former VPs of Engineering, former CIOs. We have people from GE Oil and Gas, we have people from Boeing, we have people from Pixar. You name it, across each of the different verticals. Healthcare, we have those in the Office of the CTO. And about, probably, I think 25 to 30 of us now. I can't remember the exact numbers. And really, what our day to day life is like is working significantly with the product managers and the engineering teams to help facilitate more and more enterprise-focused engineering into the products. And then working with enterprise customers, kind of the big enterprise customers that we want to see successful, and helping drive their success as they consume Google Cloud. So being the conduit, directly into engineering. >> So in market with customers, big, known customers, getting requirements, helping facilitate product management function as well. >> Yeah, and from an engineering perspective. So we actually sit in the engineering organization. >> John Furrier: Making sure you're making the good bets. >> Jonathan: Yes, exactly. >> Great, well thanks for coming on The Cube. Thanks for sharing the insight. >> Jonathan: Thanks for having me again. >> Great to have you on, great insight, again. Google, always great technology, great enterprise mojo going on right now. Of course, The Cube will be at Google Next this July, so we'll be having live coverage from Google Next here in San Francisco at that time. Thanks for coming on, Jonathan. Really appreciate it, looking forward to more coverage. Stay with us for more of day three, as we start to wrap up our live coverage of Red Hat Summit 2018. We'll be back after this short break. (upbeat electronic music)

(energetic electronic music) >> Narrator: Live from Nassau in the Bahamas, it's theCUBE! Covering POLYCON18, brought to you by Polymath. >> Hey, welcome back everyone. This is exclusive live CUBE coverage here in the Bahamas for POLYCON18, it's a crypto event. Just talking economics. It's all the players in the space really discussing the future. I'm John Furrier with my co-host Dave Vellante. Our next guest, Bill Tai, friend, Facebook friend, industry legend, venture capitalist, kite surfer. His Twitter handle is @kitevc. Follow him. He's also involved in Bitfury and a lot of Bitcoin-related activities. Been a mentor to others. Great to have you, Bill. >> Thank you, John. I really appreciate you having me on the show. >> You tweeted in 2010, "This Bitcoin thing is interesting. "Check out this white paper." Can? >> Yeah, that was a >> Seminal moment. >> You know, back then I didn't know it would be, maybe a seminal moment. I was just lonely. (laughing) So, and the back story there, a very good friend of mine is Philip Rosedale, and he had approached me when he was starting a site called Second Life, where you basically create a digital avatar, maybe of yourself, maybe not, and you have this kind of, you know, world where you have people in an unstructured environment. And in the very early days of Second Life, when people were kind of just milling about, I said to Philip, I said, "Hey, Philip. "You know, maybe we should create a currency." I said, you know like, "If you think about it. "Think about what is Las Vegas? "Las Vegas is this pile of sand "but there is this metropolis on it. "How did that happen?" I said, "You know, if you took ten people, "sat them in a circle, and you put one poker chip "in the system, and said 'Pass it to the right,' "and everybody did that a million times a year. "Everybody would have a million dollars of income. "And then you could take chunks off "and build a casino, and build a resort, "and you'd have Las Vegas." So I said, "Let's do that." And so the Linden dollar was born. And so, soon, there was this thriving economy in Second Life that just, it was quite amazing to see. And so, when Bitcoin came out in 2009, as soon as I heard about it, I wanted to see what it was. So I went to the site and I read the paper, and it just seemed really cool. And so I started to play with it a little bit, and by 2010, I just thought it was really cool, but no one else had seen it. >> Yeah. >> So I took to Twitter to say, (laughing) "Is anyone out there "using this P to P digital currency?" You know, and >> It's funny. Our first web, You know, I started SiliconANGLE in 2009. David and I partnered in 2010. Our first website, the developer didn't want PayPal. He wanted Bitcoin. It was 22 cents, I think, at the time and we used the site for about half a year, and then we changed it and went back paid fiat. But if you think about where these come from, you brought up Second Life. Okay, online virtual world, really ahead of its time, but really set the stage for what we're seeing now. Gaming people who know virtual currencies, thrive on crypto. >> Yeah. Yes. >> So I'd like to get your perspective. Because, I know you've done a lot of investing in mobile and gaming, and what not. Where does that cross over? Because there's been a lot of virtual currencies going on in games. >> Yes. >> For a long, long time. >> Yes. >> How is that influencing and impacting this industry? >> Well, you know it's, I guess you have to ask, when you ask, you know, where does the real and where does the digital, like do they cross? And what are they? What is currency? Is the U.S. dollar real, right? And actually, let me