(upbeat music) >> Welcome back to Chicago, guys and gals. Lisa Martin here in Chicago with Ansible Fest 2022 with John Furrier. John, we've had great conversations. This is day two of our coverage. We were here yesterday. >> Yeah. >> We're here today. We've gotten to talk with great folks in the Ansible community, the partner ecosystem customers. We've broken some news that they've talked about. Now we're going to talk about industrial automation, IT/OT convergence. What excites you about this conversation? >> Yeah, this is going to be a great segment. This is one of the feature keynote presenters, customer Rockwell. Huge in OT, IT, edge, robotics, plants, equipment. Everything that we probably have, they do. This guest has really great story about what's cutting edge and what's relevant in the edge and IT slash automation area. Super relevant. Looking forward to the segment. >> Yes, please welcome David Rapini, the Global PlantPAx business manager at Rockwell Automation. David, great to have you on theCUBE. >> Thank you. Nice to be here. >> Give the audience a bit of an overview of Rockwell Automation and then let's dig into what you guys are doing there. >> Sure. Rockwell Automation probably is the largest global automation provider of equipment focused exclusively on automation. About 22,000 employees. About 7 billion kind of revenue numbers. We make, basically, controllers for the automation industry, industrialized software, power drives, you know, of the robotics content, smart cart kind of applications. >> Lisa: And what are your key industries that you're covering? >> Wow, so that's a broad market. So we do a lot of different industries. So we cover, obviously, oil and gas, life science, water, wastewater. We do automotive. So just about any industry, actually. Any place that needs industrial automation covering any type of manufacturing process or any type of process application. We're pretty much there. >> John: You know, it's interesting, IOT has been a word, in and of things, light bulb, wearables, industrial IOT where you're in is a really key space. It's physical plants. Sometimes it's sensitive critical infrastructure for governments, businesses. >> David: Exactly. >> I mean there's running stuff. >> David: Definitely. >> This is huge. >> Yeah, and it's a big area for us, like getting that data, you know, everybody talks about analytics and what the world's going to be happening to in that IT, OT space. And Rockwell's really well positioned at that lower level where we actually own the data, create the data for all that analytics that you're talking about. >> What was your main message today on stage? I want to replay that here and then get into it because I think this is really, we're starting to see, real traction in adoption, in automation, cloud scale, edges happening, exploding. What was your key message on stage today? >> Yeah, I think it's that the world's really changing in that space. You know, five years ago you would have had a completely different message around, you know that connectivity and having that content actually delivered to that space and having, like even the connectivity to that OT space makes people uncomfortable in that world because there's obviously moving pieces, you know, damage to equipment, you know God forbid any types of explosions or things like that on bad environmental type conditions. So we're working in that space to really make those connections much more open and now that those connections are starting to happen and we're getting more and more comfort with that, in that layer, there's a lot more we can do in that space which is kind of why we're here. >> And talk about why Ansible and what it's going to be able to unlock for Rockwell to be able to achieve. >> Sure. There's a lot of areas that we want to play with, but our, in Ansible but our first targets are really our, primarily our servers. So there's a lot of edge based servers out there, you know, we call them a pass server, which is a process automation system server. And there's an engineering workstation operator, which are those main core servers. Some of them are redundant, you know, the OT guys to them it's a burden to manage that content. They're good at making, you know, oil and gas they know how to do water wastewater. They know how to build cars. But managing servers, you know, not in their wheelhouse. >> John: Not in their wheelhouse.(laughs) >> Exactly. Right. So having that capability and that connection to get down there gives us some power with Ansible to go ahead and start building them initially. So making that initial builds out of the gate. That makes them really consistent and built together, so every application looks and feels the same and they know what they're going to get when their servers power up. So that's a big one. But, but just maintain them, keeping them patched, you know keeping security vulnerabilities down. You know, I was in a facility not long ago that was still running Windows 2000. Right. So, you know, they have an application there that's just working. It works. They don't want to touch it and it's been running for 20 years, so why touch it? Right. So this was going to kind of hopefully break that challenge. >> Make sure that you keep that password handy. (laughs) >> David: Yeah, exactly right. (laughs) >> We've had (indistinct) people leave. What about the security aspect is OT has been locked down, mindset, hardened, end to end, supply chains, vetted. Everything's kind of tight on the old OT model. Relatively secure when you get to IT, you mentioned vulnerabilities but the innovation's there too. So how does that reconcile for you? What's your reaction to that? >> Yeah, we see a big move there, right? So it used to be they were always head head to head butting heads IT, OT, you know it focuses on, you know, keeping the system secure keeping the data down, locked down, and reliable. OT focuses more on production, right? Making sure they hit their numbers in the production. So oftentimes, you know, having it push out a patch in the middle of production line in the middle of a day and rebooting a server shuts down production and you know, that those kind of conflicts. Yeah, exactly. So those conflicts were, were pretty common. There's still a lot of that there, but it's getting better. Yeah, right. And I see more and more of that working together as a team to, to solve a lot of those challenges. And honestly, I keep going back to the analytics angle and the diagnostics and that world of deep data, you know, big data kind of mining, you know, without the IT space to cover that the cloud data storage, the horsepower. >> If you had to kind of like rank the complexity 'cause we were just talking before you came on about things got to get complex before they can get simpler 'cause the inflection points bring that new capability. What's some of the complexities that you're seeing that are going to be either abstracted away or solved with some of these new technologies like Ansible and others that are coming fast? Cause at the end of the day it's got to still be easier. It's not going to be hard. That can't be harder. >> Yeah. So I'll give you a real world example that's a little embarrassing. So today we deliver our past servers as a solution and we we provide that as a VM image that people start with as the first building block. But once you start to deploy that and actually connect it with the rest of the infrastructure, hook it up to our factory talk directory, hook it up to the DNS service, once you start doing all that work it's about 700 mouse clicks that somebody has to know what they're doing to actually spin it up the rest of the way and get it connected with Ansible. We're cutting that number like in half is the hope. So, and, and we're going to continue to expand that and make it even less work for the users to >> Talk about skill gap issue. The training alone on that is to have the right people. >> That's the second big piece, right? So, so those OT people typically don't have that skill set. So you have to have a fairly high skilled level person to do that work. We're hoping to take that, that work off of them and put that on on answer. >> Yeah, that sounds pretty consistent. Do you think, is that the, kind of the consistency of the problem space is that the OT just has a different goal and they just need something to be invisible and easy, like electricity? >> Yeah, I think so. Especially in this world, right? In that OT space, right in in that IT space. Sorry. Yeah, so, so managing servers and things like that it's just is not what they want to want to deal with and it's not what they went to school for and it's not what they're doing when their job when they get hired. Right. Yeah. >> It sounds to me like Rockwell Automation is a facilitator of the IT and OT folks coming together and actually working better together, maybe understanding each other's requirements, goals, objectives. >> Most definitely. So we have, you know we are offering a lot of cloud content now. We're continuing to expand that content. We're working with a lot of different IT departments and OT departments to try to marriage those two groups together to try to bring that stuff together. We have a partnership with Cisco where we actually, you know, industrialize you know, some of their switch components and sell that as as part of our content and that relationship gives us a big inroad with a lot of the IT departments. >> That's important to have that be able to speak the language of both sides. >> Yeah, definitely. Right. Knowing and understanding the terminology and just being able to know the challenges that IT guys face as well as the OTs is really a big component of what we do. >> You know, one of the questions I wanted to ask and 'cause the keynote was very cool, but you made a comment that your claim to fame was that you wrote the code for the Spider-Man ride at Universal. Tell a story. How does that work? I'm just, I've rode them many times. So take us through that little journey. >> Yeah, so I, every time people ask me what we do for a living and automation, you know, I can talk about, you know, making cars and things like that, but it doesn't ring troops. So I did do a lot of work on Spider-Man Ride which is at Universal Studios, you know it was a real challenge, making sure you know how that connections actually work and make, I did most of the motion control content for that to make the movements of the cars, you know, seamless with the backgrounds. Definitely a lot of fun. So those kind of projects are rare but they're really fun when you get those. >> I hope you have a free pass for any time you want to go on it. >> I don't, unfortunately. >> Oh, you should. >> I try to get in the backrooms all the time at that facility but it's rare to hear. >> I mean it's like, it's a high end rollercoaster machine. It's like, I mean that is this robotics, industrial cause, this, I mean it's an intense ride. >> It is, and you know, you never move more than like eight feet on that whole ride and it feels like you've dropped, you know 2000 feet out of the sky on some of that content. So it's really amazing. I will say it's a little dated. I've been writing on the part of my team worked on the the Harry Potter rides, which are much next generation. >> I couldn't get on that one, line was too long. >> It's a long way, but it's worth it. >> Dave I asked you a question on the future for people watching who are new observing industrial IOT. What's the most important story going on in your world today? Is it the transformation? Is it the standards? Is it the security? What's, what are the top two or three things that are going on that are really transformative right now in automating at the edge? >> I really want to say that it's standardization. It's about using open standards and standard protocols to deliver content in a reusable fashion. So, you know, having custom proprietary content like a lot of automation suppliers or even like a lot of other industries, it's hard to maintain. It doesn't work well with other products. It's great 'cause you can do a lot of flexibility what you want to do, but at the end of the day it's about keeping the thing running and hooking it up to other components so that open standards based solution you'll see us spending more energy on you know, part of the Ansible open community thing is nice in that space as well. And you'll see us doing more stuff in that place that, that play. >> Talk about your influence there in the community. You know, we, we've been talking the last couple of days about Ansible is nothing if not the power of the community, the collaboration within. Talk about being able to influence that and what that means to you personally as well as to Rockwell. >> Yeah, so open communities are big for us. We have, you know, obviously a customer advisory boards and things like that that we deal with but we also have an open community forum where people can share dialogues and share ideas. We have large events, we have a process solution users group events where we bring in, you know hundreds not thousands of engineering people to to talk to all of these problems that they're facing. And it's not a Rockwell event it's a, you know, community event, right. Where we actually are talking about, you know what industry problem people are seeing. And a lot of the IT OT convergence thing is really top of mind. A lot of people say no minds especially the cybersecurity content. >> What are some of the things that you heard the last couple of days, announcement wise? Obviously big news coming out today that excites you about the direction that Ansible's going and how it's responding to the community. >> Yeah, I think a lot of their feedback that they get and sitting a lot of these sessions, they get a lot of interesting feedback from their customer base. And reacting to that I think is very high on their priority list. And what I've been seeing here, you know, some of the AI stuff that they were showing on automatically, like defining some of the scripts for their code that intelligence behind a lot of that content was amazing. I see a lot of that moving forward. And we're heading the same direction at Rockwell as well with more AI in our company. >> The data's a big story too coming out of all the devices, analytics, great stuff. >> Yeah, I'm pulling that data up into the cloud space and trying to do something valuable with all that data. It's, you know, we've had big data for a long time. It's just figuring out analytics and how to actually act on that data and get it back into the control to do something with. >> It's all getting aside. My serious question on this is that, you know is it the year finally OT and IT converge? Seems like it's been trying for about a decade. >> Yeah, that's a tough one to answer. So I would say it's not there yet. I think there's still a lot of conflict in that space. You know, the OT guys still have a long history of that space, but as you see more retirement and more people phasing out of that and younger crowds coming in, you know the automation space is ripe for that kind of transition because coming out of college, you know jumping into automation isn't always the top of the notch. A lot of people want to go work at the big Amazons or wherever. >> A lot, a lot of stuff going on in space. It's pretty cool. A lot of physical, I've seen a lot more machine learning and physical devices in the industry we've been reporting on. It's interesting. I think it's close to a tipping point because we saw machine learning and the trivial apps like chat bots never really took off, yep. Just expert systems basically, but they're not really going the next level. So now they are, you're starting to see more, you know of wisdom projects, you know, different models being adopted. So I see AI now kind of kicking up similar to OT IT. >> Yeah, most definitely. You know, we have a lot of projects in that space like doing predictive analysis on, let's just say something simple like a pump, right? If you have pumps out there that are running for years and years, but you notice that there's a trend that on day 305 or whatever you know, a bearing starts to fail all the time. You know, that kind of analytics can start doing predictive maintenance content and start pushing out work orders in advance before the things fail because downtime costs millions of dollars for these maintenance. >> Downtime also incidents, right? So you never know, right? >> Exactly. Right, right. So it's good to have that safety net at least from a manufacturing perspective. >> Final question for me. What's the most exciting thing going on in your world right now if you had to kind of pick one thing that you're most jazzed up about? >> I have to say, you know, Rockwell's doing a big shift to cloud-based content and more big data numbers like we were just talking about for that AI. That complexity of what you can do with AI and the value that you can do to like just, you know if I can make quality of a product a half a percent better that's millions of dollars for my customer and I see us doing a lot of work in that space and moving that forward. That's big for me, I think. >> And what are some of that, my last question is what are some of the impacts that customers can expect from that? >> Yeah, so everything from downtime to product quality to increasing production rates and volumes of data that come out. You know, we do something called model predictive control that does, you know, very tight control on control loops to improve like just the general product quality with a lot of the big data numbers that are coming in on that. So you'll see us moving more in that space too to improve you know, product quality and then downtime. >> And really driving outcomes, business outcomes for your customers. David, thank you so much for joining us on the program, sharing what Rockwell Automation is doing. We appreciate your insights, your time and we want to keep watching to see what comes next. >> Sure. Glad to be here. It's great. Thank you very much. >> Our pleasure. For our guest, our John Furrier. I'm Lisa Martin. You've watched theCUBE Live in Chicago, Ansible Fest 2022. Thanks for watching. (gentle music)

>>Hey everyone. Lisa Martin of the cube here, HPE and AMD better together with Shi is the name of our segment. And I'm here with four guests. Please. Welcome Charlie Mulrooney global presales engineering manager at Athi John saws also of Shi joins this global pre-sales technical consultant. And back with me are Terry Richardson, north American channel chief and Dr. John Fry, chief technologist, sustainable transformation at HPE. Welcome gang. Great to have you all here. >>Thank you, Lisa. Thanks. You good to be here? >>All right, Charlie, let's go ahead and start with you. Keeping the earth sustainable and minimizing carbon emissions. Greenhouse gases is a huge priority for businesses, right? Everywhere. Globally. Can you talk Charlie about what Shi is seeing in the marketplace with respect to sustainable? It? >>Sure. So starting about a year and a half, two years ago, we really noticed that our customers certainly our largest enterprise customers were putting into their annual reports, their chairman's letters, their sec filings that they had sustainability initiatives ranging from achieving carbon neutral or carbon zero goals starting with 2050 dates. And then since then we've seen 20, 40, and 2030 targets to achieve net neutrality and RFPs, RFIs that we're fielding. Certainly all now contain elements of that. So this is certainly top of mind for our largest customers, our fortune two 50 and fortune 500 customers. For sure. We're, we're seeing an onslaught of requests for this. We get into many conversations with the folks that are leading these efforts to understand, you know, here's what we have today. What can we do better? What can we do different to help make an impact on those goals? >>So making an impact top of mind, pretty much for everyone, as you mentioned, John SAS, let's bring you into the conversation. Now, when you're in customer conversations, what are some of the things that you talk about with respect tohis approach to sustainability, sustainable it, are you seeing more folks that are implementing things tactically versus strategically what's going on in the customer space? >>Well, so Charlie touched on something really important that, you know, the, the wake up moment for us was receiving, you know, proposal requests or customer meeting requests that were around sustainability. And it was really around two years ago, I suppose, for the first time. And those requests started coming from European based companies, cuz they had a bit of a head start over the us based global companies even. And what we found was that sustainability was already well down the road and that they were doing very interesting things to use renewable energy for data centers utilize the, they were already considering sustainability for new technologies as a high priority versus just performance cost and other factors that you typically have at the top. So as we started working with them, I guess at beginning it was more tactical cuz we really had to find a way to respond. >>We were starting to be asked about our own efforts and in regards to sustainability, we have our headquarters in Somerset and our second headquarters in Austin, Texas, those are lead gold certified. We've been installing solar panels, reducing waste across the company, recycling efforts and so forth charging stations for electric vehicles, all that sort of thing to make our company more sustainable in, in, in our offices and in our headquarters. But it's a lot more than that. And what we found was that we wanted to look to our vast number of, of customers and partners. We have over 30,000 partners that would work with globally and tens of thousands of customers. And we wanted to find best practices and technologies and services that we could talk about with these customers and apply and help integrate together as a, as a really large global reseller and integrator. We can have a play there and bring these things together from multiple partners that we work with to help solve customer problems. And so over time it's become more strategic and we've been as a company building the, the, the, the, the forward efforts through organizing a true formal sustainability team and growing that, and then also reporting for CDP Ecova and so forth. And it's really that all has been coming about in the last couple of years. And we take it very seriously. >>It sounds like, and it also sounds like from the customer's perspective, they're shifting from that tactical, maybe early initial approach to being more strategic, to really enabling sustainable it across their organization. And I imagine from a business driver's perspective, John saws and Charlie, are you hearing customers? You talked about it being part of RFPs, but also where are customers in terms of, we need to have a sustainable it strategy so that we can attract and retain the right investors we can attract and retain customers. Charlie, John, what are your thoughts on that? >>Yeah, that's top of mind with, with all the folks that we're talking to, I would say there's probably a three way tie for the importance of attracting and retaining investors. As you said, plus customers, customers are shopping, their customers are shopping for who has aligned their ESG priorities and sustainable priorities with their own and who is gonna help them with their own reporting of, you know, scope two and ultimately scope three reporting from greenhouse gas emissions and then the attracting and retaining talent. It's another element now of when you're bringing on new talent to your organization, they have a choice and they're thinking with their decision to accept a role or not within your organization of what your strategies are and do they align. So we're seeing those almost interchangeable in terms of priorities with, with the customers we're talking to. And it was a little surprising, cuz it, we thought initially this is really focused on investors attracting the investors, but it really has become quite a bit more than that. And it's been actually very interesting to see the development of that prioritization >>More comprehensive across the organization. Let's bring Dr. John Fry into the conversation and Terry your next. So stay tuned. Dr. Fry, can you talk about HPE and S H I partnering together? What are some of the key aspects of the relationship that help one another support and enable each other's aggressive goals where sustainability is concerned? >>Yeah, it's a great question. And one of the things about the sustainability domain in solving these climate challenges that we all have is we've got to come together and partner to solve them. No one company's going to solve them by themselves and for our collective customers the same way. From an HPE perspective, we bring the expertise on our products. We bring in sustainable it point of view, where we've written many white papers on the topic and even workbooks that help companies implement a sustainable it program. But our direct sales forces can't reach all of our customers. And in many cases we don't have the local knowledge that our business partners like Shi bring to the table. So they extend the reach, they bring their own expertise. Their portfolio that they offer to the customer is wider than just enterprise products. So by working together, we can do a better job of helping the customer meet their own needs, give them the right technology solutions and enhance that customer experience because they get more value from us collectively. >>It really is better together, which is in a very appropriate name for our segment here. Terry, let's bring you into the conversation. Talk to us about AMD. How is it helping customers to create that sustainable it strategy? And what are some of the differentiators that what AMD is doing that, that are able to be delivered through partners like Shi? >>Well, Lisa, you used the word enabling just a short while ago. And fundamentally AMD enables HPE and partners like Shi to bring differentiated solutions to customers. So in the data center space, we began our journey in 2017 with some fundamental design elements for our processor technology that were really keenly focused on improving performance, but also efficiency. So now the, the most common measure that we see for the types of customers that Charlie and John were talking about is really that measure of performance per wat. And you'll continue to see AMD enabled customers to, to try to find ways to, to do more in a sustainable way within the constraints that they may be facing, whether it's availability of power data center space, or just needing to meet overall sustainability goals. So we have skills and expertise and tools that we make available to HPE and two Shi to help them have even stronger differentiated conversations with customers. >>Sounds like to me, Terry, that it's, that AMD can be even more of an more than an enabler, but really an accelerator of what customers are able to do from a strategic perspective on sustainability. >>You you're right about that. And, and we actually have tools, greenhouse gas, TCO tools that can be leveraged to really quantify the impact of some of the, the new technology decisions that customers are making to allow them to achieve their goals. So we're really proud of the work that we're doing in partnership with companies like HPE and Shi >>Better together. As we said at the beginning in just a minute ago, Charlie, let's bring you back in, talk to us a little bit about what Shi is doing to leverage sustainable it and enable your customers to meet their sustainability goals and their initiatives. >>So for quite a while, we've had some offerings to help customers, especially in the end user compute side. A lot of customers were interested in, I've got assets for, you know, let's say a large sales force that had been carrying tablets or laptops and, you know, those need to be refreshed. What do I do with those? How do I responsibly retire or recycle those? And we've been offering solutions for that for quite some time. It's within the last year or two, when we started offering for them guarantees and assurances assurances of how they can, if that equipment is reusable by somebody else, how can we issue them? You know, credits for carbon credits for reuse of that equipment somewhere else. So it's not necessarily going to be e-waste, it's something that can be recycled and reused. We have other programs with helping extend the life of, of some systems where they look at well, I have a awful lot of data on these machines where historically they might want to just retire those because the, the, the sensitivity of the data needed to be handled very specifically. We can help them properly remove the sensitive data and still allow reuse of that equipment. So we've been able to come up with some creative solutions specifically around end user compute in the past, but we are looking to new ways now to really help extend that into data center infrastructure and beyond to really help with what are the needs, what are the, the best ways to help our customers handle the things that are challenging them. >>That's a great point that you bring up. Charlie and security kind of popped into my head here, John Saul's question for you when you're in customer conversations and you're talking about, or maybe they're talking about help us with waste reduction with recycling, where are you having those customer conversations? Cause I know sustainability is a board level, it's a C level discussion, but where are you having those conversations within the customer organization? >>Well, so it's a, it's a combination of organizations within the customer. These are these global organizations. Typically when we're talking about asset life cycle management, asset recovery, how do you do that in a sustainable green way and securely the customers we're dealing with? I mean, security is top sustainability is right up there too. O obviously, but Charlie touched on a lot of those things and these are global rollouts, tens of thousands of employees typically to, to have mobile devices, laptops, and phones, and so forth. And they often are looking for a true managed service around the world that takes into consideration things like the most efficient way to ship products to, to the employees. And how do you do that in a sustainably? You need to think about that. Does it all go to a central location or to each individual's home during the pandemic that made a lot of sense to do it that way? >>And I think the reason I wanted to touch on those things is that, well for, for example, one European pharmaceutical that states in their reports that they're already in scope one in scope two they're fully net zero at this point. And, and they say, but that only solves 3% of our overall sustainability goals. 