>> Hey, welcome back everybody. Jeff Frick here with theCube. We're in Palo Alto, California, at one of the Chertoff events. It's called Security in the Boardroom. They have these events all over the country, and this is really kind of elevating the security conversation beyond the edge, and beyond CISOs to really the boardroom, which is really where the conversation needs to happen. And our next guest, really excited to have We've got Chad Sweet, he's the co-founder and CEO of the Chertoff Group. Welcome Chad. >> Great to be here. >> And with him also Reggie Brothers, he's the principal at the Chertoff Group, and spent a lot of time in Washington. Again you can check his LinkedIn and find out his whole history. I won't go through it here. First off, welcome gentlemen. >> Thank you. >> Thank you. >> So, before we jump in a little bit of-- What are these events about? Why should people come? >> Well, basically they're a form in which we bring together both practitioners and consumers of security. Often it's around a pragmatic issue that the industry or government's facing, and this one, as you just said, priority of security, cyber screening in particular, in the boardroom, which is obviously what we're reading about everyday in the papers with the Petya and NotPetya and the WannaCry attacks, these are basically, I think, teachable moments that are affecting the whole nation. And so this is a great opportunity for folks to come together in a intimate form, and we welcome everybody who wants to come. Check out our website at chertoffgroup.com >> Okay, great, and the other kind of theme here, that we're hearing over and over is the AI theme, right? >> Yeah. >> We hear about AI and machine learning all over the place and we're in Mountain View and there's self-driving cars driving all over the place and Google tells me, like, "you're home now." And I'm like, "Ah, that's great." But there's much bigger fish to fry with AI and there's a much higher level. And Reggie you just came off a panel talking about some much higher level-- I don't know if issues is the right word, maybe issues is the right word, around AI for security. So, I wonder if you can share some of those insights. >> I think issues, challenges, are the right words. >> Challenges, that's probably a better word. >> Those are good words, because particularly you're talking about security application. Whether it's corporate or government the issue becomes trust. How do you trust that this machine has made the right kind of decision, how do you make it traceable. One of the challenges with the current AI technology is it's mostly based on machine-learning. Machine-learning tends to be kind of a black box where you know know what goes in and you train what comes out. That doesn't necessarily mean you understand what's going inside the box. >> Right. >> So then if you have a situation where you really need to be able to trust this decision this machine's making How do you trust it? What's the traceability? So, in the panel we started discussing that. Why is it so important to have this level of trust? You brought up autonomous-vehicles, well of course, you want to make sure that you can trust your vehicle to make the right decision if it has to make a decision at an intersection. Who's it going to save? How do you trust that machine becomes a really big issue. I think it's something that in the machine-learning community, as we learn in the panel, is really starting to grapple with and face that challenge. So I think there's good news, but I think it's a question that when think about what we have to ask when we're adopting these kind of machine-learning AI solutions we have to make sure we do ourself. >> So, it's really interesting, the trust issue, because there's so many layers to it, right? We all get on airplanes and fly across country all the time, right? And those planes are being flown by machines, for the most part. And at the same time if you start to unpack some of these crazy algorithms, even if you could open up the black box, unless you're a data scientist and you have a PhD, in some of these statistical analysis could you really understand it anyway? So how do you balance it? We're talking about the boardroom. What's the level of discovery? What's the level of knowledge that's appropriate without necessarily being a full-fledged data scientist who are the ones that are actually writing those algorithms? >> So I think that's a challenge, right, because I think when you look at the types of ways that people are addressing this trust challenge it is highly technical, alright. People are making hybrid systems where you can do some type of traceability but that's highly technical for the boardroom. I think what's important is that the-- and one thing that we did talk about on the panel and even prior to panel was on cybersecurity and governance, we talked about the importance of being able to speak in a language that everyone-- that the laborers can understand. You can't just speak in a computer science jargon kind of manner. You have to be able to speak to the person that's actually making the decision. Which means you have to really understand the problem, because I think my experience the people that can speak in the plainest language understand the problem the best. So these problems are things that can be explained they just tend not to be explained, because they're in this super technical domain. >> But you know, Reggie is being very humble. He's got a PhD from MIT and worked at the defense advanced research-- >> Well he can open the box. >> He can open the box. I'm a simple guy from Beaumont, Texas, so I can kind of dumb it down for the average person. I think on the trust issue over time whether, and you just mentioned some of it, if you use the analogy of a car or the board room or a war scenario, it's the result. So you get comfortable, you know the first time, I have a Tesla, the first time I let go of the wheel and let it drive it's self was a scary experience but then when you actually see the result and get to enjoy and experience the actual performance of the vehicle that's when the trust can begin. And I think in a similar vein, in the military context, you know, we're seeing automation start to take hold. The big issue will be in that moment of ultimate trust, i.e. do you allow a weapon actually to have lethal decision-making authority, and we just talked about that on the panel, which is the ultimate trust is-- is not really today in the military something that we're prepared to trust yet. I think we've seen in, there's only a couple places, like the DMZ in North Korea where we actually do have a few systems that are, if they actually detect an attack because there's such a short response time, those are the rare exceptions of where lethal authority is at least being considered. I think Elon Musk has talked about how the threat of AI, and how this could, if it's not, we don't have some norms put around it then that trust could not be developed, cause there wouldn't be this checks and balances. So, in the boardroom that last scenario, I think, the boards are going to be facing these cyber attacks and the more that they experience once the attack happens how the AI is providing some immediate response in mitigation and hopefully even prevention, that's where the trust will begin. >> The interesting thing, though, is that the sophistication of the attacks is going up dramatically, right? >> Chad: Yep. >> Why do we have machine-learning in AI? Because it's fast. It can react to a ton of data and move at speeds that we as people can't, such as your self-driving car. And now we're seeing an increase in state-sponsored threats that are coming in, it's not just the crazy kid in the basement, you know, hacking away to show his friend, but you know, now they're trying to get much more significant information, trying to go after much more significant systems. So, it almost begs then that you have to have the North Korean example when your time windows are shorter, when the assets are more valuable and when the sophistication of the attacking party goes up, can people manage it, you know, I would assume that the people role, you know, will continue to get further and further up the stack where the automation takes an increasing piece of it. >> So let's pull on that, right. So if you talk to the Air Force, cause the Air Force does a lot of work on autonomy, DoD General does, but the Air Force has this chart where they show that over time the resource that will be dedicated by a machine, autonomous machine, will increase and resources to a human decrease, to a certain level, to a certain level. And that level is really governed by policy issues, compliance issues. So there's some level over which because of policy and compliance the human will always be in the loop. You just don't let the machine run totally open loop, but the point is it has to run at machine speed. So let's go back to your example, with the high speed cyber attacks. You need to have some type of defensive mechanism that can react at machine speed, which means at some level the humans are out of that part of the loop, but you still have to have the corporate board person, as Chad said, have trust in that machine to operate at this machine speed, out of the loop. >> In that human oversight one of the things that was discussed on on the panel was that interestingly AI can actually be used in training of humans to upgrade their own skills, and so right now in the Department of Defense, they do these exercises on cyber ranges and there's about a 4 month waiting period just to get on the ranges, that's how congested they are. And even if you get on it, if you think about it, right now there's a limited number of human talent, human instructors that can simulate the adversary and oversee that, and so actually using AI to create a simulated adversary and being able to do it in a gamified environment is something that's increasingly going to be necessary to make it, to keep everyone's skills, and to do it real-time 24/7 against active threats that are being morphed over time. That's really where we have to get our game up to. So, watch for companies like Circadence, which are doing this right now with the Air Force, Army, DISA, and also see them applying this, as Reggie said, in the corporate sphere where a lot of the folks who will tell you today they're facing this asymmetric threat, they have a lot of tools, but they don't necessarily trust or have the confidence that when the balloon goes up, when the attack is happening, is my team ready? And so being able to use AI to help simulate these attacks against their own teams so they can show the board actually our guys are at this level of tested-ness and readiness. >> It's interesting Hal's talking to me in the background as you're talking about the cyber threat, but there's another twist on that, right, which is where machines aren't tired, they didn't have a bad day, they didn't have a fight with the kids in the morning. So you've got that kind of human frailty which machines don't have, right, that's not part of the algorithm generally. But it's interesting to me that it usually comes down to, as most things of any importance, right, it's not really a technical decision. The technical pieces was actually pretty easy. The hard part is what are the moral considerations, what are the legal considerations, what are the governance considerations, and those are what really ultimately drive the decision to go or no-go. >> I absolutely agree. One of the challenges that we face is what is our level of interaction between the machine and the human, and how does that evolve over time. You know, people talk about the centaur model, where the centaur, the mythical horse and human, where you have this same kind of thing with the machine and human, right? You want this seamless type of interaction, but what does that really mean, and who does what? What they've found is you've got machines have beaten, obviously, our human chest masters, they've beaten our goal masters. But the things that seems to work best is when there's some level of teaming between the human and the machine. What does that mean? And I think that's going to be a challenge going forward is how we start understanding what that frontier is where the human and machine have to have this really seamless interaction. How do we train for that, how do we build for that? >> So, give your last thoughts before I let you go. The chime is running, they want you back. As you look down the road, just a couple years, I would never say more than a couple years, and, you know, Moore's Law is not slowing down people argue will argue they're crazy, you know, chips are getting faster, networks are getting faster, data systems are getting faster, computers are getting faster, we're all carrying around mobile phones and just blowing off tons of digital exhaust as our systems. What do you tell people, how do boards react in this rapidly evolving, you know, on like an exponential curve environment in which we're living, how do they not just freeze? >> Well if you look at it, I think, to use a financial analogy and almost every board knows the basic foundational formula for accounting which is assets equals liabilities plus equity. I think in the future because no business today is immune from the digital economy every business is being disrupted by the digital economy and it's-- there are businesses that are underpinned by the trust of the digital economy. So, every board I think going forward has to become literate on cybersecurity and Artificial Intelligence will be part of that board conversation, and they'll need to learn that fundamental formula of risk, which is risk equals threat, times vulnerability, times consequence. So in the months ahead part of what the Chertoff Group will be doing is playing a key role in helping to be an educator of those boards and a facilitator in these important strategic discussions. >> Alright, we'll leave it there. Chad Sweet, Reggie Brothers thanks for stopping by. >> Thank you. >> Thank you, appreciate it. >> Alright, I'm Jeff Frick, you're watching theCube. We're at the Chertoff event, it's security in the boardroom. Think about it, we'll catch ya next time.

>> Narrator: Live from San Francisco, it's the Cube. Covering Oracle OpenWorld 2016. Brought to you by Oracle. Now here's your hosts, John Furrier and Peter Burris. >> Hey welcome back everyone, we are here live at Oracle OpenWorld in San Francisco on the show floor. This is the Cube, SiliconANGLE's flagship program. We go out to the events and extract the entrepreneurs I'm John Furrier. Co-seated with me is going to be Peter Burris Head of Research for SiliconANGLE. Also the GM of Wikibon.com our research arm. Our next guest is Reggie Bradford who is a Senior Vice President of Product Development for Oracle Cloud. Reporting for Thomas Kurian who could not make the keynote last night but he did send in the tape during the Diane Bryant thing so that was really good. So hope everything is going well with his family. Welcome to the Cube. >> Thank you, glad to be here. >> Okay so you're a product guy which is great 'cause you're now on the product road map. You get to look at the holistic picture, not so much the go to market which Oracle has that separation. >> Yeah. >> The Cloud is really a conversion of Ironman when you think about it. The stack has to be set up in a way that enables innovation, at the same time preserves the value of what's moving to the Cloud or what get's started >> Yeah. >> in the Cloud. Cloud-Native. Take a minute to describe what Oracle's doing in this regard because you do have a huge install base. >> Yeah. >> And Larry pointed out in the earnings call, they're not yet moving all over yet so Microsoft started their progression. >> Yeah. >> You guys got a huge tsunami coming. >> Yeah. Well I think it's an evolution. It's not a revolution, first of all. So we have 420,000 customers worldwide as you mentioned of substantials installed base. As Larry has mentioned before with Thomas, we've been working on the Cloud applications for over 10 years. We started with a SaaS layer. Now the PaaS layer and the infrastructure layer. I think that if I was to use a sports analogy, we're in the first inning of a nine inning game so we're just getting started. >> First of all we love sports metaphors. I had it at top of the second but okay we'll give early innings. But Fusion ten years ago was kind of pre-cloud although Larry had the famous Churchill Club video I think about ten years ago with the Sun guy saying the Cloud is just a data center with an address that nobody knows. It's essentially that kind of concept. So I can see the progression of the ten year run but something happened four years ago. We could feel it when we were covering it, the show here. You saw Larry on stage almost knowing what's coming. They had not yet released the Fusion base. What's changed in your mind internally? And share with the folks, what's the internal pulse? 'Cause some say you're late to the game. Which you guys refute. You're in top of the second, how late can you be? But how much more work needs to get done? Can you share >> Yeah. >> the internal mojo, mindset, vibe and what work needs to get done? >> Well, I think let's start with it's a 135,000 person company. Not that there's corporate inertia but it's a very large company with a lot of customers that have an existing installed base. I think that we're I definitely don't think that we're late to the Cloud. I think if you look at the work loads that have been done to date. Something like six percent of workloads had been done in the Cloud. But I think that I can't speak for the past. I've been here for four years. My company was acquired. I agree with you. The energy and momentum, the acceleration, the sense of urgency is palpable. And it continues to accelerate. I think there's just this recognition that we feel like we've got a very strong position and a strong hand and we're going to play that. >> One of the things Larry mentioned on his keynote yesterday and which came up today is that Amazon is an environment where you can go to and you've got to do all this work. Oracle, you can just move stuff to Oracle, and it moves to the Cloud instantly. But it still brings up the integration game because it's still a lot more kind of point solutions out there. >> Yeah. >> You can call a startup doing something. >> Yeah. >> An ecosystem as a feature, not a company that would might want to plug into that so how do you bring friction-less integration with a suite mindset? Because essentially Oracle has that gravity. >> Yeah. >> But at the same time you don't want to get stuck in that as an Oracle only solution. >> Absolutely. >> How do you integrate well with others? >> Well first of all I'd say it starts with a mentality that when I was running my startup in 2011, if you think about just the marketing cloud alone, Scott Brinker has the landscape of startups in the Cloud. There was 100 I think back then and I think there's almost 4,000 now. Just in Marketing Cloud alone so the Cloud has opened up a huge era of new startups and innovation and credit card swiping and companies can get into that. That challenge for that is, as Larry said last night, nobody wants to integrate 50 different applications from 50 different companies. I think that we come in with this, we've got all the layers of the stack but we've also got to have a mindset and a mentality being able to be open to best and be -- to bring in end solutions from startups via APIs and making it easy for them to work with us and want to partner with us. I think that's the future for Oracle. >> Do you see Oracle inside or do you see Oracle facilitating other brands? So is it more, going back to what John's point was, is it customary to sit down with an Oracle screen and access stuff? Or is a customer going to sit down with an Oracle framework and know what they're accessing through the partners? >> Well I think it depends on the product and the customer. I'd say we're going to be both. I mean I think we've got the breadth and depth and capability to be it an inside platform type approach or infrastructure but also if you look at an HCM or ERP or Marketing Cloud, we're going to be on the front end. >> Do you anticipate that you're going to go more horizontal as opposed to vertical? So you're going to go from the one infrastructure to the horizontal and then let other folks verticalize? Is that kind of how the thinking is? >> I don't know that we see necessarily a distinction at this point. We obviously have a big industry. You guys have probably talked to them before. Go to Market Group, our entire business unit, but I think we're going to continue to take the market, what the market gives us, and continue to push out our solutions. >> So Reggie, I've talked to a lot of your customers all the time on the Cube and channel partners at Oracle and one of the things that keeps on coming up is that the swim lanes of the database is a big part of the business and you start to see now with the Cloud being more of an integrated IaaS, PaaS and SaaS, the role of database is certainly changing. But it still makes up a big bulk of the business, however you kind of consolidate the numbers. However they fall, the database is 70% roughly the business. My opinion. My analysis. Okay so I wrote a tweet last night, kind of being snarky, but kind of on the whole Tom Brady thing, bringing up sports a analogy. "Free Tom Brady," I said, "Free Database." (laughing) Meaning that one of the thesis that the Wikibon research have come up with is that with free data, you have more data exposed for potential use and by having locked in data, you can still manage the systems of record and then start getting at a whole new set of engagement data that could then spawn another set of innovation on top of it. This is clearly where the market's going in memory and whatnot. So question: What's going on with the database? How do you talk the customers into saying okay the database is going to be fine, use some other databases, they'll still work with Oracle. How do you have that conversation? Are you breaking down that swim lane, broadening the swim lane for the database team? >> Yeah I think from a business model standpoint, to use your Tom Brady analogy tweet. >> The database is suspended for four games? (laughing) >> I don't want to make any declarations on the future business models but I think the fundamental underpinnings of a lot of these new capabilities that are enabled with data, whether it's AI, machine learning, internet of things, I think that those are going to be best leveraged when you've got the broadest and deepest swath of internal and external third party data. And we feel like we've been in that business from day one forty years ago and now we have the broadest suite or capability and data and integrating that data and making it easy to consume and use. >> It just seems that the old move that Oracle made, which I thought was brilliant, the database business, and web logic was a nice sticky component of that, allowed the extensibility. So we're seeing that same dynamic in the Cloud where we want some reliability, we want some high quality. As Larry said yesterday, it's hard to do what you do, I get that. But at the same time there's a growth opportunity, an innovation strategy for Oracle and your partners. Developing an ecosystem or potentially a channel partner. >> Yeah. >> We need to see that thing so do you guys talk about that in the product group and what specifically does that translate to in terms of new features, new focus? >> Yeah we've got a very robust data cloud strategy which is leading in the internal and external third party. Marrying those data sets together and integrating those into our product suite on the applications side. Specifically around the database, opening that up to third parties and how that evolves, I think there's going to be more to come on that. >> What's the biggest thing that people are missing when they try to understand and squint through the Oracle breadth of massive size? When you look at the Cloud strategy, the numbers aren't really killing it. It's four billionth for Oracle. I mean it's still small relative to the big piece of the pie with a lot more growth to go. If that should be comforting to Wall Street at least but from a market perspective, what does the Cloud mean? I mean how do you have that conversation? >> I think that what's missing is that if this was a stand alone company it would be an incredibly viable IPO-able company with a growth rate faster than anybody would scale on the Cloud. Growing double the growth rate. I think another unknown is that we sell a lot of product to companies under 500 million in revenue. 75% of the user base, of the customer base, is under 500 million in revenue so we call that small to mid-size business so everybody thinks Oracle is only an enterprise class company. We are enterprise class but we also scale down and I think that's part of the announcement you've seen today. >> And the new net, new customers are higher than they were. >> Exactly. >> And the growth thing I'm like, okay you know 77% from where you were, I doubled my market share from one to two percent. I mean, percentage is a good benchmark, I get that, but at the end of the day the numbers are the numbers so Cloud-Native is attractive But it's hard. We were talking about it in our intro. It's hard for companies to get there. >> Yeah. >> They have their own inertia. So we're really trying to understand, what's the path for the customer? When you talk to a customer, and think about the customer from a product that you just roll out products, they want that bridge. Is that the past layer? How do you guys -- >> Well we try not to define it. I think it can be challenging because we do have so much product. >> Yeah. >> And we cover so much ground but that's what makes us so successful and that's why companies rely on us. I think the good new is, we have the most flexible platform. If you want to move some of your workloads, you want to move some of your applications to the Cloud, you want to do a hybrid, you want to transition over time, we've said a 100% of our customers are going to move to the Cloud and a 100% of our applications are going to run in the Cloud. But we haven't set a time table on that. >> I want to spend the rest of the time of the segment, to talk about your entrepreneurial background. You sold the company to Oracle four years ago, so you've been in the system for four years but prior to that, you had to be nimble and you also did some acquisitions. I don't know if they were hires but ultimately you're putting together a lot of stuff. So dealing with different product road maps. So two questions: One is how does that go on today? Is there any agile to that in terms of doing that? Is it hard? Is it easier today than it was before? And two: For startups out there, there are a lot of startups that aren't going to make it. They're not going to be the unicorn. They're not going to be that big company but they might be a nice 10 million dollar business. But it's looking for an ecosystem. >> Yeah. So the second part, which I'm going to take first is I'm a startup, I'm not going to make it to the IPO. Maybe it's a lifestyle business, cash small business whatever the word, I need a home. I need an ecosystem. It would appear that you guys would be a good fit for those kinds of companies. Can you share your thoughts on what those entrepreneurs should be thinking? Actions they can take? >> Yeah I mean I think first of all this is Reggie speaking and not Oracle but as a startup, find a big addressable market opportunity that nobody has. I know it's easier said than done. Surround yourself with great people and focus. I think the biggest challenge that startups face is they try to do too many things or be all things to all people. If you can find that niche, yes you know I've been part of -- We've acquired, personally speaking we've acquired many, many, many companies that fill a particular niche. It's easier for us to acquire and to integrate than it is for us to go build it ourselves. I think that's the mantra. >> So the first part of the question, now that you have that entrepreneurs, how's that translate inside Oracle? Because if you think about it, Oracle also does a lot of M&A. A lot of organic growth as well with R&D but you have to kind of pull those together. Does the data cloud, is there new fabric that gets developed so it's not like -- You know some startups go, you be by yourself for a little while and then some get integrated in quickly. Is there a way for an environment to be agile in the sense that you can just plug these new opportunities in. >> Well I would say again having gone through three acquisitions, and this is the God's honest truth, Oracle knows how to acquire companies better than -- certainly it's been the best experience that I've had over the other two. We can always improve. You know a lot of times you read about or follow the big tape deals. You know the NetSuites of the world and that but there's a lot of smaller companies that get acquired and I think that there's a very solid methodology and approach that we take that enables us to capture the value of these startups and make them feel like they're part of a broader company. More than half of the employees at Oracle have come through acquisitions. >> Yeah. Reggie, final question for the folks watching. What's the one thing they may not know about the Oracle Cloud that they should know about? >> Again, what I think that they probably don't know is we are working with companies that have as few as one or two employees that are using our cloud right now. So we're not just a company that's only available to enterprise. We are contemporizing our offering for companies of all sizes that want to deliver better quality and to lower cost. >> Cloud for all. >> Cloud for all. Exactly. (laughing) Democratizing the Cloud. (laughing) >> I wish we had more time. I'd love to dig into the developer conversation. How you guys were with developers. Any quick comment on the developer angle? >> We've always >> You own Java so it's like-- >> Yeah, we've always sought developers and I think if anything, you're going to see us push further towards that community. It's so vital and important for us to develop new products to integrate and create more capability. >> Looking forward to following up on that. Thanks for coming in and sharing your insight inside the Cube. Really appreciate it. >> Thanks for having me. >> Reggie Bradford here inside the Cube at Oracle OpenWorld live in San Francisco. More coverage. Three days of wall to wall live coverage. 35 segments. I just saw CNBC packing it up. They only had a few interviews and they go. So it looks like we won first round. Day one of the bake off between Bloomberg and CNBC. You're watching the Cube. Be right back with more after this short break. (upbeat electronic music) >> I remember

(mumbling) >> Voiceover: Covering Sapphire now. Headline sponsored by SAP HANA Cloud, the leader in platform as a service. With support from Console Inc., the cloud internet company. Now, here are your hosts, John Furrier and Peter Burris. >> We are here live at SAP Sapphire. This is SiliconANGLE Media's The Cube. It's our flagship program. We go out to the events and extract the signal to noise and want to do a shoutout to our sponsors SAP HANA Cloud and Console Inc. at console cloud, connecting the clouds together. I'm John Furrier with my co-host Peter Burris. Our next guest is Reggie Jackson, winner, athlete, tech athlete now, entrepreneur, overall great guy, and a cube alumni. Four years ago, we interviewed him here at SAP Sapphire. Welcome back, Reggie, to The Cube. Thanks for coming on. John, thank you very much. It's good to be here with old friends. We were havin' a little conversation about baseball there, but good to see you guys. Yeah, and obviously, the baseball, we were just talkin' about the whole fisticuffs and the glee of the grand slam walk-off. >> Reggie: Good stuff, good stuff. >> It's a good pivot point in some of the things that you're workin' on in here, the conversations in the tech world, which is social media and that notion of celebrating in a world of Instagram and Snapchat and social media. Certainly, ya flip the bat, the views go up. But then, baseball has these (laughing) unwritten rules, right. So does corporations. And so we're now a new era. Is baseball safe now with these unwritten rules and should they maintain those, certain things that have kept the game in balance? But yet with social media, the players are their own brand. And you certainly were a brand, even back in your day, which is a pioneer. What's your thoughts on that? >> You know John, Peter, I don't like the idea of someone going out of their way to promote their brand. Some of the great brands to me in history, Babe Ruth, Ty Cobb, the great Jim Brown, Joe Montana, Michael Jordan. And Michael Jordan would be a prominent example where technology and TV enhanced who he was. And he had someone behind him to enhance his brand, Nike, Phil Knight, who was a real pioneer. I'm not so in favor, I'm not in favor at all of someone manufacturing themselves as a brand. And I hear players talk about their brand and about trying to create something. If you're great, if you deserve it, I don't think Stephen Curry works on his brand. I think he works on bein' a great player. I think he works on bein' a great teammate. I think he does his best to maximize his skill set. And he's nothing but a gentleman along the way. He'll celebrate with joy once in awhile, with the Curry moves, which we've come to recognize. But for guys that talk about the manufacturing of their brand, there's something about it that's manufactured. It's not real, it's false. And I don't like it. I think it's okay, the Snapchats and the Google+ and all of the stuff, Twitter and Facebook and all that stuff, all of the things that go along with trying to create some hubbub, etc. I'm okay with that. >> So you're saying if it's not deserved. People are overplaying their hand before earning it. >> A lot of it, John, a lot of it. Joe Montana didn't work on his brand, he was great. Jim Brown didn't work on his brand, he was great. I don't want to use Jimmy Brown. I want to use Montana because even young people today will know Joe Montana. Tom Brady, Peyton Manning, they're not about their brand. They're about being classy, being great, being part of a team, being a leader, presenting themselves as something that's respected in the NFL, across the United States. Go ahead, Pete. >> So even though it's cheaper to get your name out there, you still believe in let your performance speak for itself. >> You got to be real about it. Ya got to be who you are. If you're not a great player, get out of the way. Get out of the space. So manufacturing your brand. I played with the Yankees. I was in the era of Cosell and Billy Martin and George Steinbrenner. We won championships with the team. I was part of something that helped me become recognized. And so in our era, the Sandy Koufax's became brands because they were associated with greatness around them. They stood out and so they earned that tremendous brand. >> We were just watching Graig Nettles gettin' taken out by George Brett in that big game and also the pine tar, we kind of gettin' some good laughs at it. You look at the balance of personalities. Certainly, Brett and Nettles and your team and you had a great personality, winning championships. Worked together as a team. And so I want to ask you that question about the balance, about the in baseball, certainly, the unwritten rules are a legacy and that has worked. And now in a era of personalities, in some cases, people self-promoting themselves, people are questioning that. Your thoughts on that because that applies to business too 'cause tech athletes or business athletes have a team, there are some unwritten rules. Thoughts on this baseball debate about unwritten rules. >> Pete and John, I'll try to correlate it between some tech giants that have a brand. I just left a guy with a brand, Bill McDermott, that runs SAP. Even Hasso, the boss. The face now of SAP is Bill McDermott. Dapper, slender, stylish, bright. It comes across well. So maintaining that brand, to me, relates to SAP, bills a great image for it. He's stylish, he's smooth, he's smart. He's about people. He presents himself with care. So that is a brand. I don't think it's manufactured. That's who he is in real life. If you take a look, and I'll go back to Steph Curry because that name resonates and everyone recognize it. That style of cool, that style of control, that style of team and care. And he presents to us all that he cares about us, the fan, his team, his family. And so those are things and I think you can go from the tech world. Bill Gates had a brand. Brilliant, somewhat reclusive, concerned about the world, concerned about the country, concerned about his company. And so that resonated it Microsoft because that's who he really was. Some of the people today don't really recognize that Jobs was thrown out of Apple. He was pushed out. All of his brilliance, which was marketing. And the gentleman there that really was the mind for the company, Steve Wozniak, happens to be here at SAP Sapphire. Today, I think he speaks. But those brands were real, not manufactured. And so, in today's world, I think you can manufacture a brand. And then all of a sudden, it'll crumble. It'll go away in the future. But the great brands of whether it's Jackie Robinson or whether it's Jack Welch or whether it's George Steinbrenner and the Yankee brand, those brands were real. They were not manufactured. Those guys were eccentric. They were brilliant. Go ahead. >> And also, they work hard. And I want to point out a comment you made yesterday here at the event. You were asked a question up on stage about that moment when you hit the home runs. I think we talked about it last time. I don't necessarily want to talk about the home runs. But you made a comment I'd like you to expand on and share with the audience. 