pause for a second and reach down to my phone, because did you see a tweet today from Sheila Bair? I have to read this. Okay, so I just saw a tweet from @zerohedge earlier today. Sheila Bair, on Bitcoin, Quote, "I don't think we should ban it. "The green bills in your pocket don't have "an intrinsic value either." >> Well, look, the government wants to get rid of paper money. The people want to get rid of paper money. Why not? >> What is it really? Right? I mean so >> Backed by the U.S. military maybe, I don't know, I mean what >> What is it? >> What is it? Right. >> That's a good question. >> So I don't really see a difference. You know, they're kind of the same thing. You know, it's just something that people believe in, as the embodiment of value exchange. Whatever it is. So if it's a green piece of paper, or it's not. If it's shell, if it's a pebble. There is a fascinating book that you can read called The Ascent of Money by Niall Ferguson. He's at Stanford now at the Hoover Institute, but he got widely known after the great financial crisis unfolded. He basically wrote a book called The Ascent of Money which tracks the history of value exchange across civilized communities, for thousands of years, from pebbles to shells, to feathers, to credit, to default swaps. And coined the term "Cimerica," which is sort of the interdependence of the cash flow. And what became apparent to me when I read that, was that the world of ICOs is actually no different than anything we've experienced in civilized humanity. You know, if you think about, even in the United States, in the 1800s, at one time there were over 200 currencies circulating at the same time. If you think about the formation of the United States as colonies, a bunch of guys get off the boats. They draw lines around the forest. Here's Connecticut, here's Vermont, here's New York, here's Virginia. Let's do an ICO. They all did an ICO. If you think about it, they created their own unit of currency per their community and geography, no different than what's happening today. >> When Lincoln was shot, there was a five dollar confederate bill in his wallet, right? I mean, the confederates had their own money. >> Yeah, and also you brought a point up in the conference you were in in Dubai, which I thought was really intriguing, and provocative, but also kind of real. The Oil Dollar Association post-World War II, >> Yeah >> Essentially wasn't actually securitizing oil That was an ICO. >> It was the tokenization of oil, right. Yeah, so, you know, the modern currency system that we have today, that is commonly known as the Petrodollar, so it's actually a relatively recent phenomenon. So if you think about, of course, the quote "U.S. dollar" was around a little bit longer than 1944, but it was really at Brett Woods that the dollar had its sort of birth to become the world's standard currency. And, you know, this is maybe a little bit of an over-simplification, but think about the picture after World War II. So, you basically have every major productive economy have war, destroy themselves. The U.S. enters late, finishes it all off completely, and you basically have 100 million people milling about. A little bit like Second Life, right? So, what do you do? Got to make them productive. Create a currency, set of currencies. So for every community of interest, like every token community of interest, you say, "Well, here's a lira, here's a franc, "Here's a pound, here's a mark. "Let's take gold, "reference the dollar to gold, and reference "every one of these currencies against the dollar. "Gentlemen, start your engines." Right? >> There you go. >> So how is that different than an ICO? Okay, so that was fixed to gold for a long time until people started to game it. And when the French accumulated a lot of dollars and they realized, whoa, there's more dollars than there is gold, I'm just going to go cash all this in. So they literally came over to take all the gold, and then the president took it off the gold standard. >> Dave Vellante: That's right. >> So it had to couple with something. So what it the utility token that that became? That became referenced to petroleum because the U.S. had basically forced everybody in the Middle East to accept dollars as payment and what that did was it created the dollar as a storage of energy. So you could basically take a token of oil and, as a separate nation, you could store that through your trade, if you had sort of a surplus, and you provided yourself energy security. >> Well, most currencies, right, historically have had a pretty short shelf life. Presumably the same will be true in the Blockchain world. >> Don't know. >> The crypto world. >> Yeah, it's, if you look at the history of humans over six million years, and it's arguable it's at four or six, or whatever it is, you're right. Like there have always been multiple currencies all the time. And very rarely have they ever become sort of like super-dominating currencies. That is also a very recent phenomena. I think, driven by the industrial revolution, and a combination of the Petrodollar and scale economics and manufacturing. So, so that >> Yeah, and overwhelmingly here, at this event, people feel like security tokens, as an asset class, are going to vastly overtake utility tokens. >> You know, actually, securities are a whole, I mean