97% is scope three, it's travel, it's shipping. It's, it's, it's all the, the, all these things that are out of their direct control a lot of times, but they're coming to us now as a, as a supplier and as, and, and we're filling out, you know, forms and RFPs and so forth to show that we can be a sustainable supplier in their supply chain because that's their next big goal >>Sustain sustainable supply chain. Absolutely. Yes. Dr. John Fry and Terry, I want to kind of get your perspectives. Charlie talked about from a customer requirements perspective, customers coming through RFP saying, Hey, we've gotta work with vendors who have clear sustainability initiatives that are well underway, HPE and AMD hearing the same thing Dr. Fry will start with you. And then Terry >>Sure, absolutely. We receive about 2,500 customer questionnaires just on sustainability every year. And that's come up from a few hundred. So yeah, absolutely accelerating. Then the conversations turn deeper. Can you help us quantify our carbon emissions and power consumption? Then the conversation has recently gone even further to when can HPE offer net zero or carbon neutral technology solutions to the customer so that they don't have to account for those solutions in their own carbon footprint. So the questions are getting more sophisticated, the need for the data and the accuracy of the data is climbing. And as we see potential regulatory disclosure requirements around carbon emissions, I think this trend is just gonna continue up. >>Yeah. And we see the same thing. We get asked more and more from our customers and partners around our own corporate sustainability goals. But the surveying that survey work that we've done with customers has led us to, you know, understand that, you know, approximately 75% of customers are gonna make sustainability goals, a key component of their RFIs in 2023, which is right around the corner. And, and, you know, 60% of those same customers really expect to have business level KPIs in the new year that are really related to sustainability. So this is not just a, a kind of a buzzword topic. This is, this is kind of business imperatives that, you know, the company, the companies like HPE and AMD and the partners like I, that really stand behind it and really are proactive in getting out in front of customers to help are really gonna be ahead of the game. >>That's a great point that you make Terry there that this isn't, we're not talking about a buzzword here. We're talking about a business imperative for businesses of probably all sizes across all industries and Dr. Far, you mentioned regulations. And something that we just noticed is that the S E C recently said, it's proposing some rules where companies must disclose greenhouse gas emissions. If they were, if that were to, to come into play, I'm gonna pun back to Charlie and John saws. How would Shi and, and frankly at HPE and AMD be able to help companies comply if that type of regulation were to be implemented. Charlie. >>Yeah. So we are in the process right now of building out a service to help customers specifically with that, with the reporting, we know reporting is a challenge. The scope two reporting is a challenge and scope three that I guess people thought was gonna be a ways out now, all of a sudden, Hey, if you have made a public statement that you're going to make an impact on your scope three targets, then you have to report on them. So that, that has become really important very quickly as word about this requirement is rumbling around there's concern. So we are actually working right now on something it's a little too early to fully disclose, but stay tuned, cuz we have something coming. That's interesting. >>Definitely PED my, my ears are, are, are perk here. Charlie, we'll stay tuned for that. Dr. Fry. Terry, can you talk about together with Shi HPE and AMD enabling customers to manage access to the da data obviously, which is critical and it's doing nothing but growing and proliferating key folks need access to it. We talked a little bit about security, but how are from a better together perspective, Dr. Fry will start with you, how are you really helping organizations on that sustainability journey to ensure that data can be accessible to those who need it when they need it? And at these days what it's real time requirements. >>Yeah. It's, it's an increasing challenge. In fact, we have changed the H HP story the way we talk about H HP's value proposition to talk about data first modernization. So how often do you collect data? Where do you store it? How do you avoid moving it? How do you make sure if you're going to collect data, you get insights from that data that change your business or add business value. And then how long do you retain that data afterward and all of that factors into sustainable it, because when I talk to technology executives, what they tell me again, and again, is there's this presumption within their user community, that storage is free. And so when, when they have needs for collecting data, for example, if, if once an hour would do okay, but the system would collect it once a minute, the default, the user asks for of course, once a minute. And then are you getting insights from that data? Or are we moving it that becomes more important when you're moving data back and forth between the public cloud or the edge, because there is quite a network penalty for moving that equipment across your network. There's huge power and carbon implications of doing that. So it's really making a better decision about what do we collect, why do we collect it, what we're gonna do with it when we collect and how we store it. >>And, and for years, customers have really talked about, you know, modernization and the need to modernize their data center. You know, I, I fundamentally believe that sustainability is really that catalyst to really drive true modernization. And as they think forward, you know, when we work with, with HPE, you know, they offer a variety of purpose-built servers that can play a role in, you know, specific customer workloads from the largest, super computers down to kind of general purpose servers. And when we work with partners like Shi, not only can they deliver the full suite of offerings for on premise deployments, they're also very well positioned to leverage the public cloud infrastructure for those workloads that really belong there. And, and that certainly can help customers kind of achieve an end to end sustainability goal. >>That's a great point that, that it needs to be strategic, but it also needs to be an end to end goal. We're just about out of time, but I wanted to give John saws the last word here, take us out, John, what are some of the things Charlie kind of teased some of the things that are coming out that piqued my interest, but what are some of the things that you are excited about as HPE AMD and Shi really help customers achieve their sustainability initiatives? >>Sure. Couple comments here. So Charlie, yeah, you touched on some upcoming capabilities that Shi will have around the area of monitoring and management. See, this is difficult for all customers to be able to report in this formal way. This is a train coming at everybody very quickly and they're not ready. Most customers aren't ready. And if we can help as, as a reseller integrator assessments, to be able to understand what they're currently running compare to different scenarios of where they could go to in a future state, that seems valuable if we can help in that way. That's, those are things that we're looking into specifically, you know, greenhouse gas, emissions, relevant assessments, and, and, and within the comments of, of, of Terry and, and John around the, the power per wat and the vast portfolio of, of technologies that they, that they had to address various workloads is, is fantastic. >>We'd be able to help point to technologies like that and move customers in that direction. I think as a, as an integrator and a technical advisor to customers, I saw an article on BBC this morning that I, I, I think if, if we think about how we're working with our customers and we can help them maybe think differently about how they're using their technology to solve problems. The BBC article mentioned this was Ethereum, a cryptocurrency, and they have a big project called merge. And today was a go live date. And BBC us news outlets have been reporting on it. They basically changed the model from a model called power of work, which takes a, a lot of compute and graphic, GPU power and so forth around the world. And it's now called power of stake, which means that the people that validate that their actions in this environment are correct. >>They have to put up a stake of their own cryptocurrency. And if they're wrong, it's taken from them. This new model reduces the emissions of their environment by 99 plus percent. The June emissions from Ethereum were, it was 120 telos per, per year, a Terra terat hours per year. And they reduced it actually, that's the equivalent of what the net Netherlands needed for energy, so comparable to a medium sized country. So if you can think differently about how to solve problems, it may be on-prem, it may be GreenLake. It may be, it may be the public cloud in some cases or other, you know, interesting, innovative technologies that, that AMD HPE, other partners that we can bring in along, along with them as well, we can solve problems differently. There is a lot going on >>The opportunities that you all talked about to really make such a huge societal impact and impact to our planet are exciting. We thank you so much for talking together about how HPE AMD and SSHA are really working in partnership in synergy to help your customers across every organization, really become much more focused, much more collaborative about sustainable it. Guys. We so appreciate your time and thank you for your insights. >>Thank you, Lisa. Thank you. My >>Pleasure. Thank you, Lisa. You're watching the cube, the leader in high tech enterprise coverage.

>> From "theCUBE" studios in Palo Alto, in Boston, bringing you data driven insights from "theCUBE" and ETR. This is "Breaking Analysis" with Dave Vellante. >> There are very few political issues that get bipartisan support these days, nevermind consensus spanning geopolitical boundaries. But whether we're talking across the aisle or over the pond, there seems to be common agreement that the power of big tech firms should be regulated. But the government's track record when it comes to antitrust aimed at big tech is actually really mixed, mixed at best. History has shown that market forces rather than public policy have been much more effective at curbing monopoly power in the technology industry. Hello, and welcome to this week's "Wikibon CUBE" insights powered by ETR. In this "Breaking Analysis" we welcome in frequent "CUBE" contributor Dave Moschella, author and senior fellow at the Information Technology and Innovation Foundation. Dave, welcome, good to see you again. >> Hey, thanks Dave, good to be here. >> So you just recently published an article, we're going to bring it up here and I'll read the title, "Theory Aside, Antitrust Advocates Should Keep Their "Big Tech" Ambitions Narrow". And in this post you argue that big sweeping changes like breaking apart companies to moderate monopoly power in the tech industry have been ineffective compared to market forces, but you're not saying government shouldn't be involved rather you're suggesting that more targeted measures combined with market forces are the right answer. Can you maybe explain a little bit more the premise behind your research and some of your conclusions? >> Sure, and first let's go back to that title, when I said, theory aside, that is referring to a huge debate that's going on in global antitrust circles these days about whether antitrust should follow the traditional path of being invoked when there's real harm, demonstrable harm to consumers or a new theory that says that any sort of vast monopoly power inevitably will be bad for competition and consumers at some point, so your best to intervene now to avoid harms later. And that school, which was a very minor part of the antitrust world for many, many years is now quite ascendant and the debate goes on doesn't matter which side of that you're on the questions sort of there well, all right, well, if you're going to do something to take on big tech and clearly many politicians, regulators are sort of issuing to do something, what would you actually do? And what are the odds that that'll do more good than harm? And that was really the origins of the piece and trying to take a historical view of that. >> Yeah, I learned a new word, thank you. Neo-brandzian had to look it up, but basically you're saying that traditionally it was proving consumer harm versus being proactive about the possibility or likelihood of consumer harm. >> Correct, and that's a really big shift that a lot of traditional antitrust people strongly object to, but is now sort of the trendy and more send and view. >> Got it, okay, let's look a little deeper into the history of tech monopolies and government action and see what we can learn from that. We put together this slide that we can reference. It shows the three historical targets in the tech business and now the new ones. In 1969, the DOJ went after IBM, Big Blue and it's 13 years later, dropped its suit. And then in 1984 the government broke Ma Bell apart and in the late 1990s, went after Microsoft, I think it was 1998 in the Wintel monopoly. And recently in an interview with tech journalist, Kara Swisher, the FTC chair Lena Khan claimed that the government played a major role in moderating the power of tech giants historically. And I think she even specifically referenced Microsoft or maybe Kara did and basically said the industry and consumers from the dominance of companies like Microsoft. So Dave, let's briefly talk about and Kara by the way, didn't really challenge that, she kind of let it slide. But let's talk about each of these and test this concept a bit. Were the government actions in these instances necessary? What were the outcomes and the consequences? Maybe you could start with IBM and AT&T. >> Yeah, it's a big topic and there's a lot there and a lot of history, but I might just sort of introduce by saying for whatever reasons antitrust has been part of the entire information technology industry history from mainframe to the current period and that slide sort of gives you that. And the reasons for that are I think once that we sort of know the economies of scale, network effects, lock in safe choices, lot of things that explain it, but the good bit about that is we actually have so much history of this and we can at least see what's happened in the past and when you look at IBM and AT&T they both were massive antitrust cases. The one against IBM was dropped and it was dropped in as you say, in 1980. Well, what was going on in at that time, IBM was sort of considered invincible and unbeatable, but it was 1981 that the personal computer came around and within just a couple of years the world could see that the computing paradigm had change from main frames and minis to PCs lines client server and what have you. So IBM in just a couple of years went from being unbeatable, you can't compete with them, we have to break up with them to being incredibly vulnerable and in trouble and never fully recovered and is sort of a shell of what it once was. And so the market took care of that and no action was really necessary just by everybody thinking there was. The case of AT&T, they did act and they broke up the company and I would say, first question is, was that necessary? Well, lots of countries didn't do that and the reality is 1980 breaking it up into long distance and regional may have made some sense, but by the 1990 it was pretty clear that the telecom world was going to change dramatically from long distance and fixed wires services to internet services, data services, wireless services and all of these things that we're going to restructure the industry anyways. But AT& T one to me is very interesting because of the unintended consequences. And I would say that the main unintended consequence of that was America's competitiveness in telecommunications took a huge hit. And today, to this day telecommunications is dominated by European, Chinese and other firms. And the big American sort of players of the time AT&T which Western Electric became Lucent, Lucent is now owned by Nokia and is really out of it completely and most notably and compellingly Bell Labs, the Bell Labs once the world's most prominent research institution now also a shell of itself and as it was part of Lucent is also now owned by the Finnish company Nokia. So that restructuring greatly damaged America's core strength in telecommunications hardware and research and one can argue we've never recovered right through this 5IG today. So it's a very good example of the market taking care of, the big problem, but meddling leading to some unintended consequences that have hurt the American competitiveness and as we'll talk about, probably later, you can see some of that going on again today and in the past with Microsoft and Intel. >> Right, yeah, Bell Labs was an American gem, kind of like Xerox PARC and basically gone now. You mentioned Intel and Microsoft, Microsoft and Intel. As many people know, some young people don't, IBM unwillingly handed its monopoly to Intel and Microsoft by outsourcing the micro processor and operating system, respectively. Those two companies ended up with IBM ironically, agreeing to take OS2 which was its proprietary operating system and giving Intel, Microsoft Windows not realizing that its ability to dominate a new disruptive market like PCs and operating systems had been vaporized to your earlier point by the new Wintel ecosystem. Now Dave, the government wanted to break Microsoft apart and split its OS business from its application software, in the case of Intel, Intel only had one business. You pointed out microprocessors so it couldn't bust it up, but take us through the history here and the consequences of each. >> Well, the Microsoft one is sort of a classic because the antitrust case which was raging in the sort of mid nineties and 1998 when it finally ended, those were the very, once again, everybody said, Bill Gates was unstoppable, no one could compete with Microsoft they'd buy them, destroy them, predatory pricing, whatever they were accusing of the attacks on Netscape all these sort of things. But those the very years where it was becoming clear first that Microsoft basically missed the early big years of the internet and then again, later missed all the early years of the mobile phone business going back to BlackBerrys and pilots and all those sorts of things. So here we are the government making the case that this company is unstoppable and you can't compete with them the very moment they're entirely on the defensive. And therefore wasn't surprising that that suit eventually was dropped with some minor concessions about Microsoft making it a little bit easier for third parties to work with them and treating people a little bit more, even handling perfectly good things that they did. But again, the more market took care of the problem far more than the antitrust activities did. The Intel one is also interesting cause it's sort of like the AT& T one. On the one hand antitrust actions made Intel much more likely and in fact, required to work with AMD enough to keep that company in business and having AMD lowered prices for consumers certainly probably sped up innovation in the personal computer business and appeared to have a lot of benefits for those early years. But when you look at it from a longer point of view and particularly when look at it again from a global point of view you see that, wow, they not so clear because that very presence of AMD meant that there's a lot more pressure on Intel in terms of its pricing, its profitability, its flexibility and its volumes. All the things that have made it harder for them to A, compete with chips made in Taiwan, let alone build them in the United States and therefore that long term effect of essentially requiring Intel to allow AMD to exist has undermined Intel's position globally and arguably has undermined America's position in the long run. And certainly Intel today is far more vulnerable to an ARM and Invidia to other specialized chips to China, to Taiwan all of these things are going on out there, they're less capable of resisting that than they would've been otherwise. So, you thought we had some real benefits with AMD and lower prices for consumers, but the long term unintended consequences are arguably pretty bad. >> Yeah, that's why we recently wrote in Intel two "Strategic To Fail", we'll see, Okay. now we come to 2022 and there are five companies with anti-trust targets on their backs. Although Microsoft seems to be the least susceptible to US government ironically intervention at this this point, but maybe not and we show "The Cincos Comas Club" in a homage to Russ Hanneman of the show "Silicon Valley" Apple, Microsoft, Google, and Amazon all with trillion dollar plus valuations. But meta briefly crossed that threshold like Mr. Hanneman lost a comma and is now well under that market cap probably around five or 600 million, sorry, billion. But under serious fire nonetheless Dave, people often don't realize the immense monopoly power that IBM had which relatively speaking when measured its percent of industry revenue or profit dwarf that of any company in tech ever, but the industry is much smaller then, no internet, no cloud. Does it call for a different approach this time around? How should we think about these five companies their market power, the implications of government action and maybe what you suggested more narrow action versus broad sweeping changes. >> Yeah, and there's a lot there. I mean, if you go back to the old days IBM had what, 70% of the computer business globally and AT&T had 90% or so of the American telecom market. So market shares that today's players can only dream of. Intel and Microsoft had 90% of the personal computer market. And then you look at today the big five and as wealthy and as incredibly successful as they've been, you sort of have almost the argument that's wrong on the face of it. How can five companies all of which compete with each other to at least some degree, how can they all be monopolies? And the reality is they're not monopolies, they're all oligopolies that are very powerful firms, but none of them have an outright monopoly on anything. There are competitors in all the spaces that they're in and increasing and probably increasingly so. And so, yeah, I think people conflate the extraordinary success of the companies with this belief that therefore they are monopolist and I think they're far less so than those in the past. >> Great, all right, I want to do a quick drill down to cloud computing, it's a key component of digital business infrastructure in his book, "Seeing Digital", Dave Moschella coined a term the matrix or the key which is really referred to the key technology platforms on which people are going to build digital businesses. Dave, we joke you should have called it the metaverse you were way ahead of your time. But I want to look at this ETR chart, we show spending momentum or net score on the vertical access market share or pervasiveness in the dataset on the horizontal axis. We show this view a lot, we put a dotted line at the 40% mark which indicates highly elevated spending. And you can sort of see Microsoft in the upper right, it's so far up to the right it's hidden behind the January 22 and AWS is right there. Those two dominate the cloud far ahead of the pack including Google Cloud. Microsoft and to a lesser extent AWS they dominate in a lot of other businesses, productivity, collaboration, database, security, video conferencing. MarTech with LinkedIn PC software et cetera, et cetera, Googles or alphabets of business of course is ads and we don't have similar spending data on Apple and Facebook, but we know these companies dominate their respective business. But just to give you a sense of the magnitude of these companies, here's some financial data that's worth looking at briefly. The table ranks companies by market cap in trillions that's the second column and everyone in the club, but meta and each has revenue well over a hundred billion dollars, Amazon approaching half a trillion dollars in revenue. The operating income and cash positions are just mind boggling and the cash equivalents are comparable or well above the revenues of highly successful tech companies like Cisco, Dell, HPE, Oracle, and Salesforce. They're extremely profitable from an operating income standpoint with the clear exception of Amazon and we'll come back to that in a moment and we show the revenue multiples in the last column, Apple, Microsoft, and Google, just insane. Dave, there are other equally important metrics, CapX is one which kind of sets the stage for future scale and there are other measures. >> Yeah, including our research and development where those companies are spending hundreds of billions of dollars over the years. And I think it's easy to look at those numbers and just say, this doesn't seem right, how can any companies have so much and spend so much? But if you think of what they're actually doing, those companies are building out the digital infrastructure of essentially the entire world. And I remember once meeting some folks at Google, and they said, beyond AI, beyond Search, beyond Android, beyond all the specific things we do, the biggest thing we're actually doing is building a physical infrastructure that can deliver search results on any topic in microseconds and the physical capacity they built costs those sorts of money. And when people start saying, well, we should have lots and lots of smaller companies well, that sounds good, yeah, it's all right, but where are those companies going to get the money to build out what needs to be built out? And every country in the world is trying to build out its digital infrastructure and some are going to do it much better than others. >> I want to just come back to that chart on Amazon for a bit, notice their comparatively tiny operating profit as a percentage of revenue, Amazon is like Bezos giant lifestyle business, it's really never been that profitable like most retail. However, there's one other financial data point around Amazon's business that we want to share and this chart here shows Amazon's operating profit in the blue bars and AWS's in the orange. And the gray line is the percentage of Amazon's overall operating profit that comes from AWS. That's the right most access, so last quarter we were well over a hundred percent underscoring the power of AWS and the horrendous margins in retail. But AWS is essentially funding Amazon's entrance into new markets, whether it's grocery or movies, Bezos moves into space. Dave, a while back you collaborated with us and we asked our audience, what could disrupt Amazon? And we came up with your detailed help, a number of scenarios as shown here. And we asked the audience to rate the likelihood of each scenario in terms of its likelihood of disrupting Amazon with a 10 being highly likely on average the score was six with complacency, arrogance, blindness, you know, self-inflicted wounds really taking the top spot with 6.5. So Dave is breaking up Amazon the right formula in your view, why or why not? >> Yeah, there's a couple of things there. The first is sort of the irony that when people in the sort of regulatory world talk about the power of Amazon, they almost always talk about their power in consumer markets, whether it's books or retail or impact on malls or main street shops or whatever and as you say that they make very little money doing that. The interest people almost never look at the big cloud battle between Amazon, Microsoft and lesser extent Google, Alibaba others, even though that's where they're by far highest market share and pricing power and all those things are. So the regulatory focus is sort of weird, but you know, the consumer stuff obviously gets more appeal to the general public. But that survey you referred to me was interesting because one of the challenges I sort of sent myself I was like okay, well, if I'm going to say that IBM case, AT&T case, Microsoft's case in all those situations the market was the one that actually minimized the power of those firms and therefore the antitrust stuff wasn't really necessary. Well, how true is that going to be again, just cause it's been true in the past doesn't mean it's true now. So what are the possible scenarios over the 2020s that might make it all happen again? And so each of those were sort of questions that we put out to others, but the ones that to me by far are the most likely I mean, they have the