'Cause you said, "I worked hard," but that day during warm-ups, you had batting practice. You made a comment that you were in the zone. So working hard and being great as it leads up to that. But also, in the moment, 'cause that's a theme these days, in the moment, being ready and prepared. Share your thoughts on what you meant by you had a great batting practice and you just felt it. >> I'm going to take it to what you say is in the moment. I remember when I was talkin' about it yesterday, which you reference to, when I had such a fantastic batting practice. I walked by a coupla sports writers in that era. Really well-known guys, Dave Anderson, New York Times. I can't think of his name right now, but it'll come to me, of the Daily News. It was like hey man. >> John: You were rockin' it out there. >> I kind of hope I didn't leave it out here. (laughing) That was in the moment and at the same time, >> I mean, you were crushing it. >> Yes, when the game started, I got back in that moment. I got back in what was live, what was now, what was going on. Certainly, I think our world now with the instant gratification of sending out a message or tweeting to someone or whatever certainly in the moment is about what our youth is and who we are today as a country, as a universe. >> But you didn't make that up. You worked hard, but you pulled it together in the moment. >> A comment with that is I went and did something with ESPN earlier this year in San Francisco, in Oakland with Stephen Curry. They said, "Reggie, we want ya to come up "and watch his practice, his pre-game." And it was very similar to your batting practice, where people come out and watch, etc. And so I was looking forward to it and I like to go to the games about an hour and a half or two hours early so I can see warm-up and see some of the guys and say hello. And I got a chance to watch Steph Curry. I know his dad. And happened to be the first time I went this year, the dad, Carolina, the Panthers were in town. Not the Panthers. Come on, help me, help me, help me. >> Peter: The Wizards? >> No, no, no, the Carolina. >> Peter: Carolina Panthers. >> The Carolina Hornets. >> John: Hornets. >> Were there and I know his dad, Dell Curry. And we talked a little bit. But then, Steph came out and I watched him. And I watched the dribbling exhibition. I watched the going between the legs and behind the back and the fancy passing, etc. And I watched the shots, the high-arcing threes, the normal trajectory threes, the high shots off the backboard and things like that that he did. The left-handed shots, the right-handed shots. And the guy asked me what I thought of the show. And I said, "Well, it's a cool show, "but I'm going to see all that tonight." And me watching him, the behind the backs, the between the legs, the passes, the high-arching shots from three, the high-arching touches off the glass. He does all that. >> John: He brought it into the game. >> Yeah, I said so, (laughing) >> Peter: That is his game. >> It's not a show, but that's his game. >> So Reggie, you did an interesting promotion, Reggie's Garage, where you bought a virtual reality camera and you created a really nice show of your garage demonstrating your love >> Reggie: 360. >> Peter: of cars, 360. Talk a little bit about that. And then if ya get a second, imagine what baseball's going to be like as that technology becomes available and how some of the conversation that we're having about authenticity, the fan coming into the game. >> An experience. >> Is going to change baseball. Start with the garage and how that went and then how ya think that's going to translate into baseball, if you've had any thoughts on that. >> In the technology that was used, certainly I enjoyed it. While I was doing it, I noticed where the cameras were in different spots. There was one on the floor of my car. There was one in the backseat. And then there was someone following us as closely as they could. But you could see everything. You'd see the shift and you could see my feet. It was like you were with me. When we did the 360 inside the garage as well, you could listen to me and then you could use your finger and spin around. And they had these special headset and special glasses that you could look around, just with your headset on, and see all around the room. Behind you, in front of you. And so it's an experience that I think is going to become part of who we are as a nation, who we are as a people watching television, that you're going to really feel like you're in the room. I think it's going to be exciting. And I think it's going to be fun. And when you're talking about products, when you're talking about my website, if you will, with the focus on automotive parts, where a guy can go in and shop and get any part he wants for a vehicle, you really can build a complete car from my website. You can buy a frame. You can buy body parts. You can buy a horn, an engine, brakes, tires, grills, turn signals, the whole nine yards. And it gives you an experience through 360 video of really walking into the store, walking into the building, walking into the stadium and looking around to see the hot dog stand, see the dugout, see the pitcher and the hitter, to see the parts in the garage, to see the cars and take a look and view at everything that's there. >> How are players going to react to havin' the fans virtually right there with them? >> I don't think it bothers you. I don't think ya notice. I don't think they'll show anything that will affect the player that he's going to be concerned about. I think you'd have to be sensitive if they start microphoning, start micing up and then the looseness of the language would impact. So I don't think they'll go that far. But I do think the more that you can see, the more attractive the game becomes, the more interested that you can get people. When I broadcast baseball for ABC back in the 80's, I always tried to broadcast for the lady of the house, while she worked, while she cooked the meal, she didn't have time to think about a backup slider or the fastball that painted the outside corner, the changeup, etc., the sinker. I tried to broadcast for her interpretation so I could attract another fan to the game. So I think that the technology and the viewing that you'll see from behind home plate, from under the player's feet while he's running down the bases and the slides and things of that nature, Pete, I think are going to be exciting for the fan and it'll attract more fans, attract a new type of television it's going to produce, etc. So it's exciting. >> Reggie, thanks for comin' on The Cube again. Appreciate your time. I ask ya final two questions that I want to get your thoughts on. One is obviously the cars. Reggie's Garage is goin' great. And you shared with us last time on The Cube, it's on YouTube, about you when you grew up and decide football and baseball. But when you were growin' up, what was your favorite car? What was that car that you wanted that was out of reach? That car that was your hot rod? And then the second question is, we'll get to the second question. Answer that one first. What was you dream car at the time? How did ya get >> Reggie: The dream car >> John: hooked on this? >> at the time. I had a '55 Chevrolet that I bought from a buddy by the name of Ronny Fog. I don't even know if he's still around anymore. Out of Pennsylvania. I had $300 and my dad gave me $200. I'd saved up mine from workin' for my dad. But my dream car was I went to school with a guy named Wayne Gethman and another guy named Irwin Croyes. I don't know Wayne Gethman anymore. But from the age of 16, I reengaged with Irwin Croyes, who happens to be a business investing type guy in the city of Philadelphia, right where we're still from. He's a car collector. And he drove a '62 Corvette and so did Wayne Gethman. And I always wanted one. And I now happen to have four. (laughing) >> He who get the most toys wins. Final question, 'cause you're such a legend and you're awesome and you're doin' so much work. And you're very active, engaged, appreciate that. Advice to young athletes coming up, whether they're also in business or a tech athlete or a business athlete. But the sports athletes today got travel ball, you got all this stuff goin' on. The idols like Stephen Curry are lookin' great. Great role models now emerging. What advice do you give them? >> John's got a freshman in high school. I got a junior in high school. What would ya say to 'em? >> You know, I'll tell ya. When you're young, the people you want to listen to are Mom and Dad. No one, and I'll say this to any child from the age of eight or nine years old, five, six years old to 17, 18, 19, 20, all the way up, now my daughter's 25. All the way up to the end of your parents' days. No one cares for you more than your mother or your father. Any parent, whether it's a job or whether their success in life, number one in that man or woman, mom or dad, number one in their life is their children. And so for kids, I say if there's any person you're going to listen to for advice in any path you want to walk down, it's the one that your parents talk to you about or how they show you. That is what I would leave as being most important. For kids, anything, idea that you have that you believe you can do, whether it's the athlete like Stephen Curry that has created shots and done things on the basketball court that he envisioned, that he thought about. Or whether it's the next Steve Jobs who happens to be Mark Zuckerman, who I don't know Mark is 30 years old yet. >> John: He just turned 30. >> It's an idea. He's born around the same time. He's born this week. His birthday is in this week. My birthday's tomorrow. >> John: Happy birthday. >> But thank you. Anything that you can think of in today's world of technology. With places like Silicon Valley where they take dreams and create foundations for them. I had a dream about a website that would sell automotive parts and you could go to my site and buy anything for your car. We've got about 75,000 items now. We'll get to 180,000 in a few months. We'll get to a half a million as soon as my technology is ready for it. But we have things to pay attention to and look into and issues to make sure that we iron out that aren't there for our consumer, for ease of navigation, ease of consumption and purchasing. Any idea that you have, take time to dream. It's much more so than taking time to dream when I was a young kid. Because my father would say, "Stop daydreamin' "and wastin' time." >> John: Get to work. >> Reggie: In today's world, for our children, I say take time to create a vision or to create something new. And go to someone that's in the tech world and they'll figure out a way of helping you manifest it into something that's a reality. >> Listen to your parents, kids. And folks out there, dream, build the foundation, go for it. Reggie Jackson, congratulations for being a Cube alumni again, multi-return. >> Peter: Thank you very much. >> John: Appreciate it. Congratulate on all your continued success. You're a legend. Great to have you on. And thanks so much for comin' on The Cube. >> Peter: And happy 70th birthday. >> John, Pete, always a pleasure. >> John: Happy birthday. >> Thank you very much. >> Have some cake for Reggie. It's The Cube, live here in Orlando. Bringin' all the action here on The Cube. I'm John Furrier with Peter Burris with Reggie Jackson. We'll be right back. (electronic music)

>>From around the globe. It's the cube with digital coverage of an AI ops virtual forum brought to you by Broadcom. >>Welcome to the AI ops virtual forum. Finally, some Artan extended to be talking with rich lane now, senior analyst, serving infrastructure and operations professionals at Forrester. Rich. It's great to have you today. >>Thank you for having me. I think it's going to be a really fun conversation to have today. >>It is. We're going to be setting the stage for, with Richard, for the it operations challenges and the need for AI ops. That's kind of our objective here in the next 15 minutes. So rich talk to us about some of the problems that enterprise it operations are facing now in this year, that is 2020 that are going to be continuing into the next year. >>Yeah, I mean, I think we've been on this path for a while, but certainly the last eight months has, uh, has accelerated, uh, this problem and, and brought a lot of things to light that, that people were, you know, they were going through the day to day firefighting as their goal way of life. Uh, it's just not sustainable anymore. You a highly distributed environment or in the need for digital services. And, you know, one of them has been building for a while really is in the digital age, you know, we're providing so many, uh, uh, the, the interactions with customers online. Um, we've, we've added these layers of complexity, um, to applications, to infrastructure, you know, or we're in the, in the cloud or a hybrid or multi-cloud, or do you know you name it using cloud native technologies? We're using legacy stuff. We still have mainframe out there. >>Uh, you know, the, just the, the vast amount of things we have to keep track of now and process and look at the data and signals from, it's just, it's a really untenable for, for humans to do that in silos now, uh, in, in, you know, when you add to that, you know, when companies are so heavily invested in gone on the digital transformation path, and it's accelerated so much in the last, uh, year or so that, you know, we're getting so much of our business in revenue derived from these services that they become core to the business. They're not afterthoughts anymore. It's not just about having a website presence. It's, it's about deriving core business value from the services you're providing to your, through your customers. And a lot of cases, customers you're never going to meet or see at that. So it's even more important to be vigilant. >>And on top of the quality of that service that you're giving them. And then when you think about just the staffing issues we have, there's just not enough bodies to go around it in operations anymore. Um, you know, we're not going to be able to hire, you know, like we did 10 years ago, even. Uh, so that's where we need the systems to be able to bring those operational efficiencies to bear. When we say operational efficiencies, we don't mean, you know, uh, lessening head count because we can't do that. That'd be foolish. What we mean is getting the head count. We have back to burping on and higher level things, you know, working on, uh, technology refreshes and project work that that brings better digital services to customers and get them out of doing these sort of, uh, low, uh, complexity, high volume tasks that they're spending at least 20%, if not more on our third day, each day. So I think that the more we can bring intelligence to bear and automation to take those things out of their hands, the better off we are going forward. >>And I'm sure those workers are wanting to be able to have the time to deliver more value, more strategic value to the organization, to their role. And as you're saying, you know, was the demand for digital services is spiking. It's not going to go down and as consumers, if w if we have another option and we're not satisfied, we're going to go somewhere else. So, so it's really about not just surviving this time right now, it's about how do I become a business that's going to thrive going forward and exceeding expectations that are now just growing and growing. So let's talk about AI ops as a facilitator of collaboration, across business folks, it folks developers, operations, how can it facilitate collaboration, which is even more important these days? >>Yeah. So one of the great things about it is now, you know, years ago, have I gone years, as they say, uh, we would buy a tool to fit each situation. And, you know, someone that worked in network and others who will somebody worked in infrastructure from a, you know, Linux standpoint, have their tool, somebody who's from storage would have their tool. And what we found was we would have an incident, a very high impact incident occur. Everybody would get on the phone, 24 people all be looking at their siloed tool, they're siloed pieces of data. And then we'd still have to try to like link point a to B to C together, you know, just to institutional knowledge. And, uh, there was just ended up being a lot of gaps there because we couldn't understand that a certain thing happening over here was related to an advantage over here. >>Um, now when we bring all that data into one umbrella, one data Lake, whatever we want to call it, a lot of smart analytics to that data, uh, and normalize that data in a way we can contextualize it from, you know, point a to point B all the way through the application infrastructure stack. Now, the conversation changes now, the conversation changes to here is the problem, how are we going to fix it? And we're getting there immediately versus three, four or five hours of, uh, you know, hunting and pecking and looking at things and trying to try to extrapolate what we're seeing across disparate systems. Um, and that's really valuable. And in what that does is now we can change the conversation for measuring things. And in server up time and data center, performance metrics as to how are we performing as a business? How are we overall in, in real time, how are businesses being impacted by service disruption? >>We know how much money losing per minute hour, or what have you, uh, and what that translate lights into brand damage and things along those lines, that people are very interested in that. And, you know, what is the effect of making decisions either brief from a product change side? You know, if we're, we're, we're always changing the mobile apps and we're always changing the website, but do we understand what value that brings us or what negative impact that has? We can measure that now and also sales, marketing, um, they run a campaign here's your, you know, coupon for 12% off today only, uh, what does that drive to us with user engagement? We can measure that now in real time, we don't have to wait for those answers anymore. And I think, you know, having all those data and understanding the cause and effect of things increases, it enhances these feedback loops of we're making decisions as a business, as a whole to make, bring better value to our customers. >>You know, how does that tie into ops and dev initiatives? How does everything that we do if I make a change to the underlying architectures that help move the needle forward, does that hinder things, uh, all these things factor into it. In fact, there into the customer experience, which is what we're trying to do at the end of the day, w w whether operations people like it or not, we are all in the customer experience business now. And we have to realize that and work closer than ever with our business and dev partners to make sure we're delivering the highest level of customer experience we can. >>Uh, customer experience is absolutely critical for a number of reasons. I always kind of think it's inextricably linked with employee experience, but let's talk about long-term value because as organizations and every industry has pivoted multiple times this year and will probably continue to do so for the foreseeable future, for them to be able to get immediate value that let's, let's not just stop the bleeding, but let's allow them to get a competitive advantage and be really become resilient. What are some of the, uh, applications that AI ops can deliver with respect to long-term value for an organization? >>Yeah, and I think that it's, you know, you touched upon this a very important point that there is a set of short term goals you want to achieve, but they're really going to be looking towards 12, 18 months down the road. What is it going to have done for you? And I think this helps framing out for you what's most important because it'd be different for every enterprise. Um, and it also shows the ROI of doing this because there is some, you know, change is going to be involved with things you're gonna have to do. But when you look at the, the, the longer time horizon of what it brings to your business as a whole, uh it's to me, at least it all seems, it seems like a no brainer to not do it. Um, you know, thinking about the basic things, like, you know, faster remediation of, of, uh, client impacting incidents, or maybe, maybe even predictive of sort of detection of these incidents that will affect clients. >>So now you're getting, you know, at scale, you know, it's very hard to do when you have hundreds of thousands of optics of the management that relate to each other, but now you're having letting the machines and the intelligence layer find out where that problem is. You know, it's not the red thing, it's the yellow thing. Go look at that. Um, it's reducing the amount of finger pointing and what have you like resolved between teams now, everybody's looking at the same data, the same sort of, uh, symptoms and like, Oh yeah, okay. This is telling us, you know, here's the root cause you should investigate this huge, huge thing. Um, and, and it's something we never thought we'd get to where, uh, this, this is where we smart enough to tell us these things, but this, again, this is the power of having all the data under one umbrella >>And the smart analytics. >>Um, and I think really, you know, it's a boat. Uh, if you look at where infrastructure and operations people are today, and especially, you know, eight months, nine months, whatever it is into the pandemic, uh, a lot of them are getting really burnt out with doing the same repetitive tasks over and over again. Um, just trying to keep the lights on, you know, we need, we need to extract those things for those people, uh, just because it just makes no sense to do something over and over again, the same remediation step, just we should automate those things. So getting that sort of, uh, you know, drudgery off their hands, if you will, and, and get them into, into all their important things they should be doing, you know, they're really hard to solve problems. That's where the human shine, um, and that's where, you know, having a, you know, really high level engineers, that's what they should be doing, you know, and just being able to do things I >>Think in a much faster, >>In a more efficient manner, when you think about an incident occurring, right. In, in a level, one technician picks that up and he goes and triaged that maybe run some tests. He has a script, >>Uh, or she, uh, and, >>You know, uh, they open a ticket and they enrich the ticket. They call it some log files. They can look up for the servers on it. You're in an hour and a half into an incident before anyone's even looked at it. If we could automate all of that, >>Why wouldn't we, that makes it easier for everyone. Um, >>Yeah. And I really think that's where the future is, is, is, is bringing this intelligent automation to bear, to take, knock down all the little things that consume the really, the most amount of time. When you think about it, if you aggregate it over the course of a quarter or a year, a great deal of your time is spent just doing that minutiae again, why don't we automate that? And we should. So I really think that's, that's where you get to look long-term. I think also the sense of we're going to be able to measure everything in the sense of business KPIs versus just IT-centric KPIs. That's really where we going to get to in the digital age. And I think we waited too long to do that. I think our operations models were all voted. I think, uh, you know, a lot of, a lot of the KPIs we look at today are completely outmoded. They don't really change if you think about it. When we look at the monthly reports over the course of a year, uh, so let's do something different. And now having all this data and the smart analytics, we can do something different. Absolutely. I'm glad >>That you brought up kind of looking at the impact that AI ops can make on, on minutiae and burnout. That's a really huge problem that so many of us are facing in any industry. And we know that there's some amount of this that's going to continue for a while longer. So let's get our let's leverage intelligent automation to your point, because we can to be able to allow our people to not just be more efficient, but to be making a bigger impact. And there's that mental component there that I think is absolutely critical. I do want to ask you what are some of these? So for those folks going, all right, we've got to do this. It makes sense. We see some short-term things that we need. We need short-term value. We need long-term value as you've just walked us through. What are some of the obstacles that you'd say, Hey, be on the lookout for this to wipe it out of the way. >>Yeah. I, I think there's, you know, when you think about the obstacles, I think people don't think about what are big changes for their organization, right? You know, they're, they're going to change process. They're going to change the way teams interact. They're they're going to change a lot of things, but they're all for the better. So what we're traditionally really bad in infrastructure and operations is communication, marketing, a new initiative, right? We don't go out and get our peers agreement to it where the product owner is, you know, and say, okay, this is what it gets you. This is where it changes. People just hear I'm losing something, I'm losing control over something. You're going to get rid of the tools that I have, but I love I've spent years building out perfecting, um, and that's threatening to people and understandably so because people think if I start losing tools, I start losing head count. >>And then, whereas my department at that point, um, but that's not what this is all about. Uh, this, this isn't a replacement for people. This isn't a replacement for teams. This isn't augmentation. This is getting them back to doing the things they should be doing and less of the stuff they shouldn't be doing. And frankly, it's, it's about providing better services. So when in the end, it's counterintuitive to be against it because it's gonna make it operations look better. It's gonna make us show us that we are the thought leaders in delivering digital services that we can, um, constantly be perfecting the way we're doing it. And Oh, by the way, we can help the business be better. Also at the same time. Uh, I think some of the mistakes people really don't make, uh, really do make, uh, is not looking at their processes today, trying to figure out what they're gonna look like tomorrow when we bring in advanced automation and intelligence, uh, but also being prepared for what the future state is, you know, in talking to one company, they were like, yeah, we're so excited for this. >>Uh, we, we got rid of our old 15 year old laundering system and the same day we stepped a new system. Uh, one problem we had though, was we weren't ready for the amount of incidents that had generated on day one. And it wasn't because we did anything wrong or the system was wrong or what have you. It did the right thing actually, almost too. Well, what it did is it uncovered a lot of really small incidents through advanced correlations. We didn't know we had, so there were things lying out there that were always like, huh, that's weird. That system acts strange sometimes, but we can never pin it down. We found all of those things, which is good. It goes, but it kind of made us all kind of sit back and think, and then our readership are these guys doing their job. Right? >>And then we had to go through an evolution of, you know, just explaining we were 15 years behind from a visibility standpoint to our environment, but technologies that we deployed in applications had moved ahead and modernized. So this is like a cautionary tale of falling too far behind from a sort of a monitoring and intelligence and automation standpoint. Um, so I thought that was a really good story for something like, think about as Eagle would deploy these modern systems. But I think if he really, you know, the marketing to people, so they're not threatened, I think thinking about your process and then what's, what's your day one and then look like, and then what's your six and 12 months after that looks like, I think settling all that stuff upfront just sets you up for success. >>All right. Rich, take us home here. Let's summarize. How can clients build a business case for AI ops? What do you recommend? >>Yeah. You know, I actually get that question a lot. It's usually, uh, almost always the number one, uh, question in, in, um, you know, webinars like this and conversations that, that the audience puts in. So I wouldn't be surprised, but if that was true, uh, going forward from this one, um, yeah, people are like, you know, Hey, we're all in. We want to do this. We know this is the way forward, but the guy who writes the checks, the CIO, the VP of ops is like, you know, I I've signed lots of checks over the years for tools wise is different. Um, and when I guide people to do is to sit back and, and start doing some hard math, right. Uh, one of the things that resonates with the leadership is dollars and cents. It's not percentages. So saying, you know, it's, it brings us a 63% reduction and MTTR is not going to resonate. >>Uh, Oh, even though it's a really good number, you know, uh, I think what it is, you have to put it in terms of avoid, if we could avoid that 63%. Right. You know, um, what does that mean for our, our digital services as far as revenue, right. We know that every hour system down, I think, uh, you know, typically in the market, you see is about $500,000 an hour for enterprise. We'll add that up over the course of the year. What are you losing in revenue? Add to that brand damage loss of customers, you know, uh, Forrester puts out a really big, uh, casino, um, uh, customer experience index every year that measures that if you're delivering good Udall services, bad digital services, if you could raise that up, what does that return to you in revenue? And that's a key thing. And then you just look at the, the, uh, hours of lost productivity. >>I call it, I might call it something else, but I think it's a catchy name. Meaning if a core internal system is down say, and you know, you have a customer service desk of a thousand customer service people, and they can't do that look up or fix that problem for clients for an hour. How much money does that lose you? And you multiply it out. You know, average customer service desk person makes X amount an hour times this much time. This many times it happens. Then you start seeing the real, sort of a power of AI ops for this incident avoidance, or at least lowering the impact of these incidents. And people have put out in graphs and spreadsheets and all this, and then I'm doing some research around this actually to, to, to put out something that people can use to say, the project funds itself in six to 12 months, it's paid for itself. And then after that it's returning money to the business. Why would you not do that? And when you start framing the conversation, that way, the little light bulb turn on for the people that sign the checks. For sure. >>That's great advice for folks to be thinking about. I loved how you talked about the 63% reduction in something. I think that's great. What does it impact? How does it impact the revenue for the organization? If we're avoiding costs here, how do we drive up revenue? So having that laser focus on revenue is great advice for folks in any industry, looking to build a business case for AI ops. I think you set the stage for that rich beautifully, and you were right. This was a fun conversation. Thank you for your time. Thank you. And thanks for watching >>From around the globe with digital coverage. >>Welcome back to the Broadcom AI ops, virtual forum, Lisa Martin here talking with Eastman Nasir global product management at Verizon. We spent welcome back. >>Hi. Hello. Uh, what a pleasure. >>So 2020 the year of that needs no explanation, right? The year of massive challenges and wanting to get your take on the challenges that organizations are facing this year as the demand to deliver digital products and services has never been higher. >>Yeah. So I think this is something it's so close to all the far far, right? It's, uh, it's something that's impacted the whole world equally. And I think regardless of which industry you rent, you have been impacted by this in one form or the other, and the ICT industry, the information and communication technology industry, you know, Verizon being really massive player in that whole arena. It has just been sort of struck with this massive consummation we have talked about for a long time, we have talked about these remote surgery capabilities whereby you've got patients in Kenya who are being treated by an expert sitting in London or New York, and also this whole consciousness about, you know, our carbon footprint and being environmentally conscious. This pandemic has taught us all of that and brought us to the forefront of organization priorities, right? The demand. I think that's, that's a very natural consequence of everybody sitting at home. >>And the only thing that can keep things still going is this data communication, right? But I wouldn't just say that that is, what's kind of at the heart of all of this. Just imagine if we are to realize any of these targets of the world is what leadership is setting for themselves. Hey, we have to be carbon neutral by X year as a country, as a geography, et cetera, et cetera. You know, all of these things require you to have this remote working capabilities, this remote interaction, not just between humans, but machine to machine interactions. And this there's a unique value chain, which is now getting created that you've got people who are communicating with other people or communicating with other machines, but the communication is much more. I wouldn't even use the term real time because we've used real time for voice and video, et cetera. >>We're talking low latency, microsecond decision-making that can either cut somebody's, you know, um, our trees or that could actually go and remove the tumor, that kind of stuff. So that has become a reality. Everybody's asking for it, remote learning, being an extremely massive requirement where, you know, we've had to enable these, uh, these virtual classrooms ensuring the type of connectivity, ensuring the type of type of privacy, which is just so, so critical. You can't just have everybody in a go on the internet and access a data source. You have to be concerned about the integrity and security of that data as the foremost. So I think all of these things, yes, we have not been caught off guard. We were pretty forward-looking in our plans and our evolution, but yes, it's fast track the journey that we would probably believe we would have taken in three years. It has brought that down to two quarters where we've had to execute them. >>Right. Massive acceleration. All right. So you articulated the challenges really well. And a lot of the realities that many of our viewers are facing. Let's talk now about motivations, AI ops as a tool, as a catalyst for helping organizations overcome those challenges. >>So yeah. Now on that I said, you can imagine, you know, it requires microsecond decision-making which human being on this planet can do microsecond decision-making on complex network infrastructure, which is impacting end user applications, which have multitudes of effect. You know, in real life, I use the example of a remote surgeon. Just imagine that, you know, even because of you just use your signal on the quality of that communication for that microsecond, it could be the difference between killing somebody in saving somebody's life. And it's not predictable. We talk about autonomous vehicles. Uh, we talk about this transition to electric vehicles, smart motorways, et cetera, et cetera, in federal environment, how is all of that going to work? You have so many different components coming in. You don't just have a network and security anymore. You have software defined networking. That's coming, becoming a part of that. >>You have mobile edge computing that is rented for the technologies. 