regular securities, (laughing) that's an interesting subject altogether. Right, okay, so there was a time, in my lifetime, when I was a securities analyst at Alex Brown in the '80s, and in that period of time, everything traded at ten times earnings, right? So you had a barometer for, a stock should be valued at this, because is should have a PE of actual real earnings. >> Dave Vellante: Independent of its growth or anything else, right? >> Yes, and if it grew, you had a PEG ratio, so you'd have a little bit higher growth, and so a little higher PE, but what's happened to securities over time, of that ilk, okay, you had to get these companies profitable to get them public in that era, and then over time the sort of like network effects have come in, and communities of interest have formed around companies. So, and the structure of securities has moved from give me something with earnings multiply it by a number to get the value, to give me a share of something that has no voting rights and no earnings. Does that sound like a token? That's Snapchat, right? (laughing) >> So you literally have, you know, Google, Facebook, all these companies now issue shares that don't have the characteristics of equity shares. They don't vote. What are they now, right? So tokenization is sort of a natural extension of that. >> Dave Vellante: Do you see that as a >> They don't have dividends either >> You see that as a fundamental shift in the value equation, the perceived value equation? Both? Is it sustainable? >> I think it's basically, so, you know, I go back and forth on this, because is it a trend line or is it a return in the past? Right? So what is a confederate dollar that was in Abraham Lincoln's pocket? It's a belief. So what is a share of Snapchat? It's a belief. It doesn't have earnings >> John Furrier: And a token is a belief. >> Right. >> But the trend is securing something, right? So the trend we're seeing is, obviously the ruling, first of all the ruling in Switzerland was interesting. You now have a trading so an asset, so security, asset, and then trading. So they kind of went a little bit deeper, which I think is helpful. >> Yeah. >> For the community. But what are they securing? So the trend, as we see, is percentage of revenue, non dilutive and equity in the classic sense, so kind of a token. And then some sort of either buyback options, people are doing things like that. Do you see patterns like that? What are you seeing for? >> Well. >> I mean a security token makes sense. It's all credited. The paperwork's known. >> Yeah, so, you know, it feels like, so some people refer to sort of Bitcoin as digital gold, you know, and in that sense, like gold is a commodity but is the root of securities, you know, whether it's gold ETF's or something, because you perceive a limited supply, and you perceive a storage of value, so that is where I think Bitcoin sits. But then I think this whole other category of utility tokens, that may be considered security tokens by definition of law, that resembles the petrodollar. And as we were talking about earlier, you know gold used to represent or a dollar used to represent a share of gold, but it didn't anymore. So what was underpinning it? It was basically, in my opinion, the ability for that token to have utility as an instrument to purchase oil for your energy security. And so, I think that's kind of where the utility tokens are today. >> You're a leader in the industry, and you're well-known. Communities need to thrive. And factions form, curriencies form, and can be very productive, and also can be counterproductive. >> Yeah. >> So what is the unwritten rules that you guys are putting forth. Are people meeting? Are you talking? And sometimes, as people make money, which a lot of people are making a lot of money right now. I mean, for some people, it's the first time. Didn't have money, make money. You know, egos kind of come in. So all of these are normal things. But again, this is a societal community dynamic, >> Yes. >> But super important. Institutional investors are coming in. >> Right. >> Big money. This isn't Burning Man. This isn't. Burning Man's cool, but you can't model this industry after Burning Man. Maybe you could. I don't know. What is your take? >> Well, you know, it's, I think that the guiding principle really needs to be looking out for the greater good, because I think that is the issue that everyone is trying to solve for. And it's not just endemic to Bitcoin and Blockchain. It's a societal issue that's been with us since the creation of civilization. And I don't know how to solve for that, but I think you need people to stand up and just make sure that people are thinking about that all the time. You know, and I think, over my career, I think I started as kind of like a geek hacker, sitting in the back of the room, working on little microchips and building stuff, and I still do that on weekends sometimes, but, you know, for whatever reason, I've been thrust into this role now where I do have a set of communities of interest that started actually around kiteboarding, but it became sort of a larger community around entrepreneurship. And we've actually, I have a 501(c)(3) that supports ocean causes and entrepreneurial things, and it's called ACTAI Global, and we have a couple value statements. We actually, we're codifying