traditional one of company cultures sort of getting fat and happy and all, that's always the case, but the more specific ones, first of all by far I think is China. You know, Amazon retail is a low margin business. It would be vulnerable if it didn't have the cloud profits behind it, but imagine a year from now two years from now trade tensions with China get worse and Christmas comes along and China just says, well, you know, American consumers if you want that new exercise bike or that new shoes or clothing, well, anything that we make well, actually that's not available on Amazon right now, but you can get that from Alibaba. And maybe in America that's a little more farfetched, but in many countries all over the world it's not farfetched at all. And so the retail divisions vulnerability to China just seems pretty obvious. Another possible disruption, Amazon has spent billions and billions with their warehouses and their robots and their automated inventory systems and all the efficiencies that they've done there, but you could argue that maybe someday that's not really necessary that you have Search which finds where a good is made and a logistical system that picks that up and delivers it to customers and why do you need all those warehouses anyways? So those are probably the two top one, but there are others. I mean, a lot of retailers as they get stronger online, maybe they start pulling back some of the premium products from Amazon and Amazon takes their cut of whatever 30% or so people might want to keep more of that in house. You see some of that going on today. So the idea that the Amazon is in vulnerable disruption is probably is wrong and as part of the work that I'm doing, as part of stuff that I do with Dave and SiliconANGLE is how's that true for the others too? What are the scenarios for Google or Apple or Microsoft and the scenarios are all there. And so, will these companies be disrupted as they have in the past? Well, you can't say for sure, but the scenarios are certainly plausible and I certainly wouldn't bet against it and that's what history tells us. And it could easily happen once again and therefore, the antitrust should at least be cautionary and humble and realize that maybe they don't need to act as much as they think. >> Yeah, now, one of the things that you mentioned in your piece was felt like narrow remedies, were more logical. So you're not arguing for totally Les Affaire you're pushing for remedies that are more targeted in scope. And while the EU just yesterday announced new rules to limit the power of tech companies and we showed the article, some comments here the regulators they took the social media to announce a victory and they had a press conference. I know you watched that it was sort of a back slapping fest. The comments however, that we've sort of listed here are mixed, some people applauded, but we saw many comments that were, hey, this is a horrible idea, this was rushed together. And these are going to result as you say in unintended consequences, but this is serious stuff they're talking about applying would appear to be to your point or your prescription more narrowly defined restrictions although a lot of them to any company with a market cap of more than 75 billion Euro or turnover of more than 77.5 billion Euro which is a lot of companies and imposing huge penalties for violations up to 20% of annual revenue for repeat offenders, wow. So again, you've taken a brief look at these developments, you watched the press conference, what do you make of this? This is an application of more narrow restrictions, but in your quick assessment did they get it right? >> Yeah, let's break that down a little bit, start a little bit of history again and then get to Europe because although big sweeping breakups of the type that were proposed for IBM, Microsoft and all weren't necessary that doesn't mean that the government didn't do some useful things because they did. In the case of IBM government forces in Europe and America basically required IBM to make it easier for companies to make peripherals type drives, disc drives, printers that worked with IBM mainframes. They made them un-bundle their software pricing that made it easier for database companies and others to sell their of products. With AT&T it was the government that required AT&T to actually allow other phones to connect to the network, something they argued at the time would destroy security or whatever that it was the government that required them to allow MCI the long distance carrier to connect to the AT network for local deliveries. And with that Microsoft and Intel the government required them to at least treat their suppliers more even handly in terms of pricing and policies and support and such things. So the lessons out there is the big stuff wasn't really necessary, but the little stuff actually helped a lot and I think you can see the scenarios and argue in the piece that there's little stuff that can be done today in all the cases for the big five, there are things that you might want to consider the companies aren't saints they take advantage of their power, they use it in ways that sometimes can be reigned in and make for better off overall. And so that's how it brings us to the European piece of it. And to me, the European piece is much more the bad scenario of doing too much than the wiser course of trying to be narrow and specific. What they've basically done is they have a whole long list of narrow things that they're all trying to do at once. So they want Amazon not to be able to share data about its selling partners and they want Apple to open up their app store and they don't want people Google to be able to share data across its different services, Android, Search, Mail or whatever. And they don't want Facebook to be able to, they want to force Facebook to open up to other messaging services. And they want to do all these things for all the big companies all of which are American, and they want to do all that starting next year. And to me that looks like a scenario of a lot of difficult problems done quickly all of which might have some value if done really, really well, but all of which have all kinds of risks for the unintended consequence we've talked before and therefore they seem to me being too much too soon and the sort of problems we've seen in the past and frankly to really say that, I mean, the Europeans would never have done this to the companies if they're European firms, they're doing this because they're all American firms and the sort of frustration of Americans dominance of the European tech industry has always been there going back to IBM, Microsoft, Intel, and all of them. But it's particularly strong now because the tech business is so big. And so I think the politics of this at a time where we're supposedly all this great unity of America and NATO and Europe in regards to Ukraine, having the Europeans essentially go after the most important American industry brings in the geopolitics in I think an unavoidable way. And I would think the story is going to get pretty tense over the next year or so and as you say, the Europeans think that they're taking massive actions, they think they're doing the right thing. They think this is the natural follow on to the GDPR stuff and even a bigger version of that and they think they have more to come and they see themselves as the people taming big tech not just within Europe, but for the world and absent any other rules that they may pull that off. I mean, GDPR has indeed spread despite all of its flaws. So the European thing which it doesn't necessarily get huge attention here in America is certainly getting attention around the world and I would think it would get more, even more going forward. >> And the caution there is US public policy makers, maybe they can provide, they will provide a tailwind maybe it's a blind spot for them and it could be a template like you say, just like GDPR. Okay, Dave, we got to leave it there. Thanks for coming on the program today, always appreciate your insight and your views, thank you. >> Hey, thanks a lot, Dave. >> All right, don't forget these episodes are all available as podcast, wherever you listen. All you got to do is search, "Breaking Analysis Podcast". Check out ETR website, etr.ai. We publish every week on wikibon.com and siliconangle.com. And you can email me david.vellante@siliconangle.com or DM me @davevellante. Comment on my LinkedIn post. This is Dave Vellante for Dave Michelle for "theCUBE Insights" powered by ETR. Have a great week, stay safe, be well and we'll see you next time. (slow tempo music)

>>Kicking things off for Netscout's latest threat intelligence reports. I'm Lisa Martin with Richard Hummel manager of threat intelligence at NetScout. We're going to be talking about DDoSs for hire. It's a free for all Richard, welcome to the program. >>Thanks for having me. At least that's always a pleasure to do interviews with you here on acuity. >>Likewise. So, which are the dark web is a dangerous place. We know that we're adversaries own and operate DDoS for hire platforms and botnets to launch everything from free tests to high powered multi-vector attacks. What did you find? What kind of attacks are being launched on the dark web, >>Sadly, any and every type of attack you. And I think you put it eloquently that it's free a little while ago. I got a question come in from a media journalists that I was talking to and they asked me what is the average cost of a DDoS attack? And my gut reaction was mad, 10, 20 USD. I even asked another reporter later on, what do you think it costs? And he came out with two or 300 USD. And so that was kinda my expectations. Well, just because of that question, I broke up my lab and I said, you know what? I'm just going to kind of sleuth a little bit. And so I started logging in, I started looking at these underground platforms and I spend time on 19 of hundreds. There's a website out there that lists all with like three or 400 of these things, but I just chose the top 19. >>And when I started looking at these, every platform that I evaluated had some form of free attacks during launch. And these are the typical for your five attacks like NTP, cl doubt, DNS amplification. These are the, the rope or routine types of attacks we see in the DDoS threat landscape and it's free. And then it scales from there. You have $5 entry fees to do trials. You have a week trial, you can go all the way up to 6,500 USD. And the adversary reports to launch one terabit per second attack with that costs. There's another one that says, Hey, we have 150,000 button-up nodes. He has $2,500, and then you can launch it from this platform. And they also have customization. They have these little sliders on there. You can go in and say, you know what? I have five targets. I want to launch 10 attacks at once. I want it to last this many minutes. These are the vectors I want to use. And then it just tells you here's what you got to pay. Now, it used to be, you needed to have a crypto wallet to even launch a DDoS attack. Well, that's no longer the case. Second. It used to be crypto currency. Well, now they take PayPal. They take wire transfers. They do Western union transfers. And so yeah, this barrier to entry, it doesn't exist anymore. >>Wow. The evolution of data also attacks the low barrier to entry. The customization. You mentioned that you researched the top 19 validated DDoS for hire services. You guys captured the types of attacks, reported number of users and the costs to launch what you went through. What are some of the things that really stuck out to you that you found? >>I think the biggest thing, the biggest outlier that I saw with a lot of these things is that this, the sheer amount of attacks or tech types that they purport to launch that combined with one other metric that I'll, I'll tell you in just a minute. But when I started adding all of these out, I came out with a list of something like 450 different line items. This is taking the attack types from all 19 of these platforms and putting it into a spreadsheet. And then when I actually got rid of the duplicates and I started looking at each one of these to see, did they call it this? And then this one called it, this, there was still 200 different types of attacks. And these attacks are not just your typical volume metric things or your typical like botnet net related things. I mean, they're going after applications. >>They're going after capture pages. They're going after some website based anti DDoSs stuff. They're going after specific games, grand theft, auto Counter-Strike, all of these things. And they have specific attacks designed to overwhelm those layers. And you can actually see in some of the, the, the news or the update boxes they have on their platforms that they put rolling updates similar to like what you would see with Microsoft update. Here's what changed. And so they'll list, oh, we added this capture bypass, or we tweak this bypass, or guess what? We added a new server. And now you have this, this more power to launch bigger attacks. The other thing that really surprised me was the sheer number of users and attacks that they put for it to have and have launched. So across these 19 platforms, I counted over 1 million registered users. Now it could be that multiple users are registered across multiple platforms. >>And so maybe that's a little redundant, but a million or 19. And then the attacks, just whatever they showed in their platform. Now, I don't know what time segment that says it could be all time. It could be a certain snapshot, whatever, 19 of several hundred of these things, more than 10 million attacks. Now, if we look at 2020, we saw 10 million attacks on the whole year, 2021, we saw 9.7 million. So you can just see it. I mean, we're not seeing the whole breadth of the threat landscape. We see about a third probably of the world's internet traffic. And so if what they say is true, there's a lot more attacks out there than even. We talk about >>A lot more attacks than, than are even uncovered. That's shocking. The evolution of DDoSs is, is also quite shocking. One of the things I noticed in the first half 2021 threat intelligence report that NetScout published was some of the underground services offer blacklists or delisting services to prevent attacks. And I thought that sounds like a good thing, but what does that really mean? >>So actually, when we were writing the last chart report, a colleague of mine role in Dobbins had actually talked about this and he's like, Hey, I saw this thing where it's this quasi illegal organization. And they were talking about listing you as this. And they actually turn around and sell these lists. And so I started researching that a little bit. And what it turns out is these organizations, they report to be VPN services. Yeah. And they also say, you know what, we're offer these kinds of lists or block lists. We offer this VPN service, but we are also collecting your IP address. And so if you don't want us to basically resell that to somebody else, or if you want us to add that so that people can attack you based on what they're seeing on the VPN, then you can pay us money and you can do like different tiers of this. >>You can say, block me for a week or a block me for a lifetime and all of these different platforms. I wouldn't say all of them, probably four of the 19 that I looked at had this service. Now as a user, I'm not going to go to every single DDoS for hire platform. I'm not going to purchase the VPN from every single one of these. I'm not going to go and add myself to their denialist across all of these things. That's, that's kind of way too much work for one. And the cost is going to be in the thousands, if not tens of thousands, as you start to add all of these things together. And so they, they report to do something good and in turn, take your information and sell it. And what's worse is they actually assign your username or your handle or your gamer tag to that IP address. >>And so now you have this full list of IPS with gamer tags. And so an adversary Alto that has no qualms or scruples about launching DDoS attacks can then purchase that list. And guess what, Hey, this, this gamer over here who has this gamer tag, he always tells me I don't, I don't want to face them anymore. So anytime I see him in a match, I'm going to go over here to this DDoS for hire platform. And I'm going to just launch attack against him, try to knock them off of them. And so that's the kind of shady business practices that we're seeing here in the underground forums. >>Well, I knew that wasn't a good, I knew that you would actually give me the skinny on what that was. So another thing that I was wondering if it was a good, you know, despite this, you talked about the incredible diversity of these platforms, the majority of attack types that you sign are recognized and mitigated by standard defensive practices. Is that another good, bad disguise as good? >>No, in this case, it is very much good. So I, as far as I've seen, there's not a single DDoS attack type from a Google stressor service to date that you can't mitigate using preparation and your, your typical DDoSs platforms, mitigation protection systems. And even, even the bandwidth, the throughput, what some people call the size or the speed of attacks. We don't really see anything in the terabit per second range from these services. Now they'll, they'll boast about having the capability to do X number of packets per second, or this size of an attack. And so some of them will even say that, Hey, you pay us this money and we're going to give you a one terabit per second attack to date in the four years that I've been here on NetScout. And even some of my colleagues who've been around the space for decades. >>They have yet to see an attack source from one of these details for higher platforms that exceed one terabit per second in bandwidth or volume. And so they might talk a big game. They might boast about these things, but oftentimes it's, it's smoke and mirrors. It's a way to get people into their platforms to purchase things. If I had to pick kind of an average volume or size of attacks for these beer stressors on the high-end, I would say around the 150 to 200 gigabit per second. Now they're a small organization that might seem huge, but to a service provider, that's, that's probably a drop in the bucket and they can easily saturate that across their network, or observe, absorb that even without the top of the line mitigation services. So just being able to have something in place, understand how adversaries are launching these attacks, what attack vectors they are, you know, do some research. >>We have this portal called ominous threat horizon, where you can actually go in there and into your industry segment and your country. And you can just look to see, are there attacks against people like me in my country? And so, but understanding if you are the target of attacks, which it's not, if it's a win, then you can understand, okay, I need to probably have provisions in place for up to this threshold and ensure there's a tax that will exceed that. But at least you're doing due diligence to have some measure of protection, understanding that these are the typical kinds of attacks that you can expect. >>Yeah. That due diligence is key. Richard, thanks for joining me talking about DDoSs for hire a lot of interesting things there that was uncovered in a moment. Richard and I are going to be back to talk about the rise of server class bot net armies.

(upbeat music) >> Hello, welcome back to this cube conversation, on cube on cloud startups. I'm John Furrier host of theCUBE. We're wrapping up the closing keynote fireside chat of the AWS showcase, the hottest startups in data and cloud. We've got some great guests here to eluminate what's happened and why it's important. And Michael Skok who's the founding partner, Michael Skok founding partner of Underscore VC, Mike Feinstein, principal business development manager, and the best Ben Haynes CIO advisor Lincoln Center for the Performing Arts. Gentlemen, thank you for joining me for this closing keynote for the AWS showcase. >> Pleasure to be here. >> So, first of all-- >> Happy to be here >> Guys, do you guys have a unique background from startup funding, growing companies, managing these partners at AWS and being a practitioner with Ben here. The first question I have is, what is the real market opportunity? We've heard from McKinsey that there's a trillion dollars of unlocked value in cloud and that really is going to come from all enterprises big and small. So the question is that that's what every wants to know. What's the secret answer key to the to the test if you are a business. 'Cause you don't want to be on the wrong side of cloud history here. There is a playbook, there's some formation of patterns and there's some playbook things happening out there. How do you guys see this? >> Well, I can try to take a crack at that. First of all I think, there's not only one playbook, you know, only one recipe. If it's a trillion dollar opportunity, that's in the aggregate. There's many different types of opportunities. I think you could have existing companies that are maybe older line companies that need to change the way they're doing things. You can have the younger companies that are trying to take advantage of all the data they've already collected and try to get more value out of it. There could be some radically different types of opportunities with newer technology. I think, you know, for each company just like each of the companies here at the showcase today, they are targeting some, you know, segment of this. Each of those segments is already large. And I think you're going to see a wide range of solutions taking hold here. >> Yeah, cloud drives a lot of value. Michael, I want to get your thoughts. You know, you've seen the software revolution you know, over the years. This time it seems to be accelerated, the time to value, if you're a startup. I mean, you couldn't ask for the perfect storm for our innovation if you're coming out of MIT, Stanford, any college. If you're not even going to school you can get in cloud, do anything. Starting software now is not as hard as it was or its different. What's your perspective because you know, these companies are adding treated value and they're going into an enterprise market that wants scale, they want the reliability. How do you see this evolving? >> You know, the very first time I saw Bezos get on stage and pitch AWS he said one thing which is, "We take away all the hard stuff about starting a software business and let you focus on the innovation." And I think that's still applies. So you're dead right John. And honestly, most founders don't want to spend any time on anything other than unique piece of innovation that they're going to deliver for their customers. So, I think that is fabulous news. I'm going to joke for a second, so I think we're all under shooting on this number. I mean, the reality is that every part of compute infrastructure that we talk about today was built from an infrastructure that's you know, decades old. By which I mean 30 to 50 decades in some 30 to 50 years in some cases. And we look forward in 30 to 50 years, we won't be talking about cloud or everything else. We'll be just talking about computing or whatever it is that we want to talk about at the edge. Or the application of data that you know, in a car and an ARVR heads up display that's helping surgeons work across the world. The fact is the only way this is really going to work is on the cloud. So I think it's a multi-trillion dollar opportunity, we're just taking a snapshot of it right now. And we're in an interesting point because of course digital transformation has been rapidly accelerated. I mean, there's all these jokes about you know, we've had five years of transformation in five months. I don't really care what the number is but what is obvious is that we couldn't have gone off to work and to play and to teach and all these other things without the cloud. And we just took it for granted but a year ago, that's what we all did and look, they're thriving. This whole thing is that, you know, a live broadcast that we're doing on the cloud. So yeah, I think it's a very big opportunity and whatever sector I think to Mike's point, that you look at and all the companies that you've seen this morning prove that, if you want to innovate today, you start on the cloud. Your cloud native as I would say. And as you grow, you will be a cloud assumed. It will be the basis on which everybody wants to access your products and services. So I'm excited about the future if you can't tell. >> I totally subscribe to that. Ben, I want to get your take as the CIO, now advisor to companies. If you're going to look at what Michael's laying out, which is born in the cloud native, they have an advantage, an inherent advantage right out of the gate. They have speed agility and scale. If you're an existing business you say, "Wait a minute I'm going to be competed against these hot startups." There's some serious fear of missing out and fear of getting screwed, right? I mean, you might go out of business. So this is the real threat. This is not just talked about, there's real examples now playing out. So as a practitioner, thinking about re-architecting or rejuvenating or pivoting or just being competitive. It's really the pressure's there. How do you see this? >> Yeah I know it really is. And every enterprise company and through every decade is it's a buyer versus build conversation. And with the cloud opportunities, you can actually build a lot quicker or you can leverage companies that can even go quicker than you that have a focus on innovation. 'Cause sometimes enterprise companies, it's hard to focus on the really cool stuff and that's going to bring value but maybe it won't. So if you can partner with someone and some of these companies that you just showcase, start doing some amazing things. That can actually help accelerate your own internal innovation a lot quicker than trying to spool up your own team. >> We heard some companies talking about day two operations lift and shift, not a layup either. I mean, lift and shift if not done properly as it's well discussed. And McKinsey actually puts that in their report as there's other point outs. It's not a no brainer. I mean, it's a no brainer to go to the cloud but if you lift and shift without really thinking it through or remediating anything, it could be, it could cost more. And you got the CAPEX and OPEX dynamics. So, certainly cloud is happening and this kind of gives a great segue into our next topic that I'd love to get you guys to weigh in on. And that is the business model, the business structure, business organization. Michael you brought up some interesting topics around, some of the new ideas that could be, you know, decentralized or just different consumption capabilities on both sides of the equation. So, the market's there, trillions and trillions of dollars are shifting and the spoils will go to the ones who are smart and agile and fast. But the business model, you could have it, you could be in the right market, but the wrong business model. Who wants to take the first cut at that? >> Mike do you want to go? >> Sure, I'd be happy to. I think that, you know, I mean again, there's not there only going to be one answer but I think one of the things that really make sense is that the business models can be much more consumption-based. You're certainly not going to see annual software licenses that you saw in the old world. Things are going to be much more consumption-based obviously software is a service type of models. And you're going to see, I think lots of different innovations. I've also seen a lot of companies that are starting up kind of based on open source as like a first foray. So there's an open source project that really catches hold. And then a company comes up behind it to both enhance it and to also provide support and to make it a real enterprise offering. But they get there early quick adoption of the frontline engineers by starting off with an open source project. And that's a model that I've seen work quite well. And I think it's a very interesting one. So, you know, the most important thing is that the business model has to be one that's as flexible as what the solutions are that you're trying to get the customers to adopt. The old way of everything being kind of locked in and rigid isn't going to work in this world 'cause you have to just really be agile. >> I want to come back to you Mike in a second on this 'cause I know Amazon's got some innovative go to market stuff. Michael you've written about this, I've read many blog posts on your side about SaaS piece. What's your take on business structure. I mean, obviously with remote, it's clear people are recognizing virtual companies are available. You mentioned you know, edge and compute, and these new app, these emerging technologies. Does the business structure and models shift? Do you have to be on certain side of this business model innovation? How do you view? 