5g enables we're talking augmented reality. We're talking virtual reality. All of these things require that resources and why being carbon conscious. We told them we just want to build a billion data centers on this planet, right? We, we have to make sure that resources are given on demand and the best way of resources can be given on demand and could be most efficient is that the thing is being made at million microsecond and those resources are accordingly being distributed, right? If you're relying on people, sipping their coffees, having teas, talking to somebody else, you know, just being away on holiday. I don't think we're going to be able to handle that one that we have already stepped into. Verizon's 5g has already started businesses on that transformational journey where they're talking about end user experience personalization. >>You're going to have events where people are going to go, and it's going to be three-dimensional experiences that are purely customized for you. How, how does that all happen without this intelligence sitting there and a network with all of these multiple layers? So spectrum, it doesn't just need to be intuitive. Hey, this is my private IP traffic. This is public traffic. You know, it has to not be in two, or this is an application that I have to prioritize over another task to be intuitive to the criticality and the context of those transactions. Again, that's surgeons. So be it's much more important than postman setting and playing a video game. >>I'm glad that you think that that's excellent. Let's go into some specific use cases. What are some of the examples that you gave? Let's kind of dig deeper into some of the, what you think are the lowest hanging fruit for organizations kind of pan industry to go after. >>Excellent. Brian, and I think this, this like different ways to look at the lowest hanging fruit, like for somebody like revising who is a managed services provider, you know, very comprehensive medicines, but we obviously have food timing, much lower potentially for some of our customers who want to go on that journey. Right? So for them to just go and try and harness the power of the foods might be a bit higher hanging, but for somebody like us, the immediate ones would be to reduce the number of alarms that are being generated by these overlay services. You've got your basic network, then you've got your whole software defined networking on top of that, you have your hybrid clouds, you have your edge computing coming on top of that. You know? So all of that means if there's an outage on one device on the network, I want to make this very real for everybody, right? >>It's like device and network does not stop all of those multiple applications or monitoring tools from raising and raising thousands of alarm and everyone, one capacity. If people are attending to those thousands of alarms, it's like you having a police force and there's a burglary in one time and the alarm goes off and 50 bags. How, how are you kind of make the best use of your police force? You're going to go investigate 50 bags or do you want to investigate where the problem is? So it's as real as that, I think that's the first wins where people can save so much cost, which is coming from being wasted and resources running around, trying to figure stuff out immediately. I'm tied this with network and security network and security is something which has you did even the most, you know, I mean single screens in our engineering, well, we took it to have network experts, separate people, security experts, separate people to look for different things, but there are security events that can impact the performance of a network. >>And then just drop the case on the side of et cetera, which could be falsely attributed to the metric. And then if you've got multiple parties, which are then the chapter clear stakeholders, you can imagine the blame game that goes on finding fingers, taking names, not taking responsibility that don't has all this happened. This is the only way to bring it all together to say, okay, this is what takes priority. If there's an event that has happened, what is its correlation to the other downstream systems, devices, components, and these are applications. And then subsequently, you know, like isolating it to the right cost where you can most effectively resolve that problem. Thirdly, I would say on demand, virtualized resource, virtualized resources, the heart and soul, the spirit of status that you can have them on demand. So you can automate the allocation of these resources based on customer's consumption their peaks, their cramps, all of that comes in. >>You see, Hey, typically on a Wednesday, the traffic was up significantly for this particular application, you know, going to this particular data center, you could have this automated system, uh, which is just providing those resources, you know, on demand. And so it is to have a much better commercial engagement with customers and just a much better service assurance model. And then one more thing on top of that, which is very critical is that as I was saying, giving that intelligence to the networks to start having context of the criticality of a transaction, that doesn't make sense to them. You can't have that because for that, you need to have this, you know, monkey their data. You need to have multi-cam system, which are monitoring and controlling different aspects of your overall end user application value chain to be communicating with each other. And, you know, that's the only way to sort of achieve that goal. And that only happens with AI. It's not possible >>So it was when you clearly articulated some obvious, low hanging fruit and use cases that organizations can go after. Let's talk now about some of the considerations, you talked about the importance of a network and AI ops, the approach I assume, needs to be modular support needs to be heterogeneous. Talk to us about some of those key considerations that you would recommend. >>Absolutely. So again, basically starting with the network, because if there's, if the metrics sitting at the middle of all of this is not working, then things can communicate with each other, right? And the cloud doesn't work, nothing metal. That's the hardest part of this, but that's the frequency. When you talk about machine to machine communication or IOT, it's just the biggest transformation of the span of every company is going for IOT now to drive those costs, efficiencies, and had, something's got some experience, the integrity of the topic karma, right? The security, integrity of that. How do you maintain integrity of your data beyond just a secure network components? That is true, right? That's where you're getting to the whole arena blockchain technologies, where you have to use digital signatures or barcodes that machine then, and then an intelligence system is automatically able to validate and verify the integrity of the data and the commands that are being executed by those end-user told them what I need to tell them that. >>So it's IOT machines, right? That is paramount. And if anybody is not keeping that into their equation, that in its own self is any system that is therefore maintaining the integrity of your commands and your hold that sits on those, those machines. Right? Second, you have your network. You need to have any else platform, which is able to restless all the fast network information, et cetera. And coupled with that data integrity piece, because for the management, ultimately they need to have a coherent view of the analytics, et cetera, et cetera. They need to know where the problems are again, right? So let's say if there's a problem with the integrity of the commands that are being executed by the machine, that's a much bigger problem than not being able to communicate with that machine and the best thing, because you'd rather not talk to the machine or have to do anything if it's going to start doing wrong things. >>So I think that's where it is. It's very intuitive. It's not true. You have to have subsequently if you have some kind of faith and let me use that use case self autonomous vehicles. Again, I think we're going to see in the next five years, because he's smart with the rates, et cetera, it won't separate autonomous cars. It's much more efficient, it's much more space, et cetera, et cetera. So within that equation, you're going to have systems which will be specialists in looking at aspects and transactions related to those systems. For example, in autonomous moving vehicles, brakes are much more important than the Vipers, right? So this kind of intelligence, it will be multiple systems who have to sit, N nobody has to, one person has to go in one of these systems. I think these systems should be open source enough that they, if you were able to integrate them, right, if something's sitting in the cloud, you were able to integrate for that with obviously the regard of the security and integrity of your data that has to traverse from one system to the other extremely important. >>So I'm going to borrow that integrity theme for a second, as we go into our last question, and that is this kind of take a macro look at the overall business impact that AI ops can help customers make. I'm thinking of, you know, the integrity of teams aligning business in it, which we probably can't talk about enough. We're helping organizations really effectively measure KPIs that deliver that digital experience that all of us demanding consumers expect. What's the overall impact. What would you say in summary fashion? >>So I think the overall impact is a lot of costs. That's customized and businesses gives the time to the time of enterprises. Defense was inevitable. It's something that for the first time, it will come to life. And it's something that is going to, you know, start driving cost efficiencies and consciousness and awareness within their own business, which is obviously going to have, you know, it domino kind of an effect. So one example being that, you know, you have problem isolation. I talked about network security, this multi-layers architecture, which enables this new world of 5g, um, at the heart of all of it, it has to identify the problem to the source, right? Not be bogged down by 15 different things that are going wrong. What is causing those 15 things to go wrong, right? That speed to isolation in its own sense can make millions and millions of dollars to organizations after we organize it. Next one is obviously overall impacted customer experience. Uh, 5g was given out of your customers, expecting experiences from you, even if you're not expecting to deliver them in 2021, 2022, it would have customers asking for those experience or walking away, if you do not provide those experience. So it's almost like a business can do nothing every year. They don't have to reinvest if they just want to die on the line, businesses want remain relevant. >>Businesses want to adopt the latest and greatest in technology, which enables them to, you know, have that superiority and continue it. So from that perspective that continue it, he will read that they write intelligence systems that tank rationalizing information and making decisions supervised by people, of course were previously making some of those. >>That was a great summary because you're right, you know, with how demanding consumers are. We don't get what we want quickly. We churn, right? We go somewhere else and we could find somebody that can meet those expectations. So it has been thanks for doing a great job of clarifying the impact and the value that AI ops can bring to organizations that sounds really now is we're in this even higher demand for digital products and services, which is not going away. It's probably going to only increase it's table stakes for any organization. Thank you so much for joining me today and giving us your thoughts. >>Pleasure. Thank you. We'll be right back with our next segment. >>Digital applications and services are more critical to a positive customer and employee experience than ever before. But the underlying infrastructure that supports these apps and services has become increasingly complex and expanding use of multiple clouds, mobile and microservices, along with modern and legacy infrastructure can make it difficult to pinpoint the root cause when problems occur, it can be even more difficult to determine the business impact your problems that occur and resolve them efficiently. AI ops from Broadcom can help first by providing 360 degree visibility, whether you have hybrid cloud or a cloud native AI ops from Broadcom provides a clear line of sight, including apt to infrastructure and network visibility across hybrid environments. Second, the solution gives you actionable insights by correlating an aggregating data and applying AI and machine learning to identify root causes and even predict problems before users are impacted. Third AI ops from Broadcom provides intelligent automation that identifies potential solutions when problems occur applied to the best one and learns from the effectiveness to improve response in case the problem occurs. Again, finally, the solution enables organizations to achieve digit with jelly by providing feedback loops across development and operations to allow for continuous improvements and innovation through these four capabilities. AI ops from Broadcom can help you reduce service outages, boost, operational efficiency, and effectiveness and improve customer and employee experience. To learn more about AI ops from Broadcom, go to broadcom.com/ai ops from around the globe. >>It's the cube with digital coverage of AI ops virtual forum brought to you by Broadcom. >>Welcome back to the AI ops virtual forum, Lisa Martin here with Srinivasan, Roger Rajagopal, the head of product and strategy at Broadcom. Raj, welcome here, Lisa. I'm excited for our conversation. So I wanted to dive right into a term that we hear all the time, operational excellence, right? We hear it everywhere in marketing, et cetera, but why is it so important to organizations as they head into 2021? And tell us how AI ops as a platform can help. >>Yeah. Well, thank you. First off. I wanna, uh, I want to welcome our viewers back and, uh, I'm very excited to, uh, to share, um, uh, more info on this topic. You know, uh, here's what we believe as we work with large organizations, we see all our organizations are poised to get out of the, uh, the pandemic and look for a brood for their own business and helping customers get through this tough time. So fiscal year 2021, we believe is going to be a combination of, uh, you know, resiliency and agility at the, at the same time. So operational excellence is critical because the business has become more digital, right? There are going to be three things that are going to be more sticky. Uh, you know, remote work is going to be more sticky, um, cost savings and efficiency is going to be an imperative for organizations and the continued acceleration of digital transformation of enterprises at scale is going to be in reality. So when you put all these three things together as a, as a team that is, uh, you know, that's working behind the scenes to help the businesses succeed, operational excellence is going to be, make or break for organizations, >>Right with that said, if we kind of strip it down to the key capabilities, what are those key capabilities that companies need to be looking for in an AI ops solution? >>Yeah, you know, so first and foremost, AI ops means many things to many, many folks. So let's take a moment to simply define it. The way we define AI ops is it's a system of intelligence, human augmented system that brings together full visibility across app infra and network elements that brings together disparate data sources and provides actionable intelligence and uniquely offers intelligent automation. Now, the, the analogy many folks draw is the self-driving car. I mean, we are in the world of Teslas, uh, but you know, uh, but self-driving data center is it's too far away, right? Autonomous systems are still far away. However, uh, you know, application of AI ML techniques to help deal with volume velocity, veracity of information, uh, is, is critical. So that's how we look at AI ops and some of the key capabilities that we, uh, that we, uh, that we work with our customers to help them on our own for eight years. >>Right? First one is eyes and ears. What we call full stack observability. If you do not know what is happening in your systems, uh, you know, that that serve up your business services. It's going to be pretty hard to do anything, uh, in terms of responsiveness, right? So from stack observability, the second piece is what we call actionable insights. So when you have disparate data sources, tools, sprawls data coming at you from, uh, you know, uh, from a database systems, it systems customer management systems, ticketing systems. How do you find the needle from the haystack? And how do you respond rapidly from a myriad of problems as CEO of red? The third area is what we call intelligent automation. Well, identifying the problem to act on is important, and then acting on automating that and creating, uh, a recommendation system where, uh, you know, you can be proactive about it is even more important. And finally, all of this focuses on efficiency. What about effectiveness? Effectiveness comes when you create a feedback loop, when what happens in production is related to your support systems and your developers so that they can respond rapidly. So we call that continuous feedback. So these are the four key capabilities that, uh, you know, uh, you should look for in an AI ops system. And that's what we offer as well. >>Russia, there's four key capabilities that businesses need to be looking for. I'm wondering how those help to align business. And it it's, again like operational excellence. It's something that we talk about a lot is the alignment of business. And it a lot more challenging, easier said than done, right. But I want you to explain how can AI ops help with that alignment and align it outputs to business outcomes? >>Yeah. So, you know, one of the things, uh, I'm going to say something that is, uh, that is, uh, that is simple, but, but, but this harder, but alignment is not on systems alignment is with people, right? So when people align, when organizations align, when cultures align, uh, dramatic things can happen. So in the context of AI ops VC, when, when SRE is aligned with the DevOps engineers and information architects and, uh, uh, you know, it operators, uh, you know, they enable organizations to reduce the gap between intent and outcome or output and outcome that said, uh, you know, these personas need mechanisms to help them better align, right. Help them better visualize, see the, you know, what we call single source of truth, right? So there are four key things that I want to call out. When we work with large enterprises, we find that customer journey alignment with the, you know, what we call it systems is critical. >>So how do you understand your business imperatives and your customer journey goals, whether it is car to a purchase or whether it is, uh, you know, bill shock scenarios and Swan alignment on customer journey to your it systems is one area that you can reduce the gap. The second area is how do you create a scenario where your teams can find problems before your customers do right outage scenarios and so on. So that's the second area of alignment. The third area of alignment is how can you measure business impact driven services? Right? There are several services that an organization offers versus an it system. Some services are more critical to the business than others, and these change in a dynamic environment. So how do you, how do you understand that? How do you measure that and how, how do you find the gaps there? So that's the third area of alignment that we, that we help and last but not least there are, there are things like NPS scores and others that, that help us understand alignment, but those are more long-term. But in the, in the context of, uh, you know, operating digitally, uh, you want to use customer experience and business, uh, you know, a single business outcome, uh, as a, as a key alignment factor, and then work with your systems of engagement and systems of interaction, along with your key personas to create that alignment. It's a people process technology challenge. >>So, whereas one of the things that you said there is that it's imperative for the business to find a problem before a customer does, and you talked about outages there, that's always a goal for businesses, right. To prevent those outages, how can AI ops help with that? Yeah, >>So, you know, outages, uh, talk, you know, go to resiliency of a system, right? And they also go to, uh, uh, agility of the same system, you know, if you're a customer and if you're whipping up your mobile app and it takes more than three milliseconds, uh, you know, you're probably losing that customer, right. So outages mean different things, you know, and there's an interesting website called down detector.com that actually tracks all the old pages of publicly available services, whether it's your bank or your, uh, you know, tele telecom service or a mobile service and so on and so forth. In fact, the key question around outages for, from, uh, from, uh, you know, executives are the question of, are you ready? Right? Are you ready to respond to the needs of your customers and your business? Are you ready to rapidly resolve an issue that is impacting customer experience and therefore satisfaction? >>Are you creating a digital trust system where customers can be, you know, um, uh, you know, customers can feel that their information is secure when they transact with you, all of these, getting into the notion of resiliency and outages. Now, you know, one of the things that, uh, that I, I often, uh, you know, work with customers around, you know, would that be find as the radius of impact is important when you deal with outages? What I mean by that is problems occur, right? How do you respond? How quickly do you take two seconds, two minutes, 20 minutes, two hours, 20 hours, right? To resolve the problem that radius of impact is important. That's where, you know, you have to bring a gain people, process technology together to solve that. And the key thing is you need a system of intelligence that can aid your teams, you know, look at the same set of parameters so that you can respond faster. That's the key here. >>We look at digital transformation at scale. Raj, how does AI ops help influence that? >>You know, um, I'm going to take a slightly long-winded way to answer this question. See when it comes to digital transformation at scale, the focus on business purpose and business outcome becomes extremely critical. And then the alignment of that to your digital supply chain, right, are the, are the, are the key factors that differentiate winners in the, in their digital transformation game? Really, what we have seen, uh, with, with winners is they operate very differently. Like for example, uh, you know, Nike matures, its digital business outcomes by shoes per second, right? Uh, Apple by I-phones per minute, Tesla by model threes per month, are you getting this, getting it right? I mean, you want to have a clear business outcome, which is a measure of your business, uh, in effect, I mean, ENC, right? Which, which, uh, um, my daughter use and I use very well. >>Right. Uh, you know, uh, they measure by revenue per hour, right? I mean, so these are key measures. And when you have a key business outcome measure like that, you can everything else, because you know what these measures, uh, you know, uh, for a bank, it may be deposits per month, right now, when you move money from checking account to savings account, or when you do direct deposits, those are, you know, banks need liquidity and so on and so forth. But, you know, the, the key thing is that single business outcome has a Starburst effect inside the it organization that touches a single money moment from checking a call to savings account can touch about 75 disparate systems internally. Right? So those think about it, right? I mean, all, all we're doing is moving money from checking account a savings account. Now that goats into a it production system, there are several applications. >>There is a database, there is, there are infrastructures, there are load balancers that are webs. You know, you know, the web server components, which then touches your, your middleware component, which is a queuing system, right. Which then touches your transactional system. Uh, and, uh, you know, which may be on your main frames, what we call mobile to mainframe scenario, right? And we are not done yet. Then you have a security and regulatory compliance system that you have to touch a fraud prevention system that you have to touch, right? A state department regulation that you may have to meet and on and on and on, right? This is the chat that it operations teams face. And when you have millions of customers transacting, right, suddenly this challenge cannot be managed by human beings alone. So therefore you need a system of intelligence that augments human intelligence and acts as your, you know, your, your eyes and ears in a way to, to point pinpoint where problems are. >>Right. So digital transformation at scale really requires a very well thought out AI ops system, a platform, an open extensible platform that, uh, you know, uh, that is heterogeneous in nature because there's tools, products in organizations. There is a lot of databases in systems. There are millions of, uh, uh, you know, customers and hundreds of partners and vendors, you know, making up that digital supply chain. So, you know, AI ops is at the center of an enabling an organization achieve digital op you know, transformation at scale last but not least. You need continuous feedback loop. Continuous feedback loop is the ability for a production system to inform your dev ops teams, your finance teams, your customer experience teams, your cost modeling teams about what is going on so that they can so that they can reduce the intent, come gap. >>All of this need to come together, what we call BizOps. >>That was a great example of how you talked about the Starburst effect. I actually never thought about it in that way, when you give the banking example, but what you should is the magnitude of systems. The fact that people alone really need help with that, and why intelligent automation and AI ops can be transformative and enable that scale. Raj, it's always a pleasure to talk with you. Thanks for joining me today. And we'll be right back with our next segment. Welcome back to the AI ops virtual forum. We've heard from our guests about the value of AI ops and why and how organizations are adopting AI ops platforms. But now let's see AI ops inaction and get a practical view of AI ops to deep Dante. The head of AI ops at Broadcom is now going to take you through a quick demo. >>Hello. So they've gotta head off AI ops and automation here. What I'm going to do today is talk through some of the key capabilities and differentiators of Broadcom's CII ops solution in this solution, which can be delivered on cloud or on-prem. We bring a variety of metric alarm log and applauded data from multiple sources, EPM, NetApps, and infrastructure monitoring tools to provide a single point of observability and control. Let me start where our users mostly stock key enterprises like FSI, telcos retailers, et cetera, do not manage infrastructure or applications without having a business context. At the end of the day, they offer business services governed by SLS service level objectives and SLI service level indicators are service analytics, which can scale to a few thousand services, lets our customers create and monitor the services as per their preference. They can create a hierarchy of services based on their business practice. >>For example, here, the sub services are created based on functional subsistence for certain enterprises. It could be based on location. Users can import these services from their favorite CMDB. What's important to note that not all services are born equal. If you are a modern bank, you may want to prioritize tickets coming from digital banking, for example, and this application lets you rank them as per the KPI of your choice. We can source the availability, not merely from the state of the infrastructure, whether they're running or not. But from the SLS that represent the state of the application, when it comes to triaging issues related to the service, it is important to have a complete view of the topology. The typology can show both east-west elements from mobile to mainframe or not South elements in a network flow. This is particularly relevant for a large enterprise who could be running the systems of engagement on the cloud and system of records on mainframe inside the firewall here, you can see that the issue is related to the mainframe kick server. >>You can expand to see the actual alarm, which is sourced from the mainframe operational intelligence. Similarly, clicking on network will give the hub and spoke view of the network devices, the Cisco switches and routers. I can click on the effected router and see all the details Broadcom's solution stores, the ontological model of the typology in the form of a journal graph where one can not only view the current state of the typology, but the past as well, talking of underlying data sources, the solution uses best of the pre data stores for structured and unstructured data. We have not only leveraged the power of open source, but have actively contributed back to the community. One of the key innovations is evident in our dashboarding framework because we have enhanced the open source Grafana technology to support these diverse data sources here. You can see a single dashboard representing applications to infrastructure, to mainframe again, sourcing a variety of data from these sources. >>When we talk to customers, one of the biggest challenges that they face today is related to alarms because of a proliferation of tools. They are currently drowning in an ocean of hundreds and thousands of alarms. This increases the Elmont support cost to tens of dollars per ticket, and also affects LTO efficiency leading to an average of five to six hours of meantime to resolution here is where we have the state of the art innovation utilizing the power of machine learning and ontology to arrive at the root cause we not only clusterize alarms based on text, but employ the technique of 41st. We look at the topology then at the time window duplicate text based on NLP. And lastly learn from continuous training of the model to deduce what we call situations. This is an example of a situation. As you can see, we provide a time-based evidence of how things unfolded and arrive at a root cause. >>Lastly, the solution provides a three 60 degree closed loop remediation either through a ticketing system or by direct invocation of automation actions instead of firing hard-coded automation runbooks for certain conditions, the tool leverage is machine learning to rank automation actions based on past heuristics. That's why we call it intelligent automation to summarize AI ops from Broadcom helps you achieve operational excellence through full stack observability, coupled with AIML that applies across modern hybrid cloud environments, as well as legacy ones uniquely. It ties these insights with intelligent automation to improve customer experience. Thank you for watching from around the globe. It's the cube with digital coverage of AI ops virtual forum brought to you by Broadcom. >>Welcome to our final segment today. So we've discussed today. The value that AI ops will bring to organizations in 2021, we'll discuss that through three different perspectives. And so now we want to bring those perspectives together and see if we can get a consensus on where AI ops needs to go for folks to be successful with it in the future. So bringing back some folks Richland is back with us. Senior analysts, serving infrastructure and operations professionals at Forrester smartness here is also back in global product management at Verizon and Srinivasan, Reggie Gopaul head of product and strategy at Broadcom guys. Great to have you back. So let's jump in and rich, we're going to, we're going to start with you, but we are going to get all three of you, a chance to answer the questions. So we've talked about why organizations should adopt AI ops, but what happens if they choose not to what challenges would they face? Basically what's the cost of organizations doing nothing >>Good question, because I think in operations for a number of years, we've kind of stand stood, Pat, where we are, where we're afraid change things sometimes, or we just don't think about a tooling as often. The last thing to change because we're spending so much time doing project work and modernization and fighting fires on a daily basis. >>Problem is going to get worse. If we do nothing, >>You know, we're building new architectures like containers and microservices, which means more things to mind and keep running. Um, we're building highly distributed systems. We're moving more and more into this hybrid world, a multi-cloud world, uh, it's become over-complicate and I'll give a short anecdote. I think, eliminate this. Um, when I go to conferences and give speeches, it's all infrastructure operations people. And I say, you know, how many people have three X, five X, you know, uh, things to monitor them. They had, you know, three years ago, two years ago, and everyone's saying how many people have hired more staff in that time period, zero hands go up. That's the gap we have to fill. And we have to fill that through better automation, more intelligent systems. It's the only way we're going to be able to fill back out. >>What's your perspective, uh, if organizations choose not to adopt AI ops. Yeah. So I'll do that. Yeah. So I think it's, I would just relate it to a couple of things that probably everybody >>Tired off lately and everybody can relate to. And this would resonate that we have 5g, which is all set to transform the world. As we know it, I don't have a lot of communication with these smart cities, smart communities, IOT, which is going to make us pivotal to the success of businesses. And as you've seen with this call with, you know, transformation of the world, that there's a, there's a much bigger cost consciousness out there. People are trying to become much more, forward-looking much more sustainable. And I think at the heart of all of this, that the necessity that you have intelligent systems, which are bastardizing more than enough information that previously could've been overlooked because if you don't measure engagement, not going right. People not being on the same page of this using two examples or hundreds of things, you know, that play a part in things, but not coming together in the best possible way. So I think it has an absolute necessity to drive those cost efficiencies rather than, you know, left right and center laying off people who are like 10 Mattel to your business and have a great tribal knowledge of your business. So to speak, you can drive these efficiencies through automating a lot of those tasks that previously were being very manually intensive or resource intensive. And you could allocate those resources towards doing much better things, which let's be very honest going into 20, 21 after what we've seen with 2020, it's going to be mandate treat. >>And so Raj, I saw you shaking your head there when he was mom was sharing his thoughts. What are your thoughts about that sounds like you agree. Yeah. I mean, uh, you know, uh, to put things in perspective, right? I mean we're firmly in the digital economy, right? Digital economy, according to the Bureau of economic analysis is 9% of the U S GDP. Just, you know, think about it in, in, in, in, in the context of the GDP, right? It's only ranked lower, slightly lower than manufacturing, which is at 11.3% GDP and slightly about finance and insurance, which is about seven and a half percent GDP. So the digital economy is firmly in our lives, right. And as Huisman was talking about it, you know, software eats the world and digital, operational excellence is critical for customers, uh, to, uh, you know, to, uh, to drive profitability and growth, uh, in the digital economy. >>It's almost, you know, the key is digital at scale. So when, uh, when rich talks about some of the challenges and when Huseman highlights 5g as an example, those are the things that, that, that come to mind. So to me, what is the cost or perils of doing nothing? You know, uh, it's not an option. I think, you know, more often than not, uh, you know, C-level execs are asking head of it and they are key influencers, a single question, are you ready? Are you ready in the context of addressing spikes in networks because of the pandemic scenario, are you ready in the context of automating away toil? Are you ready to respond rapidly to the needs of the digital business? I think AI ops is critical. >>That's a great point. Roger, where does stick with you? So we got kind of consensus there, as you said, wrapping it up. This is basically a, not an option. This is a must to go forward for organizations to be successful. So let's talk about some quick wins, or as you talked about, you know, organizations and sea levels asking, are you ready? What are some quick wins that that organizations can achieve when they're adopting AI? >>You know, um, immediate value. I think I would start with a question. How often do your customers find problems in your digital experience before you do think about that? Right. You know, if you, if you, you know, there's an interesting web, uh, website, um, uh, you know, down detector.com, right? I think, uh, in, in Europe there is an equal amount of that as well. It ha you know, people post their digital services that are down, whether it's a bank that, uh, you know, customers are trying to move money from checking account, the savings account and the digital services are down and so on and so forth. So some and many times customers tend to find problems before it operations teams do. So a quick win is to be proactive and immediate value is visibility. If you do not know what is happening in your complex systems that make up your digital supply chain, it's going to be hard to be responsive. So I would start there >>Visibility this same question over to you from Verizon's perspective, quick wins. >>Yeah. So I think first of all, there's a need to ingest this multi-care spectrum data, which I don't think is humanly possible. You don't have people having expertise, you know, all the seven layers of the OSI model and then across network and security and at the application level. So I think you need systems which are now able to get that data. It shouldn't just be wasted reports that you're paying for on a monthly basis. It's about time that you started making the most of those in the form of identifying what are the efficiencies within your ecosystem. First of all, what are the things, you know, which could be better utilized subsequently you have the >>Opportunity to reduce the noise of a trouble tickets handling. It sounds pretty trivial, but >>An average you can imagine every trouble tickets has the cost in dollars, right? >>So, and there's so many tickets and there's art >>That get created on a network and across an end user application value, >>We're talking thousands, you know, across and end user >>Application value chain could be million in >>A year. So, and so many of those are not really, >>He, you know, a cause of concern because the problem is something. >>So I think that whole triage is an immediate cost saving and the bigger your network, the bigger >>There's a cost of things, whether you're a provider, whether you're, you know, the end customer at the end of the day, not having to deal with problems, which nobody can resolve, which are not meant to be dealt with. There's so many of those situations, right, where service has just been adopted, >>Which is just coordinate quality, et cetera, et cetera. So many reasons. So those are the, >>So there's some of the immediate cost saving them. They are really, really significant. >>Secondly, I would say Raj mentioned something about, you know, the user, >>Your application value chain, and an understanding of that, especially with this hybrid cloud environment, >>Et cetera, et cetera, right? The time it takes to identify a problem in an end user application value chain across the seven layers that I mentioned with the OSI reference model across network and security and the application environment. It's something that >>In its own self has massive cost to business, >>Right? That could be >>No sale transactions that could be obstructed because of this. There could be, and I'm going to use a really interesting example. >>We talk about IOT. The integrity of the IOT machine is exciting. >>Family is pivotal in this new world that we're stepping into. >>You could be running commands, >>Super efficient. He has, everything is being told to the machine really fast with sending yeah. >>Everything there. What if it's hacked? And if that's okay, >>Robotic arm starts to involve the things you don't want it to do. >>So there's so much of that. That becomes a part of this naturally. And I believe, yes, this is not just like from a cost >>standpoint, but anything going wrong with that code base, et cetera, et cetera. These are massive costs to the business in the form of the revenue. They have lost the perception in the market as a result, the fed, >>You know, all that stuff. So >>These are a couple of very immediate problems, but then you also have the whole player virtualized resources where you can automate the allocation, you know, the quantification of an orchestration of those virtualized resources, rather than a person having to, you know, see something and then say, Oh yeah, I need to increase capacity over here, because then it's going to have this particular application. You have systems doing this stuff and to, you know, Roger's point your customer should not be identifying your problems before you, because this digital is where it's all about perception. >>Absolutely. We definitely don't want the customers finding it before. So rich, let's wrap this particular question up with you from that senior analyst perspective, how can companies use make big impact quickly with AI ops? Yeah, >>Yeah, I think, you know, and it was been really summed up some really great use cases there. I think with the, uh, you know, one of the biggest struggles we've always had in operations is isn't, you know, the mean time to resolve. We're pretty good at resolving the things. We just have to find the thing we have to resolve. That's always been the problem and using these advanced analytics and machine learning algorithms now across all machine and application data, our tendency is humans is to look at the console and say, what's flashing red. That must be what we have to fix, but it could be something that's yellow, somewhere else, six services away. And we have made things so complicated. And I think this is what it was when I was saying that we can't get there anymore on our own. We need help to get there in all of this stuff that the outline. >>So, so well builds up to a higher level thing of what is the customer experience about what is the customer journey? And we've struggled for years in the digital world and measuring that a day-to-day thing. We know an online retail. If you're having a bad experience at one retailer, you just want your thing. You're going to go to another retailer, brand loyalty. Isn't one of like it, wasn't a brick and mortal world where you had a department store near you. So you were loyal to that because it was in your neighborhood, um, online that doesn't exist anymore. So we need to be able to understand the customer from that first moment, they touch a digital service all the way from their, their journey through that digital service, the lowest layer, whether it be a database or the network, what have you, and then back to them again, and we're not understanding, is that a good experience? >>We gave them. How does that compare to last week's experience? What should we be doing to improve that next week? Uh, and I think companies are starting and then the pandemic certainly, you know, push this timeline. If you listened to the, the, the CEO of Microsoft, he's like, you know, 10 years of digital transformation written down. And the first several months of this, um, in banks and in financial institutions, I talked to insurance companies, aren't slowing down. They're trying to speed up. In fact, what they've discovered is that they're, you know, obviously when we were on lockdown or what have you, they use of digital servers is spiked very high. What they've learned is they're never going to go back down. They're never going to return to pretend endemic levels. So