it, so we actually have a little pin, you know the ACTAI stands for Athletes, Conservationists, Technologists, Artists and Innovators, and all of us collectively, we combine our energy to work on causes. Some of the things that we support are around ocean conservation and the preservation of ecosystems, but we also work on a lot of other entrepreneurial efforts to help each other. But the thing that I've realized with our group is we've been very productive as a community, and you see a lot of companies that are born in our community, funded in our community, like, you know, whether it's Canva or Zoom, or any number of projects that turn into community-based companies because the group of people, they think and they stand for something greater than themselves. So that's kind of one principle. It's sort of like, how do you, how do you place your values as something to support the greater community, and that's something that I think, if everybody would just think about that a little bit, and stand for something greater than themselves, the world would be a better place. And on that note, the second ethos that we operate to is that we strive to leave every person or place we touch better than before we touched it. So when you see us like kiting at a beach, you'll see us picking up garbage, too. You know? We don't go someplace without trying to improve it a little bit. And I think we help each other on the companies, too. And I think the last thing that people really should try to do, everybody in this world of technology, has a little bit of a superpower, whatever that is. You know, they wouldn't be doing the things that they're doing if they weren't totally insanely focused on a piece of technology. They know something that other people don't. And if everybody would just try a little bit to use the powers the universe has granted them, to empower others, to unlock other people, the world would be a better place. So I think, you know, I think all of these factions, if we could just get people to stand for something greater than themselves, work to make people and places better off than before they touched them, and empower other people, I think we'll have some great outcomes. >> You know, empathy, empathy is a wonderful thing. And also you mentioned, know your neighbor. You know, that's a big thing. We're doing our part here in theCUBE, bringing our mission content. Bill, been great to have you on. And we'll get that clip out on the network about your mission. Great stuff. >> Thank you, thanks. >> And great to see you >> It's an awesome philosophy. >> be successful, you're a great leader. People look up to you, and certainly we're glad to have you on theCUBE. Thanks for joining us. Hey, more live coverage after this short break here on theCUBE in the Bahamas for crypto currency, token economics, POLYCON18. We'll be back with more after this short break.

>> Narrator: Live from Las Vegas, it's theCUBE covering AWS re:Invent 2017 presented by AWS, Intel, and our ecosystem of partners. >> We are life back here in Las Vegas at the Sands Expo as we continue our coverage here on theCUBE of re:Invent, AWS here on the fourth day of what has been a very successful show. I still hear a lot of buzz, a lot of activity on the show floor. It certainly indicative of what happened here in terms of bringing this community together in a very positive way. I'm with Justin Warren, I'm John Walls. We go from Justin to Dustin, Dustin Kirkland, who is the vice president of product development for Ubuntu on the Canonical. It's good to see you again. >> Likewise, John. >> I should let the two of you probably chat about Australia. We heard these great diving stories about your adventures, your home, your native country. >> Yep. >> Maybe afterwards will get a little photos, travel thing going on. >> Yeah that's right. (laughing) >> All right, 17 years you have been diving. Were going to have to get into that a little bit later on. First off, let's talk about Ubuntu, and maybe the footprint within AWS. Maybe not only what brings you here, but what gets you there? What are you doing there? >> First of all, this is a fantastic conference. Hundreds of these organizations here are involved in Ubuntu, using Ubuntu in AWS and taking advantage of open source, using it for lots of scale out services. To date this year in 2017, over 125 million instances of Ubuntu have launched in AWS alone just this year, and the year is not even over yet. We see anything from media entertainment. Netflix is here. I spent some time with them. One of Netflix's performance engineers gave a talk yesterday about how Netflix tunes their Ubuntu instances in Amazon to the tune of 100,000 instances of Ubuntu running in Amazon to deliver the Netflix experience that I'm sure all of us have. >> John: 100,000? >> Yeah. >> That's amazing. >> It's crazy, yeah. >> I'm a big fan of Ubuntu because I am a mad person. I've been running it as my primary desktop for something like 10 years. >> All right! >> I run it on a laptop. >> Okay. >> I love it, it's great. >> Good. >> People use Ubuntu all the time but it's like it just became the de facto, it seems like overnight of pretty much, hey, if you want to run Linux in cloud, you just spin up in Ubuntu. Just run it up, so what is it about Ubuntu itself, where are you taking the product for people who