'Cause you're seeing the startups who are usually crazy at first, but then they become correct at the end of the day. What's your take? >> Well first of all, I love this debate because it's over. We used to have things that were not successful that would become shelfware. And that just doesn't work in the cloud. There is no shelfware. You're either live and being used or you're dead. So the great news about this is, it's very visible. You know, you can measure every person's connection to you for how long and what they're doing. And so the people that are smart, don't start with this question, the business model. They start with what am I actually doing for my user that's in value them? So I'll give you some examples like build on Mike's team. So, you know, I backed a company called Acquia. But it was based on an open source project called Drupal. Which was initially used for content management. Great, but people started building on it and over time, it became used for everything from the Olympics and hosting, you know, theirs to the Grammy's, to you know, pick your favorite consumer brand that was using it to host all of their different brands and being very particular about giving people the experiences. So, it's now a digital experience platform. But the reason that it grew successfully as a company is because on top of the open source project, we could see what people were doing. And so we built what in effect was the basis for them to get comfortable. By the way, Amazon is very fundamental partner in this was, became an investor extremely helpful. And again, took away all the heavy lifting so we could focus on the innovation. And so that's an example of what's going on. And the model there is very simple. People are paying for what they use to put that digital experience of that, to create a great customer journey. And for people to have the experience that obviously you know, makes the brand look good or makes the audience feel great if it's the Grammy's or whatever it is. So I think that's one example, but I'll give you two others because they are totally different. And one of the most recent investments we made is in a company called Coder. Which is a doc spelled backwards. and it's a new kind of doc that enables people to collaborate and to bring data and graphics and workflow and everything else, all into the simplicity of what's like opening up a doc. And they don't actually charge anybody who uses their docs. They just charge for people who make their docs. So its a make a best pricing, which is very interesting. They've got phenomenal metrics. I mean they're like over 140% net dollar retention, which is astoundingly good. And they grew over three and a half times last year. So that's another model, but it's consumer and it's, you know, as I said, make a price. And then, you know, another company we've been involved with if I look at it way back was Demand Web. It was the first e-commerce on demand company. We didn't charge for the software at all. We didn't charge for anything in fact. what we did was to take a percentage of the sales that went through the platform. And of course everybody loved that because, you know, if we were selling more or getting better uplift then everybody started to do very well. So, you know, the world's biggest brands moved online and started using our platform because they didn't want to create all that infrastructure. Another totally different model. And I could go on but the point is, if you start from the customer viewpoint like what are you doing for the customer? Are you helping them sell more? Or are you helping them build more effective business processes or better experiences? I think you've got a fantastic opportunity to build a great model in the cloud. >> Yeah, it's a great point. I think that's a great highlight also call out for expectations become the experience, as the old saying goes. If a customer sees value in something, you don't have to be tied to old ways of selling or pricing. And this brings up, Ben, I want to tie in you in here and maybe bring Mike back in. As an enterprise, it used to be the old adage of, well startups are unreliable, blah, blah, blah, you know, they got to get certified and enterprise usually do things more complicated than say consumer businesses. But now Amazon has all kinds of go to market. They have the marketplace, they have all kinds of the partner networks. This certification integration is a huge part of this. So back to, you know, Michael's point of, if you're dead you're dead or knows it, but if you're alive you usually have some momentum it's usually well understood, but then you have to integrate. So it has to be consumable for the enterprise. So Ben, how do you see that? Because at the end of the day, there's this desire for the better product and the better use case. That can, how do I procure it? Integration? These used to be really hard problems. Seems to be getting easier or are they? What's your take? >> Not 100%. I mean, even five years ago you would have to ask a lot of startups for a single sign on and as table stakes now. So the smart ones are understanding the enterprise principles that we need and a lot of it is around security. And then, they're building that from the start, from the start of their products. And so if you get out of that security hurdle, the stability so far is a lot more improved because they are, you know, a lot more focused and moving in a really, really quick way which can help companies, you know, move quickly. So definitely seen an improvement and there's still, the major entry point is credit card, small user base, small pricing, so you're not dealing with procurement. And building your way up into the big purchase model, right? And that model hasn't changed except the start is a lot lot quicker and a lot easier to get going. >> You know, I remember the story of the Amazon web stores, how they won the CIA contract is someone put a test on a credit card and IBM had the deal in their back pocket. They had the Ivory Tower sales call, Michael, you know the playbook on enterprise sales, you know, you got the oracles and you guys call it the top golf tournament smoothing and then you got the middle and then you got the bottoms up you got the, you know, the data dogs of the world who can just come in with freemium. So there's different approaches. How do you guys see that? Michael and Mike, I'd love for you to weigh in on this because this is really where there's no one answer, but depending upon the use case, there's certain motions that work better. Can you elaborate on which companies should pay attention to what and how customers should understand how they're buying? >> Yeah, I can go first on that. I think that first of all, with every customer it's going to be a little different situation, depends on the scale of the solution. But I find that, these very large kind of, you know, make a huge decision and buy some really big thing all at once. That's not happening very much anymore. As you said John, people are kind of building up it's either a grassroots adoption that then becomes an enterprise sale, or there is some trials or smaller deployments that then build up at enterprise sales. Companies can't make those huge mistake. So if they're going to make a big commitment it's based on confidence, that's come from earlier success. And one of the things that we do at AWS in addition to kind of helping enterprises choose the right technology partners, such as many of the companies here today. We also have solutions partners that can help them analyze the market and make the choice and help them implement it. So depending on the level of help that they need, there's lots of different resources that are going to be available to help them make the right choice the first time. >> Michael, your thoughts on this, because ecosystems are a part of the entire thing and partnering with Amazon or any cloud player, you need to be secure. You need to have all the certifications. But the end of the day, if it works, it works. And you can consume it whatever way you can. I mean, you can buy download through the marketplace. You can go direct, it's free. What do you see as the best mix of go to market from a cloud standpoint? Given that there's a variety of different use cases. >> Well, I'm going to play off Ben and Mike on this one and say, you know, there's a perfect example of what Ben brought up, which is single sign on. For some companies, if you don't have that you just can't get in the door. And at the other extreme to what Mike is saying, you know, there are reasons why people want to try stuff before they buy it. And so, you've got to find some way in between these two things to either partner with the right people that have the whole product solution to work with you. So, you know, if you don't have single sign on, you know, go work with Okta. And if you don't have all the certification that's needed well, work with AWS and you know, take it on that side of cash and have better security than anybody. So there's all sorts of ways to do this. But the bottom line is I think you got to be able to share value before you charge. And I'll give you two examples that are extreme in our portfolio, because I think it will show the sort of the edge with these two things. You know, the first one is a company called Popcart. It's been featured a lot in the press because when COVID hit, nobody could find whatever it was, that TP or you know, the latest supplies that they wanted. And so Popcart basically made it possible for people to say, "Okay, go track all the favorite suppliers." Whether it's your Walmarts or your Targets or your Amazons, et cetera. And they would come back and show you the best price and (indistinct) it cost you nothing. Once you started buying of course they were getting (indistinct) fees and they're transferring obviously values so everybody's doing well. It's a win-win, doesn't cost the consumer anything. So we love those strategies because, you know, whenever you can make value for people without costing them anything, that is great. The second one is the complete opposite. And again, it's an interesting example, you know, to Ben's point about how you have to work with existing solutions in some cases, or in some cases across more things to the cloud. So it's a company called Cloud Serum. It's also one we've partnered with AWS on. They basically help you save money as you use AWS. And it turns out that's important on the way in because you need to know how much it's going to cost to run what you're already doing off premises, sorry off the cloud, into the cloud. And secondly, when you move it there to optimize that spend so you don't suddenly find yourself in a situation where you can't afford to run the product or service. So simply put, you know, this is the future. We have to find ways to specifically make it easy again from the customer standpoint. The get value as quickly as possible and not to push them into anything that feels like, Oh my God, that's a big elephant of a risk that I don't obviously want to take on. >> Well, I'd like to ask the next question to Michael and Ben. This is about risk management from an enterprise perspective. And the reason Michael we just want to get you in here 'cause you do risk for living. You take risks, you venture out and put bets on horses if you will. You bet on the startups and the growing companies. So if I'm a customer and this is a thing that I'm seeing both in the public and private sector where partnerships are super critical. Especially in public right now. Public private partnerships, cybersecurity and data, huge initiatives. I saw General Keith Alexander talking about this, about his company and a variety of reliance on the private problem. No one winning formula anymore. Now as an enterprise, how do they up level their skill? How do you speak to enterprises who are watching and learning as they're taking the steps to be cloud native. They're training their people, they're trying to get their IT staff to be superpowers. They got to do all these. They got to rejuvenate, they got to innovate. So one of the things that they got to take in is new partnerships. How can an enterprise look at these 10 companies and others as partners? And how should the startups that are growing, become partners for the enterprise? Because if they can crack that code, some say that's the magical formula. Can you guys weigh in on that? (overlapping chatter) >> Look, the unfortunate starting point is that they need to have a serious commitment to wanting to change. And you're seeing a lot of that 'cause it is popping up now and they're all nodding their heads. But this needs people, it needs investment, and it needs to be super important, not just to prior, right? And some urgency. And with that behind you, you can find the right companies and start partnering to move things forward. A lot of companies don't understand their risk profile and we're still stuck in this you know, the old days of global network yet infiltrated, right? And that's sort of that its like, "Oh my God, we're done." And it's a lot more complicated now. And there needs to be a lot of education about the value of privacy and trust to our consumers. And once the executive team understands that then the investments follow. The challenge there is everyone's waiting, hoping that nothing goes wrong. When something goes wrong, oh, we better address that, right? And so how do we get ahead of that? And you need a very proactive CSO and CIO and CTO and all three if you have them really pushing this agenda and explaining what these risks are. >> Michael, your thoughts. Startups can be a great enabler for companies to change. They have their, you know, they're faster. They bring in new tech to the scenario scene. What's your analysis? >> Again, I'll use an example to speak to some of the things that Ben's talking about. Which is, let's say you decide you want to have all of your data analysis in the cloud. It turns out Amazon's got a phenomenal set of services that you can use. Do everything from ingest and then wrangle your data and get it cleaned up, and then build one of the apps to gain insight on it and use AI and ML to make that whole thing work. But even Amazon will be the first to tell you that if you have all their services, you need a team understand the development, the operations and the security, DevSecOps, it's typically what it's referred to. And most people don't have that. If you're sure and then say you're fortune 1000, you'll build that team. You'll have, you know, a hundred people doing that. But once you get below that, even in the mid tier, even in a few billion dollar companies, it's actually very hard to have those skills and keep them up to date. So companies are actually getting built that do all of that for you, that effectively, you know, make your services into a product that can be run end to end. And we've invested in one and again we partnered with Amazon on gold Kazina. They effectively make the data lake as a service. And they're effectively building on top of all the Amazon services in orchestrating and managing all that DevSecOps for you. So you don't need that team. And they do it in, you know, days or weeks, not months or years. And so I think that the point that Ben made is a really good one. Which is, you know, you've got to make it a priority and invest in it. And it doesn't just happen. It's a new set of skills, they're different. They require obviously everything from the very earliest stage of development in the cloud, all the way through to the sort of managing and running a bit. And of course maintaining it all securely and unscalable, et cetera. (overlapping chatter) >> It's interesting you bring up that Amazon's got great security. You mentioned that earlier. Mike, I wanted to bring you in because you guys it's graduating a lot of startups, graduating, it's not like they're in school or anything, but they're really, you're building on top of AWS which is already, you know, all the SOC report, all the infrastructure's there. You guys have a high bar on security. So coming out of the AWS ecosystem is not for the faint of heart. I mean, you got to kind of go through and I've heard from many startups that you know, that's a grueling process. And this is, should be good news for the enterprise. How are you guys seeing that partnership? What's the pattern recognition that we can share with enterprises adopting startups coming on the cloud? What can they expect? What are some best practices? What are the things to look for in adopting startup technologies? >> Yeah, so as you know we have a shared security model where we do the security for the physical infrastructure that we're operating, and then we try to share best practices to our partners who really own the security for their applications. Well, one of the benefits we have particularly with the AWS partner network is that, we will help vet these companies, we will review their security architecture, we'll make recommendations. We have a lot of great building blocks of services they can use to build their applications, so that they have a much better chance of really delivering a more secure total application to the enterprise customer. Now of course the enterprise customers still should be checking this and making sure that all of these products meet their needs because that is their ultimate responsibility. But by leveraging the ecosystem we have, the infrastructure we have and the strength of our partners, they can start off with a much more secure application or use case than they would if they were trying to build it from scratch. >> All right. Also, I want to get these guys out of the way in on this last question, before we jump into the wrap up. products and technologies, what is the most important thing enterprises should be focused on? It could be a list of three or four or five that they should be focused on from emerging technologies or a technology secret sauce perspective. Meaning, I'm going to leverage some new things we're going to build and do or buy from cloud scale. What are the most important product technology issues they need to be paying attention to? >> I think I'll run with that first. There's a major, major opportunity with data. We've gone through this whole cycle of creating data lakes that tended to data's forms and big data was going to solve everything. Enterprises are sitting on an amazing amount of information. And anything that can be done to, I actually get insights out of that, and I don't mean dashboards, PI tools, they're like a dime a dozen. How can we leverage AI and ML to really start getting some insights a lot quicker and a lot more value to the company from the data they owns. Anything around that, to me is a major opportunity. >> Now I'm going to go just a little bit deeper on that 'cause I would agree with all those points that Ben made. I think one of the real key points is to make sure that they're really leveraging the data that they have in kind of in place. Pulling in data from all their disparate apps, not trying to generate some new set of data, but really trying to leverage what they have so they can get live information from the disparate apps. Whether it's Salesforce or other systems they might have. I also think it's important to give users the tools to do a lot of their own analytics. So I think definitely, you know, kind of dashboards are a dime a dozen as Ben said, but the more you can do to make it really easy for users to do their own thing, so they're not relying on some central department to create some kind of report for them, but they can innovate on their own and do their own analytics of the data. I think its really critical to help companies move faster. >> Michael? >> I'll just build on that with an example because I think Ben and Mike gave two very good things, you know, data and making it self service to the users et cetera So, an example is one of our companies called Salsify, which is B2B commerce. So they're enabling brands to get their products out into the various different channels the day that people buy them on. Which by the way, an incredible number of channels have been created, whether it's, you know, Instagram at one extreme or of course you know, traditional commerce sites is another. And it's actually impossible to get all of the different capabilities of your product fully explained in the right format in each of those channels humanly. You actually have to use a computer. So that highlights the first thing I was thinking is very important is, what could you not do before that you can now do in the cloud? And you know, do in a distributed fashion. So that's a good example. The second thing is, and Mike said it very well, you know, if you can give people the data that Ben was referring to in a way that they line a business user, in this case, a brand manager, or for example the merchandiser can actually use, they'll quickly tell you, "Oh, these three channels are really not worth us spending a lot of money on. We need waste promotion on them. But look at this one, this one's really taking up. This TikTok thing is actually worth paying attention to. Why don't we enable people to buy, you know, products there?" And then focus in on it. And Salsify, by the way, is you know, I can give you stats with every different customer they've got, but they've got huge brands. The sort of Nestlés, the L'Oreals et cetera. Where they're measuring in terms of hundreds of percent of sales increase, because of using the data of Ben's point and making itself service to Mike's point. >> Awesome. Thought exercise for this little toss up question, for anyone who wants to grab it. If you had unlimited budget for R&D, and you wanted to play the long game and you wanted to take some territory down in the future. What technology and what area would you start carving out and protecting and owning or thinking about or digging into. There's a variety of great stuff out there and you know, being prepared for potentially any wildcards, what would it be? >> Well, I don't mind jumping in. That's a tough question. Whatever I did, I would start with machine learning. I think we're still just starting to see the benefits of what this can do across all of different applications. You know, if you look at what AWS has been doing, we, you know, we recently, many of our new service offerings are integrating machine learning in order to optimize automatically, to find the right solution automatically, to find errors in code automatically. And I think you're going to see more and more machine learning built into all types of line of business applications. Sales, marketing, finance, customer service. You know, you already see some of it but I think it's going to happen more and more. So if I was going to bet on one core thing, it would be that. >> I'll jump on that just because I-- >> You're VC, do you think about this as an easy one for you. >> Well, yes or no (indistinct) that I've been a VC now for too long. I was you know (indistinct) for 21 years. I could have answered that question pretty well but in the last 19 of becoming a VC, I've become ruined by just capital being put behind things. But in all seriousness, I think Mike is right. I think every single application is going to get not just reinvented completely reimagined by ML. Because there's so much of what we do that there is indeed managing the data to try to understand how to improve the business process. And when you can do that in an automated fashion and with a continuous close loop that improves it, it takes away all the drudgery and things like humans or the other extreme, you know, manufacturing. And in-between anything that goes from border to cash faster is going to be good for business. And that's going to require ML. So it's an exciting time ahead. That's where we're putting our money. >> Ben, are you going to go off the board here or you're going to stay with machine learning and dating, go wild card here. Blockchain? AR? VR? (overlapping chatter) >> Well I'd have to say ML and AI applying to privacy and trust. Privacy and trust is going to be a currency that a lot of companies need to deal with for a long time coming. And anything you can do to speed that up and honestly remove the human element, and like Michael said, there's a lot of, before there's a lot of services on AWS that are very creative. There's a lot of security built-in But it's that one S3 bucket that someone left open on the internet, that causes the breach. So how are we automating that? Like how do we take the humans out of this process? So we don't make human errors to really get some security happening. >> I think trust is an interesting one. Trust is kind of data as well. I mean, communities are, misinformation, we saw that with elections, huge. Again, that's back to data. We're back to data again. >> You know, John if I may, I'd like to add to that though. It's a good example of something that none of us can predict. Which is, what will be a fundamentally new way of doing this that we haven't really thought of? And, you know, the blockchain is effectively created a means for people to do distributed computing and also, you know, sharing of data, et cetera. Without the human being in the middle and getting rid of many of the intermediaries that we thought were necessary. So, I don't know whether it's the next blockchain or there's blockchain itself, but I have a feeling that this whole issue of trust will become very different when we have new infrastructure. >> I think I agree with everyone here. The data's key. I come back down to data whether you're telling the sovereignty misinformation, the data is there. Okay. Final, final question before we wrap up. This has been amazing on a more serious note for the enterprise folks out there and people in general and around the world. If you guys could give a color commentary answer to, what the post COVID world will look like. With respect to technology adoption, societal impact and technology for potentially good and aura for business. Now that we're coming closer to vaccines and real life again, what is the post COVID world going to look like? What do we learn from it? And how does that translate into everyday in real life benefits? >> Well, I think one of the things that we've seen is that people have realized you can do a lot of work without being in the office. You could be anywhere as long as you can access the data and make the insights from it that you need to. And so I think there's going to be an expectation on the part of users, that there'll be able to do that all the time. They'll be able to do analytics on their phone. They'll be able to do it from wherever they are. They'll be able to do it quickly and they'll be able to get access to the information that they need. And that's going to force companies to continue to be responsive to the expectations and the needs of their users, so that they can keep people productive and have happy employees. Otherwise they're going to go work somewhere else. >> Michael, any thoughts? Post COVID, what do we learn? What happens next? >> You said one key thing Mike, expectations. And I think we're going to live in a very difficult world because expectations are completely unclear. And you might think it's based on age, or you might think it's based on industry or geography, etc. The reality is people have such wildly different expectations and you know, we've tried to do surveys and to try and understand, you know, whether there are some patterns here. I think it's going to be one word, hybrid. And how we deal with hybrid is going to be a major leadership challenge. Because it's impossible to predict what people will do and how they will behave and how they want to for example, go to school or to you know, go to work or play, et cetera. And so I think the third word that I would use is flexibility. You know, we just have to be agile and flexible until we figure out, you know, how this is going to settle out, to get the best of both worlds, because there's so much that we've learned that has been to your point, really beneficial. The more productivity taking out the community. But there's also a lot of things that people really want to get back to such as social interaction, you know, connecting with their friends and living their lives. >> Ben, final word. >> So I'll just drill in on that a little bit deeper. The war on talent, if we talk about tech, if we talk a lot about data, AI, ML. That it's going to be a big differentiator for the companies that are willing to maintain a work from home and your top level resources are going to be dictating where they're working from. And they've seen our work now. And you know, if you're not flexible with how you're running your organization, you will start to lose talent. And companies are going to have to get their head around that as we move forward. >> Gentlemen, thank you very much for your time. That's a great wrap up to this cube on cloud, the AWS startup showcase. Thank you very much on behalf of Dave Vellante, myself, the entire cube team and Amazon web services. Thank you very much for closing out the keynote. Thanks for your time. >> Thank you John and thanks Amazon for a great day. >> Yeah, thank you John. >> Okay, that's a wrap for today. Amazing event. Great keynote, great commentary, 10 amazing companies out there growing, great traction. Cloud startup, cloud scale, cloud value for the enterprise. I'm John Furrier on behalf of theCUBE and Dave Vellante, thanks for watching. (bright music)