now they're stuck with this new reality. Well, how do we service those customers and how do we make sure we keep them loyal to our brand? >>Uh, so, you know, they're looking for modernization opportunities. A lot of that that's things have been exposed. And I think Raj touched upon this very early in the conversation is visibility gaps. Now that we're on the outside, looking in at the data center, we know we architect things in a very way. Uh, we better ways of making these correlations across the Sparrow technologies to understand where the problems lies. We can give better services to our customers. And I think that's really what we're going to see a lot of the innovation and the people really clamoring for these new ways of doing things that starting, you know, now, I mean, I've seen it in customers, but I think really the push through the end of this year to next year when, you know, economy and things like that straightened out a little bit more, I think it really, people are gonna take a hard look of where they are and is, you know, AI ops the way forward for them. And I think they'll find it. The answer is yes, for sure. >>So we've, we've come to a consensus that, of what the parallels are of organizations, basically the cost of doing nothing. You guys have given some great advice on where some of those quick wins are. Let's talk about something Raj touched on earlier is organizations, are they really ready for truly automated AI? Raj, I want to start with you readiness factor. What are your thoughts? >>Uh, you know, uh, I think so, you know, we place our, her lives on automated systems all the time, right? In our, in our day-to-day lives, in the, in the digital world. I think, uh, you know, our, uh, at least the customers that I talk to our customers are, uh, are, uh, you know, uh, have a sophisticated systems. Like for example, advanced automation is a reality. If you look at social media, AI and ML and automation are used to automate away, uh, misinformation, right? If you look at financial institutions, AI and ML are used to automate away a fraud, right? So I want to ask our customers why can't we automate await oil in it, operation systems, right? And that's where our customers are. Then the, you know, uh, I'm a glass half full, uh, cleanup person, right? Uh, this pandemic has been harder on many of our customers, but I think what we have learned from our customers is they've Rose to the occasion. >>They've used digital as a key needs, right? At scale. That's what we see with, you know, when, when Huseman and his team talk about, uh, you know, network operational intelligence, right. That's what it means to us. So I think they are ready, the intersection of customer experience it and OT, operational technology is ripe for automation. Uh, and, uh, you know, I, I wanna, I wanna sort of give a shout out to three key personas in this mix. It's about people, right? One is the SRE persona, you know, site, reliability engineer. The other is the information security persona. And the third one is the it operator automation engineer persona. These folks in organizations are building a system of intelligence that can respond rapidly to the needs of their digital business. We at Broadcom, we are in the business of helping them construct a system of intelligence that will create a human augmented solution for them. Right. So when I see, when I interact with large enterprise customers, I think they, they, you know, they, they want to achieve what I would call advanced automation and AI ML solutions. And that's squarely, very I ops is, you know, is going as it, you know, when I talk to rich and what, everything that rich says, you know, that's where it's going and that's what we want to help our customers to. So, which about your perspective of organizations being ready for truly automated AI? >>I think, you know, the conversation has shifted a lot in the last, in, in pre pandemic. Uh, I'd say at the end of last year, we're, you know, two years ago, people I'd go to conferences and people come up and ask me like, this is all smoke and mirrors, right? These systems can't do this because it is such a leap forward for them, for where they are today. Right. We we've sort of, you know, in software and other systems, we iterate and we move forward slowly. So it's not a big shock. And this is for a lot of organizations that big, big leap forward where they're, they're running their operations teams today. Um, but now they've come around and say, you know what? We want to do this. We want all the automations. We want my staff not doing the low complexity, repetitive tasks over and over again. >>Um, you know, and we have a lot of those kinds of legacy systems. We're not going to rebuild. Um, but they need certain care and feeding. So why are we having operations? People do those tasks? Why aren't we automating those out? I think the other piece is, and I'll, I'll, I'll send this out to any of the operations teams that are thinking about going down this path is that you have to understand that the operations models that we're operating under in, in INO and have been for the last 25 years are super outdated and they're fundamentally broken for the digital age. We have to start thinking about different ways of doing things and how do we do that? Well, it's, it's people, organization, people are going to work together differently in an AI ops world, um, for the better. Um, but you know, there's going to be the, the age of the 40 person bridge call thing. >>Troubleshooting is going away. It's going to be three, four, five focused engineers that need to be there for that particular incident. Um, a lot of process mailer process we have in our level, one level, two engineering. What have you running of tickets, gathering of artifacts, uh, during an incident is going to be automated. That's a good thing. We should be doing those, those things by hand anymore. So I'd say that the, to people's like start thinking about what this means to your organization. Start thinking about the great things we can do by automating things away from people, having to do them over and over again. And what that means for them, getting them matched to what they want to be doing is high level engineering tasks. They want to be doing monitorization, working with new tools and technologies. Um, these are all good things that help the organization perform better as a whole great advice and great kind of some of the thoughts that you shared rich for what the audience needs to be on the lookout. For one, I want to go over to you, give me your thoughts on what the audience that should be on the lookout for, or put on your agendas in the next 12 months. >>So there's like a couple of ways to answer that question. One thing would be in the form of, you know, what are some of the things they have to be concerned about in terms of implementing this solution or harnessing its power. The other one could be, you know, what are the perhaps advantages they should look to see? So if I was to talk about the first one, let's say that, what are some of the things I have to watch out for like possible pitfalls that everybody has data, right? So yeah, there's one strategy we say, okay, you've got the data, let's see what we can do with them. But then there's the exact opposite side, which has to be considered when you're doing that analysis. What are the use cases that you're looking to drive? Right. But then use cases you have to understand, are you taking a reactive use case approach? >>Are you taking active use cases, right? Or, yeah, that's a very, very important concentration. Then you have to be very cognizant of where does this data that you have, where does it reside? What are the systems and where does it need to go to in order for this AI function to happen and subsequently if there needs to be any backward communication with all of that data in a process manner. So I think these are some of the very critical points because you can have an AI solution, which is sitting in a customer data center. It could be in a managed services provider data center, like, right, right. It could be in a cloud data center, like an AWS or something, or you could have hybrid views, et cetera, all of that stuff. So you have to be very mindful of where you're going to get the data from is going to go to what are the use cases you're trying to get out to do a bit of backward forward. >>Okay, we've got this data thing and I think it's a journey. Nobody can come in and say, Hey, you've built this fantastic thing. It's like Terminator two. I think it's a journey where we built starting with the network. My personal focus always comes down to the network and with 5g so much, so much more right with 5g, you're talking low latency communication. That's like the true power of 5g, right? It's low latency, it's ultra high bandwidth, but what's the point of that low latency. If then subsequently the actions that need to be taken to prevent any problems in application, IOT applications, remote surgeries, uh, self driving vehicles, et cetera, et cetera. What if that's where people are sitting and sipping their coffees and trying to take action that needs to be in low latency as well. Right? So these are, I think some of the fundamental things that you have to know your data, your use cases, that location, where it needs to be exchanged, what are the parameters around that for extending that data? >>And I think from that point at one word, it's all about realizing, you know, sense of business outcomes. Unless AI comes in as a digital labor that shows you, I have, I have reduced your this amount of time and that's a result of big problems or identified problems for anything. Or I have saved you this much resource in a month, in a year or whatever timeline that people want to see it. So I think those are some of the initial starting points, and then it all starts coming together. But the key is it's not one system that can do everything. You have to have a way where, you know, you can share data once you've caught all of that data into one system. Maybe you can send it to another system at make more, take more advantage, right? That system might be an AI and IOT system, which is just looking at all of your street and make it sure that Hey parents. So it's still off just to be more carbon neutral and all that great stuff, et cetera, et cetera, >>Stuff for the audience to can cigarette rush, take us time from here. What are some of the takeaways that you think the audience really needs to be laser focused on as we move forward into the next year? You know, one thing that, uh, I think a key takeaway is, um, uh, you know, as we embark on 2021, closing the gap between intent and outcome and outputs and outcome will become critical, is critical. Uh, you know, especially for, uh, you know, uh, digital transformation at scale for organizations context in the, you know, for customer experience becomes even more critical as who Swan Huseman was talking, uh, you know, being network network aware network availability is, is a necessary condition, but not sufficient condition anymore. Right? The what, what, what customers have to go towards is going from network availability to network agility with high security, uh, what we call app aware networks, right? How do you differentiate between a trade, a million dollar trade that's happening between, uh, you know, London and New York, uh, uh, versus a YouTube video training that an employee is going through? Worse is a YouTube video that millions of customers are, are >>Watching, right? Three different context, three different customer scenarios, right? That is going to be critical. And last but not least feedback loop, uh, you know, responsiveness is all about feedback loop. You cannot predict everything, but you can respond to things faster. I think these are sort of the three, three things that, uh, that, uh, you know, customers aren't going to have to have to really think about. And that's also where I believe AI ops, by the way, AI ops and I I'm. Yeah. You know, one of the points that was smart and shout out to what he was saying was heterogeneity is key, right? There is no homogeneous tool in the world that can solve problems. So you want an open extensible system of intelligence that, that can harness data from disparate data sources provide that visualization, the actionable insight and the human augmented recommendation systems that are so needed for, uh, you know, it operators to be successful. I think that's where it's going. >>Amazing. You guys just provided so much content context recommendations for the audience. I think we accomplished our goal on this. I'll call it power panel of not only getting to a consensus of what, where AI ops needs to go in the future, but great recommendations for what businesses in any industry need to be on the lookout for rich Huisman Raj, thank you for joining me today. We want to thank you for watching. This was such a rich session. You probably want to watch it again. Thanks for your time. Thanks so much for attending and participating in the AI OBS virtual forum. We really appreciate your time and we hope you really clearly understand the value that AI ops platforms can deliver to many types of organizations. I'm Lisa Martin, and I want to thank our speakers today for joining. We have rich lane from Forrester who's fund here from Verizon and Raj from Broadcom. Thanks everyone. Stay safe..

>>From around the globe with digital coverage brought to you by Broadcom. >>So our final segment today, so we've discussed today, the value that AI ops will bring to organizations in 2021, we'll discuss that through three different perspectives. And so now we want to bring those perspectives together and see if we can get a consensus on where AI ops needs to go for folks to be successful with it in the future. So bringing back some folks Richland is back with us. Senior analysts, serving infrastructure and operations professionals at Forester with smartness here is also back global product management at Verizon and Srinivasan, Reggie Gopaul head of product and strategy at Broadcom guys. Great to have you back. So let's jump in and Richard, we're going to, we're going to start with you, but we are going to get all three of you, a chance to answer the questions. So rich, we've talked about why organizations should adopt AI ops, but what happens if they choose not to what challenges would they face? Basically what's the cost of organizations doing nothing. >>Yeah. So it's a really good question because I think in operations for a number of reviews, we've kind of stand, uh, stood Pat, where we are, where we're afraid change things sometimes. Or we just don't think about a tooling is often the last thing to change because we're spending so much time doing project work and modernization and fighting fires on a daily basis. Uh, that problem is going to get worse if we do nothing. Um, you know, we're building new architectures like containers and microservices, which means more things to mind and keep running. Um, we're building highly distributed systems where you got moving more and more into this hybrid world, the multicloud world, uh, it's become over-complicate and I'll give a short anecdote. I think, eliminate this. Um, when I go to conferences and give speeches, it's all infrastructure operations people. And I say, you know, how many people have three X, five X, you know, uh, things to monitor them. They had, you know, three years ago, two years ago, and everyone's hand goes up, say how many people have hired more staff in that time period. Zero hands go up. That's the gap we have to fill. And we have to fill that through better automation, more intelligent systems. It's the only way we're going to be able to feel back out. >>What's your perspective, uh, if organizations choose not to adopt AI ops. >>Yeah. >>That's pretty good. So I'll do that. >>Yeah. So I think it said, I say it's related to a couple of things that probably everybody tired off lately and everybody can relate to. And this would resonate that we'd have 5g, which is old set to transform the one that we know it, of communication with these smart cities, smart communities, IOT, which is going to become pivotal to the success of businesses. And as we seen with this, COVID, you know, transformation of the world that there's a, there's a much bigger cost consciousness out there. People are trying to become much more, forward-looking much more sustainable. And I think at the heart of all of this, that the necessity that you have intelligent systems, which are bastardizing more than enough information that previous equipment overlooked, because if you don't measure engagement, not going right. People love being on the same page of this using two examples for hundreds of things that play a part in things not coming together in the best possible way. So I think it has an absolute necessity to grind those cost efficiencies rather than, you know, left right and center laying off people who are like pit Mattel to your business and have a great tribal knowledge of your business. So to speak, you can drive these efficiencies through automating a lot of those tasks that previously were being very manually intensive or resource intensive. And you could allocate those resources towards doing much better things, which let's be very honest going into 20, 21, after what we've seen with 2020, it's going to be mandate >>Shaking your head there when you, his mom was sharing his thoughts. What are your thoughts about this sounds like you agree. Yeah. I mean, uh, you know, uh, to put things in perspective, right? I mean, we are firmly in the digital economy, right? Digital economy, according to the Bureau of economic analysis is 9% of the us GDP. Just, you know, think about it in, in, in, in, in the context of the GDP, right? It's only ranked lower, slightly lower than manufacturing, which is at 11.3% GDP and slightly about finance and insurance, which is about seven and a half percent GDP. So G the digital economy is firmly in our lives, right? And so someone was talking about it, you know, software eats the world and digital, operational excellence is critical for customers, uh, to, uh, you know, to, uh, to drive profitability and growth, uh, in the digital economy. >>It's almost, you know, the key is digital at scale. So when, uh, when rich talks about some of the challenges and when newsman highlights 5g, as an example, those are the things that, that, that come to mind. So to me, what is the cost or perils of doing nothing? You know, uh, it's not an option. I think, you know, more often than not, uh, you know, C-level execs are asking their head of it and they are key influencers, a single question, are you ready? Are you ready in the context of addressing spikes in networks because of, uh, the pandemic scenario, are you ready in the context of automating away toil? Are you ready to respond rapidly to the needs of the digital business? I think AI ops is critical. >>That's a great point, Roger, where gonna stick with you. So we got kind of consensus there, as you said, wrapping it up. This is basically a, not an option. This is a must to go forward for organizations to be successful. So let's talk about some quick wins. So as you talked about, you know, organizations and C-levels asking, are you ready? What are some quick wins that that organizations can achieve when they're adopting AI? >>You know, um, immediate value. I think I would start with a question. How often do your customers find problems in your digital experience before you think about that? Right. You know, if you, if you, you know, there's an interesting web, uh, website, um, uh, you know, down detector.com, right? I think, uh, in, in Europe, there is an equal amount of that as well. It ha you know, people post their digital services that are down, whether it's a bank that, uh, you know, customers are trying to move money from checking account, the savings account and the digital services are down and so on and so forth. So some and many times customers tend to find problems before it operation teams do. So. A quick win is to be proactive and immediate value is visibility. If you do not know what is happening in your complex systems that make up your digital supply chain, it's going to be hard to be responsive. So I would start there >>Vice visibility. There's some question over to you from Verizon's perspective, quick wins. >>Yeah. So I think first of all, there's a need to ingest this multi-layered monetize spectrum data, which I don't think is humanly possible. You don't have people having expertise, you know, all seven layers of the OSI model and then across network and security and at the application of it. So I think you need systems which are now able to get that data. It shouldn't just be wasted reports that you're paying for on a monthly basis. It's about time that you started making the most of those in the form of identifying what are the efficiencies within your ecosystem. First of all, what are the things, you know, which could be better utilized subsequently you have the opportunity to reduce the noise of a troubled tickets handle. It sounds pretty trivial, but as an average, you can imagine every shop is tickets has the cost in dollars, right? >>So, and there's so many tickets and there's desserts that get on a network and across an end-user application value chain, we're talking thousands, you know, across and end user application value chain could be million in a year. So, and so many of those are not really, you know, cause of concern because the problem is somewhere else. So I think that whole triage is an immediate cost saving and the bigger your network, the bigger the cost of whether you're a provider, whether you're, you know, the end customer at the end of the day, not having to deal with problems, which nobody can resolve, which are not meant to be dealt with. If so many of those situations, right, where service has just been adopted, which is coordinate quality, et cetera, et cetera. So many reasons. So those are the, those are some of the immediate cost savings. >>They are really, really significant. Secondly, I would say Raj mentioned something about, you know, the end user application value chain and an understanding of that, especially with this hybrid cloud environment, et cetera, et cetera, right? The time it takes to identify a problem in an end-user application value chain across the seven layers that I mentioned with the OSI reference model across network and security and the application environment, it's something that in its own self has a massive cost to business, right? They could be point of sale transactions that could be obstructed because of this. There could be, and I'm going to use a very interesting example. When we talk IOT, the integrity of the IOT machine is extremely pivotal in this new world that we're stepping into. You could be running commands, which are super efficient. He has, everything is being told to the machine really fast. >>We're sending everything there. What if it's hacked? And if that robotic arm starts to involve the things you don't want it to do. So there's so much of that. That becomes a part of this naturally. And I believe, yes, this is not just like from a cost saving standpoint, but anything going wrong with that code base, et cetera, et cetera. These are massive costs to the business in the form of the revenue. They have lost the perception in the market as a result, the fed, you know, all that stuff. So these are a couple of very immediate funds, but then you also have the whole player virtualized resources where you can automate the allocation, you know, the quantification of an orchestration of those virtualized resources, rather than a person having to, you know, see something and then say, Oh yeah, I need to increase capacity over here, because then it's going to have this particular application. You have systems doing this stuff to, you know, Roger's point your customer should not be identifying your problems before you, because this digital where it's all about perception. >>Absolutely. We definitely don't want the customers finding it before. So rich, let's wrap this particular question up with you from that analyst perspective, how can companies use make big impact quickly with AI? >>Yeah, I think, you know, and it has been really summed up some really great use cases there. I think with the, uh, you know, one of the biggest struggles we've always had in operations is isn't, you know, the mean time to resolve. We're pretty good at resolving the things. We just have to find the thing we have to resolve. That's always been the problem and using these advanced analytics and machine learning algorithms now across all machine and application data, our tendency as humans is to look at the console and say, what's flashing red. That must be what we have to fix, but it could be something that's yellow, somewhere else, six services away. And we have made things so complicated. And I think this is what it was. One was saying that we can't get there anymore on our own. We need help to get there in all of this stuff that the outline. >>So, so well builds up to a higher level thing of what is the customer experience about what is the customer journey? And we've struggled for years in the digital world and measuring that a day-to-day thing. We know an online retail. If you're having a bad experience at one retailer, you just want your thing. You're going to go to another retailer, brand loyalty. Isn't one of the light. It wasn't the brick and mortal world where you had a department store near you. So you were loyal to that cause it was in your neighborhood, um, online that doesn't exist anymore. So we need to be able to understand the customer from that first moment, they touch a digital service all the way from their, their journey through that digital service, the lowest layer, whether it be a database or the network, what have you, and then back to them again, and we not understand, is that a good experience? >>We gave them. How does that compare to last week's experience? What should we be doing to improve that next week? And I think companies are starting and then the pandemic, certainly you push this timeline. If you listen to the, the, the CEO of Microsoft, he's like, you know, 10 years of digital transformation written down. And the first several months of this, um, in banks and in financial institutions, I talked to insurance companies, aren't slowing. Now they're trying to speed up. In fact, what they've discovered is that there, obviously when we were on lockdown or what have you, the use of digital services spiked very high. What they've learned is they're never going to go back down. They're never going to return to pretend levels. So now they're stuck with this new reality. Well, how do we service those customers and how do we make sure we keep them loyal to our brand? >>Uh, so, you know, they're looking for modernization opportunities. A lot of that, that things have been exposed. And I think Raj touched upon this very early in the conversation is visibility gaps. Now that we're on the outside, looking in at the data center, we know we architect things in a very specific way. Uh, we better ways of making these correlations across the Sparrow technologies to understand where the problems lies. We can give better services to our customers. And I think that's really what we're going to see a lot of the, the innovation and the people really for these new ways of doing things starting, you know, w now, I mean, I think I've seen it in customers, but I think really the push through the end of this year to next year when, you know, economy and things like that, straighten out a little bit more. I think it really, people are going to take a hard look of where they are is, you know, AI ops the way forward for them. And I think they'll find it. The answer is yes, for sure. >>So we've, we've come to a consensus that, of what the parallels are of organizations, basically the cost of doing nothing. You guys have given some great advice on where some of those quick wins are. Let's talk about something Raj touched on earlier, is organizations, are they really ready for truly automated AI? Raj, I want to start with you readiness factor. What are your thoughts? >>Uh, you know, uh, I think so, you know, we place our, her lives on automated systems all the time, right? In our, in our day-to-day lives, in the, in the digital world. I think, uh, you know, our, uh, at least the customers that I talked to our customers are, uh, are, uh, you know, uh, have a sophisticated systems, like for example, advanced automation is a reality. If you look at social media, AI and ML and automation are used to automate away, uh, misinformation, right? If you look at financial institutions, AI and ML are used to automate away a fraud, right? So I want to ask our customers why can't we automate await oil in it, operation systems, right? And that's where our customers are. Then, you know, uh, I'm a glass half full, uh, clinical person, right? Uh, this pandemic has been harder on many of our customers, but I think what we have learned from our customers is they've Rose to the occasion. >>They've used digital as a key moons, right? At scale. That's what we see with, you know, when, when Huseman and his team talk about, uh, you know, network operational intelligence, right. That's what it means to us. So I think they are ready, the intersection of customer experience it and OT, operational technology is ripe for automation. Uh, and, uh, you know, I, I wanna, I wanna sort of give a shout out to three key personas in, in this mix. It's somewhat right. One is the SRE persona, you know, site, reliability engineer. The other is the information security persona. And the third one is the it operator automation engineer persona. These folks in organizations are building a system of intelligence that can respond rapidly to the needs of their digital business. We at Broadcom, we are in the business of helping them construct a system of intelligence that will create a human augmented solution for them. Right. So when I see, when I interact with large enterprise customers, I think they, they, you know, they, they want to achieve what I would call advanced automation and AI ML solutions. And that's squarely, very I ops is, you know, is going as an it, you know, when I talked to rich and what, everything that rich says, you know, that's where it's going. And that's what we want to help our customers to. >>So rich, talk to us about your perspective of organizations being ready for truly automated AI. >>I think, you know, the conversation has shifted a lot in the last, in, in pre pandemic. Uh, I'd say at the end of last year, we're, you know, two years ago, people I'd go to conferences and people come up and ask me like, this is all smoke and mirrors, right? These systems can't do this because it is such a leap forward for them, for where they are today. Right. We we've sort of, you know, in software and other systems, we iterate and we move forward slowly. So it's not a big shock. And this is for a lot of organizations that big, big leap forward in the way that they're running their operations teams today. Um, but now they've come around and say, you know what? We want to do this. We want all the automations. We want my staff not doing the low complexity, repetitive tasks over and over again. >>Um, you know, and we have a lot of those kinds of legacy systems. We're not going to rebuild. Um, but they need certain care and feeding. So why are we having operations? People do those tasks? Why aren't we automating those out? I think the other piece is, and I'll, I'll, I'll send this out to any of the operations teams that are thinking about going down this path is that you have to understand that the operations models that we're operating under in INO and have been for the last 25 years are super outdated and they're fundamentally broken for the digital age. We have to start thinking about different ways of doing things and how do we do that? Well, it's, it's people, organization, people are going to work together differently in an AI ops world, um, for the better, um, but you know, there's going to be the, the age of the 40 person bridge call thing. >>Troubleshooting is going away. It's going to be three, four, five focused engineers that need to be there for that particular incident. Um, a lot of process mailer process we have for now level one level, two engineering. What have you running of tickets, gathering of artifacts, uh, during an incident is going to be automated. That's a good thing. We shouldn't be doing those, those things by hand anymore. So I'd say that the, to people's like start thinking about what this means to your organization. Start thinking about the great things we can do by automating things away from people, having to do them over and over again. And what that means for them, getting them matched to what they want to be doing is high level engineering tasks. They want to be doing monitorization, working with new tools and technologies. Um, these are all good things that help the organization perform better as a whole >>Great advice and great kind of some of the thoughts that you shared rich for what the audience needs to be on the, for going on. I want to go over to you, give me your thoughts on what the audience should be on the lookout for, or put on your agendas in the next 12 months. >>So there's like a couple of ways to answer that question. One thing would be in the form of, you know, what are some of the things they have to be concerned about in terms of implementing this solution or harnessing its power. The other one could be, you know, what are the perhaps advantages they should look to see? So if I was to talk about the first one, let's say that, what are some of the things you have to watch out for like possible pitfalls that everybody has data, right? So yeah, that's one strategy, we'd say, okay, you've got the data, let's see what we can do with them. But then there's the exact opposite side, which has to be considered when you're doing that analysis that, Hey, what are the use cases that you're looking to drive, right? But then use cases you have to understand, are you taking a reactive use case approach? >>Are you taking quite active use cases, right? Or that that's a very, very important consideration. Then you have to be very cognizant of where does this data that you have vision, it reside, what are the systems and where does it need to go to in order for this AI function to happen and subsequently if there needs to be any, you know, backward communication with all of that data in a process better. So I think these are some of the very critical points because you can have an AI solution, which is sitting in a customer data center. It could be in a managed services provider data center, like, right, right. It could be in a cloud data center, like an AWS or something, or you could have hybrid scenarios, et cetera, all of that stuff. So you have to be very mindful of where you're going to get the data from is going to go to what are the use cases you're trying to, you have to do a bit of backward forward. >>Okay. We've got this data cases and I think it's the judgment. Nobody can come in and say, Hey, you've built this fantastic thing. It's like Terminator two. I think it's a journey where we built starting with the network. My personal focus always comes down to the network and with 5g so much, so much more right with 5g, you're talking low latency communication. That's like the two power of 5g, right? It's low latency, it's ultra high bandwidth, but what's the point of that low latency. If then subsequently the actions that need to be taken to prevent any problems in critical applications, IOT applications, remote surgeries, uh, test driving vehicles, et cetera, et cetera. What if that's where people are sitting and sipping their coffees and trying to take action that needs to be in low latency as well. Right? So these are, I think some of the fundamental things that you have to know your data, your use cases and location, where it needs to be exchanged, what are the parameters around that for extending that data? >>And I think from that point onward, it's all about realizing, you know, in terms of business outcomes, unless AI comes in as a digital labor, that shows you, I have, I have reduced your, this amount of, you know, time, and that's a result of big problems or identified problems for anything. Or I have saved you this much resource right in a month, in a year, or whatever, the timeline that people want to see it. So I think those are some of the initial starting points, and then it all starts coming together. But the key is it's not one system that can do everything. You have to have a way where, you know, you can share data once you've got all of that data into one system, maybe you can send it to another system and make more, take more advantage, right? That system might be an AI and IOT system, which is just looking at all of your streetlights and making sure that Hey, parent switched off just to be more carbon neutral and all that great stuff, et cetera, et cetera >>For the audience, you can take her Raj, take us time from here. What are some of the takeaways that you think the audience really needs to be laser focused on as we move forward into the next year? You know, one thing that, uh, I think a key takeaway is, um, uh, you know, as we embark on 2021, closing the gap between intent and outcome and outputs and outcome will become critical, is critical. Uh, you know, especially for, uh, uh, you know, uh, digital transformation at scale for organizations context in the, you know, for customer experience becomes even more critical as Swan Huseman was talking, uh, you know, being network network aware network availability is, is a necessary condition, but not sufficient condition anymore. Right? The what, what, what customers have to go towards is going from network availability to network agility with high security, uh, what we call app aware networks, right? >>How do you differentiate between a trade, a million dollar trade that's happening between, uh, you know, London and New York, uh, versus a YouTube video training that an employee is going through? Worse is a YouTube video that millions of customers are, are watching, right? Three different context, three different customer scenarios, right? That is going to be critical. And last but not least feedback loop, uh, you know, responsiveness is all about feedback loop. You cannot predict everything, but you can respond to things faster. I think these are sort of the three, uh, three things that, uh, that, uh, you know, customers are going to have to, uh, have to really think about. And that's also where I believe AI ops, by the way, AI ops and I I'm. Yeah. You know, one of the points that was smart, shout out to what he was saying was heterogeneity is key, right? There is no homogeneous tool in the world that can solve problems. So you want an open extensible system of intelligence that, that can harness data from disparate data sources provide that visualization, the actionable insight and the human augmented recommendation systems that are so needed for, uh, you know, it operators to be successful. I think that's where it's going. >>Amazing. You guys just provided so much content context recommendations for the audience. I think we accomplished our goal on this. I'll call it power panel of not only getting to a consensus of what, where AI ops needs to go in the future, but great recommendations for what businesses in any industry need to be on the lookout for rich Huisman Raj, thank you for joining me today. >>Pleasure. Thank you. Thank you. >>We want to thank you for watching. This was such a rich session. You probably want to watch it again. Thanks for your time.