are using it in cloud? We are hearing a lot about all these different services, and we are hearing about serverless, so how does Ubuntu fit into that AWS world? >> That's a great question. First of all, it's not overnight. We have been doing this since 2004, so we are going on 14 years of building the thing that is Ubuntu. We brought Ubuntu into Amazon in about 2008, which is right when I got involved at Canonical. I was working on Ubuntu before that, but working for Canonical, and that was relatively early in the entire Amazon adventure. You said Ubuntu on the desktop. That's certainly where Ubuntu got its start, but it was Amazon that really busted Ubuntu out into the server space, and so now as you said, if you are starting a new company or a new technology, you almost by default start on Ubuntu. Now where are we taking that? Here we are talking about cloud, but the other half of cloud is the edge. The edge being embedded devices, embedded IOT connected devices. The thing about every IOT device, the I in IOT is Internet. The connected part of a connected device means it has to be connected to something, and what is going to be connected to? The cloud. Every smart autonomous driving vehicle, every oil rig out in West Texas, every airplane, every boat, every ship, every place where you are going to find compute in these next couple of years as we move into the 5G revolution, are connected to services on the backend, the majority of those hosted in Amazon, and the majority of those running Ubuntu. >> When you talk about IOT though, what kind of challenges that that bring into your world? Because you are talking about this, I mean, I can't even think about the order of growth. >> Yeah, billions, literally billions. >> It's just massive connectivity, and in a mobile environment, throw that on top of that, so what does that do for you then in terms of what you are looking at down the road and the kind of capabilities that you have got to build in? >> Security, I mean it starts with security. When we think about devices in our homes accompanying our kids to school, devices that are inside of buses and hospitals, it's all about security, and security is first and foremost. We put a lot of effort into securing Ubuntu. We've created new features as part of where we are taking Ubuntu. Many of the new features we created around Ubuntu are about updates, security updates, being able to make those updates active without rebooting the system, so zero downtime kernel updates is something we call a live patch service which we deliver in Amazon for Ubuntu Amazon users. Extended security maintenance. Security for Ubuntu after end-of-life, say you said you've been using Ubuntu for a long time. Each Ubuntu release has basically a five year lifecycle but some enterprises actually need to run Ubuntu for much longer than five years, and for those enterprises, we provide security updates after the end of life, after that five-year end-of-life, and in many cases, that helps them bridge that gap until the next release of Ubuntu. We've also worked with IBM and the US government to provide FIPS certified cryptography for Ubuntu also available in Amazon, so the Department of Defense contractors, many federal contractors are required to use FIPS bits, and this actually allows them to bring their Ubuntu usage into compliance with what's required for government regulation. >> I'm so glad that you went from IOT to security in, like, a nanosecond. That was going to be my next question. >> Well that is the only answer to that. It's the only right answer to that question in my mind. >> Not enough companies put that much focus on security and you follow it up with specific concrete examples of things that are going to work. The live kernel patching without rebooting things so that you can have the-- I mean, services in the cloud, it has to be always on. You can't take a maintenance window when something is down four hours or a weekend. That's just not acceptable in the cloud world anymore. >> Especially in the retail season. We are just now getting into the retail-- you know, Black Friday was last week, Cyber Monday this week, and the roll up all the way to Christmas, Canonical works with quite a bit with the largest retailers in the world, Walmart, Best Buy, other ones like that, and downtime is just not acceptable. At the same time, security is of the utmost importance. When you are taking people's credit cards, you are placing large amounts of money on the line every time these transactions take place. Security has to be utmost, and being able to do that without impacting the downtime. Downtime is seriously hundreds of thousands of dollars per second on some of these sites during the major holiday rush. >> You just mentioned some of the big names you're working with, so what kind of assurance can you give them that you can sleep with both eyes closed? You don't have to keep that one eye open. Don't worry, if there is an incident of some kind, we are going to take care of it. If you have a problem, rest assured, we are going to be there because, as you pointed out, with the volume involved and the issues of security infiltrations being what they are today, it's hard to rest. >> Right, the return on value, the return on investment of the live patch is easily apparent. Any time someone does the math and