>> Hello everyone. On today's panel, the theme is Drug Discovery and how Artificial Intelligence can make a difference. On the panel today, we are honored to have Dr. Ryan Yates, principal scientist at The National Center for Natural Products Research, with a focus on botanicals specifically the pharmacokinetics, which is essentially how the drug changes over time in our body and pharmacodynamics which is essentially how drugs affects our body. And of particular interest to him is the use of AI in preclinical screening models to identify chemical combinations that can target chronic inflammatory processes such as fatty liver disease, cognitive impairment and aging. Welcome, Ryan. Thank you for coming. >> Good morning. Thank you for having me. >> The other distinguished panelist is Dr. Rangan Sukumar, our very own, is a distinguished technologist at the CTO office for High Performance Computing and Artificial Intelligence with a PHD in AI and 70 publications that can be applied in drug discovery, autonomous vehicles and social network analysis. Hey Rangan, welcome. Thank you for coming, by sparing the time. We have also our distinguished Chris Davidson. He is leader of our HPC and AI Application and Performance Engineering team. His job is to tune and benchmark applications, particularly in the applications of weather, energy, financial services and life sciences. Yes so particular interest is life sciences he spent 10 years in biotech and medical diagnostics. Hi Chris, welcome. Thank you for coming. >> Nice to see you. >> Well let's start with your Chris, yes, you're regularly interfaced with pharmaceutical companies and worked also on the COVID-19 White House Consortium. You know tell us, let's kick this off and tell us a little bit about your engagement in the drug discovery process. >> Right and that's a good question I think really setting the framework for what we're talking about here is to understand what is the drug discovery process. And that can be kind of broken down into I would say four different areas, there's the research and development space, the preclinical studies space, clinical trial and regulatory review. And if you're lucky, hopefully approval. Traditionally this is a slow arduous process it costs a lot of money and there's a high amount of error. Right, however this process by its very nature is highly iterate and has just huge amounts of data, right it's very data intensive, right and it's these characteristics that make this process a great target for kind of new approaches in different ways of doing things. Right, so for the sake of discussion, right, go ahead. >> Oh yes, so you mentioned data intensive brings to mind Artificial Intelligence, you know, so Artificial Intelligence making the difference here in this process, is that so? >> Right, and some of those novel approaches are actually based on Artificial Intelligence whether it's deep learning and machine learning, et cetera, you know, prime example would say, let's just say for the sake of discussion, let's say there's a brand new virus, causes flu-like symptoms, shall not be named if we focus kind of on the R and D phase, right our goal is really to identify target for the treatment and then screen compounds against it see which, you know, which ones we take forward right to this end, technologies like cryo-electron, cryogenic electron microscopy, just a form of microscopy can provide us a near atomic biomolecular map of the samples that we're studying, right whether that's a virus, a microbe, the cell that it's attaching to and so on, right AI, for instance, has been used in the particle picking aspect of this process. When you take all these images, you know, there are only certain particles that we want to take and study, right whether they have good resolution or not whether it's in the field of the frame and image recognition is a huge part of this, it's massive amounts of data in AI can be very easily, you know, used to approach that. Right, so with docking, you can take the biomolecular maps that you achieved from cryo-electron microscopy and you can take those and input that into the docking application and then run multiple iterations to figure out which will give you the best fit. AI again, right, this is iterative process it's extremely data intensive, it's an easy way to just apply AI and get that best fit doing something in a very, you know, analog manner that would just take humans very long time to do or traditional computing a very long time to do. >> Oh, Ryan, Ryan, you work at the NCNPR, you know, very exciting, you know after all, you know, at some point in history just about all drugs were from natural products yeah, so it's great to have you here today. Please tell us a little bit about your work with the pharmaceutical companies, especially when it is often that drug cocktails or what they call Polypharmacology, is the answer to complete drug therapy. Please tell us a bit more with your work there. >> Yeah thank you again for having me here this morning Dr. Goh, it's a pleasure to be here and as you said, I'm from the National Center for Natural Products Research you'll hear me refer to it as the NCNPR here in Oxford, Mississippi on the Ole Miss Campus, beautiful setting here in the South and so, what, as you said historically, what the drug discovery process has been, and it's really not a drug discovery process is really a therapy process, traditional medicine is we've looked at natural products from medicinal plants okay, in these extracts and so where I'd like to begin is really sort of talking about the assets that we have here at the NCNPR one of those prime assets, unique assets is our medicinal plant repository which comprises approximately 15,000 different medicinal plants. And what that allows us to do, right is to screen mine, that repository for activities so whether you have a disease of interest or whether you have a target of interest then you can use this medicinal plant repository to look for actives, in this case active plants. It's really important in today's environment of drug discovery to really understand what are the actives in these different medicinal plants which leads me to the second unique asset here at the NCNPR and that is our what I'll call a plant deconstruction laboratory so without going into great detail, but what that allows us to do is through a how to put workstation, right, is to facilitate rapid isolation and identification of phytochemicals in these different medicinal plants right, and so things that have historically taken us weeks and sometimes months, think acetylsalicylic acid from salicylic acid as a pain reliever in the willow bark or Taxol, right as an anti-cancer drug, right now we can do that with this system on the matter of days or weeks so now we're talking about activity from a plant and extract down to phytochemical characterization on a timescale, which starts to make sense in modern drug discovery, alright and so now if you look at these phytochemicals, right, and you ask yourself, well sort of who is interested in that and why, right what are traditional pharmaceutical companies, right which I've been working with for 20, over 25 years now, right, typically uses these natural products where historically has used these natural products as starting points for new drugs. Right, so in other words, take this phytochemical and make chemicals synthetic modifications in order to achieve a potential drug. But in the context of natural products, unlike the pharmaceutical realm, there is often times a big knowledge gap between a disease and a plant in other words I have a plant that has activity, but how to connect those dots has been really laborious time consuming so it took us probably 50 years to go from salicylic acid and willow bark to synthesize acetylsalicylic acid or aspirin it just doesn't work in today's environment. So casting about trying to figure out how we expedite that process that's when about four years ago, I read a really fascinating article in the Los Angeles Times about my colleague and business partner, Dr. Rangan Sukumar, describing all the interesting things that he was doing in the area of Artificial Intelligence. And one of my favorite parts of this story is basically, unannounced, I arrived at his doorstep in Oak Ridge, he was working Oak Ridge National Labs at the time, and I introduced myself to him didn't know what was coming, didn't know who I was, right and I said, hey, you don't know me you don't know why I'm here, I said, but let me tell you what I want to do with your system, right and so that kicked off a very fruitful collaboration and friendship over the last four years using Artificial Intelligence and it's culminated most recently in our COVID-19 project collaborative research between the NCNPR and HP in this case. >> From what I can understand also as Chris has mentioned highly iterative, especially with these combination mixture of chemicals right, in plants that could affect a disease. We need to put in effort to figure out what are the active components in that, that affects it yeah, the combination and given the layman's way of understanding it you know and therefore iterative and highly data intensive. And I can see why Rangan can play a huge significant role here, Rangan, thank you for joining us So it's just a nice segue to bring you in here, you know, given your work with Ryan over so many years now, tell I think I'm also quite interested in knowing a little about how it developed the first time you met and the process and the things you all work together on that culminated into the progress at the advanced level today. Please tell us a little bit about that history and also the current work. Rangan. >> So, Ryan, like he mentioned, walked into my office about four years ago and he was like hey, I'm working on this Omega-3 fatty acid, what can your system tell me about this Omega-3 fatty acid and I didn't even know how to spell Omega-3 fatty acids that's the disconnect between the technologist and the pharmacologist, they have terms of their own right since then we've come a long way I think I understand his terminologies now and he understands that I throw words like knowledge graphs and page rank and then all kinds of weird stuff that he's probably never heard in his life before right, so it's been on my mind off to different domains and terminologies in trying to accept each other's expertise in trying to work together on a collaborative project. I think the core of what Ryan's work and collaboration has led me to understanding is what happens with the drug discovery process, right so when we think about the discovery itself, we're looking at companies that are trying to accelerate the process to market, right an average drug is taking 12 years to get to market the process that Chris just mentioned, Right and so companies are trying to adopt what's called the in silico simulation techniques and in silico modeling techniques into what was predominantly an in vitro, in silico, in vivo environment, right. And so the in silico techniques could include things like molecular docking, could include Artificial Intelligence, could include other data-driven discovery methods and so forth, and the essential component of all the things that you know the discovery workflows have is the ability to augment human experts to do the best by assisting them with what computers do really really well. So, in terms of what we've done as examples is Ryan walks in and he's asking me a bunch of questions and few that come to mind immediately, the first few are, hey, you are an Artificial Intelligence expert can you sift through a database of molecules the 15,000 compounds that he described to prioritize a few for next lab experiments? So that's question number one. And he's come back into my office and asked me about hey, there's 30 million publications in PubMag and I don't have the time to read everything can you create an Artificial Intelligence system that once I've picked these few molecules will tell me everything about the molecule or everything about the virus, the unknown virus that shows up, right. Just trying to understand what are some ways in which he can augment his expertise, right. And then the third question, I think he described better than I'm going to was how can technology connect these dots. And typically it's not that the answer to a drug discovery problem sits in one database, right he probably has to think about uniproduct protein he has to think about phytochemical, chemical or informatics properties, data and so forth. Then he talked about the phytochemical interaction that's probably in another database. So when he is trying to answer other question and specifically in the context of an unknown virus that showed up in late last year, the question was, hey, do we know what happened in this particular virus compared to all the previous viruses? Do we know of any substructure that was studied or a different disease that's part of this unknown virus and can I use that information to go mine these databases to find out if these interactions can actually be used as a repurpose saying, hook, say this drug does not interact with this subsequence of a known virus that also seems to be part of this new virus, right? So to be able to connect that dot I think the abstraction that we are learning from working with pharma companies is that this drug discovery process is complex, it's iterative, and it's a sequence of needle in the haystack search problems, right and so one day, Ryan would be like, hey, I need to match genome, I need to match protein sequences between two different viruses. Another day it would be like, you know, I need to sift through a database of potential compounds, identified side effects and whatnot other day it could be, hey, I need to design a new molecule that never existed in the world before I'll figure out how to synthesize it later on, but I need a completely new molecule because of patentability reasons, right so it goes through the entire spectrum. And I think where HP has differentiated multiple times even the recent weeks is that the technology infusion into drug discovery, leads to several aha! Moments. And, aha moments typically happened in the other few seconds, and not the hours, days, months that Ryan has to laboriously work through. And what we've learned is pharma researchers love their aha moments and it leads to a sound valid, well founded hypothesis. Isn't that true Ryan? >> Absolutely. Absolutely. >> Yeah, at some point I would like to have a look at your, peak the list of your aha moments, yeah perhaps there's something quite interesting in there for other industries too, but we'll do it at another time. Chris, you know, with your regular work with pharmaceutical companies especially the big pharmas, right, do you see botanicals, coming, being talked about more and more there? >> Yeah, we do, right. Looking at kind of biosimilars and drugs that are already really in existence is kind of an important point and Dr. Yates and Rangan, with your work with databases this is something important to bring up and much of the drug discovery in today's world, isn't from going out and finding a brand new molecule per se. It's really looking at all the different databases, right all the different compounds that already exist and sifting through those, right of course data is mind, and it is gold essentially, right so a lot of companies don't want to share their data. A lot of those botanicals data sets are actually open to the public to use in many cases and people are wanting to have more collaborative efforts around those databases so that's really interesting to kind of see that being picked up more and more. >> Mm, well and Ryan that's where NCNPR hosts much of those datasets, yeah right and it's interesting to me, right you know, you were describing the traditional way of drug discovery where you have a target and a compound, right that can affect that target, very very specific. But from a botanical point of view, you really say for example, I have an extract from a plant that has combination of chemicals and somehow you know, it affects this disease but then you have to reverse engineer what those chemicals are and what the active ones are. Is that very much the issue, the work that has to be put in for botanicals in this area? >> Yes Doctor Goh, you hit it exactly. >> Now I can understand why a highly iterative intensive and data intensive, and perhaps that's why Rangan, you're highly valuable here, right. So tell us about the challenge, right the many to many intersection to try and find what the targets are, right given these botanicals that seem to affect the disease here what methods do you use, right in AI, to help with this? >> Fantastic question, I'm going to go a little bit deeper and speak like Ryan in terminology, but here we go. So with going back to about starting of our conversation right, so let's say we have a database of molecules on one side, and then we've got the database of potential targets in a particular, could be a virus, could be bacteria, could be whatever, a disease target that you've identified, right >> Oh this process so, for example, on a virus, you can have a number of targets on the virus itself some have the spike protein, some have the other proteins on the surface so there are about three different targets and others on a virus itself, yeah so a lot of people focus on the spike protein, right but there are other targets too on that virus, correct? >> That is exactly right. So for example, so the work that we did with Ryan we realized that, you know, COVID-19 protein sequence has an overlap, a significant overlap with previous SARS-CoV-1 virus, not only that, but it overlap with MERS, that's overlapped with some bad coronavirus that was studied before and so forth, right so knowing that and it's actually broken down into multiple and Ryan I'm going to steal your words, non-structural proteins, envelope proteins, S proteins, there's a whole substructure that you can associate an amino acid sequence with, right so on the one hand, you have different targets and again, since we did the work it's 160 different targets even on the COVID-19 mark, right and so you find a match, that we say around 36, 37 million molecules that are potentially synthesizable and try to figure it out which one of those or which few of those is actually going to be mapping to which one of these targets and actually have a mechanism of action that Ryan's looking for, that'll inhibit the symptoms on a human body, right so that's the challenge there. And so I think the techniques that we can unrule go back to how much do we know about the target and how much do we know about the molecule, alright. And if you start off a problem with I don't know anything about the molecule and I don't know anything about the target, you go with the traditional approaches of docking and molecular dynamics simulations and whatnot, right. But then, you've done so much docking before on the same database for different targets, you'll learn some new things about the ligands, the molecules that Ryan's talking about that can predict potential targets. So can you use that information of previous protein interactions or previous binding to known existing targets with some of the structures and so forth to build a model that will capture that essence of what we have learnt from the docking before? And so that's the second level of how do we infuse Artificial Intelligence. The third level, is to say okay, I can do this for a database of molecules, but then what if the protein-protein interactions are all over the literature study for millions of other viruses? How do I connect the dots across different mechanisms of actions too? Right and so this is where the knowledge graph component that Ryan was talking about comes in. So we've put together a database of about 150 billion medical facts from literature that Ryan is able to connect the dots and say okay, I'm starting with this molecule, what interactions do I know about the molecule? Is there a pretty intruding interaction that affects the mechanism of pathway for the symptoms that a disease is causing? And then he can go and figure out which protein and protein in the virus could potentially be working with this drug so that inhibiting certain activities would stop that progression of the disease from happening, right so like I said, your method of options, the options you've got is going to be, how much do you know about the target? How much do you know the drug database that you have and how much information can you leverage from previous research as you go down this pipeline, right so in that sense, I think we mix and match different methods and we've actually found that, you know mixing and matching different methods produces better synergies for people like Ryan. So. >> Well, the synergies I think is really important concept, Rangan, in additivities, synergistic, however you want to catch that. Right. But it goes back to your initial question Dr. Goh, which is this idea of polypharmacology and historically what we've done with traditional medicines there's more than one active, more than one network that's impacted, okay. You remember how I sort of put you on both ends of the spectrum which is the traditional sort of approach where we really don't know much about target ligand interaction to the completely interpretal side of it, right where now we are all, we're focused on is, in a single molecule interacting with a target. And so where I'm going with this is interesting enough, pharma has sort of migrate, started to migrate back toward the middle and what I mean by that, right, is we had these in a concept of polypharmacology, we had this idea, a regulatory pathway of so-called, fixed drug combinations. Okay, so now you start to see over the last 20 years pharmaceutical companies taking known, approved drugs and putting them in different combinations to impact different diseases. Okay. And so I think there's a really unique opportunity here for Artificial Intelligence or as Rangan has taught me, Augmented Intelligence, right to give you insight into how to combine those approved drugs to come up with unique indications. So is that patentability right, getting back to right how is it that it becomes commercially viable for entities like pharmaceutical companies but I think at the end of the day what's most interesting to me is sort of that, almost movement back toward that complex mixture of fixed drug combination as opposed to single drug entity, single target approach. I think that opens up some really neat avenues for us. As far as the expansion, the applicability of Artificial Intelligence is I'd like to talk to, briefly about one other aspect, right so what Rang and I have talked about is how do we take this concept of an active phytochemical and work backwards. In other words, let's say you identify a phytochemical from an in silico screening process, right, which was done for COVID-19 one of the first publications out of a group, Dr. Jeremy Smith's group at Oak Ridge National Lab, right, identified a natural product as one of the interesting actives, right and so it raises the question to our botanical guy, says, okay, where in nature do we find that phytochemical? What plants do I go after to try and source botanical drugs to achieve that particular end point right? And so, what Rangan's system allows us to do is to say, okay, let's take this phytochemical in this case, a phytochemical flavanone called eriodictyol and say, where else in nature is this found, right that's a trivial question for an Artificial Intelligence system. But for a guy like me left to my own devices without AI, I spend weeks combing the literature. >> Wow. So, this is brilliant I've learned something here today, right, If you find a chemical that actually, you know, affects and addresses a disease, right you can actually try and go the reverse way to figure out what botanicals can give you those chemicals as opposed to trying to synthesize them. >> Well, there's that and there's the other, I'm going to steal Rangan's thunder here, right he always teach me, Ryan, don't forget everything we talk about has properties, plants have properties, chemicals have properties, et cetera it's really understanding those properties and using those properties to make those connections, those edges, those sort of interfaces, right. And so, yes, we can take something like an eriodictyol right, that example I gave before and say, okay, now, based upon the properties of eriodictyol, tell me other phytochemicals, other flavonoid in this case, such as that phytochemical class of eriodictyols part right, now tell me how, what other phytochemicals match that profile, have the same properties. It might be more economically viable, right in other words, this particular phytochemical is found in a unique Himalayan plant that I've never been able to source, but can we find something similar or same thing growing in, you know a bush found all throughout the Southeast for example, like. >> Wow. So, Chris, on the pharmaceutical companies, right are they looking at this approach of getting, building drugs yeah, developing drugs? >> Yeah, absolutely Dr. Goh, really what Dr. Yates is talking about, right it doesn't help us if we find a plant and that plant lives on one mountain only on the North side in the Himalayas, we're never going to be able to create enough of a drug to manufacture and to provide to the masses, right assuming that the disease is widespread or affects a large enough portion of the population, right so understanding, you know, not only where is that botanical or that compound but understanding the chemical nature of the chemical interaction and the physics of it as well where which aspect affects the binding site, which aspect of the compound actually does the work, if you will and then being able to make that at scale, right. If you go to these pharmaceutical companies today, many of them look like breweries to be honest with you, it's large scale, it's large back everybody's clean room and it's, they're making the microbes do the work for them or they have these, you know, unique processes, right. So. >> So they're not brewing beer okay, but drugs instead. (Christopher laughs) >> Not quite, although there are pharmaceutical companies out there that have had a foray into the brewery business and vice versa, so. >> We should, we should visit one of those, yeah (chuckles) Right, so what's next, right? So you've described to us the process and how you develop your relationship with Dr. Yates Ryan over the years right, five years, was it? And culminating in today's, the many to many fast screening methods, yeah what would you think would be the next exciting things you would do other than letting me peek at your aha moments, right what would you say are the next exciting steps you're hoping to take? >> Thinking long term, again this is where Ryan and I are working on this long-term project about, we don't know enough about botanicals as much as we know about the synthetic molecules, right and so this is a story that's inspired from Simon Sinek's "Infinite Game" book, trying to figure it out if human population has to survive for a long time which we've done so far with natural products we are going to need natural products, right. So what can we do to help organizations like NCNPR to stage genomes of natural products to stage and understand the evolution as we go to understand the evolution to map the drugs and so forth. So the vision is huge, right so it's not something that we want to do on a one off project and go away but in the process, just like you are learning today, Dr. Goh I'm going to be learning quite a bit, having fun with life. So, Ryan what do you think? >> Ryan, we're learning from you. >> So my paternal grandfather lived to be 104 years of age. I've got a few years to get there, but back to "The Infinite Game" concept that Rang had mentioned he and I discussed that quite frequently, I'd like to throw out a vision for you that's well beyond that sort of time horizon that we have as humans, right and that's this right, is our current strategy and it's understandable is really treatment centric. In other words, we have a disease we develop a treatment for that disease. But we all recognize, whether you're a healthcare practitioner, whether you're a scientist, whether you're a business person, right or whatever occupation you realize that prevention, right the old ounce, prevention worth a pound of cure, right is how can we use something like Artificial Intelligence to develop preventive sorts of strategies that we are able to predict with time, right that's why we don't have preventive treatment approach right, we can't do a traditional clinical trial and say, did we prevent type two diabetes in an 18 year old? Well, we can't do that on a timescale that is reasonable, okay. And then the other part of that is why focus on botanicals? Is because, for the most part and there are exceptions I want to be very clear, I don't want to paint the picture that botanicals are all safe, you should just take botanicals dietary supplements and you'll be safe, right there are exceptions, but for the most part botanicals, natural products are in fact safe and have undergone testing, human testing for thousands of years, right. So how do we connect those dots? A preventive strategy with existing extent botanicals to really develop a healthcare system that becomes preventive centric as opposed to treatment centric. If I could wave a magic wand, that's the vision that I would figure out how we could achieve, right and I do think with guys like Rangan and Chris and folks like yourself, Eng Lim, that that's possible. Maybe it's in my lifetime I got 50 years to go to get to my grandfather's age, but you never know, right? >> You bring really, up two really good points there Ryan, it's really a systems approach, right understanding that things aren't just linear, right? And as you go through it, there's no impact to anything else, right taking that systems approach to understand every aspect of how things are being impacted. And then number two was really kind of the downstream, really we've been discussing the drug discovery process a lot and kind of the kind of preclinical in vitro studies and in vivo models, but once you get to the clinical trial there are many drugs that just fail, just fail miserably and the botanicals, right known to be safe, right, in many instances you can have a much higher success rate and that would be really interesting to see, you know, more of at least growing in the market. >> Well, these are very visionary statements from each of you, especially Dr. Yates, right, prevention better than cure, right, being proactive better than being reactive. Reactive is important, but we also need to focus on being proactive. Yes. Well, thank you very much, right this has been a brilliant panel with brilliant panelists, Dr. Ryan Yates, Dr. Rangan Sukumar and Chris Davidson. Thank you very much for joining us on this panel and highly illuminating conversation. Yeah. All for the future of drug discovery, that includes botanicals. Thank you very much. >> Thank you. >> Thank you.