>>From the cube studios in Palo Alto in Boston. It's the cube covering the IBM thing brought to you by IBM. Everybody we're back. This is Dave Vellante the cube, and this is our wall-to-wall coverage, IBM's digital thing experienced for 2020. We're really excited to have Jerry Cuomo on. He's the, uh, vice president of blockchain technologies and an IBM fellow and longtime cube alum. Jerry, good to see you again. Thanks for coming on and wish we were face to face, but yeah, this'll do. Good to see you too. Yes, thanks for having me. So we've been talking a lot of and talking to, I've been running a CEO series a, of course, a lot of the interviews around, uh, IBM think are focused on, on COBIT 19. But I wonder if you could start off by just talking a little bit about, you know, blockchain, why blockchain, why now, especially in the context of this pandemic. >>David's, it's as if we've been working out in the gym, but not knowing why we needed to be fixed. And I know now why we need to be fit. You know, blockchain is coming just in time. Mmm. You know, with the trust factor and the preserving privacy factor. Okay. The way we move forward the world is now becoming more digital than ever people working from home. Um, the reliance and online services is, that's critical. our ability to work as a community accompanies companies. The shared data is critical. you know, blockchain brings a magical ingredient and that's the ingredient of trust, you know, in sharing data. Okay. When, if that data and the sources that are providing that data arc okay. From verified and trusted, we're more likely to use that data and you the, any friction that's caused for fear of trepidation that the data is going to be misused. >>Mmm. It goes start to go away. And when that happens, you speed up an exchange and we need speed. Time is of the essence. So blockchain brings a platform for trusted data exchange while preserving privacy. And that provides a foundation. I can do some amazing things in this time of crisis, right? Yeah. And it's, it's not only trust, it's also expediency and you know, cutting out a lot of the red tape. And I want to talk about some of the applications. You're heavily involved in that in the distributed ledger, a project, you know, one of the early leads on that. Um, talk about some of the ways in which you're flying that distributed a ledger. And let's go into some of the examples. So we're, we're really fortunate to be an early adopter blockchain and, and provider of blockchain technology and kind of the fruit of that. >>Um, as I said, it couldn't happen any sooner where we have, Mmm, I would say over a thousand, alright. Users using IBM blockchain, which is powered by the opensource Hyperledger fabric, I'd say over a hundred of those users, um, have reached a level of production networks. you know, it's been great to see some of the proprietors of those networks now repurpose the networks towards hastening the relief of, uh, and one, a couple of examples that stand out, Dave. Mmm. You've seen what's happening to our supply chain. And then I think we got some rebound happening as we speak, but companies all of a sudden woke up one morning and their supply chains were, I'm exhausted. So suppliers, we're out of key goods and the buyers needed very rapidly to expand. They're, the supplier is in their, in their supply chain. there are laws and regulations about what it takes to onboard a new supplier. >>You want to make sure you're not onboarding bad actors. So in IBM for example, we have over 20,000 suppliers to our business and it takes 30 to 40 days who, uh, validate and verify one of those suppliers. We don't have 30 to 45 days, you know, think about you're a healthcare company or a food company. So working with a partner called Jane yard, uh, co-created a network called trust yourself buyer. And we've been able to repurpose, trust your supplier now or companies that are looking, you know, around Kobe 19 to rapidly okay, expand, you know, their, their supply chain. So if you imagine that taking us 45 days or 40 days to onboard a new supplier, okay. Pick, pick a company in our supply chain, Lenovo, that supplier may very well want to go to Lenovo to and provide services to them. Well guess what, it's going to take 40 days, the onboard to Lenovo. >>But if they're part of the trust or supplier network and they've already onboarded to IBM, they're well on their way. You're being visible to all of these other buyers that are part of the IBM network, like Lenovo and many others. And instead of taking 40 days, maybe it only takes five days. All right. So radically, radically, you know, improving the time it takes them. You know, with companies like Ford making ventilators and masks, it will kind of be able to onboard Ford into, you know, health care, uh, companies. But you know, we want to be able to do it with speed. So trust your supplier is a great use of blockchain. Two, expand a buyer and suppliers. Mmm. Exposure. Mmm. And they expand their network to quickly onboard. And you know, with the trust that you get an exchanging data from blockchain with the Mmm provenance, that Hey, this company information was truly vetted by one of the trusted members of the network. >>There's no fee or trepidation that somehow these records were tampered with or, or misused. So that's one example they have of using blockchain. That's a huge, uh, example that you gave because you're right, there are thousands and thousands of companies that are pivoting to making, like you said, ventilators and masks and yeah, they're moving so fast and there's gotta be a trust involved. On the one hand, they're moving fast to try to save their businesses or you know, in the case of Ford, you help save the, the country or the world. On the other hand, you know, there's risks there. So that, that helps. I want to understand me. Pasa basically is, if I understand it, you can privately share, uh, information on folks that are asymptomatic but might be carriers of covert 19. Am I getting that right on? Okay. So me Pasa starts as a project, uh, from a company called has Sarah and their CEO Jonathan Levy. >>And among other things, Jonathan Levy is an amazing, uh, software developer and he's helped us and the community at large, bill, the Hyperledger fabric, uh, blockchain technology, that's part of IBM. Mmm. The power is IBM blockchain. So Jonathan, I have this idea because w what was happening is there were many, many data sources, you know, from the very popular and well known, uh, Johns Hopkins source. And we have information coming from the weather company. There are other governments, um, putting out data. Jonathan had this, this idea of a verified Mmm. Data hub, right? So how do we kind of bring that information together in a hub where a developer can now to get access to not just one feed, but many feeds knowing that both the data is an a normalized format. So that's easy to consume. And like if you're consuming 10 different data sources, you don't have to think about 10 different ways to interact it. >>No kind of normalizing it through a fewer, like maybe one, but also that we really authentically know that this is the world health organization. This is indeed John Hopkins. So we have that trust. So, okay. Yeah. With me, Pasa being I'm a data hub four, uh, information verified information related to the Kronos virus, really laying a foundation now for a new class of applications that can mash up information to create new insights, perhaps applying Mmm. Artificial intelligence machine learning to really look not just at any one of those, uh, data sources, but now look across data sources, um, and start to make some informed decisions. No, I have to say operate with the lights on, uh, and with certainty that the information is correct. So me Pasa is that foundation and we have a call for code happening that IBM is hosting for developers to come out and okay. Bring their best ideas forward and X for exposing me Pasa as a service to the, in this hackathon so that developers can bring some of their best ideas and kind of help those best ideas come alive with me. Me has a resource. >>That's great. So we've got two, we got the supply chain, we just need to share the Pasa. There's the other one then I think we can all relate to is the secure key authentication, >>which I love. >>Uh, maybe you can explain that and talk about the role that blockchain >>we're launching fits, right. So you know, there is people working from home and digital identity verification. It is key. You know, think about it. You're working remotely, you're using tools like zoom. Um, there's a huge spike in calls and online requests from tele-health or government benefits programs. Yeah. So this is all happening. Everything behind the scenes is, yeah. Around that is, is this user who they say they are, is this doctor who they say they are, et cetera. And there are scams and frauds out there. So working with speed, it means working with certainty. and with the verified me networks set out to do a couple of years ago and the beautiful part is, you know, it's ready to go now for this, for this particular usage it's been using. Mmm. Basically think about it as my identity is my identity and I get to lease out information too different institutions to use it for my benefit, not necessarily just for their benefit. >>So it's almost like digital rights management. Like if you put out a digital piece of art or music, you can control the rights. Who gets to use it? What's the terms and conditions, um, on, on your terms? So verified me, um, allows through a mobile app users to invite institutions who represent them, verify them. No. And so I'll allow my department of motor vehicle and my employer, Mmm. Two to verify me, right? Because I want to go back to work sooner. I want to make sure my work environment, um, I'm making this up. I want to make sure my work environment, the people have been tested and vaccinated, but I don't want to necessarily, you know, kind of abuse people's privacy. Right? So I'll opt in, I'll share that information. I'll get my, my doctor and my, uh, department of motor vehicle to say, yes, this is Gary. >>He's from this address. Yes, he has been vaccinated and now I can kind of onboard to services as much quicker whether that service is going through TSA. Do you get on an airplane badging back into my office or you know, signing on to a, you know, telemedicine, a service or government, a benefits program, et cetera. So verify me is using the self, uh, at the station through a mobile application to help speed up the process of knowing that that is truly you and you truly want this service. Uh, and you are also calling the shots as to that. What happens with your information that, you know, it's not spread all over the interweb it's under your control at all time. Right. So I think it's the best of all worlds. The national Institute for standards and technology looked at, verified me. They're like, Oh my gosh, this is like the perfect storm of goodness for identity. >>They actually appointed, yeah, it has a term, it's called triple blind data exchange. It sounds like a magical act. A triple blind data exchange means the requester. Mmm. Doesn't know who the provider is and less know the requester. Um, allows the provider to know, Mmm, the provider doesn't know who the requester requested, doesn't know who the prior provider is that is double-blind. And then the network provider doesn't know either. Right. But somehow across disformed and that's the magic of blockchain. I'm allowing that to happen and with that we can move forward knowing we're sharing information where it matters without the risk of it leaking out to places we don't want to do. So great application of secure key and verified me. Yeah, I love that. Then the whole concept of being able to control your own data. You hear so much today about, you know, testing and in contact tracing using mobile technology to do that. >>But big privacy concerns. I've always felt like, you know, blockchain for so many applications in healthcare or just being able to, as you say, control your own data. I want to better understand the technology behind this. When I think about blockchain, Mmm. I obviously you don't think about it. Cryptography, you've mentioned developers a number of times. There's software engineering. Yeah. Distributed ledger. Um, I mean there's, there's game theory in the, in the, in the cryptocurrency world, we're not talking about that, but there's the confluence of these technologies coming to them. What's the technology underneath these, these applications? Talking about it there, there is an open source, an organization called Hyperledger. It's part of the Linux foundation. They're the gold standard and open source, openly governed, Mmm. Technology you know, early on in 2018 yep. 18, 26. I mean, we got involved, started contributing code and developers. >>Two Hyperledger fabric, which is the industry's first permissioned blockchain technology. Permission meaning members are accountable. So the network versus Bitcoin where members are anonymous and to pass industry Reggie regulations, you can't be anonymous. You have to be accountable. Um, that's not to say that you can't, okay. Work privately, you know, so you're accountable. But transactions in the network, Mmm. Only gets shared with those that have a need, need to know. So that the foundation is Hyperledger fabric. And IBM has a commercial offering called the IBM blockchain platform that embodies that. That kind of is a commercial distribution of Hyperledger fabric plus a set of advanced tools to make it really easy to work with. The open source. All the networks that I talked about are operating their network across the worldwide IBM public cloud. And so cloud technology lays a really big part of blockchain because blockchains are networks. >>Mmm. You know, our technology, IBM blockchain platform runs really well in the IBM wow. But it also allows you to run anywhere, right? Or like to say where it matters most. So you may have companies, I'm running blockchain nodes in the IBM cloud. You may have others running it on their own premises behind their firewall. You might have others running an Amazon and Microsoft Azure. Right. So we use, um, you may have heard of red hat open shift, the container technology so that we can run Mmm. Parts of a blockchain network, I guess they said where they matter most and you get strengthened a blockchain network based on the diversity of the operators. Because if it was all operated by one operator, there would be a chance maybe that there can be some collusion happening. But now if you could run it know across different geographies across the IBM cloud. >>So almost three networks all run on use this technology or run on the IBM cloud. And Dave, one more thing. If you look at these applications, they're just modern application, you know, their mobile front ends, their web portals and all of that kind of, okay. Okay. The blockchain part of these applications, usually it's only 20% of the overall endeavor that companies are going through. The other 80% it's business as usual. I'm building a modern cloud application. So what we're doing in IBM with, but you know, red hat with OpenShift with our cloud packs, which brings various enterprise software across different disciplines, blends and domains like integration, application, data, security. All of those things come together to fill the other 80% the above and beyond blockchain. So these three companies, okay. You know, 99 plus others are building applications as modern cloud applications that leverage this blockchain technology. So you don't have to be a cryptographer or you know, a distributed database expert. It's all, it's all embodied in this code. Mmm. Available on the IBM cloud, 29 cents a CPU hour. It was approximately the price. So it's quite affordable. And you know, that's what we've delivered. >>Well, the thing about that, that last point about the cloud is it law, it allows organizations, enterprises to experiment very cheaply, uh, and so they can get, uh, an MVP out or a proof of concept out very quickly, very cheaply, and then iterate, uh, extremely quickly. That to me is the real benefit, the cloud era and the pricing model. >>I just mentioned, David, as I said it when I started, you know, it's like we were working out in a gym, but we weren't quite sure. We knew why we were, we were so keen on getting fit. And what I see now is this, you know, blossoming of users who are looking at, you know, a new agreement. We thought we understood digital transformation. Mmm. But there's a whole new nice to be digitized right now. You know, we're probably not going to be jumping on planes and trains, uh, working as, as, as more intimately as we were face to face. So the need for new digital applications that link people together. Uh, w we're seeing so many use cases from, um, trade finance to food safety, to proxy voting for stock, know all of these applications that we're kind of moving along at a normal speed. I've been hyper accelerated, uh, because of the crisis we're in. So blockchain no. Couldn't come any sooner. >>Yeah. You know, I want to ask you, as a technologist, uh, you know, I've learned over the years, there's a lot of ways to skin a cat. Um, could you do the types of things that you're talking about without blockchain? Um, I'm, I'm sure there are ways, but, but why is blockchain sort of the right path, >>Dave? Mmm. You can, you can certainly do things with databases. Mmm. But if you want the trust, it's as simple as this. A database traditionally has a single administrator that sets the rules up for when a transaction comes in. Mmm. What it takes to commit that transaction. And if the rules are met, the transactions committed, um, the database administrator has access who commands like delete and update. So at some level you can never be a hundred percent sure that that data was the data that was intended in there. With a blockchain, there's multiple administrators to the ledger. So the ledger is distributed and shared across multiple administrators. When a transaction is submitted, it is first proposed for those administrators, a process of consent happens. And then, and only then when the majority of the group agrees that it's a valid transaction, is it committed? And when it's committed, it's committed in a way that's cryptographically linked two other transactions in the ledger, I'm making it. >>Mmm tamper-proof right. Or very difficult to tamper with. And unlike databases, blockchains are append only so they don't have update and delete. Okay. All right. So if you really want that center of trusted data that is a tested, you know, that has checks and balances across different organizations, um, blockchain is the key to do it, you know? So could you do it in data with a database? Yes. But you have to trust that central organization. And for many applications, that's just fine. All right. But if we want to move quickly, we really want to share systems of record. Mmm. I hear you. Sharing a system of record, you have regulatory obligations, you can say, Oh, sorry, the record was wrong, but it was put in there by, by this other company. Well, they'll say, well, >>okay, >>nice for the other company, but sorry, you're the one in trouble. So with a blockchain, we have to bring assurances that we can't get into that kind of situation, right? So that shared Mmm. Distributed database that is kind of provides this tamper resistant audit log becomes the Colonel cross. And then with the privacy preservation that you get from encryption and privacy techniques, um, like we have like these things, both channels, um, you can transact, um Hm. And be accountable, but also, Mmm. Only share of transactions with those that have a need to know, right? So you get that level of privacy in there. And that combination of trust and privacy is the secret sauce that makes blockchain unique and quite timely for this. So yeah, check it out. I mean, on the IBM cloud, it's effortless. So to get up and running, you know, building a cloud native application with blockchain and you know, if you're used to doing things, um, on other clouds or back at the home base, we have the IBM blockchain software, which you can deploy. Yeah. Open shift anywhere. So we have what you need in a time of need. >>And as a technologist, again, you're being really, I think, honest and careful about the word tamper. You call it tamper resistant. And if I understand it right, that, I mean, obviously you can fish for somebody's credentials. Yeah. That's, you know, that's one thing. But if I understand that, that more than 50% of the peers in the community, it must agree to tamper in order for the system. You tampered with it. And, and that is the beauty of, of blockchain and the brilliance. Okay. >>Okay. Yeah. And, and, and for, um, performance reasons we've created optimizations. Like you can set a consensus policy up because maybe one transaction it's okay just to have a couple people agree and say, Oh, well, you know, out of the a hundred nodes, Mmm. Three agree, it's good enough. Okay. Other, other policies may be more stringent depending on the nature of the data and the transaction, right? So you can tone, you can kind of tune that in based on the class of transaction. And so it's kind of good and that's how we can get performance levels in the, you know, thousand plus. In fact, IBM and RBC, um, recently did, um, a series of performance analysis because RBC said, Hey, can I use this for some of my bank to bank exchanges and we need to support over a thousand transactions per second. They were able, in their use case, there's support over 3000. Transact for a second. Okay. Mmm. You know, that we were very encouraged by that. I'm glad you clarified that because, so essentially you're saying you can risk adjust the policies if you will. >>That's great to know. Mmm. I could go on forever on this topic. Well, we're unfortunately, Jerry, we're well over our time, but I want to thank you for coming back, planning this important topic. Thrilled. IBM has taken a leadership position here, and I think, you know, to your point, this pandemic is just going to, can accelerate a lot of things and blockchain is, but in my view anyway, one of them. Thank you, Dave. Oh, great questions and I really appreciate it. So everyone out there, um, stay safe. Stay healthy. All right. Thank you Jerry, and thank you for watching everybody. This is Dave Volante for the cube. Our coverage of the IBM think digital 2020 event. We'll be right back. Perfect. The short break.

>> Is and who we are today as as a country, as a universe. >> Narrator: Congratulations Reggie Jackson, (inspirational music) you are a CUBE alumni. (upbeat music) >> Announcer: Live from Las Vegas it's theCUBE covering Splunk.Conf19. Brought to you by Splunk. >> Okay, welcome back everyone it's theCUBE's live coverage here in Las Vegas for Splunk.Conf19. I am John Furrier host of theCUBE. It's the 10th Anniversary of Splunk's .Conf user conference. Our 7th year covering it. It's been quite a ride, what a wave. Splunk keeps getting stronger and better, adding more features, and has really become a powerhouse from a third party security standpoint. We got a C-SO in theCUBE on theCUBE today. Chief Information Security, John Frushour Deputy Chief (mumbles) New York-Presbyterian The Award Winner from the Data to Everywhere Award winner, welcome by theCube. >> Thank you, thank you. >> So first of all, what is the award that you won? I missed the keynotes, I was working on a story this morning. >> Frushour: Sure, sure. >> What's the award? >> Yeah, the Data Everything award is really celebrating using Splunk kind of outside its traditional use case, you know I'm a security professional. We use Splunk. We're a Splunk Enterprise Security customer. That's kind of our daily duty. That's our primary use case for Splunk, but you know, New York Presbyterian developed the system to track narcotic diversion. We call it our medication analytics platform and we're using Splunk to track opioid diversion, slash narcotic diversions, same term, across our enterprise. So, looking for improper prescription usage, over prescription, under prescription, prescribing for deceased patients, prescribing for patients that you've never seen before, superman problems like taking one pill out of the drawer every time for the last thirty times to build up a stash. You know, not resupplying a cabinet when you should have thirty pills and you only see fifteen. What happened there? Everything's data. It's data everything. And so we use this data to try to solve this problem. >> So that's (mumbles) that's great usage we'll find the drugs, I'm going to work hard for it. But that's just an insider threat kind of concept. >> Frushour: Absolutely. >> As a C-SO, you know, security's obviously paramount. What's changed the most? 'Cause look at, I mean, just looking at Splunk over the past seven years, log files, now you got cloud native tracing, all the KPI's, >> Frushour: Sure. >> You now have massive volumes of data coming in. You got core business operations with IOT things all instrumental. >> Sure, sure. >> As a security offer, that's a pretty big surface area. >> Yeah. >> How do you look at that? What's your philosophy on that? >> You know, a lot of what we do, and my boss, the C-SO (mumbles) we look at is endpoint protection and really driving down to that smaller element of what we complete and control. I mean, ten, fifteen years ago information security was all about perimeter control, so you've got firewalls, defense and depth models. I have a firewall, I have a proxy, I have an endpoint solution, I have an AV, I have some type of data redaction capability, data masking, data labeling capability, and I think we've seen.. I don't think security's changed. I hear a lot of people say, "Oh, well, information security's so much different nowadays." No, you know, I'm a military guy. I don't think anything's changed, I think the target changed. And I think the target moved from the perimeter to the endpoint. And so we're very focused on user behavior. We're very focused on endpoint agents and what people are doing on their individual machines that could cause a risk. We're entitling and providing privilege to end users today that twenty years ago we would've never granted. You know, there was a few people with the keys to the kingdom, and inside the castle keep. Nowadays everybody's got an admin account and everybody's got some level of privilege. And it's the endpoint, it's the individual that we're most focused on, making sure that they're safe and they can operate effectively in hospitals. >> Interviewer: What are some of the tactical things that have changed? Obviously, the endpoint obviously shifted, so some tactics have to change probably again. Operationally, you still got to solve the same problem: attacks, insider threats, etc. >> Frushour: Yeah. >> What are the tactics? What new tactics have emerged that are critical to you guys? >> Yeah, that's a tough question, I mean has really anything changed? Is the game really the game? Is the con really the same con? You look at, you know, titans of security and think about guys like Kevin Mitnick that pioneered, you know, social engineering and this sort of stuff, and really... It's really just convincing a human to do something that they shouldn't do, right? >> Interviewer: Yeah. >> I mean you can read all these books about phone freaking and going in and convincing the administrative assistant that you're just late for meeting and you need to get in through that special door to get in that special room, and bingo. Then you're in a Telco closet, and you know, you've got access. Nowadays, you don't have to walk into that same administrative assistant's desk and convince 'em that you're just late for the meeting. You can send a phishing email. So the tactics, I think, have changed to be more personal and more direct. The phishing emails, the spear phishing emails, I mean, we're a large healthcare institution. We get hit with those types of target attacks every day. They come via mobile device, They come via the phishing emails. Look at the Google Play store. Just, I think, in the last month has had two apps that have had some type of backdoor or malicious content in them that got through the app store and got onto people's phones. We had to pull that off people's phones, which wasn't pretty. >> Interviewer: Yeah. >> But I think it's the same game. It's the same kind to convince humans to do stuff that they're not supposed to do. But the delivery mechanism, the tactical delivery's changed. >> Interviewer: How is Splunk involved? Cause I've always been a big fan of Splunk. People who know me know that I've pretty much been a fan boy. The way they handle large amounts of data, log files, (mumbles) >> Frushour: Sure. >> and then expand out into other areas. People love to use Splunk to bring in their data, and to bring it into, I hate to use the word data leg but I mean, Just getting... >> Yeah >> the control of the data. How is data used now in your world? Because you got a lot of things going on. You got healthcare, IOT, people. >> Frushour: Sure, sure. >> I mean lives are on the line. >> Frushour: Lives are on the line, yeah. >> And there's things you got to be aware of and data's key. What is your approach? >> Well first I'm going to shamelessly plug a quote I heard from (mumbles) this week, who leads the security practice. She said that data is the oxygen of AI, and I just, I love that quote. I think that's just a fantastic line. Data's the oxygen of AI. I wish I'd come up with it myself, but now I owe her a royalty fee. I think you could probably extend that and say data is the lifeline of Splunk. So, if you think about a use case like our medication analytics platform, we're bringing in data sources from our time clock system, our multi-factor authentication system, our remote access desktop system. Logs from our electronic medical records system, Logs from the cabinets that hold the narcotics that every time you open the door, you know, a log then is created. So, we're bringing in kind of everything that you would need to see. Aside from doing something with actual video cameras and tracking people in some augmented reality matrix whatever, we've got all the data sources to really pin down all the data that we need to pin down, "Okay, Nurse Sally, you know, you opened that cabinet on that day on your shift after you authenticated and pulled out this much Oxy and distributed it to this patient." I mean, we have a full picture and chain of everything. >> Full supply chain of everything. >> We can see everything that happens and with every new data source that's out there, the beauty of Splunk is you just add it to Splunk. I mean, the Splunk handles structured and unstructured data. Splunk handles cis log fees and JSON fees, and there's, I mean there's just, it doesn't matter You can just add that stream to Splunk, enrich those events that were reported today. We have another solution which we call the privacy platform. Really built for our privacy team. And in that scenario, kind of the same data sets. We're looking at time cards, we're looking at authentication, we're looking at access and you visited this website via this proxy on this day, but the information from the EMR is very critical because we're watching for people that open patient records when they're not supposed to. We're the number five hospital in the country. We're the number one hospital in the state of New York. We have a large (mumbles) of very important people that are our patients and people want to see those records. And so the privacy platform is designed to get audit trails for looking at all that stuff and saying, "Hey, Nurse Sally, we just saw that you looked at patient Billy's record. That's not good. Let's investigate." We have about thirty use cases for privacy. >> Interviewer: So it's not in context of what she's doing, that's where the data come in? >> That's where the data come in, I mean, it's advanced. Nurse Sally opens up the EMR and looks at patient Billy's record, maybe patient Billy wasn't on the chart, or patient Billy is a VIP, or patient Billy is, for whatever reason, not supposed to be on that docket for that nurse, on that schedule for that nurse, we're going to get an alarm. The privacy team's going to go, "Oh, well, were they supposed to look at that record?" I'm just giving you, kind of, like two or three uses cases, but there's about thirty of them. >> Yeah, sure, I mean, celebrities whether it's Donald Trump who probably went there at some point. Everyone wants to get his taxes and records to just general patient care. >> Just general patient care. Yeah, exactly, and the privacy of our patients is paramount. I mean, especially in this digital age where, like we talked about earlier, everyone's going after making a human do something silly, right? We want to ensure that our humans, our nurses, our best in class patient care professionals are not doing something with your record that they're not supposed to. >> Interviewer: Well John, I want to hear your thoughts on this story I did a couple weeks ago called the Industrial IOT Apocalypse: Now or Later? And the provocative story was simply trying to raise awareness that malware and spear phishing is just tactics for that. Endpoint is critical, obviously. >> Sure. >> You pointed that out, everyone kind of knows that . >> Sure. >> But until someone dies, until there's a catastrophe where you can take over physical equipment, whether it's a self-driving bus, >> Frushour: Yeah. >> Or go into a hospital and not just do ransom ware, >> Frushour: Absolutely. >> Actually using industrial equipment to kill people. >> Sure. >> Interviewer: To cause a lot of harm. >> Right. >> This is an industrial, kind of the hacking kind of mindset. There's a lot of conversations going on, not enough mainstream conversations, but some of the top people are talking about this. This is kind of a concern. What's your view on this? Is it something that needs to be talked about more of? Is it just BS? Should it be... Is there any signal there that's worth talking about around protecting the physical things that are attached to them? >> Oh, absolutely, I mean this is a huge, huge area of interest for us. Medical device security at New York Presbyterian, we have anywhere from about eighty to ninety thousand endpoints across the enterprise. Every ICU room in our organization has about seven to ten connected devices in the ICU room. From infusion pumps to intubation machines to heart rate monitors and SPO2 monitors, all this stuff. >> Interviewer: All IP and connected. >> All connected, right. The policy or the medium in which they're connected changes. Some are ZP and Bluetooth and hard line and WiFi, and we've got all these different protocols that they use to connect. We buy biomedical devices at volume, right? And biomedical devices have a long path towards FDA certification, so a lot of the time they're designed years before they're fielded. And when they're fielded, they come out and the device manufacturer says, "Alright, we've got this new widget. It's going to, you know, save lives, it's a great widget. It uses this protocol called TLS 1.0." And as a security professional I'm sitting there going, "Really?" Like, I'm not buying that but that's kind of the only game, that's the only widget that I can buy because that's the only widget that does that particular function and, you know, it was made. So, this is a huge problem for us is endpoint device security, ensuring there's no vulnerabilities, ensuring we're not increasing our risk profile by adding these devices to our network and endangering our patients. So it's a huge area. >> And also compatible to what you guys are thinking. Like I could imagine, like, why would you want a multi-threaded processor on a light bulb? >> Frushour: Yeah. >> I mean, scope it down, turn it on, turn it off. >> Frushour: Scope it down for its intended purpose, yeah, I mean, FDA certification is all about if the device performs its intended function. But, so we've, you know, we really leaned forward, our CSO has really leaned forward with initiatives like the S bomb. He's working closely with the FDA to develop kind of a set of baseline standards. Ports and protocols, software and services. It uses these libraries, It talks to these servers in this country. And then we have this portfolio that a security professional would say, "Okay, I accept that risk. That's okay, I'll put that on my network moving on." But this is absolutely a huge area of concern for us, and as we get more connected we are very, very leaning forward on telehealth and delivering a great patient experience from a mobile device, a phone, a tablet. That type of delivery mechanism spawns all kinds of privacy concerns, and inter-operability concerns with protocol. >> What's protected. >> Exactly. >> That's good, I love to follow up with you on that. Something we can double down on. But while we're here this morning I want to get back to data. >> Frushour: Sure. >> Thank you, by the way, for sharing that insight. Something I think's really important, industrial IOT protection. Diverse data is really feeds a lot of great machine learning. You're only as good as your next blind spot, right? And when you're doing pattern recognition by using data. >> Frushour: Absolutely. >> So data is data, right? You know, telecraft, other data. Mixing data could actually be a good thing. >> Frushour: Sure, sure. >> Most professionals would agree to that. How do you look at diverse data? Because in healthcare there's two schools of thought. There's the old, HIPAA. "We don't share anything." That client privacy, you mentioned that, to full sharing to get the maximum out of the AI or machine learning. >> Sure. >> How are you guys looking at that data, diverse data, the sharing? Cause in security sharing's good too, right? >> Sure, sure, sure. >> What's your thoughts on sharing data? >> I mean sharing data across our institutions, which we have great relationships with, in New York is very fluid at New York Presbyterian. We're a large healthcare conglomerate with a lot of disparate hospitals that came as a result of partnership and acquisition. They don't all use the same electronic health record system. I think right now we have seven in play and we're converging down to one. But that's a lot of data sharing that we have to focus on between seven different HR's. A patient could move from one institution to the next for a specialty procedure, and you got to make sure that their data goes with them. >> Yeah. >> So I think we're pretty, we're pretty decent at sharing the data when it needs to be shared. It's the other part of your question about artificial intelligence, really I go back to like dedication analytics. A large part of the medication analytics platform that we designed does a lot of anomaly detections, anomaly detection on diversion. So if we see that, let's say you're, you know, a physician and you do knee surgeries. I'm just making this up. I am not a clinician, so we're going to hear a lot of stupidity here, but bare with me. So you do knee surgeries, and you do knee surgeries once a day, every day, Monday through Friday, right? And after that knee surgery, which you do every day in cyclical form, you prescribe two thousand milligrams of Vicodin. That's your standard. And doctors, you know, they're humans. Humans are built on patterns. That's your pattern. Two thousand milligrams. That's worked for you; that's what you prescribe. But all of the sudden on Saturday, a day that you've never done a knee surgery in your life for the last twenty years, you all of a sudden perform a very invasive knee surgery procedure that apparently had a lot of complications because the duration of the procedure was way outside the bounds of all the other procedures. And if you're kind of a math geek right now you're probably thinking, "I see where he's going with this." >> Interviewer: Yeah. >> Because you just become an anomaly. And then maybe you prescribe ten thousand milligrams of Vicodin on that day. A procedure outside of your schedule with a prescription history that we've never seen before, that's the beauty of funneling this data into Splunk's ML Toolkit. And then visualizing that. I love the 3D visualization, right? Because anybody can see like, "Okay, all this stuff, the school of phish here is safe, but these I've got to focus on." >> Interviewer: Yeah. >> Right? And so we put that into the ML Toolkit and then we can see, "Okay, Dr. X.." We have ten thousand, a little over ten thousand physicians across New York Presbyterian. Doctor X right over here, that does not look like a normal prescriptive scenario as the rest of their baseline. And we can tweak this and we can change precision and we can change accuracy. We can move all this stuff around and say, "Well, let's just look on medical record number, Let's just focus on procedure type, Let's focus on campus location. What did they prescribe from a different campus?" That's anomalous. So that is huge for us, using the ML Toolkit to look at those anomalies and then drive the privacy team, the risk teams, the pharmacy analytics teams to say, "Oh, I need to go investigate." >> So, that's a lot of heavy lifting for ya? Let you guys look at data that you need to look at. >> Absolutely. >> Give ya a (mumbles). Final question, Splunk, in general, you're happy with these guys? Obviously, they do a big part of your data. What should people know about Splunk 2019, this year? And are you happy with them? >> Oh, I mean Splunk has been a great partner to New York Presbyterian. We've done so much incredible development work with them, and really, what I like to talk about is Splunk for healthcare. You know, we've created, we saw some really important problems in our space, in this article. But, we're looking, we're leaning really far forward into things like risk based analysis, peri-op services. We've got a microbial stewardship program, that we're looking at developing into Splunk, so we can watch that. That's a huge, I wouldn't say as big of a crisis as the opioid epidemic, but an equally important crisis to medical professionals across this country. And, these are all solvable problems, this is just data. Right? These are just events that happen in different systems. If we can get that into Splunk, we can cease the archaic practice of looking at spreadsheets, and look up tables and people spending days to find one thing to investigate. Splunk's been a great partner to us. The tool it has been fantastic in helping us in our journey to provide best in-class patient care. >> Well, congratulations, John Frushour, Deputy Chief Information Security Officer, New York Presbyterian. Thanks for that insight. >> You're welcome. >> Great (mumbles) healthcare and your challenge and your opportunity. >> Congratulations for the award winner Data to Everything award winner, got to get that slogan. Get used to that, it's two everything. Getting things done, he's a doer. I'm John Furrier, here on theCube doing the Cube action all day for three days. We're on day two, we'll be back with more coverage, after this short break. (upbeat music)