realizes, "Let's actually look at how much it costs us "to reboot a data center, "or how much it costs us to wake up the dev ops team "on a Saturday and have them work through a weekend "to roll out this update," whereas with the live patch, at least the patch is applied in milliseconds without downtime, and then we get back on Monday and we rollout a comprehensive plan as to what do we actually need to do about this going forward? That is for the kernel side of things. The other half of it is the user space side of Ubuntu. In the user space side of Ubuntu, we continue to make Ubuntu smaller, smaller and smaller. That might be one of the reasons you are attracted to Ubuntu on your laptop early on is because we really did a good job of making a Linux that was consumable, usable, but also very small and secure. We've actually taken that same approach in the cloud where we continue to minimize the footprint of Ubuntu. That has a security impact in that if you simply leave software out of the default image you are not vulnerable to problems in that software, so we've heard that quite a bit around the container space, the work we do in the container space. We will be in Austin next week for CUBE Con talking about containers. I will save the container talk for next week, but minimizing Ubuntu is an important of that security story as well. >> All right, just reducing that attack surface is fabulous. It also means that when you are actually doing this patching, it's less things to patch, there are less opportunities for downtime, there are less things that can go wrong and cause outages in the rest of the place. Simple is better. >> Dustin : That's right, that's exactly right. >> What else are you doing? We've talked about security a lot here. What are some of the other things that you are doing around supporting the services that we are hearing here at AWS? We've heard a lot about things like serverless. We've heard a lot about high performance computing. We've had guests here on theCUBE talking about what they are doing around data analytics and machine learning, so maybe you could give us a little bit of color around that. >> Let's start with that last point, machine learning and data analytics. We work very closely with both Amazon and Nvidia to enable the GPGPUs, the general-purpose graphics processing units that Nvidia produces which go into servers and Amazon exposes in the some of the largest machine learning type instances. Those instances powered by Ubuntu are working directly with that GPU out of the box by default, and that's something that we've worked very hard on and closely with both Amazon and Nvidia to make sure the Ubuntu experience when using the graphics accelerated instance types just work, and just work out of the box. Those are important for the machine learning and the data analytics because many of those algorithms take advantage of CUDA. CUDA is a set of libraries that allows developers to write applications that scale very, very wide across the CUDA cores, so a given Nvidia GPU may have several thousand Nvidia CUDA cores. Each of those are running little process bits and then the answers are summed up, basically, at the end. That is at the heart of everything that's happening in the AI space, and that I will tie that back to our IOT space in that for those connected devices where memory discs, CPU, power are very constrained, part of the important part of that connection is that they are talking to a cloud that has essentially infinite resources, infinite data at its disposal, enough memory to load those entire data sets and crunch those. The fastest CPUs and the fastest GPUs that can crunch that data, so to really take that and make that real, that's exactly what's powering every autonomous vehicle in the world, essentially, is a little unit inside of the car, a majority of those autonomous vehicles are running Ubuntu on the auto driving unit. Tesla, Google, Uber, all running Ubuntu inside of that car. Every one of those cars are talking to a cloud. Some clouds are Amazon, other, in Google's case, certainly the Google cloud, but they are talking to GPU Nvidia powered AI instances that are crunching all the data that these Tesla cars and GM, and Ford cars are sending to the cloud and constantly making the inference engine better. What gets downloaded to the car is an updated inference engine. That inference engine comes down to the car, and that's how that car decides is it safe to change lanes right now or not? That answer has to be determined inside of the car, not in the cloud, but you can understand why data training and modeling in the cloud is powerful, far more powerful than what can happen inside of a little CPU in a the car. >> John: Let's just keep it on the right side of the road. Can we do that? (laughing) >> Well, you need to talk to this gentleman about that. >> Yeah, I drive on the left side. (laughing) >> Or the left side of the road. >> Don't cross the streams. >> How about the correct side of the road? >> Don't cross the streams. >> Dustin thanks for the time. >> Thank you, John. >> Always good seeing you. >> Likewise. >> And we'll see you next week as well. Down in your hometown, a little barbecue in Austin. >> That sounds good. >> All right, back with more here at re:Invent. We are live in Las Vegas back with more on theCUBE in just a bit.