>> Announcer: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Hi, I'm Stuart Miniman and welcome to this episode of CUBE conversations. I'm here from our Boston area studio. Happy to welcome to the program, Doug Matthews. He's the vice president of product management with Veritas coming to us from Atlanta. Doug, thanks so much for joining us. Nice to see you. >> Hey, great to see you Stuart and thanks for having me today. >> Yeah, so Doug obviously, 2020, there's a lot of change going on, globally, a lot of things happening financially, but one of the ongoing changes that we've been watching and has had huge ripple effects, is of course the impact on cloud. So why don't you bring us in a little bit. Tell us, what you work on, and how cloud has been impacting, what's happening with the data protection or resiliency in your world? >> Sure, so, Veritas Technologies is a long brand of focus on data protection. And we are highly focused on protecting data regardless of where it lives, whether it lives on a customer's premise or whether it lives in a cloud, public cloud architecture, or even in a cloud application. So, for us, this has been a transformational change as more and more people begin to adopt cloud services as the work from home trend starts and we're seeing them much higher emergence of ransomware. >> Yeah, so cloud of course, it is a unevenly distributed if you look at, if look at a countries, if you look at industries, >> Right. >> I'm wondering what you're hearing from customers, what's kind of the 2020 snapshot of where we are with the overall cloud wave. >> Sure, yeah. What we're seeing is a much more rapid adoption of cloud services as businesses and organizations begin to wrestle with the fact that they can't bring people into the office. So the work from home trend, the access to resources needs to be delivered through the cloud applications, even data centers. We're now beginning to see you some supply chain hiccups that are causing the supply chain fulfillment of server orders beginning to slow down. So customers are beginning to think more broadly about cloud gives you agility, operational ability to react to change. So people are accelerating their adoption of cloud resources because they're almost being forced to. >> Yeah, is there anything specific you're seeing are you getting any data maybe with coronavirus as to what service is in the cloud and what impact that's having on your customers? >> Yeah, so dramatic change, right. So for example, Azure Cloud Services are up something like 775%, which is just astounding number, VDI, Virtual Desktops up over 300%, and just massive of these cloud resources is just a continuing component trim. >> Yeah, and how about from a data protection standpoint and security. Obviously, we've seen that the malicious attacks have increased, unfortunately, and when you have more people outside of the enterprise walls itself, there's more things we need to make sure that our data is secure. >> Yeah, absolutely. And we have without a doubt seen a rise in ransomware attacks and malware attacks. What's interesting to note is increasingly the consumer is placing the blame for these attacks, less on the perpetrators and more on the organization and business leaders. For example, over 40% of consumers actually hold the business leader responsible where ransomware attack that their business suffers And (indistinct) percent would actually say that they would stop buying from an organization that suffers from a malware or has been a victim of an attack. So the mindset here is no longer place blame on the perpetrators, but on the business leader and owner that didn't protect their data in such a way that kept the user from being exposed. >> Yeah, Doug, why don't you bring us inside and explain how Veritas is helping in these environments to protect our data? >> Yeah, so I think the first thing is as a business leader begins to think about their cloud contract, they need to understand their SLAs and how that maps to what that cloud provider is going to provide for them. We actually found, recently, we produced a report called the "Truth in Cloud Report" and in that report, we talked to cloud architects and business leaders over 1600 of them that respond, and one of the things that we found pretty interesting is that 85% of the respondents said that the cloud service provider is responsible for protecting their data, but that's completely disconnected from the actual fact that over 53% or so of those that responded actually had an SLA that was higher than their cloud service provider would provide. So they believe it's supposed to be done by the cloud provider, but it isn't being done by the cloud provider to meet their needs. So people really need to think about and analyze who's protecting their data and how they're protected when they move into that cloud architecture. >> Yeah, I have to say I'm a little surprised to hear those results, the drum beat that I've heard from the security industry for the last couple of years has been about the shared responsibility model, there have been some rather public and highly visible failures where say somebody made a false assumption that was something would be turned on and the cloud service providers have come back and said, "Hey, you all, if there's these things you need to do and just because there's a lock on the door, if you don't lock it, we're not responsible for it". It is kind of the analogy I use. Shouldn't we, by 2020 now, where cloud is not new. I would have thought that we would have gotten through some of these rather basic understanding of who's responsible for what and ultimately who needs to answer for these things. >> Yeah, I think we're still in that adoption life cycle and I think there was the... We mapped this as a hype cycle of our own... We're people right in the adoption of cloud and we believe that classically cloud architects, probably 20 to 25% of organizations, have actually fully adopted cloud at this point and are aggressively adopting cloud, but there is such a rush now to get in from these business leaders and architects, who haven't really you've taken the time to frame and understand things that they're now being pulled along in this journey and rediscovering this thing. So we have to keep that drum beat up as some of the cloud laggers or more mainstream technology adopters are beginning to adopt cloud 'cause they haven't stayed aware. I completely agree with you. We've been talking about the shared responsibility model for a long time, but these survey results showed that it's still a problem. >> Doug, you make a great point. You talk about companies have had to compress their cycles and while normally they would have been able to really plan things, walk through what they were going to do, they're often rushing into things a little bit more. So what advice would you give other companies that are now been dipping their toe, but jumping into cloud or they need to accelerate what they're doing, what advice would you make sure that people don't get in a little over their skis or do something that they're going to regret? >> Sure, so the first thing I would say is, have a recovery plan and make sure you rehearse it. Again, back to the blame here is falling on business leaders, so don't get caught by it, make sure that you understand your recovery plan, make sure that you rehearse it and that it works. The second thing is, I would absolutely read that fine print of your contract and make sure that your required SLAs match up with what your cloud services provider provides, or you need to adapt technology that helps you to adjust to make sure that you achieve that SLA. And then the final thing as you're doing all this, so many people look at cloud for cost optimization as an outcome, make sure you don't overpay because the there are various levels of cloud storage, cloud storage is extremely expensive, cloud resources are expensive. Typically people think about the actual host itself or the instance itself, make sure that you think about the storage as well. So use things like deduplication or lower tiers of storage to optimize your cost efficiency. >> All right, so Doug as we mentioned earlier in the discussion Veritas has been around for awhile really well understood how you help customers, help connect us as to what you're doing for the cloud specifically. >> Sure, so specifically for cloud, let's focus on an upcoming release. I think most people that are probably watching this are familiar with our product called NetBackup, it's the enterprise leader in data protection. NetBackup is designed to solve the data protection challenges across all infrastructure whether it's your typical on premise infrastructure or new cloud architectures. So in these new cloud architectures, we've done things to make sure that you efficiently utilize cloud storage. So we do things like deduplication, we also control network bandwidth and make sure that you minimize rather your impact on network bandwidth. So you've minimize your overall cost requirements associated with cloud or data protection. The other thing that we're doing in this next release, which I think is really exciting is, we're going to take our cloud point solution and our resiliency platform solution, these solutions are designed to help customers, efficiently recover in cloud as well as do it in a very quick and automated fashion. And we're going to bake those into our NetBackup product. So the NetBackup consumer will automatically have access to these two new technologies that we've been developing for the last several years. So that's really exciting for us to be including those with our NetBackup product. >> All right, and Doug, when we talk about cloud, is this supported across any cloud or there are specific integrations that we should understand or just where does this fit in the entire, on a multicloud ecosystem? >> Yeah, so the one other thing, again, about NetBackup being a platform, it support over 1400 different data sources, over 800 different data targets, and that includes over 60 cloud providers, so it supports us this broad ecosystem of cloud architecture but where that makes sense, we always go deep. So we go deep with your traditional cloud providers, like AWS or Azure and provide that deeper level capability for those those cloud providers. >> All right, great. What else should we know about what's new from Veratis's cloud offering? >> Yeah, I think when we build our cloud solutions, we focus on a four stage lifecycle of a customer. For example, we realized that customer wants to migrate the cloud, they want to protect their resources in cloud, they want to be able to recover when the time comes and then optimize their cloud footprint. So we tend to focus in those four pillars to achieve success for our customers. >> Yeah, a question on that, I think about moving to the cloud, there's a lot of discussion about how do I modernize my environment and often it's I move to the cloud, but then how do I really become cloud native, if you will. So I'm making updates and I'm making changes. If I think about backup traditionally, it was, let me get something, let me put it in place and I'm going to run it that way for years. So how does Veritas make sure that as I'm modernizing as I'm making changes that my data is still going to be protected no matter where I am along that journey. >> Sure, so I think as customers are migrating to and adopting cloud, their first stage on the train or their first station that they come to on the train is that lift and shift approach. We're going to take everything from on premise and we're going to move it to the cloud. So we have technologies that will help our customer do that with automated failback, so they can set up the replication solution, push a button now they're up and running in cloud, hey, it didn't work, push the button and they're back down in their on premise environment, adjust and do it when it makes sense and they're ready to make it make it work. So we have a fairly robust set of technologies that can help in that lift and shift process, lift and shift process. The other thing that we provide is for those infrastructure as code guys, the guys that are further out that are thinking, how do I natively build cloud based solutions? We have a very full suite of APIs so that the customer can implement their infrastructure as code requirements right there through that Swagger interface that you would expect and deploy infrastructure as code environments in cloud, utilizing our enterprise class API. So we're purpose built to be able to help customers get the cloud, and then also support those cloud applications that are built there natively. >> Yeah, Doug, I'm wondering, do you have either a customer example, maybe anonymized you can share, or just any general cloud learnings about where your customers are and how Veritas is helping them? >> Sure, so one of the first things that we see customers try to accomplish is the move of their backup storage infrastructure into a longterm storage in cloud. So they might use it as a replacement for tape, they might use it as a replacement for disk, and they want to live in the cloud environment. So we have a capability, we call it CloudCatalyst that moves data very efficiently from on prem into the cloud, keeps it deduplicated, optimizes it for wide area network transmit, and really efficiently moves that data in the cloud, and then really what's important is once it gets in the cloud, it doesn't touch that data. So we have a large customer who's got over a couple of petabytes of data in Europe that wanted to make that migration to cloud, they were using another provider at the time, so we came in and we were actually able to save them over 98% of their overall operational cost associated with moving and migrating that data just based on this one capability. So that's a key element, right. As people are moving that data to cloud, make sure that it stays efficient, optimized, deduplicated in stored efficient. >> All right, Doug, I'll give you the final word. >> Yeah, I think my warning for customers is to make sure that they are well-protected with their data state in cloud. Understand what your cloud service provider provides, make sure that your SLOs, your service level objectives are going to be met by the technologies that you deploy in order to solve your cloud problems. And then think about things holistically, think about it first from the migration, then how you protect it, then once you get there, what do you do to recover, make you test that. And then once you've got everything kind of thought through and ready to implement, make sure that you've optimized it to be efficient in it's cost utilization and in it's operations. >> All right, well, Doug Matthews, thank you so much for the updates, we really appreciate you sharing us some important tips for customers as they go along their cloud journey. >> Thank you so much, Stuart. >> All right, I'm Stuart Miniman and thank you for watching theCUBE. (gentle music)

>> Narrator: From around the global its theCUBE, covering HPE Discover Virtual Experience, brought to you by HPE. >> Hi, I'm Stu Miniman and this is theCUBE's coverage of HPE, discover the virtual experience for 2020, getting to talk to Hp executives, their partners, the ecosystem, where they are around the globe, this session we're going to be digging in about artificial intelligence, obviously a super important topic these days. And to help me do that, I've got two guests from Nvidia, sitting in the window next to me, we have Paresh Kharya, he's director of product marketing and sitting next to him in the virtual environment is Kevin Deierling, who is this senior vice president of marketing as I mentioned both with Nvidia. Thank you both so much for joining us. >> Thank you, so great to be here. >> Great to be here. >> All right, so Paresh when you set the stage for us? AI, obviously, one of those mega trends to talk about but just, give us the stages, where Nvidia sits, where the market is, and your customers today, that they think about AI. >> Yeah, so we are basically witnessing a massive changes that are happening across every industry. And it's basically the confluence of three things. One is of course, AI, the second is 5G and IOT, and the third is the ability to process all of the data that we have, that's now possible. For AI we are now seeing really advanced models, from computer vision, to understanding natural language, to the ability to speak in conversational terms. In terms of IOT and 5G, there are billions of devices that are sensing and inferring information. And now we have the ability to act, make decisions in various industries, and finally all of the processing capabilities that we have today, at the data center, and in the cloud, as well as at the edge with the GPUs as well as advanced networking that's available, we can now make sense all of this data to help industrial transformation. >> Yeah, Kevin, you know it's interesting when you look at some of these waves of technology and we say, "Okay, there's a lot of new pieces here." You talk about 5G, it's the next generation but architecturally some of these things remind us of the past. So when I look at some of these architectures, I think about, what we've done for high performance computing for a long time, obviously, you know, Mellanox, where you came from through NVIDIA's acquisition, strong play in that environment. So, maybe give us a little bit compare, contrast, what's the same, and what's different about this highly distributed, edge compute AI, IOT environment and what's the same with what we were doing with HPC in the past. >> Yeah, so we've--Mellanox has now been a part of Nvidia for a little over a month and it's great to be part of that. We were both focused on accelerated computing and high performance computing. And to do that, what it means is the scale and the type of problems that we're trying to solve are just simply too large to fit into a single computer. So if that's the case, then you connect a lot of computers. And Jensen talked about this recently at the GTC keynote where he said that the new unit computing, it's really the data center. So it's no longer the box that sits on your desk or even in Iraq, it's the entire data center because that's the scale of the types of problems that we're solving. And so the notion of scale up and scale out, the network becomes really, really critical. And we're doing high-performance networking for a long time. When you move to the edge, instead of having, a single data center with 10,000 computers, you have 10,000 data centers, each of which as a small number of servers that is processing all of that information that's coming in. But in a sense, the problems are very, very similar, whether you're at the edge or you're doing massive HPC, scientific computing or cloud computing. And so we're excited to be part of bringing together the AI and the networking because they are really optimizing at the data center scale across the entire stack. >> All right, so it's interesting. You mentioned, Nvidia CEO, Jensen. I believe if I saw right in there, he actually could, wrote a term which I had not run across, it was the data processing unit or DPU in that, data center, as you talked about. Help us wrap our heads around this a little bit. I know my CPU, when I think about GPUs, I obviously think of Nvidia. TPUs, in the cloud and everything we're doing. So, what is DPUs? Is this just some new AI thing or, is this kind of a new architectural model? >> Yeah. I think what Jensen highlighted is that there's three key elements of this accelerated disaggregated infrastructure that the data center has becoming. And so that's the CPU, which is doing traditional single threaded workloads but for all of the accelerated workloads, you need the GPU. And that does massive parallelism deals with massive amounts of data, but to get that data into the GPU and also into the CPU, you need really an intelligent data processing because the scale and scope of GPUs and CPUs today, these are not single core entities. These are hundreds or even thousands of cores in a big system. And you need to steer the traffic exactly to the right place. You need to do it securely. You need to do it virtualized. You need to do it with containers and to do all of that, you need a programmable data processing unit. So we have something called our BlueField, which combines our latest, greatest, 100 gig and 200 gig network connectivity with Arm processors and a whole bunch of accelerators for security, for virtualization, for storage. And all of those things then feed these giant parallel engines which are the GPU. And of course the CPU, which is really the workload at the application layer for non-accelerated outs. >> Great, so Paresh, Kevin talked about, needing similar types of services, wherever the data is. I was wondering if you could really help expand for us a little bit, the implications of it AI at the edge. >> Sure, yeah, so AI is basically not just one workload. AI is many different types of models and AI also means training as well as inferences, which are very different workloads or AI printing, for example, we are seeing the models growing exponentially, think of any AI model, like a brain of a computer or like a brain, solving a particular use case a for simple models like computer vision, we have models that are smaller, bugs have computer vision but advanced models like natural language processing, they require larger brains or larger models, so on one hand we are seeing the size of the AI models increasing tremendously and in order to train these models, you need to look at computing at the scale of data center, many processors, many different servers working together to train a single model, on the other hand because of these AI models, they are so accurate today from understanding languages to speaking languages, to providing the right recommendations whether it's for products or for content that you may want to consume or advertisements and so on. These models are so effective and efficient that they are being powered by AI today. These applications are being powered by AI and each application requires a small amount of acceleration, so you need the ability to scale out or, and support many different applications. So with our newly launched MPR architecture, just couple of weeks to go that Jensen announced, in the virtual keynote for the first time, we are now able to provide both, scale up and scale out both training data analytics as well as imprints on the single architecture and that's very exciting. >> Yeah, so look at that. The other thing that's interesting is you're talking about at the edge and scale out versus scale up, the networking is critical for both of those. And there's a lot of different workloads. And as Paresh was describing, you've got different workloads that require different amounts of GPU or storage or networking. And so part of that vision of this data center as the computer is that, the DPU lets you scale independently, everything. So you can compose, you desegregate into DPUs and storage and CPUs, and then you compose exactly the computer that you need on the fly container, right, to solve the problem that you're solving right now. So these new way of programming is programming the entire data center at once and you'll go grab all of it and it'll run for a few hundred milliseconds even and then it'll come back down and recompose itself onsite. And to do that, you need this very highly efficient networking infrastructure. And the good news is we're here at HPE Discover. We've got a great partner with HPE. You know, they have our M series switches that uses the Mellanox hundred gig and now even 200 and 400 gig ethernet switches, we have all of our adapters and they have great platforms. The Apollo platform for example, is break for HPC and they have other great platforms that we're looking at with the new telco that we're doing or 5G and accelerating that. >> Yeah, and on the edge computing side, there's the edge line set of products which are very interesting, the other sort of aspect that I wanted to touch upon, is the whole software stack that's needed for the edge. So edge is different in the sense that it's not centrally managed, the edge computing devices are distributed remote locations. And so managing the workflow of running and updating software on it is important and needs to be done in a very secure manner. The second thing that's, that's very different again, for the edges, these devices are going to require connectivity. As Kevin was pointing out, the importance of networking so we also announced, a couple of weeks ago at our GTC, our EGX product that combines the Mellanox NIC and our GPUs into a single a processor, Mellanox NIC provides a fast connectivity, security, as well as the encryption and decryption capabilities, GPUs provide acceleration to run the advanced DI models, that are required for applications at the edge. >> Okay, and if I understood that, right. So, you've got these throughout the HPE the product line, HPE's got long history of making, flexible configurations, I remember when they first came out with a Blade server it was, different form factors, different connectivity options, they pushed heavily into composable infrastructure. So it sounds like this is just a kind of extending, you know, what HP has been doing for a couple of decades. >> Yeah, I think HP is a great partner there and these new platforms, the EGX, for example that was just announced, a great workload there is a 5G telco. So we'll be working with our friends at HPE to take that to market as well. And, you know, really, there's a lot of different workloads and they've got a great portfolio of products across the spectrum from regular servers. And 1U, 2U, and then all the way up to their big Apollo platform. >> Well I'm glad you brought up telco, I'm curious, are there any specific, applications or workloads that, where the low hanging fruit or the kind of the first targets that you use for AI acceleration? >> Yeah, so you know, the 5G workload is just awesome. We're introduced with the EGX, a new platform called Ariel which is a programming framework and there were lots of partners there that were part of that, including, folks like Ericsson. And the idea there is that you have a software defined hardware accelerated radio area network, so a cloud RAM and it really has all of the right attributes of the cloud and what's nice there is now you can change on the fly, the algorithms that you're using for the baseband codex without having to go climb a radio tower and change the actual physical infrastructure. So that's a critical part. Our role in that, on the networking side, we introduced the technology that's part of EGX then are connected, It's like the DX adapter, it's called 5T for 5G. And one of the things that happens is you need this time triggered transport or a telco technology. That's the 5T's for 5G. And the reason is because you're doing distributed baseband unit, distributed radio processing and the timing between each of those server nodes needs to be super precise, 20 nanosecond. It's something that simply can't be done in software. And so we did that in hardware. So instead of having an expensive FPGA, I try to synchronize all of these boxes together. We put it into our NIC and now we put that into industry standard servers HP has some fantastic servers. And then with the EGX platform, with that we can build, really scale out software to client cloud RAM. >> Awesome, Paresh, anything else on the application side you'd like to add in just about what Kevin spoke about. >> Oh yeah, so from application perspective, every industry has applications that touch on edge. If you take a look at the retail, for example, there is, you know, all the way from supply chain to inventory management, to keeping the right stock units in the shelves, making sure there is a there is no slippage or shrinkage. So to telecom, to healthcare, we are re-looking at constantly monitoring patients and taking actions for the best outcomes to manufacturing. We are looking to automate production detecting failures much early on in the production cycle and so on every industry has different applications but they all use AI. They can all leverage the computing capabilities and high-speed networking at the edge to transform their business processes. >> All right, well, it's interesting almost every time we've talked about AI, networking has come up. So, you know, Kevin, I think that probably ease up a little bit why, Nvidia, spent around $7 billion for the acquisition of Mellanox and not only was it the Mellanox acquisition, Cumulus Networks, very known in the network space for software defined really, operating system for networking but give us strategically, does this change the direction of Nvidia, how should we be thinking about Nvidia in the overall network? >> Yeah, I think the way to think about it is going back to that data center as the computer. And if you're thinking about the data center as computer then networking becomes the back plane, if you will of that data center computer and having a high performance network is really critical. And Mellanox has been a leader in that for 20 years now with our InfiniBand and our Ethernet product. But beyond that, you need a programmatic interface because one of the things that's really important in the cloud is that everything is software defined and it's containerized now and there is no better company in the world then Cumulus, really the pioneer and building Cumulus clinics, taking the Linux operating system and running that on multiple homes. So not just hardware from Mellanox but hardware from other people as well. And so that whole notion of an open networking platform more committed to, you need to support that and now you have a programmatic interface that you can drop containers on top of, Cumulus has been the leader in the Linux FRR, it's Free Range Routing, which is the core routing algorithm. And that really is at the heart of other open source network operating systems like Sonic and DENT so we see a lot of synergy here, all the analytics that Cumulus is bringing to bear with NetQ. So it's really great that they're going to be part here of the Nvidia team. >> Excellent, well thank you both much. Want to give you the final word, what should they do, HPE customers in their ecosystem know about the Nvidia and HPE partnership? >> Yeah, so I'll start you know, I think HPE has been a longtime partner and a customer of ours. If you have accelerated workloads, you need to connect those together. The HPE server portfolio is an ideal place. We can combine some of the work we're doing with our new amp years and existing GPUs and then also to connect those together with the M series, which is their internet switches that are based on our spectrum switch platforms and then all of the HPC related activities on InfiniBand, they're a great partner there. And so all of that, pulling it together, and now as at the edge, as edge becomes more and more important, security becomes more and more important and you have to go to this zero trust model, if you plug in a camera that's somebody has at the edge, even if it's on a car, you can't trust it. So everything has to become, validated authenticated, all the data needs to be encrypted. And so they're going to be a great partner because they've been a leader and building the most secure platforms in the world. >> Yeah and on the data center, server, portfolio side, we really work very closely with HP on various different lines of products and really fantastic servers from the Apollo line of a scale up servers to synergy and ProLiant line, as well as the Edgeline for the edge and on the super computing side with the pre side of things. So we really work to the fullest spectram of solutions with HP. We also work on the software side, wehere a lot of these servers, are also certified to run a full stack under a program that we call NGC-Ready so customers get phenomenal value right off the bat, they're guaranteed, to have accelerated workloads work well when they choose these servers. >> Awesome, well, thank you both for giving us the updates, lots happening, obviously in the AI space. Appreciate all the updates. >> Thanks Stu, great to talk to you, stay well. >> Thanks Stu, take care. >> All right, stay with us for lots more from HPE Discover Virtual Experience 2020. I'm Stu Miniman and thank you for watching theCUBE. (bright upbeat music)