>>Live from Washington DC. It's the cube covering Boomi world 19 how to bide bullying. >>Welcome to the cue of the leader in live tech coverage. Lisa Martin with John furrier live at Boomi world 2019 in DC. John and I are pleased to welcome one of our next guests, Rajiv Ahuja managing director, Deloitte consulting. Rajiv welcome to theCUBE. Thank you Lisa. So just saw the news yesterday, a partner summit, Deloitte named the 2019 innovation partner of the year. Congratulations to Deloitte on that. >>Thank you very much. We are very proud and honored to be an innovation partner with Boomi Uh, it's been a great journey with boomi. >>You are worldwide partner of the year last year. Talk to us about the Deloitte Boomi partnership, the Alliance, all the good stuff that's going on there. >>imooBSo we've been a boomi partner for a number of years now and our partnership has grown leaps and bounds over this time. Uh, we picked up Boomi as a, as an Alliance partner as years back because of the strength of their product. Phenomenal innovative product, great I-PASS platform. Uh, we love booming because of not just the features of its platform and product, but also because of the fact that it's easy to implement for our clients. Uh, it, it, it's easy to implement, uh, from a business perspective. Um, beauty of the product is that it has a lot of prebuilt integrations that it provides to our, our partners. Uh, and, and, and as a, as an Alliance partner with them. Uh, it provides by this all that we need from, in terms of training, in terms of, uh, you know, sales opportunities that we worked together with them on. >>As a management consultant and a global system integrator. You guys are, you work with a lot of big customers with big problems, big projects, broken down into smaller projects. What's the landscape look like from a customer? Digital transformation has been talked about for many, many years. People process technology. Why is Boomi doing so well? What's the, what's their secret sauce and what are the customers liking about booming? >>Excellent question. Um, so when we think about our clients right now, our clients are dealing with really business problems. They're talking about digital transformation. They're talking about, uh, cloud. They're talking about IoT, they're talking about, about, uh, how do we, how do they use AI? So those are the big problems that our clients are dealing with. Those are the big challenges and opportunities that declines have in front of them. And when our clients think of these, these opportunities and challenges are, there are three things that they need to deal with. They, they need to make sure that when they undertake these large transformations, they're able to easily integrate data that currently resides in a lot of their on-prim applications. In many of these transformation, the long pole in the tent happens to be the integration layer. That's what kind of holds back a lot of these transformation efforts. >>And Boomi is an excellent product to help them with that. A second area where clients kind of have to deal with Israeli, the speed of innovation. That's a big challenge that our clients have to deal with today. Uh, and, and, and, uh, you know, go another day is when you could bring out a new release of your product every three months, every six months. Our clients, customers, they need to see some new features every few weeks. And, and a large part about making change happen quickly is around being able to bring in the relevant data from your enterprise pretty quickly as well. And again, Boomi with its simplicity, uh, and providing an ability to simply integrate, uh, uh, products quickly. And you know, that helps with that agility as well as the speed of innovation or the number of projects increasing in companies. Because, you know, with data and agile application development, there's more projects happening. >>Do you see the numbers increasing? Can you share some insight into what that looked like? Is it a lot, is there order of magnitude? Is it changed? Is it the same game is 10, 15 years ago, but just broken down into smaller projects? One big project comes in. What's the, what's the, what's the project landscape like? >> So for us, uh, it's been, uh, a tremendous growth journey over the last 10 years. Okay. The number of projects, again driven by digital transformation efforts, cloud efforts, the number of projects, the kind of projects, the flavor of projects that is coming up. And the sheer volume of projects is around clients thinking about moving to SAS based application models, thinking about their digital transformation and then taking up more mobile as well as digital projects at this stage. Thinking about their, their uh, you know, big M and a deals at this stage. Uh, all these kind of changes within their environment and within their demands that their customers and the mining of them. That has really spiked up the level of number of projects that we see at the state. >>Are you seeing that in terms of the spike in projects similar between like an established business that might have all these silos of, of applications that don't connect versus like a, say a younger startup that might have a ton of data and they're trying to move so quickly? Are there the types of integration projects that they're needing to implement to transform? Pretty similar, >>so, so, eh, similar, but there are some unique characteristics for each of these. Uh, two uh, sort of buckets of clients I would say, or bucket of companies in a more traditional companies today. Really the need is around. Um, and I'll give you a few examples, right. Um, there is a big need among larger companies to, to move to cloud. A number of our clients have mandated that moving to cloud and taking their, their applications to the cloud is their priority number one. For a typical large sized company, their application landscape could be anywhere from about five to 600 applications in the ID portfolio to close to four to 5,000 applications. So if you look at that application landscape, the reality is that the push to the cloud at this moment of time across most of our clients, they have 15 20% of their applications in the cloud. They're using certain sass applications, they have their own custom applications that have been put on a cloud platform and then they still have a large proportion of their applications on prem as well. So that's the reality of application landscape. For our last scale clients and with this reality, the ability to integrate cloud to cloud applications, cloud two on-prem applications and on-prem to application on prem applications. That's, that's the key need for integration for our large scale clients. >>Reggie, I want to get your personal opinion on something. You've been in the industry for long time now. You seen many waves, maybe computer, client server, local area networking, inter networking, internet, web, web two. Dot. Oh, cloud cloud one. Dot. Oh, cloud 2.0 which we're in now. What is the big story in your mind, what's the most important story that in tech today in your mind and what's the most important story that isn't being told or isn't being shared? Talked enough about >>the, the big story that has been talked about and I mentioned earlier, right? Is, is multicloud that's the big story that kind of is on the surface. The big story is that ultimately everything has to be business driven. It's the customer that is demanding change from our clients. The customer is saying that they are, they want to just deal with mobile. The younger customer, which will be the customer for of tomorrow, they want to be mobile. Right? And our clients, whether it's financial services clients or retail clients or any clients, uh, in most of the industry, you know, that's where their mind is. They want to be mobile first. They want to be cloud first. So that's the big story that's being told. And every client across flawless, all all industries that we support, that's the same story that we hear at every line. Right? The second big story at our clients is, is that that, that the computational power as has gone has, has improved so much that IOT connections with IOT, that's reality now that is coming reality, that's becoming reality. The third big story at our clients is that the traditional on prem applications that run the core guts of our clients, they haven't gone away. They're here to stay for some time. Most of our clients want to transform their core applications, but, but they haven't yet spend the money to, to transform them, >>you know, and great perspective. Thank you for sharing that insight. Uh, one of the interesting things about cloud 2.0 I'm calling it cloud 2.0 cause we were kind of in cloud 2.0 world cloud one. Dot. O was compute storage scale up Amazon born in the cloud API APIs, agile grade cloud, cheap windows enterprise is hard. Multicloud hybrid cloud Coobernetti's containers, legacy infrastructure sins you mentioned. But one thing that's interesting and I'd like to get your thoughts on is that network management used to be a small white space. Then that turned into observability companies going public great solutions. So observability is now a big category. Automation is taking configuration management and turning that into a whole category around automation. Automation is a really big hot trend right now that's ultimately a data driven business driven opportunity. So observability automation, these are tell signs for cloud 2.0 what is your view on this? Someone who's been in the industry for while talking to customers as they start to think about standing up IOT or scaling up mobile automation's important. Data's important. What's your >>no, absolutely. At the end of the day it's all about data. At the end of the day, uh, when we talk about automation, right, and we're talking about end devices, we're talking about connectivity with the end devices, we're talking about our IOT and those connectivity. But at the end of the day, the heart of it is integration and bringing data that is residing either on prem, in core systems that you have all on the cloud in the courses from that you have, how do you bring that data at the forefront of your edge? A second key aspect around around cloud to auto is it's an ecosystem. Basically. It's an ecosystem place based basically not just in terms of sharing data within your walls and sharing data with your own ecosystem partners, but it's an ecosystem based play in cloud to Datto in terms of also utilizing what your ecosystem provides. So today there is really no need for a lot of our partners to kind of do a lot of lot of their compute inside. You know, when you think about AI, a lot of gold is available in the market today that you can leverage with your ecosystem players. So ecosystem players. Also another interesting aspect about cloud dude auto that often gets old. >>You talked a minute ago about you know, the, the need to have cloud to on prem integration on prem to on-prem, et cetera. And one of the things that I was reading about Boomi is, well, iPads used to be all about 10 years ago connecting on prem, sorry, the cloud to on-prem. Now it's any data source anywhere, any integration edge. You talked about that we have this as consumers, we have this demand to have everything mobile, right? Whenever, whatever it is that we want to call an Uber or maybe a CFO needs to procure some software. What, how does that influence Dillard's go to market strategy with Boomi knowing that booby is integrating on prem cloud edge? All of it? >>So great question. Uh, there are, there are really freaky, um, kind of opportunities that we see when we implement with our clients. Uh, the first big opportunity that we see is when our clients are, are taking a journey to the cloud. Uh, let's say many of our clients want to implement core SAS solution. They're implementing a net net suite solution, they're thinking of SAP S four HANA implementation on the cloud. They're thinking of both the implementation on the cloud, right? With any large SAS platform implementation, there is always need for connectivity to on-prem applications, other SAS applications at times two end devices, right? That's the point where we see a lot of our projects. That's the point where we see a lot of opportunity to help our clients using Boomi as an integration platform. Right? A second big area where we see, uh, our clients needing help is when in their life cycle there is a big event, for example, a big MNA deal, a big divestiture that that might be planning product launch or something significant, something significant. >>And at that point of time, for example, a typical divestiture deal, typically the company that is being so love at times as a part of the deal, the expectation from the buyer is that the core ID infrastructure that they're buying from the company would also be transformed as a part of the deal. And when that's the case and we have a number of examples of those where where you know as a part of the deal itself, the seller tries to modernize it infrastructure and the first thing they do is they go for a plethora of SAS applications to replace their core legacy applications and they want to integrate them very quickly. And that's another situation where we've seen a product like Boomi being very successful in helping us implement. So those are the two big use cases. And the third one is as obviously as you talked about around digital transformation, so driven by digital transformation, whether it's mobile alone or mobile along with transformations along with gain of some edge computational transformation. That's a situation where again, you know they're there, they're leading a large transformation within their organization. And a part of that is answer is making sure that from an integration perspective they standardize and that's where Boomi comes into a lot, a lot of picture as well. >>Well where do you have tons of opportunity? Tons of momentum. Thank you for joining John and me on the QB day, sharing what Deloitte and Boomi are doing together. And again, congratulations to Deloitte on the partner of innovation partner of the year. Thank you so much. Pleasure to talk with you for Regina and John furrier. I'm Lisa Martin. You're watching the cube from Boomi world 19 thanks for watching. Thank you very much.

>> from our studios in the heart of Silicon Valley, Palo Alto, California It is a cute conversation. >> Hello and welcome to the Special Cube conversation with remote gas. Steve, harried managing director of General Catalyst, is he's a venture capitalist. >> Former >> CTO of the M. Where? Cube alumni. Steve, welcome to this special cube conversation coming in remote from Palo Alto. You're right across town, but still grab you big news happening. And also get your thoughts on the emerald 2019. Welcome to our remote conversation. >> Yeah, we were close. And yet this makes it even more convenient. We >> love the new format. Bring people into no matter where they are, no matter. Whatever it takes to get the stories we want to do that. And two important ones having. We know the emeralds coming next week. But congratulations. In order to you and your portfolio companies signal FX, another cube alumni from we've been covering since the beginning of their funding acquisition. Bye, Splunk today for over a billion dollars. 60% in cash and 40%. And stop. Congratulations. You've been on the board. You've known these guys from VM. We're quite a team. Quite an exit It's a win win for those guys. Congratulations. >> Yeah, Great group of guys. Several, which were at being where, as you as you mentioned, and as you've had on your show, that's great. They were doing a really good job of monitoring and getting metrics about applications and how they're doing it. And they're marrying it with spunk, stability to ingest logs and really understand operational >> data. And I think that combination will be very powerful. >> It brings kind of what we've been monitored. Calling Cloud 2.0, Suzie, monitoring 2.0, is really observe ability As the world starts moving into the kinds of service is we're seeing with Cloud on premises operations more than ever, that game has changed much more dynamic, and the security impact is significant. And certainly as as applications connect with its coyote or any I p device having that day, that scales really critical part of that. And I know signal left fax was one of those companies where you invested early, and I remember interviewing a couple of years ago in saying, Damn, these guys might be too early. I mean, they're so smart, they're so on it. But this is an example of skating to where the puck is As we increase, Key would say, These guys were just hitting their stride. Steve, can you Can you share any color commentary on on the deal and or you know why this is so important? >> Well, they've been at this for a long time, and they're a great team. I've been involved. Is investor less time? Obviously. But it was the really original team out of Facebook monitoring really at scale applications and then trying to take that technology that Facebook could use and applied it to our world. And, you know, as you discovered, we're in a world of micro service's and containers, and that is definitely hitting its stride right now. And so they were in the right place knowing how >> to monitor this very fast moving >> information and make some sense out of it. So you're a really good job on their part, and it was a pleasure to be >> along for part of the ride with him. >> It's great to me, great founders that have a vision and stay the course because, you know it's always it's always tricky when you're early to see the future especially around their top micro surfaces and containers way back before became the rage and now more relevant operationally for enterprises, it's easy to get distracted and man that fashion. We'll just jump on this trend of this way. They stayed the course. They stayed the nose to the grindstone and now observe ability. Which, to me is code word for monitoring. 2.0 is probably one of the hottest segments you saw Cummings going public companies filing the pager Duty dynatrace. Now you guys with your acquisition with Signal FX, This is an important sector this would normally be viewed in. I t. Rule is kind of list of white space, but it seems to be a much bigger landscape. Can you comment on your view on this and why it's so important? Why is observe ability so hot? Steve? >> Well, it's been this actually had a great market to be in for quite a while. They've been a large number of companies, continue to be both built up, and it's pretty simple. That amount of e commerce, or the amount of customer interactions you're having over applications and over the Web has gone up, and so anything that's not performing well or as downtime literally cost you a lot of money as a company. And so as these applications get more complex and they're being relied on >> Maur for revenue and for custom directions, >> you simply have to have better tools. And that's gonna be something that continues to evolve, that we got more complex, absent, more commerce is going >> to go through them. >> Complexity is actually something that people, a lot of people are talking about. I want to ask you something around today's marketplace, but I want you to compare and contrast it, similar to what your experience wasn't v m Where were you? The CTO virtual ization of all very, very quickly on ended up becoming a really critical component of the infrastructure, and a lot of people were pooh poohing that initially at first, then all sudden became. We've got to kill the M where you know so the resiliency of the M, where was such that they continue to innovate on virtualization, and so that's been a part of the legacy of V M wear, and the embers will cover next next week. But when you look at what's happening now with cloud computing and now some of the hybrid cloud up opportunities with Micro Service's and other other cool things. The role of the application is being is important part of the equation. It used to be the standup infrastructure, and that would enable the application to do things virtualization kind of change that game. Now you don't need to stand up. Any infrastructure could just deploy an application, and the infrastructure can be code and be self form, so you can have unique requirements. As infrastructure driven by the application, the whole world seemed to have flipped around. Do you see it that way? Is that accurate assessment? What's your thoughts on that? >> I think you're right on a bunch of fronts. People have been calling a different things, but the beauty of the, um where and you know this is a while ago now, but the reason it was successful is that you didn't have to change any of your software to use. It sort of slid him underneath an added value. But at the same time applications evolved. And so the that path of looking like hardware was something that was great for not changing applications. You have to think about a little differently when people are taking advantage of new application patterns or new service. Is that air in the cloud? And as you build up these as they're called cloud Native applications, it really is about the infrastructure. You know. It's job in life is to run applications. It sort of felt like the other way around. It used to be you wrote an application for what your infrastructure was. It shouldn't be like that anymore. It's about what you need to do to get the job done. And so we see the evolution of the clouds and their service. Is that air there? Certainly the notion of containers and a lot of the stuff that being where is now doing has been focused on those new applications and making sure Veum, where adds value to them, whatever type >> of application they are. >> It's interesting one of the exciting things in this way that we're on this year around multi cloud hybrid cloud in Public Cloud Now that we've kind of crossed over to the reality that public cloud has been there, done that succeeded I call that cloud 1.0, you saw the emergence of hybrid cloud. Even early on, around 2012 2013 we were talking about that of'em world instantly pad Kelsey here, but now you're seeing hybrid cloud validated. You got Outpost, you've got Azure stack, among other things. The reality is, if you are cloud native, you might not need to have anything on premise. Like companies like ours with 50 plus people. We don't have an I T department, but most enterprises have stuff on premise, so the nuance these days is around. You know, what's the architecture of of I T. These days, we add security into It's complicated. So these debates can there be a soul cloud for a workload? Certainly that's been something that we've been covering with the Amazon Jet I contract, where it's not necessarily a soul cloud for the entire Department of Defense. It's a soul cloud for the workload, the military application workload or app. The military. It's $10 million application, and it's okay to have one cloud, as we would say, But yet they're going to use Microsoft's cloud for other things. So the ODS having a multiple cloud approach, multiple environments, multiple vendors, if you will, but you don't have to split the cloud up. Her say This is kind of one of those conversations really evolving quickly because there's no real school of thought around this other than the old way, which was have a multi vendor environment split the things. What's your thoughts on the the workload relationship to the cloud? Is it okay to have a workload, have a single cloud for that workload and coexist with other clouds? >> It's funny. I've been thinking about this more lately. Where if you went back earlier in time, forgetting cloud, there used to be a lot of different type of servers that you >> can run on, whether it >> be a mainframe or a mini mainframe or Unix system or Olynyk system. And to some extent, people are choosing what would run where, based on the demands of the application, sometimes on price, sometimes on certifications or even what's been poured into the right one. So this is a beating myself, you know, that's that's a while ago. It's not too different to kind of think about the different kind of cloud service is there out there, whether you're running your own on your own data center or whether you're leveraging one from the other partners. I really do think in the ideal world you get your choice of the best possible platform for the application across a variety of characteristics. And it's kind of up to the vendors of management software and monitoring software at security software to give you more flexibility to choose where to run. And so for getting D'Amore exactly. But think of a virtualization layer that really tries to abstract out and let you more fluidly run things on different clouds. Do you think that's where a lot of the the core software is head of these days really >> enable that toe work better >> as a >> 1,000,000 other use cases, but with storage being moved around >> for disaster recovery or for whatever it else might >> be? But that quarter flexibility reminds me a lot of choosing what application >> would want. Run would run where within your own company >> and the kubernetes trend in containers certainly really makes that so much more flexible because you can still run VM. Where's viens beams under the covers over Put stuff on bare metal a lot of great opportunities that's exciting >> and you slap in a P I in front of them and micro service is sort of works in tandem with that so that you could really have your application composed >> across multiple environments. >> And I think the ob surveilling observe ability is so hot because it takes what network management was doing in the old way, which is monitoring. Make sure things are operating effectively and combining with data. And so when I heard about the acquisition of signal effects into Splunk, I'm like, There it is. We're back to data. So observe ability is really a data challenge and opportunity for using what would be a white space monitoring. But it's more than monitoring because it's about the data and the efficacy of that data and how it's being used, whether it's for security or whatever your thoughts >> s. So there's more data than ever, for sure, and so being able to stream that in being able to capture it at cost, all that is a big part of our environment still working. The key thing is turning that into some actionable insight, and whether you're using no interesting calculations for that or different forms of machine learning like that's where this really has to go is with all this data coming in. How do >> I avoid false false >> positives? How do I only alert people when needed, then that allows you to do what everyone's talked about for 30 years, which is automatic remediation. But for now, let's talk about it. Is how do I process all of this rich data and give me the right information to take action? >> Do you want to thank you for coming on this promote cube conversation? You've been with us at the Cube since 2010. I think our first cube event was A M C. World 2010. That show doesn't existing longer because that folded into Del Technologies world. So VM world next week is the last show standing that has been around since the Cube. You've been around? Of course, you guys had VM worlds had their 10th anniversary was 2013 as a show. But this is our 10th year. Well, thank you for being part of our community and being a contributor with your commentary and your friendship and referral. Appreciate all that. So I gotta ask you looking back over the 10 years since you been with Doug, you've vm world. What's the most exciting moments? What are moments that you can say? Hey, that was an amazing time. That was a grind, but we got through it. Funny moments. Your thoughts. >> Boy, that's a tough question. I've enjoyed working with you, John and the Cube. There's been somebody really interesting things for me. The sum of the big acquisitions that we went through a V Um, where? Where? I think the NSX exposition. When we get a syrah, I think that really pushed us an interesting spots. But we have gone through, uh, I pose an acquisition ourself by the emcee begun Theo. It's a pretty vicious competition from Be Citrix Airs in or Microsoft. Yeah, that's just the joy of being a These companies is lots of ups and downs along the way that they almost kind of fit together to make an exciting life. >> What was some moments for you? I know you had left was the 2015 or 26 boys with your last day of >> the world. You go now, you know about six years. >> What do you miss about the end? Where >> the team is what everyone kind of cliche says. But it's totally true. The chance to kind of work with all those people at the executive staff all the way down to like these awesome engineers with Koi is so I definitely missed that Miss Shipping products. You don't get to do that as much directly as a venture capitalist. But on the flip side, this is a great world to be, and I get to see enthusiastic. You're very optimistic founders all day long, pushing the envelope. And while that was existing at the end where, uh, it's it's what I see every single day here. >> You've been on The Cube 10 times at the M World. That's the all time spot you're tied for. First congratulates on the leaderboard. It's been a great 10 years. Going forward. We've seen are so good. Looking back, I would say that you know Palmer, it's taking over from Diane Greene. Really set the table. He actually laid out. Essentially, what I think now is a clearly a cloud SAS architecture. I think he got that pretty much right again. Or maybe early in certain spots of what he proposed at that time. There's some things that didn't materialize is fast, but ultimately from core perspective. You guys got that right, Um, and then went in Try to do the cloud. But then and this year it comes in for suffered to find, you know, line with Amazon. And since that time, the stock has been really kind of it on the right. So, you know, some key moments there for Of'em. Where from Self >> Somali. More stuff. It's fun to see Pivotal now possibly coming back into after after getting started there. But I think you know, there's there's a hugely talented team of execs there. Pat L Singers come >> in and done a great job. I think, Greg, >> you and all these folks that Aaron, >> there are good thinkers. And so I >> think you'll consider just continue to see it evolved. Quite event and probably some cool announcements next week. >> Talk aboutthe roll Ragu and the team play because he doesn't really get a lot of the spotlight. He avoids it. I know he did talk to him privately that he won't come on the Q. I don't know what the other guys go on other guys in jail, so he's been instrumental. He was really critical in multiple deals. Could you share some insight into his role at bm bm were and why it's been so important. >> I'll push him to get on, especially now that you have remote. You can probably grab him now. He and Rajiv and Rayo Funeral Just all the guys air. I think he and Reggie basically split up half and half of the products. But Roger is very, very seminal in the whole cloud strategy that has clearly been working Well, he's a good friend in a very smart guy. >> Well, I want you to give me a personal word that you're gonna get me in a headlock and tell him to come on the Cube this year. We want him on. He's a great, great great guest. He's certainly knowledgeable going forward. Steve, 10 years out, we still got 10 more years of great change coming. If you look at the wee that's coming, you're out investing in companies again. You had one big exit today with the $1,000,000,000 acquisition that was happen by Splunk and signal effects. Ah, lot more action. You've been investing in security. What's your outlook? As you look at the next 10 years is a lot more action to happen. We seem to be early days in this new modern era. Historic time in the computer industry as applications without dictating infrastructure capabilities is still a lot more to do. What do you excited about? >> There's a million things I get to see every day, which are clearly where the world is headed. But I think at the end of the day there's there's infrastructure, which the job in life of infrastructure is to run applications. And so then you look at applications. How are they changing and what is the underlying fabric gonna need to do to support them? And if you look at the future of applications, it's clearly some amazing things around artificial intelligence and machine learning to actually make them smarter. It's all different factors form factors that they're running on and being displayed on. I think we clearly have a world where with the next generation of networking, you could do even more at the edge and communicate in a very different way with the back end. I kind of look at all these application patterns and really trying to think about what is the change to the underlying clouds and fabrics and compute that's gonna be needed to run them. I think we have plenty of head room of interesting ideas ahead. >> Stew, Dave and I were talks to Dave. Stupid Valenti student and I were talking about, you know, as infrastructure and cloud get automate as automation comes in, new waves are gonna be formed from it. What new waves do you see? Is it like R P ay, ay, ay, ay. Because as those things get sucked in and the ships and two new waves What? Oh, that's some of the key ways people should pay attention to. I'm not saying the industries is going away, but as it becomes automated, and as the shift happens, the value still is there. Where is those new waves? >> Well, then, today it looks like most applications they're gonna be composed of a lot of service is, um and I think they're gonna be able. They're going to need to be displaying on everything from big screens to small screens to purely as a headless 80. I front ends, and so again, I think at the end of the day, this this infrastructure is gonna have to have a lot of computation capability after crunch do tons of data but also have to stitch together these connections between components and provide really good experiences and predictability in the network and all those air very hard problems that we've been working on for a while. I think we'll keep working on them and new forms for the next 10 years at least. >> Awesome. Steve. Thanks for being a friend with us in the queue, but you're funny. Favorite moment of the Q. Can you share any observations about the cube and your experiences? Your observations over the 10 years we've come a long way, >> you go ugly, actually enjoyed it. I mean, it's a microcosm of all the other stuff going on, but I saw your first little box that you built and used for the Cube like that was that was really cool. But now the fact that I'm on my laptop, you doing this over the network and it's showing up is pretty awesome. So think you're following the same patterns of the other, have the other applications moving the cloud and having good user experiences. >> Cube native here software native Steve. Thank you so much for stating the time commenting on the acquisition. I know it's fresh on the press. Ah, lot more analysis and cut to come next week. It's certainly I'll be co hosting at Splunk dot com later in the year. So I'm looking forward to connect with a team there and again. Thanks for all your contribution into the cube community. We really appreciate one. Thank you for your time. >> Thanks. You guys are awesome. Thanks for chatting. >> Okay. Steve Herod, managing director at general counsel, Top tier VC From here in Silicon Valley and offices around the world, I'm John for breaking down the news as well as a V Emerald preview with the former CTO of'em. Were Steve hair now a big time venture capitalists. I'm John Ferrier. Thanks for watching.