(upbeat instrumental music) >> Narrator: Live from San Francisco, Celebrating 10 years of high tech coverage, it's theCUBE. Covering VMworld 2019. (upbeat instrumental music) Brought to you by VMware and its ecosystem partners. Hello and welcome back everyone. theCUBE's Live coverage here in San Francisco, California. I'm John Furrier, Dave Vellante, VMworld 2019 coverage. Dave, 10 years of Cube coverage, Yip! we started out 10 years ago. VMworld is the last show standing. Our next guest is Todd Forsythe, CMO of Veritas. Great to see you, first time on theCUBE. Thanks Todd. It is inaugural. (John laughs) Aafter 25 years in the industry, it's crazy. With your talent, I think we're going to have a good segment here. I'm sure we will. Very entertaining. No, seriously we've known each other, we were on an advisory board together. You're a prolific marketer, you do a lot of great things. You're progressive, you try new things with startups, but also you got to run a big operation. >> Todd: That's right. MarTech stacks, you like to look at platforms. This is a re-platforming of the internet we're seeing with Cloud 2.0, and I want to get your thoughts on this, because you got a unique perspective at Veritas, you know, an older brand modernized in real time. That's right. New products refresh in a massively changing growth, still growth market. It's a data business. Absolutely. That's right, a 100%. So what's your take on this? As you look at the landscape, you've got the modern brand, you got to take it out there, new products. You know it's interesting, I had a really fascinating conversation yesterday with a customer, and the customer said, "You know, I was walking through the expo hall, "and I saw Amazon, I saw Microsoft, "I saw IBM, I saw Dell Technologies, "I saw Kubernetes, I saw Pure, I saw Nutanix, "I thought I was in my own data center." And it's interesting, I think about our business, and in our business, data doesn't care. Like you know data doesn't care if you're running a modern architecture. Data doesn't care if you're running Legacy. So what we're really focused on is helping companies manage data in highly complex, and extremely demanding environments regardless of their infrastructure. And Cloud 2.0 speaks to the complexity of that, because you know, these, and we were talking earlier with VMware about these categories that used to exist, these Gartner Magic Quadrants. You know, you can't put something that's not a silo in a silo, you're horizontally disrupting. And data does that, data has to move around and it's got to move everywhere. So there's no more silo boxes of categories. A 100% agree, you know it's interesting, we launched Enterprise Data Services earlier this year, and that was the precise reason why, because we've relooked at what data protection is. Data protection is no longer backing up your data from a cloud to a cloud from your on Prime, it's a much broader category. It covers how your data becomes available, how resilient you are, understanding where your data is, how it's categorized so you can respond to ransomware attacks, manage regulations around the world. So our view of data protection is a platform that is horizontal and cuts across. Well you guys, I mean the heritage of Veritas is the original data management company, right? Yeah. With no hardware agenda, and so my question for you, Todd, is what attracted you to Veritas? Softball question, so the most amazing customers any company could possibly imagine, Global 2000, the top telecommunications companies, the top banks, top stock exchanges. Secondly a product strategy that's really zoned in, back to your point about this, a platform that cuts across all of these diverse technologies and solves problems for customers that abstracts them from the complex environments that they're in so they could focus on outcomes, and Greg has done an amazing job recruiting a top notch leadership team. So it was really great product, good leaders. Okay now, follow up is you guys, you know, number one, top anyway, right and with Gartner Magic Quadrant, everybody wants a piece of your hide, (chuckles) the whole industry is coming at you. So, what's the sort of messaging strategy to keep top spot from both outward facing and also product development? Sure, sure. So we look at two types of competitors. Competitors that are offering point solutions, predominately playing in the mid-market, and when you're a large financial institution, and you have a highly complex environment, you're in a multi-cloud world, and you can't afford to have a siloed backup data. So you need to understand how your data is classified, where it's stored. So if you're responding to ransomware, and that ransomware attack is targeted to a specific server, you need to know if you have PII there, or if you have cat pictures there. If you have cat pictures there, then, (chuckles). >> John: Let 'em have it. Let 'em have it, exactly. (John laughs) So our platform cuts across protection, availability, and insights, which categorizes your data. So the data gets categorized in NetBackup, extends to the analytics platform, so you know where your data is, and you could take action on your data. The hard question of the day, instead of a softball I'll give you a hard one, you got to refresh the brand of Veritas has got a lot of pros and cons. The pros are, you know, well-known, a lot of customers, I got a customer question later, but the brand is important, because you have the new modern platform products, platform and products. Yeah, yeah. You got to get the name, Veritas has old meaning. You have a lot of older customers, you have legacy customers. How are you going to go out there and refresh? Is there any new plans there? We have a ton of plans. You know, we have the product, we have the customers. The product, the platform product is amazing. We are a quiet company, so we need to be noisier in the marketplace, and we need to insert ourselves into relevant conversations that are top of mind with CEOs and CIOs, whether it's ransomware. If you look at all of the ransomware attacks, It's a huge opportunity I read like two weeks ago in the State of Texas there were 10, 15 municipalities that were attacked. At the same time. At the same time! and we have a solution that can help customers recover from ransomware, so we have to insert ourselves in those dialogues because we have a very, very specific point of view that can help customers. Well but to John's point, right? Everybody that you compete with will say, we have a solution that, you know, helps solve ransomware. So, how do you separate from the pack? Like I said, everybody's trying to take pick you off. You know, we want a piece of that install base, right? 'Cause you got to keep the install base, and you got to keep growing, right? I'll lay down the gauntlet. I would love any competitor to showcase how they can support 500 workloads, a 150 storage targets, 60 cloud providers, at enterprise scale with a high degree of reliability. Our differentiator is we can cut across these very complex, very demanding IT environments, at scale. I want to get your thoughts on the customer journey question, because I think, you know, you mentioned the customer base, we've been following what you guys do. I mean I ran, I was in Bahrain for a regional Amazon event I was covering in the Middle East, and in the exhibit was this Veritas, and they recognized, hey, there's theCUBE guy. I was like, hey, thanks for watching. But seriously, you guys are everywhere. You got huge customers, but you probably have a lot of customers that are trying to go from here to there, VMware was talking almost specifically around, you know, you got the enterprise scale world, and they want that cloud Nirvana, and then there's that missing middle in between. So, you probably have a lot of transformational stories. What is the patterns of customer profile that you see? Some of them making the journey? Some of them are having a hard time? What's the state of the mind of the customer that you guys have? Well, we are definitely seeing a hybrid, multi-cloud world as you've heard here this week. 52% Of our customers are running in a hybrid cloud environment, and we have a core relationship with their legacy infrastructure, and our customers are asking our help to extend their data protection, and their NetBackup environment into the cloud, to backup the cloud, and across new modern workloads. So our customers are pulling us into their environments to do more. And that's cloud and hybrid basically. Cloud and hybrid. Public cloud and on premises. And our customers are also realizing that they're responsible for backing up their own data in the cloud. There's this misperception in the industry that if I move to a cloud provider, the cloud provider will manage my data, when in actuality you are still responsible for your data. You know, Amazon with security has a shared responsibility model. They say, okay, we protect the EC2, the infrastructure for S3, et cetera. You're responsible for pretty much everything else. And I think that you could draft off that message. Yeah, yeah! You guys too, a couple of years ago, had a great event call Veritas Vision where everybody came in, and then you changed that. Now you sort of go to where the customers are, and I'm wondering, how's that working out? It predated you. Yeah! Yeah, yeah, yeah, yeah, yeah! So I won't ask you why that decision was made, but you know, how's it working out? I mean, a company like yours, there was like four, 5,000 people there, it was a really good event. So, a great question, and a highly relevant question, because we're just about to launch our series. So, you know, having run large, large, large user conferences, and you look at distribution of your customers and, you know, you typically find that 80% of your customers are coming from the US. You look at our customer base, global international customers. We have a high percentage of customers that are outside of the U.S. So, our strategy is let's take our user conference, let's take our message, let's take our value proposition to the customer. So, we are kicking off next month an entire series around the world, Germany, Paris, Rome, Seoul, Bali, Singapore, Melbourne, our vision series, where it's our anti-user conference. We're taking content directly to our customers. Is this regional or are those cities based? How is that segment? City based. So it's like an Amazon Summit kind of thing you go to? Yeah, yep. Okay so as a follow-up. So, as a seasoned pro in this space, why either, or, why not do both? I mean there's a budget obviously is one thing, it's expensive to run these events, I get it, but. I would prefer to put more money to where the customer is at. The field, kind of. Yeah, into the fields, you know, one of the life lessons of being a marketer is go to where the customer is. Don't try to get the customer to come to you. Well, your head of sales will love that message, you're going well. (Todd laughs) So our strategy is to go where the customer is. Yeah, and that does help sales actually. So, while you're on that point, you're a very progressive marketer, for the folks that don't know you, I'll share with them that, you know, you like to try things, and you love start-ups, and you love to promote new things. The marketing stack, I've said on theCUBE, and we'd love to have you challenge us if you want, love to debate it, I said, the MarTech Stack just didn't pan out. I mean, it worked? No, no, it didn't, no! Did it work? Is it evolving? Is it siloed? Is the cloud changing the MarTech Stack? So again, pretty aggressive statement, but my point is, email marketing was great for that generation, still is. There's new organic flows, maybe I'm biased, but I'd love to get your thoughts. How is the marketing tech world evolving with cloud computing? So, I'm going to say something provocative. >> John: Okay, all right, here we go. I think the CRM industry has gotten B2B marketing wrong. What I mean by that is you look at most CRM capabilities in B2B and they're focused on an individual. They're focused on a lead, they're focused on nurturing an individual, but if you look at our customers and enterprise, individuals don't buy, buying groups, committees, and accounts buy. So where we're focused is looking at accounts, and understanding account company based behavior that shows buying intent and triggers, which then initiate our marketing. So it's not built around a lead, it's built around-- >> John: So account based marketing? Account based marketing, but account based insight and intelligence around, is there a project or buying opportunity? And you know our good friends at Manigo, that's what they do, which is AI driven, trigger-based marketing. And that's where I think the industry is going. And what's your thoughts on organic marketing, because one of the things that's hot, is we live this world with theCUBE, and we've been kind of pioneering this model where co-creating content together and pushing it out into these digital streams is an organic process. It's technically earned media and PR parlance, but we're seeing the evolution of the CMO-like action around storytelling, right? And so, like community based storytelling, it's an organic function, it's hard to control. You can't just buy it, it's got to be kind of nurtured or enabled. That's right. What's your view on that? Because this is an emerging trend we're seeing, VM were just reorganizing a whole storytelling integrated group of PR pros, that are acting like the marketing, in their marketing. Well you know, one of the most active, customer segments we have is our VOX Community, and if you think to your point about co-creation of content in collaboration, our VOX Community collaborates on solving problems that customers have, they call that-- >> John: Can you take a minute to explain, what is VOX Community to us? VOX is a community of our technical users, where they help each other share best practices and solve problems. >> Dave: A lot of how-to? A lot of how-to-- Not Vox Media. Not Vox Media, correct. Just need to make sure to get that out there. Forums, there's videos. Is this your community, or is it third-party? Veritas. Okay, Veritas. It's a Veritas community, yeah. And then to your other point, John, the marketing world has changed. We've quickly moved into a world where we now have an anonymous relationship with our customer, with email, with direct mail. Yeah, we're always driving to registration to capture a name, that world is long gone. A Facebook show that's been weaponized, so you know. Yeah, that's right. It's the data business, at the end of the day. The user experience is horrible, right? Everybody hates that, and so yeah, there are other ways now you can use data, you can infer. Yeah, that's right, exactly. You can read the tea leaves, and probably make a pretty high prediction, or highly accurate prediction. What is the most under reported trend that you think marketers should look at in terms of capabilities that are working out in the field for you? I would say the ability to leverage predicative analytics, call it AI or machine learning, understand what's happening at an account, and whether there's a buying trigger. I think accessing that information, learning from that information in terms of how should you initiate a selling motion, and then enabling the sales force with that intelligence, I think is a wide open territory. All right, we got a-- So a couple of other things. If I can? Yeah! Just to get it in. So you guys made a big platform enhancements a couple of years ago, and then a big eight dot, whatever it was, eight dot something, two, three, five. I think it was 8.2. Customer momentum, can you update us on that? Maybe even customer examples, and then I've got a partner question for you. Yeah, so I talked about the value of the platform, and we'll take Renault as an example. So Renault, a NetBackup customer, Renault wanted to make their virtualized SAP environment highly available, and they looked at a variety of different solutions, and they looked at some solutions that were homegrown and others, and they realized just extending the Veritas platform was faster time to market, 60% cost savings. So, there's a perfect example of a customer leveraging our platform play. And a couple partner questions. So, you know, we're here at VMworld, so your VMware partnership obviously pretty important, and then we're at Pure Accelerate next month, you guys are there, you got a big presence there, I know you got a tight partnership with them. That's right. Give us the partner update. Partner update, so we have very solid relationships with Amazon, Microsoft, VMware, Google, Nutanix, Pure, and that's where we're really doubling down in terms of technology integration, joint go-to-market. >> Dave: Great. And the community site is vox.veritas.com, I just was checking it out. Thank you for the plug. There's a church one, there's a religious one, not to be confused with Vox Media, so just want to make sure everyone got that URL. We think community is super important. Thanks for coming on theCUBE Excellent! and sharing your insights. Thank you gentlemen. Thank you. Todd Forsythe, CMO of Veritas. More live coverage of VMworld after this short break. (upbeat dance music)

>> live from San Francisco celebrating 10 years of high tech coverage. It's the Cube covering Veum World 2019 brought to you by IBM wear and its ecosystem partners. >> Well, good afternoon. And welcome back to San Francisco. Where Mosconi north along with David Dante, John Wall's You're watching our coverage here. Live on the Cuba Veum world. 2019 days. I've been over on the other set. I know you've been busy on this side as well. Show going. All right for you >> so far. Yeah, A lot of action going on over here. We had a pact Hellsing on this morning, Michael Dell, with this VM wear hat, we get Sanjay Putin downtown later. >> Yeah, yeah. Good light up. And that lineup continues. Great. Use the CEO Veritas. >> Great to be here. Very John, >> actually, just outside the Veritas Meadow here. Sponsored the this area. This is the meadow set. That >> nice to be here? Yeah, I didn't know >> that. All right, just first off, just give me your your idea of the vibe here. What you are. You're feeling >> what? I think there's a tremendous amount of energy. It's been a lot of fun to be here Obviously VM was talking about this hybrid multi cloud world, and Veritas is 100% supportive of that vision. We work with all the major cloud service providers, you know, eight of us. Google. Microsoft is or we share thousands of customers with the M, where some of the biggest customers, the most complicated customers in the world, where we provide availability and protection and insights for those customers has always >> been the ethos of veritas. When you go back to the early days of Veritas, essentially, it was the storage management, you know, the no hardware agenda, the sort of independent storage company, but pure software. >> That sounds. You >> know, years ago there was no cloud, but there were different platforms, and so that that that that culture has really migrated now into this multi cloud work world. Your thoughts on that >> absolutely look, you know, I'll give an example of a customer that we worked with closely with VM wear on, and that is Renault. America's Renault is Ah, big joint venture. They've got a huge ASAP installation 8000 users 40 terabytes, Big Net backup customer. They also use their products in for a scale and V. R P for availability and D r. And they work with us because we are hardware agnostic. They looked at us against the other competitors, and we're hardware agnostic. And because of that where we came in its 60% lower TCO than those other providers. So we that hardware agnostic approach works really well. You were >> Just touch it on this great little bit when you said, You know whether Tiger, whether it's multi, whether it's private, whatever it is, you know we're here to provide solutions. The fact that this stuff is hard to figure out and really kind of boggle the mind a bit, it's very complex. Um, how much of an inhibitor is that? In terms of what you're hearing from clients and in terms of their progress and and their decision making >> well, let me explain where we sit. And we are the leader in enterprise data protection, availability and insights. We work with the largest, most complex, most high route, highly regulated and most demanding customers on the planet. 99 of the Fortune 100 are customers of Veritas. 10 of the top 10 tell coast 10 of the top 10 healthcare companies and 10 of the top 10 financial institutions. I spend about 50% of my time talking to these customers, so we learn a lot. And here the four big challenges they're facing first is the explosion of data. Data is just growing so fast, Gardner estimates will be 175 Zita bytes of data in 2025. If you cram that in, iPhones will take 2.6 trillion iPhones and go to the sun and back, right? It's an enormous amount of data. Second, they're worried about Ransomware. It's not a question off if you'll be attacked. It's when you'll be attacked. Look at what's happening in Texas right now with the 22 municipalities dealing with that. What you want in that case is a resilient infrastructure. You wanna be terrible to restore from a really good backup copy of data. Third, they want the hybrid multi cloud world, just like Pak Gil Singer has been talking about. That's what customers want, but they want to be able to protect their data wherever it is, make it highly available and get insights in the data wherever it's located. And then finally, they're dealing with this massive growth in government regulations around the world because of this concern about privacy. I was in Australia a few weeks ago and one of our customers she was telling me that she deals with 27 different regulatory environments. Another customer was saying the California Privacy Act will be the death of him. And he's based in St Louis, right? So our strategy is focused on taking away the complexity and helping the largest companies in the world deal with these challenges. And that's why we introduce the enterprise. Data Service is platform, and that's why we're here. VM world Talking >> about Greg. Let's unpack some of those, Asai said. Veritas kind of created a market way back when and now you see come full circle, you got multi cloud. You have a lot of new entrance talking about data management. That's it's always been your play, but you came to the king of the Hell's. Everybody wants a piece of your hide, so that's kind of interesting, But but data growth. So let's let's start there. So it used to be data was, ah, liability. Now it's becoming an asset. So what? What your customers saying about sort of data is something that needs to be managed, needs to be done cost effectively and efficiently versus getting more value on data. And what's Veritas is sort of perspective. >> They're really trying to get insights in their data. Okay. And, uh, that's why we acquired a company called Apt Are. So when I This is my second time of Veritas. I was here from 2003 to 2010 rejoined the company of 2018. I talked to a lot of customers. I've found that their infrastructure was so complex that storage infrastructure so complex the companies were having a hard time figuring out anything about their data. So they're having the hardest time just answering some fundamental questions that boards were asking. Boards are saying because of the ransomware threat. Is all our data protected? Is it backed up? Are all our applications backed up and protected and customers could not answer that question. On the other hand, they also were backing up some data 678 times wasting storage. What apt are does, and it's really amazing. I recommend seeing a demo of that. If you get a chance, it pulls information from Santa raise network file systems, virtual machines, uh, san networking and all data protection applications to get a complete picture of what's happening with your data. And that is one example off what customers really want. >> Okay, so then that kind of leads to the second point, which is ransomware now. Part of part of that is analytics and understanding what's going on in the system as well. So but it's a relatively new concept, right? And ransom. Where is the last couple of years? We've really started to see it escalate. How does Veritas help address that problem? And does apt our play a role there? >> Well, Veritas, it just helps it. Cos address that problem because veritas helps create a resilient infrastructure. Okay, the bad guys are going to get in spear. Phishing works. You know, you you are going to find some employees were gonna click on a link, and the malware is going to get in so all you can do to protect you ultimately have tohave a good backup copies so you can restore at scale and quickly. And so there's been a lot of focus from these large enterprises on restoring at scale very quickly after ransom or attack, it's you're not beholden. You can't be extorted by the ransom or >> the third piece was hybrid. And of course, that leads to a kind of hybrid multi cloud. Let's let's put that category out there now. I've been kind of skeptical on hybrid multi cloud from an application perspective in other words, the vision that you can run any app anywhere in the world without having a retest Rica pile. I've been skeptical that, but the one area that I'm not skeptical and the courage with is data protection because I think actually, you can have a consistent data protection model across your on Prem different on prams, different clouds, because you know you're partnering with all the different cloud cos you obviously have expertise in on premise. So so talk about your approach, their philosophy and maybe any offering. >> Well, this is really what sets us apart. We have been around for 25 years, 2000 patents. We protect everything. 500 different sources of data 150 different targets, 60 different cloud service providers, you know, we compete with two categories of players. We compete with the newcomers, and they only they will only protect your most current technology. They don't go back. We've been around for 25 years. We protect everything, right? We also can't compete with the conglomerates, Okay? In their case, they're not focused. They're trying to do everything. All we do is availability, protection and insights. And that's why we've been in Gardner M Q 13 times and where the market share leader also absolutely >> touch me. Someone Dave was saying about the application side of this. I mean, just your thoughts about, you know, the kinds of concerns the day raises. I mean, it is not alone in that respect. I mean, there are general concerns here, right about whether that that'll fly. What do you think? In terms, >> I think the vision is spot on and like, oh, visions, it takes a while to get to. But I think what VM wears done recently in the acquisition, there've been basically trying to make the control plane for compute okay, and their acquisition of carbon, black and pivotal add to that control plane we're gonna be We are the control plane for data protection. I mean, that's that's the way our customers rely on, >> but that makes sense to me. So I think I feel like the multi cloud vision is very aspirational today, and I think it's gonna be really hard to get there without homogeneous infrastructure. And that's why you see things like Outpost to see the Oracle has clouded customer. You've got Azure Stack. So and I think it's gonna be a multi vendor world. However I do think is it relates the data protection you can set a standard and safe. We were going to standardize on Veritas. So one of us So I think that it's it's achievable. So that was my point there. The last one was was regulations. Do you think GDP are will be a sort of a framework globally body of customers seeing there? >> Well, they're dealing with more than GDP are like I talked about that one customer, 27 different regulatory environments and the challenge there is. How do you deal with that when you don't know what you have in terms of data, the 50% of data is what we call dark data. You don't know anything about right, so you need help classifying it, understanding and getting insight into that data, and that's what we can help >> our customers. But howdy, howdy, dildo. In that environment, I mean, I mean, a day raises the point. This is obvious. A swell that mean you cite California right, which is somewhat infamous for its own regulatory mindset. I mean, how do you exist? What? The United States has privacy concerns and Congress can address it, and various federal agencies could do the same Europe. Obviously we talked about now Australia. Now here. Now there you get this Balkan I system that has no consistency, no framework. And so how do you operate on a global scale? >> A. Mentally. It relies on classifying that data right. Understanding what's where and what do you have is a P I. I personally identifiable information. Is it information that's intellectual property? What kind of data you have once you have that insight, which is what we provide, you can layer on top of the regulatory Is that compliance? >> Star I P. Is that Veritas i p. A blender? >> It's a blend of avatar and veritas I p. We have a product called Info Studio that helps toe provide that now Remember one of the things that are net backup product has is a catalogue of data. So we know where the data is primary to secondary storage, and we have all the versions of that data. And then we can run analytics against the secondary storage and not hit the primary systems. Right? So we're out of band to the primary systems, and that turns out to be very valuable in the state's a >> question. The catalog. I can't do this without a catalogue in the enough to geek out here a little bit, but but you've got a little bit when you bring in multi clouds. Other clouds. How do you incorporate you know that knowledge into your catalog? >> Yeah. Art, art, technology work Idol of works across multiple clouds. So we work with 60 different Cloud service providers. There's three big ones represented here today. Microsoft, AWS and Google. We work very closely with all three, and >> that's because you do the engineering at the A P. I level. Our engineering teams work very, very closely together. Okay, um, so let's talk about competition a little bit. The markets heated up. It's great. It's good to see all this VC money floating in. Everybody I said wants a piece of your hide. Why Veritas? >> Well, I explained that, you know, we are the leader in enterprise, data protection, availability and insights. There are some newcomers. They just will support you on your current technology. They don't support the infrastructure you've had for many years. If your large complicated enterprise you have layers of technology, we support all that with VIN amount for 25 years against, the big conglomerates were completely focused. And that's why we're the leader, according to Gartner, in the Leader's Quadrant 13 years >> now. And just as we close up you talked about, you brought up the case in Texas, about 22 municipalities. You do a lot of public sector work states, federal government ever. It's just what is the difference of different animal between public and private and and what you need to do in terms of providing that >> we're struggling with the same challenge. In fact, we work with some of the largest government agencies in the world, and they're struggling with exactly the same challenge. They also want leverage the public cloud. They're worried about ransom where you know they're dealing with data growth. All of these are challenges to them. And that's the, uh So these are common challenges we're addressing. Our strategy is to help our customers with these challenges so they can focus on the value of data >> 18 months in. You seem pumped up. Does having a great time team fired up >> way. Get that right. Great. But you're okay with big geeking out to write a very good thanks for the time You've run out of time. 40 Niners next time. All right. Greg Hughes joining us from Veritas. Back with more Veum, World 2019 right here on the Cube. >> Thank you.