>> What are you? This's and who we are today? A za country as a university. Congratulations, Reggie Jackson. You are Cube alumni? >> No. >> Live from San Diego, California. It's the queue covering Sisqo live US 2019 Tio by Cisco and its ecosystem barkers. >> Welcome back to San Diego. Everybody who went to the Cube, the leader in live tech coverage. My name is Dave Volante, and I'm here with my co host Student of the day. One of our wall to wall coverage of Sisqo Live 2019 behind us is the definite zone. A lot of action here. A lot of the C c e E. Folks learning howto code infrastructure. A big trend in the business G written houses here is the senior vice president and general manager of the security business group Francisco. Gee, thanks for coming on the Cube. My pleasure. Thank you for inviting me. So we've been talking on the cube a lot about Cisco coming at it. Multi cloud, for example, from a position of strength, try to convince your customers that your networks air higher performance, more cost effective and very importantly, more secure, of course. And I mean everybody always wants more performance. They want lower costs. Security in many ways has begun to trump those other two attributes. They they become table stakes, security as well. But security is really number one. Now talk about that. Talk about the major trends that you're seeing. >> Well, of course, of course, security now is top of mind for everyone. Board level conversations, executive level conversations all the time. I think what ends up happening is in the past. We would think about it as network performance cost, etcetera security as a tangent kind of side conversation. Now, of course, it's built into everything that we do in the conversations that we have. And it's equally around performance, but also round simplicity, because security tends to be a little bit hard and lots of process. And how do you go through with compliance? Regulations were also folk. He's in a lot of effort on making it simple. >> Okay, so the big trendy, obviously, here's people talk about what you used to put all the money in the perimeter, hardened the perimeter. Now you can't dig a moat anymore. The queen leaves your castle. Yeah, it's a whole new paradigm. Yeah, So customers are realizing that it's a board level topic. Now, how is Cisco responding to that trend specifically? >> Well, quite frankly, what we're doing is taking that old perimeter and moving that perimeter to the appropriate spots Could be your branch. Now doing direct Internet access will move the perimeter to the branch. Could be your users. Your local mobile workforce will move the perimeter to surround those users and, of course, those applications that are sitting in the data center. Now, as they moved to and from the public cloud, we put segmentation, micro segmentation and follow them as well, to those perimeters are breaking down from one giant moat with the queen. Now we have lots and lots of little ones. >> So it's like the cubes do. You could bring it in exactly everywhere, everywhere built in. >> So you know what we know. It's a multi cloud world for customers today. One of the important pieces to help pull together the multi cloud is the SD land piece. Francisco, as a few diff different solutions in that space, an area. I was hoping you could explain that security piece of S t win, because people think of it so It's kind of like the old way, an opt or some of these other things. But security is such an important piece of that, you know, ever growing landscape. >> So you know, it's funny because people are adopting Ston for simplicity as well as lower costs, and the last thing we want to have forced people to do is to have tto bolt on various security solutions. Right then also, you know, the next day your network operations is complex again. So what we did last year was we took part of the security portfolio and built it directly into our on premises ston appliances so that you could take that ston deploy it. And so security is built in. That is a huge, huge market opportunity. And of course, since we also have a secure cloud platform, we're moving that same feature functionality into the clouds. So whether our customers want to secure their ston with technologies on Prem or in the cloud, Cisco has both ends >> covered wound. It ties into the whole development dev ops mentality and Christians appropriate here in the definite soon. But do you want to ask you how have organizations? However, there was security regimes or how are they evolving? How are they changing? It used to be okay. SEC ops. That's your problem, guys. It's your problem. And we know that doesn't work. Yes, a team effort. But talk about the organizational evolution that you're saying. >> We'll not only so the organizational effort. You were seeing a lot of the technology emerge and from an organization perspective, whether it's it's under a CEO or see. So that's a separate conversation. But from a technology perspective, they're getting heavily, heavily integrated. And that is now forcing network people to actually think about policy segmentation security muchmore than they were in the past and, conversely, security people starting to think about mobile devices and networking and things like that. So we're seeing this big blur across the organization, both from an operational perspective as well as processes and work flows. >> What about the role of data and analytics in terms of Howard informs you how that's evolving machine intelligence coming into play? How Cisco exploiting that? What's it going to >> mean for your customers? Well, as the industry leader in terms of security, we consume massive amounts of data. For example, we block 6,000,000,000 events per day. That's more than Google queries, right? We do 185,000,000,000 DNA s queries. That's 5% of the global Internet traffic. Of course, Ria's humans can't like calculate what's the good in the bad? So we rely heavily on machine learning, artificial intelligence and whatnot. We have the largest non government threat research group in the industry, and that's what they do day after day, looking for those needles in a haystack, thes threats in the sea of normal. >> And you can't do that with with alerts. I mean, just that way you've gotta have automation. So in his world of cloud, so so talk a little bit about the automation principles that you guys are done designing into your products. >> Well, security is one of the fields where not only do we have to calculate the alert, but we operate in the environment of false positives. You could turn on like we're going to protect you and block everything. But then also a lot of things that appear as threats actually weren't threats, those air, false positives. So our goal is to protect the enterprise and get zero false positive go all the way to the edge and the way we do that, of course, is not only tow, automate and say these are all your events, but we have to rank. Stack them in terms of importance. There's only a certain amount of time in the day, so you want to go to the most important, most critical event. Automate that, then go next the neck. So we automate but also ranks stack in the presence >> of false and do you see the day? Or maybe you're starting to get their ready where the machine actually acts as an agent for you and certainly, I'm sure a plugs, holes and things like that, but actually takes it one step further and makes decisions about what to go after. So >> in many cases, yes, particularly riel time around files and things like that in other cases? No, because there's a work floor flow there that says I'm actually not going to deploy those firewall >> rules >> until I test them and evaluate them and whatnot. So everything from rial time into probably >> aware you need a human and that you do, in the end, the Yeah, yeah, >> So in an ever 10 changing threat landscape. But, you know, how do you make sure you keep up? Cisco's made a number of acquisitions. How do you make it a seamless, you know, security environment for them, despite all of these various threats and attacks. >> So welcome to my day job studio. So essentially, we've done two things. We've taken all these assets, and we do accumulate and acquire the market leaders in the space. And the first thing that we do is integrate the back end. Though all those events I was telling you about, they're coming from all of these technologies, so we bring them all back so that we can focus on the efficacy. That is a big step, but that's what we do first. Then the second step, once that's done, is to integrate the front end so that the user, the customer, can sit there and go. Oh, I'm tracking an event. It came in through our email. It came in through a firewall, came through our end point and unify the front and experience. But the first thing we do is always on the back, >> so you get a lot of pressure from customers, obviously, because you are the network. You get a lot of pressure for them. But you in a position now, toe, actually lead the transformation with your customers. I mean, the whole paradigm shift, the mind, this shift. And what do you doing along those lines? >> So we are absolutely leading our customers were leading it and secure D A direct Internet access and SD win. The other thing that we've been investing heavily is in zero trust. So instead of just allowing everyone on the network and follow the threats we acquired Duo last year the leader in M F A. A and zero Trust. And now we're integrating that into the network so that we can also establish trust. But then block and verify. >> Craigie, I know you gotta jump, so thanks so much for your time. I recognize you. Thank you so much for coming. You're welcome. Great to have you. All right, keep it right to everybody. We'll be back with her next guess right after this short break, David, want a student at Lisa? Martin is also here. You watching the Cube from Cisco Live? San Diego back? >> No,

>> Narrator: Live from Nassau in the Bahamas. It's The Cube! Covering PolyCon 18. Brought to you by PolyMath. >> Welcome back everyone, we're live here in the Bahamas with The Cube's exclusive coverage of PolyCon 18, I'm John Furrier with my co-host Dave Vellante, both co-founders of SiliconANGLE. We start our coverage of the crypto-currency ICO, blockchain, decentralized world internet that it is becoming. It's the beginning of our tour, 2018. Our next guest is Hartej Sawhney who's the advisor at Pink Sky Capital, but also the co-founder of Hosho.io. Welcome to The Cube. >> Thank you so much. >> Hey thanks for coming on. Thanks for coming on. >> Thanks guys. >> We had a great chat last night, and you do some real good work. You're one of the smartest guys in the business. Got a great reputation. A lot of good stuff going on. So, take a minute to talk about who you are, what you're working on, what you're doing, and the projects you're involved in. >> So first of all, thank you so much for having me, it's really exciting to see the progress of high-quality content being created in the space. So my name is Hartej Sawhney. We have a team based in Las Vegas. I've been based in Las Vegas for about five years. But I was born and raised in central New Jersey, in Princeton. And my co-founder is Yo Sup Quan. We started this company about seven months ago and my co-founder's background was he's the co-founder of Coin Sighter in Exchange out of New York, which exited to Kraken. After that he started Launch Key which exited to Iovation. And prior to this company, my previous company was Zuldi, Z-U-L-D-I .com where we had a mobile point of sale system specifically for high volume food and beverage companies and businesses. So we were focused on Fintech and mobile point of sale and payment processing. So both of us have a unique background in both Fintech and cyber-security and my co-founder Yo, he's a managing partner of a crypto hedge fund named Pink Sky Capital. And he was doing diligence for Pink Sky, and he realized that the quality of the smart contracts he was seeing for deals that he wanted to participate as an investor in, and I'm an advisor in that hedge fund, we both realized that essentially the quality of these smart contracts is extremely low. And that there was nobody in this space that we saw laser focused on just blockchain security. And all the solutions that would be entailed in there. And so we began focusing on just auditing smart contracts, doing a line-by-line code review of each smart contract that's written, conducting a GAS analysis, and conducting a static analysis, making sure that the smart contract does what the white paper says, and then putting a seal of approval on that smart contract to mitigate risk. So that the code has not been changed once we've done an analysis of it, that there's no security vulnerabilities in this code, and that we can mitigate the risks for exchanges and for investors that someone has done a thorough code analysis of this. That there's no chance that this is going to be hacked, that money won't be stolen, money won't be lost, and that there's no chance of a security vulnerability on this. And we put our company's name and reputation on this. >> And what was the problem that is the alternative to that? Was there just poorly written code? Was it updated code? Was it gas was too expensive? They were doing off-chain transactions. I mean what are some of the dynamics that lead you guys down this path? I mean this makes sense. You're kind of underwriting the code, or you're ensuring it or I don't know what you call it, but essentially verifying it. What was the problem? And what were some of the use cases of problems? >> I would say that the underlying problem today in this whole industry, of the blockchain space, is that the most commonly found blockchain is Ethereum. The language behind Ethereum is called Solidity. Solidity is a brand new software language that very few people in the world are sufficient programmers in Solidity. On top of that, Solidity is updated, as a language on a weekly basis. So there are a very limited number of engineers in the world who are full-stack engineers, that have studied and understand Solidity, that have a security background, and have a QA mindset. Everything that I just said does exist on this Earth today and if it does, there's a chance that that person has made too much money to want to get out of bed. Because Ethereum's price has gone up. So the quality of smart contracts that we're seeing being written by even development shops, the developers building them are actually not full-stack engineers, they're web developers who have learned the language Solidity and so thus we believe that the quality of the code has been significantly low. We're finding lots of critical vulnerabilities. In fact, 100% of the time that Hosho has audited code for a smart contract, we have found at least a couple of vulnerabilities. Even as a second or the third auditor after other companies conduct an audit, we always find a vulnerability. >> And is it correct that Solidity is much more easy to work with than say, Bitcoin scripting language, so you can do a lot more with it, so you're getting a lot more, I don't want to say rogue code, but maybe that's what it is. Is that right? Is that the nature of the theory? >> Compared to Bitcoin script, yes. But compared to JavaScript, no. Because Fortune 500 companies have rooms full of Java engineers, Java developers. And now the newer blockchains are being written, are being written on in block JavaScript, right? So you have IBM's Hyperledger program, you have EOS, you have ICX, Cardano, Stellar, Waves, Neo, there's so many new projects that are coming, that all of them are flexing about the same thing. Including Rootstock, RSK. RSK is a project where they're allowing smart contracts to be tied to the Bitcoin blockchain for the first time ever. Right, so Fortune 500 companies may take advantage of the fact that they have Java developers to take advantage of already, that already work for them, who could easily write to a new blockchain, and possibly these new blockchains are more enterprise grade and able to take more institutional capital. But only time will tell. And us as the auditor, we want to see more code from these newer blockchains, and we want to see more developers actually put in commits. Because it's what matters the most, is where are the developers putting in commits and right now maximum developers are on the Ethereum blockchain. >> Is that, the numbers I mean. Just take a step there. So the theory of blockchain. Percentage of developers vis-a-vis other platforms percentages-- >> By far the most is on developed on Ethereum. >> And in terms of code, obviously the efficiencies that are not yet realized, 'cause there's not enough cycles of coding going on, it's evolution, right? >> Yes. >> Seems to be the problem, wouldn't you say? So a combination of full-stack developer requirements, >> Yes. >> To people who aren't proficient in all levels of the stack. >> Yes. >> Just are inefficient in the coding. It's not a ding on the developers, it's just they're writing code and they miss something, right? Or maybe they're not sufficient in the language-- >> It's a new language. The functions are being updated on a weekly basis, so sometimes you copied and pasted a part of another contract, that came from a very sophisticated project, so they'll say to us, well we copied and pasted this portion from EOS, so it should be great. But what that's leading to is either A, they're using a function that's now outdated, or B, by copying and pasting someone else's code from their smart contract, this smart contract is no longer doing what you intended it to do. >> So now Hartej, how much of your capability is human versus machine? >> Yeah I was going to ask that. >> ML, AI type stuff? >> So we're increasingly becoming automated, but because of the over, there's so much demand in the space. And we've had so much demand to consistently conduct audits, it's tough to pull my engineers away from conducting an audit to work on the tooling to automate the audit, right? And so we are building a lot of proprietary tooling to speed up the process, to automate conducting a GAS analysis, where we make sure you're not clogging up the blockchain by using too much GAS. Static analysis, we're trying to automate that as fast as possible. But what's a bit more difficult to automate, at least right now, is when we have a qualified full-stack engineer read the white paper or the source of truth and make sure the smart contract actually does it, that is, it's a bit longer tail where you're leveraging machine learning and AI to make that fully automated. (talking over each other) >> But maybe is that, I'm sorry John. Is that the long term model or do you think you can actually, I mean there's people that say augmented intelligence is going to be a combination of humans and machines, what do you think? >> I think it's going to be a combination for a long time. Every single day that we audit code, our process gets faster and faster and faster because once we find a vulnerability, finding that same vulnerability next time will be faster and easier and faster and easier. And so as time goes on, we see it as, since the bundle of our work today is ICOs, token generation events, there are ERC 20 tokens on the Ethereum blockchain. And we don't know how long this party will last. Like maybe in a couple years or a couple months, we have a big twist in the ICO space that the numbers will drastically go down. The long tail of Hosho's business for us, is to keep track of people writing smart contracts, period. But we think they are going to become more functional smart contracts where the entire business is on a smart contract and they've cut out sophisticated middle men. Right and it may be less ICOs, and in those cases I mean, if you're a publicly traded company, and you're going from R&D phase where you wrote a smart contract and now actually going to deploy it, I think the publicly traded company's going to do three to five audits. They're going to do multiple audits and take security as a very major concern. And in the space today, security is not being discussed nearly as much as it should. We have the best hedge funds cutting checks into companies, before the smart contract is even written, let alone audited. And so we're trying to partner with all the biggest hedge funds and tell the hedge funds to mandate that if you cut a check into a company that is going to do a token generation event, that they need to guarantee that they're going to at least value security, both in-house for the company and for the smart contract that's going to be written. >> How much do you charge for this? I mean just ballpark. Is it a range of purchase price, sales price? What's the average engagement go for, is it on a scope of work? Statement of work? Or is it license? I mean how does it work? >> So first it depends is it a penetration test of the website or the exchange? Penetration testing of exchanges are far more complex than just a website. Or if it's a smart contract audit, is it an ICO or is it a functional smart contract? In either case for the smart contract audit, we have to build a long set of custom tooling to attack each and every smart contract. So it's definitely very case-by-case. But a ballpark that we could maybe give is somewhere around the lines of 10 to 15 thousand dollars per 100 lines of functional code. And we ask for about three weeks of lead time for both a smart contract audit and a penetration test. And surprisingly in this space, some of the highest caliber companies and high caliber projects with the best teams, are coming to us far too late to get a security audit and a penetration test. So after months of fundraising and a private pre-sale and another pre-sale, and going and throwing parties and events and conferences to increase the excitement for participating in their token sale, what we think is the most important part, the security audit for a smart contract is left to the last week before your ICO. And a ridiculous number of companies are coming to us within seven days of the token sale, >> John: Scrambling. >> Scrambling, and we're saying but we've seen you at seven conferences, I think that we need to delay your ICO by two or three weeks. We can assure you that all of your investors will say thank you for valuing security, because this is irreversible. Once this goes live and the smart contract is deployed. >> Horse is out of the barn. >> It's irreversible. >> Right right. >> And once we seal the code, no one should touch it. >> It's always the case with security, it's bolted on at the last minute. >> It's like back road recovery too, oh we'll just back it up. It's an architectural decision we should have made that months ago. So question for you, the smart contract, because again I'm just getting my wires crossed, 'cause there's levels of smart contracts. So if we, hypothetical ICO or we're doing smart contracts for our audience that's going to come out soon. But see that's more transactional. There's security token sales, >> Yes. >> That are essentially, can be ERC 20 tokens, and that's not huge numbers. It could be big, but not massive. Not a lot transaction costs. That's a contract, right? That's a smart contract? >> People are writing smart contracts to conduct a token generational event, most commonly for an ERC 20 token, that's correct. >> Okay so that's the big, I call that the big enchilada. That's the big-- >> Right now that is the most important, the most common. >> Okay so as you go in the future, I can envision a day where in our community, people going to be doing smart contracts peer-to-peer. >> Sure. >> How does that work? Is that a boiler plate? Is is audited, then it's going to be audited every time? Do the smart contracts get smaller? I mean what's your vision on that? Because we are envisioning a day where people in our audience will say hey Hartej, let's do a white paper together, let's write it together, have a handshake, do a smart contract click, click. Lock it in. And charge a dollar a download, get a million downloads, we split it. >> I envision a day where you can have a more drag and drop smart contract and not need a technical developer to be a full-stack engineer to have to write your smart contract. Yes I totally envision that day. >> John: But that's not today. >> We are very far from that today. >> Dave, kill that project. >> We're so far, we're very far from that. We're light years far from that. >> Okay well look. If we can't eliminate the full-stack engineers, I'm okay with that. Can we eliminate the lawyers? At least minimize them. >> We can minimize them possibly, but we have five stacks of lawyers for our company, I don't see them going anywhere. We need lawyers all the time. >> I see that in the press sometimes, yeah it's going to get disrupted. I don't see it happening. Okay we were having a great conversation off-camera about what makes a good ICO. You see, you have a huge observation space. And you were very opinionated. A lot of companies are out there just floating a token because they're trying to raise money. And they could do the same thing with Ethereum or Bitcoin. >> That's correct. >> Your thoughts? >> My thoughts are that it's very important for companies who are sophisticated, I think, to start by giving away a little bit of equity in the business. And that if you want to be in the blockchain space, and you really firmly believe you have a model to have a token within a decentralized application, I would still start by finding quality investors in the space, in the world. They might be still in Silicon Valley. Silicon Valley didn't just disappear overnight now that the blockchain is out. I am all for the fact that Silicon Valley no longer has as much of a grip on tech because of their blockchain world. And they're not seeing as much deal flow, and there's not as much reliance on venture capitalists, that's exciting to me. But let's not forget the value, that top-tier VCs like Andreessen Horowitz and Vinod Khosla. and Fintech VCs like Commerce Ventures and Nyca Partners in New York, Propel VC, these are good Fintech VC arms that continue to time and time again add immense value to companies. >> And they have networks. They add value. >> They have strong-valued networks, but they're just not going to disappear. And those VCs, if they've invested into a company, took a board seat, fostered their growth, taught them what it means to actually be a real business that's growing at 7-15% week over week, maybe two years down the line, after they've given away a board seat to someone like Nyca Partners, I would be interested in understanding what your token economics look like. Now that you have a revenue generating business, how you've placed a token model into this already running business that makes 25 to 50 grand a month and you have a team of 10, self-sustaining themselves off of revenue. Much more intriguing of a conversation. What's happening today in the space is, hey my buddy Jim and Steve and I came up with an idea for this business. There's going to be a token, and we're starting a private pre-sale tomorrow. I'm going to give you 300% bonus and will you be my advisor? And they're going to start raising capital because of an idea. You know what we used to say in the Silicon Valley startup world, you can raise on just a PowerPoint. I think in the blockchain world, you could raise on just an idea? And then maybe a white paper? And the white paper is one page? And so you've raised a bunch of capital, you have a white paper. >> Now you got to build it. >> Now you got to build, you got to write a smart contract, you got to build it, you got to do it, and then everyone loses excitement and it goes back to our previous conversation the development talent. So, another thing not being discussed in the space is company employee retention, right? So if you have a growing number of ICOs, that have very large budgets because investors have found a way to sink millions of dollars into a company early, you've got $5 million in the hands of a company to start, well this company can afford to pay someone a very ridiculous salary to come join them to write the smart contract now. So they could offer an engineer 500 Eth a month to come join them for three months. So you have good engineers just bouncing from one ICO to the next and as soon as the ICO goes live, they quit. This is a problem to companies who are-- >> It's migration, out migration. >> How do you retain, even capital? >> Companies like Hosho, ShapeShift, companies that are selling picks and shovels of the industry, that want to be household names in the space, we have to really think about how we're going to retain our employees in the space. >> So the recruitment and bringing on the new generation, we were also talking off camera about Bill Tye and the younger generation and kind of riffing on the notion that, because there is a new set of mission-driven developers and builders, on the business side as well. Your thoughts and reaction to what you see and what you see that's good and what you see that we need more of? >> So the most powerful thing in the blockchain space that I think is so exciting is that you have a lot of people between the age of 25 and 35 that don't come from money, that didn't go to Stanford, didn't go to Y Combinator, they're probably not white, from-- >> John: Ivy League schools. >> Ivy League schools. I'm not trying to make it about race, but if you're a white male and went to Stanford and went to Y Combinator, chances of you raising VC money on sand hill are a lot higher, right? And you have a guy looking like me who didn't go to Stanford, doesn't come from money, running up and down sand hill, I have personally faced that battle and it wasn't easy. And we were based in Vegas and so being based in Vegas, I'd also have to deal with so why do you live in Vegas? When are you going to move to Silicon Valley? And if we invest in you, you're going to open an office in sand hill right? And now in the blockchain world, what's exciting is you have so many heavy-hitters running as founders, some of the most successful companies in the space, who don't come from money and a big prestigious background, but they're honest, they're hard-working, they're putting in 12 to 15 hours of work every single day, seven days a week. And to space, six weeks is like six years. And we all have a level of trust that goes back to times when we were all running struggling startups. And so our bond is, to me, even more significant than what must have been between Keith Rabois and Peter Thiel in the PayPal Mafia. We have our own mafias being formed of much stronger bonds of younger people who will be able to share much more significant deal flow so if the PayPal Mafia was able to join forces to punch out companies like eBay and Square, wait 'til companies in this space, we have young, heavy-hitters right now who are non-reliant on some of the more traditional older folks. Wait 'til you see what happens in the next couple years. >> Hartej, great conversation. And I want to get one more question in. We've seen Keiretsu Forum, mafias, teams more than ever as community becomes an integral part of vetting and by the way trust, you have unwritten rules. I mean baseball, Dave and I used to do sports analogies. >> Self-governance. >> Reggie Jackson talked about unwritten rules and it works. If you beam the batter, the other guy, your best star, your side's going to get beamed. That's an unwritten rule. These are what keeps things going, balanced through the course of a season. What are the unwritten rules in the Ethos right now? >> Honesty, transparency, and that's the key. We need self-governance. This is a very unregulated market. There's rules being broken by people who are ignorant to the rules. The most common rule I've seen being broken is by people who are not broker dealers, running around fundraising capital, they don't even know what an institutional advisor license is. They don't know what a Series 7 and a Series 63 is. I asked a guy just last night, he said I'm pooling capital, I'm syndicating, let me know if you want in on the deal. And I said when did you take your Series 7? He goes what's that? Get away from me. You're an American, you need to look up what US securities laws are and make sure that you're playing by the rules and if someone who doesn't know the rules has entered our inner circle of investors, of advisors, of people sharing deal flow, we have a good network of people that are closing the loop for companies, whether it's lawyers, investors, exchanges, security auditors, people who write smart contracts, dev shops, people who write white papers, PR marketing, people who do the road show, there's a full circle-- >> So people are actually doing work to put into the community, to know your neighbor if you will, know the deals that are going down, to identify potential trip wires that are being established by either bad actors or-- >> KYC, AML, this is a new space that's also attracting people that have a criminal background. Right? And that's just a harsh reality of the space. That in the United States if you have a felony on your record, maybe getting a job has become really difficult and you figured let's do an ICO, no one's going to check my record. That is a reality of the space. Another reality is the money that was invested into this entire ICO clean. Right, that's a massive issue for the US government right now. It's been less than 15 hours since the SEC has issued actually subpoenas to people on this exact topic, today. >> This is a great topic, we'd like to do more on. >> Dozens of them. >> We'd like to continue to keep in touch with you on The Cube. Obviously you're welcome anytime, loved your insight. Certainly we'd love to have you be an advisor on our mission, you're welcome anytime. >> For sure, let's talk about it. Come out to Las Vegas. Hosho's always happy to host you. >> John And Dave: We're there all the time. >> The Cube lives at the sands. >> It's our second home. >> Come by Hosho's office and let us know. Vegas is our home. We are hosting a conference in Vegas after DEFCON. So DEFCON is the biggest security conference in the world. You have the best black hats and white hats show up as security experts in Vegas and right on the tail end of it, Hosho's going to host a very exclusive invite-only conference. >> What's it called? Just Hosho Conference? >> Just Blockchain. It'll be called the just, it'll be by the Just Blockchain Group and Hosho's the main backer behind it. >> Well we appreciate your integrity and your sharing here on The Cube, and again you're paying it forward in the community, that's great. Ethos we love that. That's our mission here, paying it forward content. Here in the Bahamas. Live coverage here at PolyCon 18. We're talking about securitized token, a decentralized future for awesome things happening. I'm Jeff Furrier, Dave Vellante. We'll be back with more after this short break. (upbeat music)

>> And who we are today as a country, as a universe. >> Announcer: Congratulations, Reggie Jackson. You are Cube alumni. (gentle music) Live from Silicon Valley, it's theCube, covering Google Cloud Next '17. (techno music) >> Hi, and welcome back to theCube's coverage of Google Next 2017. We're at the heart of Silicon Valley in our great studio in Palo Alto. We've got a team of reporters and analysts up in San Francisco with the 10,000 people attending, really, Google's enterprise show. It's got Cloud, it's got G Suite. It's got a little bit of the devices. I'm happy to welcome back to the program, someone we've had on many times, Nelson Nahum, the CEO of Zadara Storage. Really a company that's in there, understanding this cloud transition from, kind of, how the enterprise gets in multicloud and all those pieces. Nelson, welcome back to the program. >> Thank you, sir, how are you? >> All right, it's good. So, you know, you and I last time we talked was at another cloud show, a little bigger cloud show, one that's been going on for a number of years, but let's start talking about Google. What's, you know, we think a lot of progress over the last couple of years. I mean, Diane Green definitely has put her stamp on this company. A ton of people that have been brought in, many of them, those of us in the industry, we know these people. We've seen them grow these businesses, understand how to talk to the enterprise, so, what's your take on the show so far and how Google's doing as a company? And we'll get into how they are as a partner soon, too. >> So this is our first Google Cloud show for us, for Zadara. We've been in, I think, since 2011, in Amazon Prime event, and we like it. This is going very well. We have a lot of conversations. We saw that there are many, many customers looking to have multicloud strategy. That actually works very well for us, because we can provide storage that can be accessible at the same time concurrently from Amazon, and from Google and Azure and others. So, yeah, it's a good trend. I think most of the people we found, they're either already on Amazon and looking to expand to Google or some on-premise to Google, and so on. >> Can you help unpack that multicloud a bit for us? So you know, maybe some of our audience might not know, you guys sit in some of those mega-datacenters, like the Equinixes of the world, and direct connect to the public cloud. >> Exactly, exactly. >> So, I've got, kind of, my storage being Zadara, and there actually is, you know, physical storage there, and then that, you know, plugs into the Cloud resources, of course. We know AWS's Direct Connect. Amazon has, you know, their equivalent, and Google has the same, so, can you have, you know, it's a single solution that, does it just get fibers to all three of them? Is there software that takes care of it? >> Yeah, actually- >> How does that work? >> Yeah, great question. So we sit in Equinix data centers with our cloud, and from there, in many cases, we use Equinix Cloud Exchange, that is, basically, like a networking inside Equinix, and can be connected to many different potential targets, so, currently we are cross-connected to Amazon, Google and Azure. So our customer, at first, can create a storage and mount with NFS or ZFS, or Block, and can mount the storage, especially if it is file storage, then you can share data. You can mount the same storage to virtual machines in Google, and to virtual machines in Amazon, and at the same time, they see the same files. >> Yeah, and what's the use case, why are they doing that? Is that for redundancy or certain features? You know, there was a certain cloud outage a week ago, were your customers riding through that, based on what they're doing? >> Yeah, so, the measured cloud outage that Amazon had last week, S3 ... it caused my people to rethink (laughs), I guess. Fortunately, for us, all our customers that sit in our storage, wasn't impacted, because they sit in our storage and they don't use, we don't use Amazon infrastructure, so they could continue- >> Stu: No S3 for your customers, right? >> Right, so we are doing the Block and the file storage for our customers. I think that, what is important here is not the outage, but what is important is people start recognizing that you need to have the data in two locations in order to be safe. >> Yeah, it's ... People that have done architecture and understand infrastructure is, you know, I need to be thoughtful as to how I architect things, so either I need to make sure I have the availability zones and the services and can take care of that, or perhaps even multicloud to be able to take care of that. >> So, multicloud and you're completely independent to each other. So, we have an array of many customers using us and Amazon and, again, because our storage can be cross-connected to multiple clouds, it's very easy to access from virtual machines in any cloud at the same time. So, people that are using that, it's either for a, kind of, these are tolerant solutions or more robust solutions. As well, in some cases for migration. Each cloud provider has the places or the attributes that it has. You can run applications better in that particular cloud, so, for example, in Microsoft Azure, anything that is related to Windows, they are the best, and, Oracle Cloud, if you run Oracle, probably is the best way to start. So, I will say that the multicloud is not only the disaster recovery type, but people want to use the best cloud for the particular application they have, and they have multiple applications, so use multiple clouds. >> I'm curious, do you get visibility, as to, you know, why are customers choosing Google? Are there, do you have customers that are using Google that aren't using the other public clouds, is it primarily your customers are using it as a secondary source, any data you've got or anecdotes would be helpful. >> So, we have two types of customers, the ones that are multicloud and the others that are going from on-premise to the cloud. As you know, we have an on-premise business, and we make it very easy, from on-premise, to move to the cloud. We just launched it, here in Google Cloud, a service called cloud iteratation, that basically, we allow a customer to move their entire infrastructure from on-premise to the cloud with zero, or minimal, downtime. So, we will ship all the storage to the on-premise facilities, the customer will pay per use, we will start doing replication to the cloud, or in some cases, if it is multiple petabytes, we will ship the equipment to the cloud, and, in the meantime, we can do replication and, at the end, we can switch and fail over, and the customer can continue from the cloud. >> Cloud hydration, >> Cloud hydration, yes. >> is that service. Does that support all the services, all the clouds? >> Yeah, so today, we are doing this for many customers, and the good use case is when a customer wants to move a lot of data to the cloud, but they don't want to have downtime. Because, Amazon Snowball and all these boxes, you need to copy the data, and then ship, and then restore. >> Stu: So, it's not a truck that takes three months >> Yeah, exactly. >> sitting on your location. >> This is what we do, we ship double amount of equipment to the customer, they start doing the copy, and then, half of it, we ship to the cloud. We connect to the cloud, and resume the connection, and, all the time, the customer continues to run, okay? And, at the last moment, they do the fail over. So, it's minimum downtime, even if you need to ship one petabyte of storage. >> Yeah. I'm curious, we've been going through such tremendous changes in the storage industry, do you guys sell, you know, is it the storage person, who do you sell to, and where is their mind at when they think about storage today? >> Yeah. Yeah, we sell storage, so the storage person is the one that's buying- >> Yeah, you know, a lot of people, if they're buying Google, or even if they're putting in AWS services, the storage person is, a lot of time, kind of shoved out of the mix, you're a little bit- >> Shoved out of the mix until they have a problem that they need to bring back the storage- >> Wait, are you saying that could be a problem? (laughs) >> So, what happen is that, and this is, I think, how the cloud started, is cloud storage is, "Ah, storage is just storage," until you start running real applications and you need the performance, and you need the reliability, and so on. So, this is why you need the storage guy to architect the solution, and this is where we, we come in and actually act as a really good outsourcing team of storage experts to the customer, and we help them with this transition from on-premise to the cloud and, in many cases, back and forth, if the customer wants to have a leg in the cloud, a leg on-premise, and move data easily back and forth. >> So, Google made a good push at the show, talking about building the ecosystem, how they want to work with partners. They had companies, like you know, PwC's all over the place, SAP, very strong partnership. How have you found it to work with Google? Any things you'd say to them as to how they can accelerate and move things faster to, you know, build up the ecosystem? >> Yeah, so far, our experience with Google was extremely good. The people are very dynamic, they have the Google dynamism that is very good, and, for us, it was really good to have a close relationship with the Google product managers and sales people, and so on, so we enjoy, have a really good relationship with Google Cloud. >> All right, well, Nelson, I want to give you the final word. You know, things you've learned this week, any cool customer conversation you've had, give us the final takeaway. >> Yeah, so, the ... I guess my summary is that, here in Google Cloud, we have a big advantage because we have ... NAS, NFS, ZFS, we've architected their integration and all the snapshot capabilities that enterprises need. And, you know that Google doesn't have a EFS type of functionality, and our functionality's actually higher than EFS. So, this is what we are talking to customers, here in Google Cloud, anybody that needs NFS and ZFS, and NAS and multicloud, and on-premise to the cloud, they talk to us and we are ready to go. >> All right, Nelson Nahum, really appreciate you coming to the studio here to share what's happening at the Google event. Be sure to check out wikibon.com for our cloud research and, of course, siliconangle.tv to see all the shows we're going to be at, as well as the replays from this and lots of other cloud infrastructure, IoT and big data shows. We'll be back with lots more coverage here, day two of two, covering Google Cloud. From the SiliconANGLE media studio in Palo Alto, you're watching The Cube. (techno music)

>> Is about what our youth is, and who we are today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (gentle music) Live from Silicon Valley it's The Cube covering Google Cloud Next '17. (upbeat music) >> Hi, welcome back to The Cube's coverage of Google Next 2017 happening in San Francisco. We're shooting live from our 4,500 square foot here in Palo Alto in the heart of SiliconANGLE. Happy to welcome back to the program, I guess we haven't had him for a little while, but one that we know quite well, Ron Bianchini who's the CEO of Avere. Thanks for joining us. >> Thanks for having me. >> All right, so Ron, for our audience, why don't you give us the update? What's happening with Avere the company itself, and what brings you guys, which I think of you, no offense, you guys are infrastructure company I think of on there. How does cloud fit into the whole discussion you guys are having, and your customers? >> That's great, great segue. So, we started out as an infrastructure company and really what Avere learned to do, our whole IP, actually let me start this way. We started in 2008. Think about where the world was in 2008. People were trying to figure out how to get flash into the data center. And what we did is we came up with a storage system, a NAS server, that knew about two types of storage. It knew that there was very high performance nearby precious flash storage, but that big bulk storage, much cheaper, 1/10 the price disk was a high latency away. And we're able to take that solution, and we started out in the data center, we went after very high performance applications, but showed how you could do it at very low cost. >> It's great, nine years later, I mean, storage is infinite and free, right? >> That's right. The good news for us is the world is very much in the same place. The cost delta between flash and disk has stayed at 10 to one. Both have gotten a lot less expensive, but that difference between the two has stayed. It turns out a solution that knows how to use local high performance flash and store big bulk data at high latency away is an ideal solution for the cloud. And really what we're helping customers now is we're helping customers that are in the data center, in the Enterprise data center, we're helping them adopt cloud. And it works two ways. We support the gateway model where you can keep your compute on-prem and put your big bulk storage in the cloud, and we enable that model without seeing any delta, any change in performance or availability. But we also do the opposite of that, we enable customers to put their compute out in the cloud, and now the big bulk capacity could either stay in the cloud or could be on-prem. So really, I think about us as an enterprise data center play, just like you said, but now we're helping customers take baby steps and slowly adopt the cloud. >> All right, so terms I heard from Google this week, they talked about building the planetary scale computer. They talked about Google Spanner which gives us global, the time synchronization across the globe, the things that those of us with storage backgrounds, it's like, boy these are big, heavy challenges. >> Ron: Big words, right. >> Talking about some of the things, just physics that we try to figure all that. So, how do you guys fit into that? I mean, doesn't GFS, Google File System, solve all these issues for us? >> Right, great. So, one thing to understand is that enterprise storage uses a very different consistency model than Google Storage. So, there's a theorem called the CAP principle, C-A-P. It's consistency, availability, and partition tolerance. And basically what the CAP principle says is, of those three parameters, pick two, because it's impossible to build a storage system that does all three. And really, GFS is all about availability and partition tolerance, because they have big, scalable solutions. What it doesn't give you is exact consistency, and that's what NAS solutions do. NAS solutions are really the high consistency, still partition tolerant because you have big distributed scale systems, but you don't get that high availability piece. And it turns out, in the enterprise there are times when you need high availability storage, that's what you get from Google's file system, but then there are also times you need high consistency storage, that's what you get from an Avere solution. Imagine a bank account where you deposited a million dollars, and then you withdraw a million dollars from two locations, maybe 10 seconds apart. If you don't have a high consistency model, it might be possible to withdraw money from both places. That's what NAS guarantees. >> Ron, I want to get your viewpoint, I'm sure you talk to a lot of your customers. What's their mindset of cloud today, and what are the kinds of conversations that you're having with people stop by your booth at Moscone West. >> I think you said it right, Google is proposing big, scalable, huge features that the customers are trying to get access to, but moving everything from the data center into the cloud all at once to get them is a big, scary step. And so really what we enable people to do is to take baby steps. If you want to move a little bit of your capacity to the clouds, or petabytes of storage in the clouds, like one of our Genomics customers does, you could do that. Your compute and a lot of where they start in storage stays on-prem, but now they're leveraging the cloud for big, scalable capacity. Then we have other customers that want access to the compute and the performance of the scaling you can get. We allow them to get access to that as well. >> Any commentary on, I think about just the trend itself. There's no doubt how big cloud is and how fast it's growing. When we look on the data side Diane Green threw out a number that only 5% of the world's data sits in the public cloud, and that's going to shift. We know that there's a lot of compute-heavy workloads that really started out in those environments, or are leveraging that. So, there's a lot of kind of reasons why we haven't had the data there. We are starting to see some rapid acceleration. What do you see happening in the environment? >> I think that's right. I think the 5% number just gives us a window into how big this cloud movement is, how much is still left to be accomplished. We talk about cloud, cloud, cloud, as if it's already happened, but we're only at the cusp of what's possible. And that's really what we see as this next big phase of the cloud is ingest, is cloud adoption, it's migrating applications and storage into the cloud. >> Yeah, you said what, the future's already here, just unevenly distributed. >> That's right. It hasn't quite made it yet. >> You guys are headquartered in Pittsburgh. >> We are. >> I'm out of Boston. I always joke every time I come out here, it's like okay, I'm going to go spend a week in the Valley and in San Francisco, then I'm going to go back to the real world where I'm not seeing autonomous vehicles in front of me. You guys have some cool autonomous cars driving around Pittsburgh these days? >> Ron: We absolutely do. >> And not everybody is fully cloud-native, serverless and everything else like that. What are you seeing in the marketplace, what's interesting you these days? >> There's no doubt that in the future world all data, all applications, everything will be in the cloud unless there's a very important reason to have it nearby. We think with our Genomics customers, it has to start where the patients are. It has to start on-prem, and then it gets migrated to the cloud. But there's no doubt in the future all compute, especially the big, scalable things that we hear Google talk about will be there. The next five, seven years is all about how we get there from here. >> All right, and Ron, as people look at your company what should we be expecting kind of throughout the rest of this year as we look at you growing your future? >> It's all about making it easier to adopt the cloud. You're going to see higher levels of integration with our cloud partners, Google in particular. We do a lot of work with Google. You're going to see big steps as we move forward and make that integration better. >> You're working with the other cloud players, yes this is a Google show, but we want to talk about the environment. Lots of companies I talk to are like, "Look, yes Google's a player," but I talk to plenty of companies that, "Look, 3/4 of my customers are all on Amazon," and that's where a lot of the market is today. So, what's the breadth of the offering that you have to that? >> It is. We support all the three big cloud players, we support Amazon, Microsoft, and Google. What I will say is the Google team is very much focused on the enterprise, just like Avere is. And that actually helps us a lot. It's really helping us knock down customers and really helping get customers moved into the cloud. >> All right, Ron, I'll give you the final word. Takeaways for the week, anything else you want to share before we wrap. >> You know, it's exactly what you said. The cloud is coming, now it's just a matter of how we get there and watching the big momentum shift. >> I think Eric Schmidt said last year we were like kind of meet you were we are. This year it's, come on. It's, now's the time, we need to go. I think we understand how big cloud is going to be, it's one of the generational shifts that we're all going to be watching, and we're in the thick of it. So, thank you, Ron, for joining us, and we'll be back with lots more coverage here. We've got call-ins and people at the show itself doing dial-ins, pulling people in. Really broad community at this event, so stay tuned for lots more coverage, and you're watching The Cube. (upbeat music) (upbeat music)

(light music) You are Cube alumni. You are Cube alumni. (light music) >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) You are Cube alumni. (light music) >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. 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(light music) You are Cube alumni. You are Cube alumni. (light music) >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) You are Cube alumni. (light music) >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) You are Cube alumni. You are Cube alumni. (light music) >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) You are Cube alumni. (light music) >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) >> Today as a country, as a universe. >> Narrator: Congratulations, Reggie Jackson. You are Cube alumni. (light music) (light music) >> Narrator: Live from the Silicon Valley, It's the Cube. Covering Google Cloud Next 17. >> Hello and welcome to the Cube special coverage of Google Next 2017. This is the Cube's two days of live coverage here in Palo Alto studio. We have reporters and analysts on the ground. We have all the Wikibon analysts in San Francisco. Have been up there since Monday for the Google analyst summit. As well as reporters at the keynote. We're going to be going live to folks on the ground for a reaction and commentary from the keynotes. As well as all the big break outs and news coverage. Again, two days of live coverage and we want to put a shout out to Intel for their sponsorship and allowing us to do the two days of in depth coverage. Really breaking down the Cloud. And really talking about this new mega trend around Cloud service providers where it's a multi-cloud game, which is pretty clear that's happening. And then the SaaSification of the world with AI machine learning. Really changing the game on infrastructure, software development. This is the digital transformation. This is the May trend. And here to help kick off our two days of coverage is venture capitalist, Scott Raney, who's a partner at Redpoint Ventures, who has a lot of history in network software SaaS. Scott, thanks for joining us on the kickoff here. >> My pleasure. >> For our coverage. Yeah, the big story I on Google News is obviously Diane Green, great executive. She gets a lot of criticism for her presentation. Some people were saying it's a little bit sleepy, but she's got a folksy kind of, I call it the Berkeley kind of vibe, but she's super smart. She's a very cool person. But she came in from VMWare, which has a lot of chops in the enterprise so it's no surprise that Google Cloud is now marching heavily towards the enterprise. They have all the window dressing. You're seeing the all the check boxes next to the sales and marketing, some of the things that they're doing. But the end of the day, it's an AI machine learning at the center of all this. Where data and a new cloud developer or new developer market has been emerging very fast. They call it cloud native. You're investing in this space. Give me your thoughts on this because you guys have to look at the 20 mile stare down the road. Look at kind of that five year horizon or plus for investments whether it's early stage or what not, but you guys have done a lot with startups that have been successful. Twilio went public that you're on the board of. You have a lot of investments in there that are doing very, very well. The developers, the opportunities, what's your take as an investor writing big checks. >> Yeah, well I think Google is a really interesting way to start this conversation. Not just the Google Cloud platform, but Google as an entity. I think Google is frankly been defining about 10 years ahead of where enterprises are in terms of how they're thinking about building and deploying applications. And so, if you look at Google, the work they've done to actually support their internal efforts, these guys then create white papers, the white papers are then disseminated, and then a whole set of industries get kicked off around those. So obviously one of the great examples of that is what happen around Hadoop and that wave. I think what we're in the process of seeing right now is a whole series of innovations that are being developed around more kind of cloud native technologies. I think Kubernetes is a great example, which is really the outgrowth of work that Google had done around Borg. And so we spend a lot of time thinking about the work that Google's, the things that Google is working on now. Recognizing that's the future of enterprise computing. Obviously, it takes a while to get there. But, there have been massive industries you can create from that. >> And it's transformative too. Again, I mentioned Twillio. They went public. Great service. We saw Snap go public. They're now running on Google Cloud and some on AWS. There's game changing opportunities out there that are going to come out of these unique perspectives that developers and entrepreneurs might have. And say hey I'm going to innovate on camera technology. That becomes Snap, which becomes kind of a unique, weird app and then to a main stream. This is not a one off. I mean there's a lot happening around creative, young entrepreneurs and old, some guys our age. But either way, it's not just apps. It's transformation at the network level. All the way up to the top of the stack. >> Yeah. >> What are the trends around that? I mean because machine learning is obviously hot. What are you hearing for pitches? What's coming through your door? What are you looking at? You guys see a lot of deals. What's the trends that are coming out of there? >> Well, every pitch we see has machine learning in it. Every company has become an AI company at some level. So that's clearly a big trend. I think for us the way that we look at it in terms of investments is we're recognizing that the algorithms are really becoming commoditized in some level. And Google, with TensorFlow, is actually helping make that happen. As we just talked about, they're democratizing machine learning at some level. The key there is data. And so, when we look at these companies, we're looking for companies that have a unique, proprietary access to data that they can apply those algorithms to, deliver insight. I think one of the more interesting areas or applications around that we're seeing is in the SaaS space. Kind of upper level at the cloud space, how it's really not enough now to build a SaaS application that just automates a business process. What you have to do is deliver insights. You have to help make the people that are using these applications better at there job at some level and the way to do that is through things like machine learning. >> What's interesting, Peter Burris, who's one of our heads of research for Wikibon pointed out, last week when we we're covering Mobile World Congress, he goes it's interesting, you know years ago, when I was breaking into the business in the late 80s, early 90s, it was known processes, unknown technology, and those were automated. Now you have known technology and unknown processes. So getting those insights to get that discovery could really disrupt existing incumbents, big players. So someone can innovate, say hey, I'm going to innovate on a new process that's emerging. This seems to be the big trend that's going on and again the software model is changing. So how do you guys see entrepreneurs looking at the AI and are they that focused on that? Or do they see that? I mean what are the key areas? Do they actually say hey, I'm going to disrupt this marketplace with this one feature? We always hear the MVP or pick something and do it great. What are some of the things that you've seen? >> We're really seeing two things in the AI and ML space. We're seeing one is the general kind of platform play. People that are trying to actually offer machine learning to developers in some way, shape or form. And the reality is I think those are very difficult businesses to build. I think Google Cloud is actually extremely well positioned to be able to actually kind of drive that forward for developers based on all the work they've done internally and they way that cloud is built and architected. The second are applications are AI and ML. And that's where we're spending the vast majority of our time because we think that's where the most value we be created there for folks that don't own a cloud like Google. >> The thing that's interesting about entrepreneurs is it's been a nice thing, the cloud you can get into the game with open source and build a business. You don't have to get all the, provision the data center. That's kind of been talked about, it's not new news. Yeah, you can get up and running, but it's interesting. It was easy to get into the enterprise and then all of sudden now, as it gets more complicated, we're almost going back to the old days of it was really hard to crack the code in the enterprise. It seems to be a lot of new table stakes are emerging. It used to be could native, oh we're going to go to the enterprise. And you saw box.net, now being Box and Dropbox, they're getting in the enterprise very easily. But now, as we go I'd say post-2012, all these new requirements start to rear their ugly head around it's hard to get into the enterprise. So this is something that Google is certainly challenged with right now is that they have a lot of tech, they're serious about the enterprise, that's clear. But to be an enterprise contender and winner and winning deals, how hard is it to win the enterprise? And is that some that you see where the enterprise landscape has changed where it's harder or is it easier? What's your thoughts in the complexities in the enterprise? >> Yeah, I maybe have a different point of view than you do. Which is actually, I actually think it's actually easier now to penetrate the enterprise at some level than it ever has been before. But it has to start with product. And open source is an incredible phenomenon that we're seeing that's kind of overtaking the way that enterprises think about building infrastructure today. I don't think you can build an infrastructure company unless you're offering it as open source software. And so, what we look for in terms of investments and I think what entrepreneurs need to do is think about how do I build products that enterprises will love and release that as open source and open to see some level of adoption. When you see that then that's the best path to be able to go in and sell to them and building revenue around it. Kind of transitioning back to Google and what they're doing with the cloud effort, I think that their approach is actually, it's intriguing. You know, Diane is a world class executive in this way and, you know, I think brought in the last big transition that we've seen through the work she did with virtualization. And I wouldn't bet against her here. I think the things that those guys are doing is offering a pretty compelling set of higher level services now that are getting traction with things like BigQuery. I think TensorFlow is obviously very interesting. And then what they now announced recently with Spanner as a service. These are all technologies that Google understands and mastered and are very compelling technologies that I think the average developer will want. And they are highly differentiated from the services that are available from the Amazon's and Microsofts' of the world. >> Yeah, Spanner certainly got that horizontally-scalable mojo going on. They still got some work to do outside of MySQL and there on the relational database side, which we're watching. But they know that. I mean Google is clearly not saying they're, you know, fully-baked. They're actually candid in the analyst meeting. They were very candid on the security side and very candid on some of these things that they know they've got to do. But they are peddling as fast as they can. So I got to ask you the venture capital question. Developers are out there. Because there was a line, literally a blockbuster as they called it. People around the block to get in. Google IO had similar attraction. Those events are awesome. Google runs great events. They have, I would call them the technology store. People love to go in there and see what they have. But as an entrepreneur coming in, I'm going to build on a stack, whether it's Amazon or Google or somewhere else, you got to worry about the viability when you have the big gorillas out there. You got Amazon, now Google. What's the formula for and what do you worry about as an investor because the things you must think about is okay, what's the approach, where's the viability, is there a marketplace, is there monetization, can they get traction, can they go beyond the first three million in sales, because SaaS you can get there pretty quickly, as it's been discussed. What are the fears that you worry about and what advice would you give entrepreneurs as they start to start really innovating and saying hey I'm going to take the democratization of AI and I'm going to do some damage. I want to enter a market. These are considerations that you got to think about and you, as an investor, where's the risk? And what's the opportunity? >> Oh man, well there are lots of risks starting a company. We could talk for an hour about the challenges associated with being an entrepreneur. It's probably the hardest job you can imagine having. You know I think that the first and foremost is you got to build products that people love. And you got to solve a real problem. And so, I think for us as investors, we look for that. It's different now in enterprise investing in infrastructure than before where there used to be 10, 20 million dollar efforts required to build the technology and then you take it to the enterprise. And you would hope that it would sell. Now, with a couple million dollars, you have the ability to go out and write some compelling software, release it in the open source and see whether or not it gets traction. And then, really the challenge is figuring out whether you can monetize that or not, right. And in today's model, that's really where we struggle. It's ultimately in how you ultimately package this and sell it. I think that the primary models that we're seeing are either some form of upsell on open source, so either service support, open core, or an enterprise grade application built on top of the open source. The other alternative is to deliver it as a service. And we see lots of folks that are taking that open source and saying we're going to run this as a service. We have a company, a platform of mine, that does that for cribinetties, but there are companies like Data Bricks that are doing that for Spark and the whole data pipeline. And that is potentially a very compelling model too. >> Do you have a formula or an algorithm for investment? I remember talking to Jeremy Lu way back in the day and I just saw him in an interview on Snapchat, was an investor and he actually jumped into the stats with Evan Spiegel and saw the traction cause he was skeptical. A lot of people had passed on it, but you know that story. Is there an algom that you look for besides the team and being an exceptional team of people, you know technical chops and product chops. Is there a way that you look at to identify traction in this marketplace because it could be, there's a lot of turbulence, mircoservices, you got Kubernetes, another Google innovation that's kind of becoming a glue layer if you will across services. Is there a way to say oh that's got traction, I like that? Or here's some benchmarks that I look for for hurdles in ventures. >> Yeah, within this infrastructure space primarily around models that are going to be delivered as open source, there's a couple things that we can look at. We'll track GitHub stars and so we'll get a sense from that how the community views this. Whether this is something that they are particularly interested in and the level of traction they're getting within that community. It's almost like that is almost like a stamp of approval from the technology community that says this is a really cool project, right? And then, beyond that you start to look at download volumes. And to understand just how widespread the adoption of this technology is. Those are imperfect metrics, you know. And so, a lot of times it comes back to >> Market forces or whatever. >> Switching gears and looking at the customers and asking them the kinds of problems they are experiencing and whether or not these technologies have a chance to actually address real long standing challenges that they've had in either building or deploying or running applications. And so, it's different than consumer. Yeah, consumer is a little bit easier to measure. And you have a lot of data. Consumer has it's own challenges and it's very difficult to kind of predict a priority or what's going to be successful. But the good news for us is that with high-quality teams, these guys typically know where to focus and where to spend time and ultimately will be able to create it. >> And customer traction is always a great one to look at. I mean sell the data points. Scott Raney, what's new with Redpoint Ventures? Give a quick plug for what you guys are doing, what you're investing in, size of the fund, how much dry powder you have as they say. Are you still writing checks? What kind of checks? >> We are in business and we're looking for great entrepreneurs. So we have two funds. One is a 400 million dollar early stage fund that focuses primarily on Series A and an occasional Series B. And then we have a 400 million dollar early growth fund that is really more an occasional Series B and Series C. You know our attitude to the entrepreneurs is they should be indifferent to which fund they're in. We treat every investment the same. Really, we just want to be a part of great companies and get a chance to work with great entrepreneurs. >> And you guys also sponsored the party last night with the CNCF After Cloud Native Compute Foundation. >> Yeah. >> How'd that go? What were some of the conversations in the hall way there? Or in the hall way, in the event, it was a social event, but you know great community, the CNCF After Development. A couple new projects emerging. >> They've done some great work. And the projects that are coming in represent a lot of the foundation work that's going to be required to build cloud native applications. The first thing we did at this event last night is try to find what cloud native actually is. (laughs) And I think everybody has a different definition for that. >> What's the most common one? Is there a trend pattern in there? >> Yeah, I think people were saying these are applications that are built, traditionally built, using containers. They're built leveraging microservices. And they are built with the assumption that the underlying infrastructure is going to be ephemeral in some way. So you know built... >> And you have a pony in that game with Azicorp so update on those guys? >> It's a company that is doing extremely well and solving a broad set of problems around helping developers build and run applications on top of the cloud and I think what were setting there and we're seeing kind of across the board is a general desire to start to think about multi-cloud. To start to understand what it takes to actually deploy applications and run applications across multiple clouds. And also to be more agnostic about what they underlying substrate looks like. And those are trends that bode well for Google and Microsoft. >> Yeah, we're excited, we're going to be watching. Scott, thanks for coming on. We're going to be watching that. Kubernetes, that orchestration layer that's going on around microservices that's a hot I'd say battleground around innovation, a lot of good things happening there. Great opportunities when there's a lot of turbulence. Great opportunities to invest. Good luck with your investments. Scott Raney, partner at Redpoint Ventures. Very active in the community. A great VC, check him out. It's the Cube two days of live coverage all day. Going to 4:30, 5:00 pm today. And then tomorrow, Thursday. And then we're off to South by Southwest again. More coverage, we wrap with more coverage after the short break.