[Music] hi I'm Peter Burris and welcome to another Cube conversation from the cube studios here in beautiful Palo Alto California today we're going to talk about some new things that are happening in the security world obviously this is one of the most important domains within the technology industry and increasingly because of digital business in business overall now to do that we've asked Eric manki to come back Derick is the chief of security insights and global threat alliances at Fort Net Derek welcome back to the cube absolutely the same feel the same way Derek okay so we're going to get into some some predictions about what the bad guys are doing and some predictions about what the defenses are doing how we're going to see them defense opportunities improve but let's set the stage because predictions always are made on some platforms some understanding of where we are and that has also changed pretty dramatically so what's the current state in the overall security world Derek yeah so what we saw this year in 2019 a lot is a big increase on automation and I'm talking from an attackers point of view I think we talked about this a little bit earlier in the year so what we've been seeing is the use of frameworks to enhance sort of the day-to-day cycles that cyber criminals and attackers are using to make their you know criminal operations is that much more efficient sort of a well-oiled machine so we're seeing toolkits that are taking you know things within the attack cycle and attack change such as reconnaissance penetration you know exploitation getting into systems and just making that that much quicker so that that window to attack the time to breach has been shrinking thanks to a lot of these crime kits and services that are offered out there now one other comment on this or another question that I might have on this is that so speed is becoming an issue but also the risk as digital business takes on a larger four portion of overall business activities that ultimately the risks and costs of doing things wrong is also going up if I got the right yeah absolutely for sure and you know it's one of those things that it's the longer that a cybercriminal has a foothold in your system or has the opportunity to move laterally and gain access to other systems maybe it's your I o T or you know other other platforms the higher the risk right like the deeper down they are within an attack cycle the higher the risk and because of these automated toolkits are allowing allowing them to facilitate that it's a catalyst really right they can get into the system they can actually get out that much quicker the risk is a much higher and we're talking about risk we're talking about things like intellectual property exfiltration client information this sort of stuff that can be quite damaging to organizations so with the new foundation of speed is becoming an increasingly important feature probably think about security and the risks are becoming greater because digital assets are being recognized as more valuable why do you take us through some of the four Donets predictions on some of the new threats or the threat landscape how's the threat landscape changing yeah so as I said we've already seen this shift in automation so what I would call the basics I mean knowing the target trying to break into that target right when it comes to breaking into the target cyber criminals right now they're following the path of least resistance right they're finding easy ways that they can get into IOT devices I into other systems in our world when we talk about penetration or breaking into systems it's through zero days right so the idea of a zero day is essentially a cyber weapon there's movies and Hollywood that have been made off of this you look at attacks like Stuxnet in the past they all use zero day vulnerabilities to get into systems all right so the idea of one of the predictions we're seeing is that cyber criminals are gonna start to use artificial intelligence right so we talk about machine learning models and artificial intelligence to actually find these zero days for them so in the world of an attacker to find a zero day they have to do a practice called fuzzing and fuzzing is basically trying to trick up computer code right so you're throwing unverified parameters out at your turn T of throwing and unanticipated sequences into code parameters and and input validation and so forth to the point that the code crashes and that's from an attackers point of view that's when you take control of that code this how you know finding weapons into system cyber weapons in this systems work it typically takes a lot of a lot of resource it takes a lot of cycles it takes a lot of intelligence that takes a lot of time to discovery we can be talking on month for longer it's one of the predictions that we're hitting on is that you know cyber criminals are gonna start to use artificial intelligence fuzzing or AI F as I call it to be able to use AI to do all of that you know intelligent work for them so you know basically having a system that will find these gateways if you will these these you know new vulnerabilities into systems so sustained use of AI F to corrupt models so that they can find vulnerabilities that can then be exploited yeah absolutely and you know when it comes to the world of hacking and fuzzing it's one of the toughest things to do it is the reason that zero days are worth so much money you know they can suffer hundreds of thousands of dollars on darknet and in the cyber criminal you know economy so it's because they're talk talk to finally take a lot of resources a lot of intelligence and a lot of effort to be able to not only find the vulnerability but then actively attack it and exploit it right there's two phases to that yeah so the idea is by using part of the power of artificial intelligence that cyber criminals will start to leverage that and harness it in a bad way to be able to not only discover you know these vulnerabilities but also create that weapon right create the exploit so that they can find more you know more holes if you will or more angles to be able to get into systems now another one is that virtualization is happening in you know what the good guys as we virtualized resources but is it also being exploited or does it have the potential be exploited by the bad guys as well especially in a swarming approach yeah virtualization for sure absolutely so the thing about virtualization too is you often have a lot of virtualization being centralizes especially when we talk about cloud right so you have a lot of potential digital assets you know valuable digital assets that could be physically located in one area so when it comes to using things like artificial intelligence fuzzing not only can it be used to find different vulnerabilities or ways into systems it can also be combined with something like I know we've talked about the const that's warm before so using you know multiple intelligence infected pieces of code that can actually try to break into other virtual resources as well so virtualization asked definitely it because of in some cases close proximity if you will between hypervisors and things like this it's also something of concern for sure now there is a difference between AI fai fuzzing and machine learning talk to us a little bit about some of the trends or some of the predictions that pertain to the advancement of machine learning and how bad guys are going to exploit that sure so machine learning is a core element that is used by artificial intelligence right if you think of artificial intelligence it's a larger term it can be used to do intelligent things but it can only make those decisions based off of a knowledge base right and that's where machine learning comes into place machine learning is it's data it's processing and it's time right so there's various machine learning learning models that are put in place it can be used from everything from autonomous vehicles to speech recognition to certainly cybersecurity and defense that we can talk about but you know the other part that we're talking about in terms of reductions is that it can be used like any tool by the bad guys so the idea is that machine learning can be used to actually study code you know from from a black hat attacker point of view to studying weaknesses in code and that's the idea of artificial intelligence fuzzing is that machine learning is used to find software flaws it finds the weak spots in code and then it actually takes those sweet spots and it starts probing starts trying to attack a crisis you know to make the code crash and then when it actually finds that it can crash the code and that it can try to take advantage of that that's where the artificial intelligence comes in right so the AI engine says hey I learned that this piece of software or this attack target has these weak pieces of code in it that's for the AI model so the I fuzzy comes into place to say how can I actually take advantage how can i exploit this right so that's where the AI trussing comes into play so we've got some predictions about how black hats and bad guys are going to use AI and related technologies to find new vulnerabilities new ways of exploiting things and interacting new types of value out of a business what are the white hats got going for them what are their some of the predictions on some of the new classes of defense that we're going to be able to put to counter some of these new classes of attacks yeah so that's that's you know that's honestly some of the good news I believe you know it's always been an armor an arms race between the bad guys and the good guys that's been going on for decades in terms of cybersecurity often you know the the bad guys are in a favorable position because they can do a million things wrong and they don't care right from the good guys standpoint we can do a million things right one thing wrong and that's an issue so we have to be extra diligent and careful with what we do but with that said you know as an example of 49 we've deployed our forty guard AI right so this is six years in the making six years using machine learning using you know precise models to get higher accuracy low false positives to deploy this at reduction so you know when it comes to the defensive mechanism I really think that we're in the drivers position quite frankly we have better technology than the Wild West that they have out on the bad guys side you know from an organization point of view how do you start combating this sort of onslaught of automation in AI from from the bad guys side well you gotta fight fire with fire right and what I mean by that is you have to have an intelligent security system you know perimeter based firewalls and gateways they don't cut it anymore right you need threat intelligence you need systems that are able to orchestrate and automate together so in different security products and in your security stack or a security fabric that can talk to each other you know share intelligence and then actually automate that so I'm talking about things like creating automated security policies based off of you know threat intelligence finding that a potential threat is trying to get into your network that sort of speed through that integration on the defensive side that intelligence speed is is is the key for it I mean without that any organization is gonna be losing the arms race and I think one of the things that is also happening is we're seeing a greater willingness perhaps not to share data but to share information about the bad things that are happening and I know that fort and it's been something at the vanguard of ensuring that there's even better clearing for this information and then driving that back into code that actually further automates how customers respond to things if I got that right yeah you hit a dead-on absolutely you know that is one of the key things that were focused on is that we realized we can't win this war alone right nobody can on a single point of view so we're doing things like interoperating with security partners we have a fabric ready program as an example we're doing a lot of work in the industry working with as an example Interpol and law enforcement to try to do attribution but though the whole endgame what we're trying to do is to the strategy is to try to make it more expensive for cyber criminals to operate so we obviously do that as a vendor you know through good technology our security fabric I integrated holistic security fabric and approach to be able to make it tougher you know for attackers to get into systems but at the same time you know we're working with law enforcement to find out who these guys are to go after attribution prosecution cut off the head of the snake as I call it right to try to hit cyber criminal organizations where it hurts we're also doing things across vendor in the industry like cyber threat Alliance so you know forty knots a founding member of the cyber threat Alliance we're working with other security vendors to actually share real time information is that speed you know message that we're talking about earlier to share real time information so that each member can take that information and put it into you something actionable right in our case when we get intelligence from other vendors in the cyber threat Alliance as an example we're putting that into our security fabric to protect our customers in new real-time so in sum we're talking about a greater value from being attacked being met with a greater and more cooperative use of technology and process to counter those attacks all right yeah absolutely so open collaboration unified collaboration is is definitely key when it comes to that as well you know the other thing like I said is is it's the is the technology piece you know having integration another thing from the defensive side too which is becoming more of a topic recently is deception deception techniques this is a fascinating area to me right because the idea of deception is the way it sounds instead of to deceive criminals when they're coming knocking on your door into your network so it's really what I call like the the house of a thousand mirrors right so they get into your network and they think they're going to your data store but is it really your data store right it's like it's there's one right target and a thousand wrong targets it's it's a it's a defensive strategy that organizations can play to try to trip up cyber criminals right it makes them slower it makes them more inaccurate it makes them go on the defensive and back to the drawing board which is something absolutely I think we have to do so it's very interesting promising you know technology moving forward in 2019 to essentially fight back against the cyber criminals and to make it more expensive to get access to whatever it is that they want Derek max Lilly yeah Derrick McKey chief of security insights and global threat Alliance this is for net thanks once again for being on the cube it's a pleasure anytime look forward to the next chat and from Peter Burroughs and all of us here at the cube in Palo Alto thank you very much for watching this cube conversation until next time you

>> Narrator: Live from Las Vegas, it's theCUBE, covering AWS re:Invent 2017, presented by AWS, Intel, and our ecosystem of partners. >> Hey, welcome back everyone, this is theCUBE's exclusive live coverage here in Las Vegas for AWS Amazon web services re:Invent 2017. I'm John Furrier with Keith Townsend. Our next guest is Laura Stevens, data scientist at the American Heart Association, an AWS customer, welcome to theCUBE. >> Hi, it's nice to be here. >> So, the new architecture, we're seeing all this great stuff, but one of the things that they mention is data is the killer app, that's my word, Verna didn't say that, but essentially saying that. You guys are doing some good work with AWS and precision medicine, what's the story? How does this all work, what are you working with them on? >> Yeah, so the American Heart Association was founded in 1924, and it is the oldest and largest voluntary organization dedicated to curing heart disease and stroke, and I think in the past few years what the American Heart Association has realized is that the potential of technology and data can really help us create innovative ways and really launch precision medicine in a fashion that hasn't been capable to do before. >> What are you guys doing with AWS? What's that, what's the solution? >> Yeah so the HA has strategically partnered with Amazon Web Services to basically use technology as a way to power precision medicine, and so when I say precision medicine, I mean identifying individual treatments, based on one's genetics, their environmental factors, their life factors, that then results in preventative and treatment that's catered to you as an individual rather than kind of a one size fits all approach that is currently happening. >> So more tailored? >> Yeah, specifically tailored to you as an individual. >> What do I do, get a genome sequence? I walk in, they throw a high force computing, sequence my genomes, maybe edit some genes while they're at it, I mean what's going on. There's some cutting edge conversations out there we see in some of the academic areas, course per that was me just throwing that in for fun, but data has to be there. What kind of data do you guys look at? Is it personal data, is it like how big is the data? Give us a sense of some of the data science work that you're doing? >> Yeah so the American Heart Association has launched the Institute for Precision Cardiovascular Medicine, and as a result, with Amazon, they created the precision medicine platform, which is a data marketplace that houses and provides analytic tools that enable high performance computing and data sharing for all sorts of different types of data, whether it be personal data, clinical trial data, pharmaceutical data, other data that's collected in different industries, hospital data, so a variety of data. >> So Laura, there's a lot of think fud out there around the ability to store data in a cloud, but there's also some valid concerns. A lot of individual researchers, I would imagine, don't have the skillset to properly protect data. What is the Heart Association doing with the framework to help your customers protect data? >> Yeah so the I guess security of data, the security of the individual, and the privacy of the individual is at the heart of the AHA, and it's their number one concern, and making anything that they provide that a number one priority, and the way that we do that in partnering with AWS is with this cloud environment we've been able to create even if you have data that you'd like to use sort of a walled garden behind your data so that it's not accessible to people who don't have access to the data, and it's also HIPAA compliant, it meets the standards that the utmost secure standards of health care today. >> So I want to make sure we're clear on this, the Heart Association doesn't collect data themselves. Are you guys creating a platform for your members to leverage this technology? >> So there's, I would so maybe both actually. The American Heart Association does have data that it is associated with, with its volunteers and the hospitals that it's associated with, and then on top of that, we've actually just launched My Research Legacy, which allows individuals of the community to, who want to share their data, whether you're healthy or just sick, either one, they want to share their data and help in aiding to cure heart disease and stroke, and so they can share their own data, and then on top of that, anybody, we are committed to strategically partnering with anybody who's involved and wants to share their data and make their data accessible. >> So I can share my data? >> Yes, you can share your data. >> Wow, so what type of tools do you guys use against that data set and what are some of the outcomes? >> Yeah so I think the foundation is the cloud, and that's where the data is stored and housed, and then from there, we have a variety of different tools that enable researchers to kind of custom build data sets that they want to answer the specific research questions they have, and so some of those tools, they range from common tools that are already in use today on your personal computer, such as Python or R Bioconductor, and then they have more high performance computing tools, such as Hal or any kind of s3 environment, or Amazon services, and then on top of that I think what is so awesome about the platform is that it's very dynamic, so a tool that's needed to use for high performance computing or a tool that's needed even just as a on a smaller data set, that can easily be installed and may be available to researchers, and so that they can use it for their research. >> So kind of data as a service. I would love to know about the community itself. How are you guys sharing the results of kind of oh this process worked great for this type of analysis amongst your members? >> Yeah so I think that there's kind of two different targets in that sense that you can think of is that there's the researchers and the researchers that come to the platform and then there's actually the patient itself, and ultimately the HA's goal is to make, to use the data and use the researcher for patient centered care, so with the researchers specifically, we have a variety of tutorials available so that researchers can one, learn how to perform high performance computing analysis, see what other people have done. We have a forum where researchers can log on and enable, I guess access other researchers and talk to them about different analysis, and then additionally we have My Research Legacy, which is patient centered, so it's this is what's been found and this is what we can give back to you as the patient about your specific individualized treatment. >> What do you do on a daily basis? Take us through your job, are you writing code, are you slinging API's around? What are some of the things that you're doing? >> I think I might say all of the above. I think right now my main effort is focused on one, conducting research using the platform, so I do use the platform to answer my own research questions, and those we have presented at different conferences, for example the American Heart Association, we had a talk here about the precision medicine platform, and then two, I'm focused on strategically making the precision medicine platform better by getting more data, adding data to the platform, improving the way that data is harmonized in the platform, and improving the amount of data that we have, and the diversity, and the variety. >> Alright, we'll help you with that, so let's help you get some people recruited, so what do they got to do to volunteer, volunteer their data, because I think this is one of those things where you know people do want to help. So, how do they, how you onboard? You use the website, is it easy, one click? Do they have to wear an iWatch, I mean what I mean? >> Yeah. >> What's the deal? What do I got to do? >> So I think I would encourage researchers and scientists and anybody who is data centric to go to precision.heart.org, and they can just sign up for an account, they can contact us through that, there's plenty of different ways to get in touch with us and plenty of ways to help. >> Precision.heart.org. >> Yup, precision.heart.org. >> Stu: Register now. >> Register now click, >> Powered by AWS. >> Yup. >> Alright so I gotta ask you as an AWS customer, okay take your customer hat off, put your citizen's hat on, what is Amazon mean to you, I mean is it, how do you describe it to people who don't use it? >> Okay yeah, so I think... the HA's ultimate mission right, is to provide individualized treatment and cures for cardiovascular disease and stroke. Amazon is a way to enable that and make that actually happen so that we can mine extremely large data sets, identify those individualized patterns. It allows us to store data in a fashion where we can provide a market place where there's extremely large amounts of data, extremely diverse amounts of data, and data that can be processed effectively, so that it can be directly used for research. >> What's your favorite tool or product or service within Amazon? >> That's a good question. I think, I mean the cloud and s3 buckets are definitely in a sense they're my favorites because there's so much that can be stored right there, Athena I think is also pretty awesome, and then the EMR clusters with Spark. >> The list is too long. >> My jam. >> It is. (laughs) >> So, one of the interesting things that I love is a lot of my friends are in non-profits, fundraising is a big, big challenge, grants are again, a big challenge, have you guys seen any new opportunities as a result of the results of the research coming out of HA and AWS in the cloud? >> Yeah so I think one of the coolest things about the HA is that they have this Institute for Precision Cardiovascular Medicine, and the strategic partnership between the HA and AWS, even just this year we've launched 13 new grants, where the HA kind of backs the research behind, and the AWS provides credit so that people can come to the cloud and use the cloud and use the tools available on a grant funded basis. >> So tell me a little bit more about that program. Anybody specifically that you, kind of like saying, seeing that's used these credits from AWS to do some cool research? >> Yeah definitely, so I think specifically we have one grantee right now that is really focused on identifying outcomes across multiple clinical trials, so currently clinical trials take 20 years, and there's a large variety of them. I don't know if any of you are familiar with the Framingham heart study, the Dallas heart study, the Jackson heart study, and trying to determine how those trials compare, and what outcomes we can generate, and research insights we can generate across multiple data sets is something that's been challenging due to the ability to not being able to necessarily access that data, all of those different data sets together, and then two, trying to find ways to actually compare them, and so with the precision medicine platform, we have a grantee at the University of Colorado-Denver, who has been able to find those synchronicities across data sets and has actually created kind of a framework that then can be implemented in the precision medicine platform. >> Well I just registered, it takes really two seconds to register, that's cool. Thanks so much for pointing out precision.heart.org. Final question, you said EMR's your jam. (laughing) >> Why, why is it? Why do you like it so much, is it fast, is it easy to use? >> I think the speed is one of the things. When it comes to using genetic data and multiple biological levels of data, whether it be your genetics, your lifestyle, your environment factors, there's... it just ends up being extremely large amounts of data, and to be able to implement things like server-less AI, and artificial intelligence, and machine learning on that data set is time consuming, and having the power of an EMR cluster that is scalable makes that so much faster so that we can then answer our research questions faster and identify those insights and get them to out in the world. >> Gotta love the new services they're launching, too. It just builds on top of it. Doesn't it? >> Yes. >> Yeah, soon everyone's gonna be jamming on AWS in our opinion. Thanks so much for coming on, appreciate the stories and commentary. >> Yeah. >> Precision.heart.org, you want to volunteer if you're a researcher or a user, want to share your data, they've got a lot of data science mojo going on over there, so check it out. It's theCUBE bringing a lot of data here, tons of data from the show, three days of wall to wall coverage, we'll be back with more live coverage after this short break. (upbeat music)

Section 1 of 13 [00:00:00 - 00:10:04] (NOTE: speaker names may be different in each section) Speaker 1: Ladies and gentlemen our program will begin momentarily. Thank you. (singing) This presentation and the accompanying oral commentary may include forward looking statements that are subject to risks uncertainties and other factors beyond our control. Our actual results, performance or achievements may differ materially and adversely from those anticipated or implied by such statements because of various risk factors. Including those detailed in our annual report on form 10-K for the fiscal year ended July 31, 2017 filed with the SEC. Any future product or roadmap information presented is intended to outline general product direction and is not a commitment to deliver any functionality and should not be used when making any purchasing decision. (singing) Ladies and gentlemen please welcome Vice President Corporate Marketing Nutanix, Julie O'Brien. Julie O'Brien: All right. How about those Nutanix .NEXT dancers, were they amazing or what? Did you see how I blended right in, you didn't even notice I was there. [French 00:07:23] to .NEXT 2017 Europe. We're so glad that you could make it today. We have such a great agenda for you. First off do not miss tomorrow morning. We're going to share the outtakes video of the handclap video you just saw. Where are the customers, the partners, the Nutanix employee who starred in our handclap video? Please stand up take a bow. You are not going to want to miss tomorrow morning, let me tell you. That is going to be truly entertaining just like the next two days we have in store for you. A content rich highly interactive, number of sessions throughout our agenda. Wow! Look around, it is amazing to see how many cloud builders we have with us today. Side by side you're either more than 2,200 people who have traveled from all corners of the globe to be here. That's double the attendance from last year at our first .NEXT Conference in Europe. Now perhaps some of you are here to learn the basics of hyperconverged infrastructure. Others of you might be here to build your enterprise cloud strategy. And maybe some of you are here to just network with the best and brightest in the industry, in this beautiful French Riviera setting. Well wherever you are in your journey, you'll find customers just like you throughout all our sessions here with the next two days. From Sligro to Schroders to Societe Generale. You'll hear from cloud builders sharing their best practices and their lessons learned and how they're going all in with Nutanix, for all of their workloads and applications. Whether it's SAP or Splunk, Microsoft Exchange, unified communications, Cloud Foundry or Oracle. You'll also hear how customers just like you are saving millions of Euros by moving from legacy hypervisors to Nutanix AHV. And you'll have a chance to post some of your most challenging technical questions to the Nutanix experts that we have on hand. Our Nutanix technology champions, our MPXs, our MPSs. Where are all the people out there with an N in front of their certification and an X an R an S an E or a C at the end. Can you wave hello? You might be surprised to know that in Europe and the Middle East alone, we have more than 2,600 >> Julie: In Europe and the Middle East alone, we have more than 2,600 certified Nutanix experts. Those are customers, partners, and also employees. I'd also like to say thank you to our growing ecosystem of partners and sponsors who are here with us over the next two days. The companies that you meet here are the ones who are committed to driving innovation in the enterprise cloud. Over the next few days you can look forward to hearing from them and seeing some fantastic technology integration that you can take home to your data center come Monday morning. Together, with our partners, and you our customers, Nutanix has had such an exciting year since we were gathered this time last year. We were named a leader in the Gartner Magic Quadrant for integrated systems two years in a row. Just recently Gartner named us the revenue market share leader in their recent market analysis report on hyper-converged systems. We know enjoy more than 35% revenue share. Thanks to you, our customers, we received a net promoter score of more than 90 points. Not one, not two, not three, but four years in a row. A feat, I'm sure you'll agree, is not so easy to accomplish, so thank you for your trust and your partnership in us. We went public on NASDAQ last September. We've grown to more than 2,800 employees, more than 7,000 customers and 125 countries and in Europe and the Middle East alone, in our Q4 results, we added more than 250 customers just in [Amea 00:11:38] alone. That's about a third of all of our new customer additions. Today, we're at a pivotal point in our journey. We're just barely scratching the surface of something big and Goldman Sachs thinks so too. What you'll hear from us over the next two days is this: Nutanix is on it's way to building and becoming an iconic enterprise software company. By helping you transform your data center and your business with Enterprise Cloud Software that gives you the power of freedom of choice and flexibility in the hardware, the hypervisor and the cloud. The power of one click, one OS, any cloud. And now, to tell you more about the digital transformation that's possible in your business and your industry and share a little bit around the disruption that Nutanix has undergone and how we've continued to reinvent ourselves and maybe, if we're lucky, share a few hand clap dance moves, please welcome to stage Nutanix Founder, CEO and Chairman, Dheeraj Pandey. Ready? Alright, take it away [inaudible 00:13:06]. >> Dheeraj P: Thank you. Thank you, Julie and thank you every one. It looks like people are still trickling. Welcome to Acropolis. I just hope that we can move your applications to Acropolis faster than we've been able to move people into this room, actually. (laughs) But thank you, ladies and gentlemen. Thank you to our customers, to our partners, to our employees, to our sponsors, to our board members, to our performers, to everybody for their precious time. 'Cause that's the most precious thing you actually have, is time. I want to spend a little bit of time today, not a whole lot of time, but a little bit of time talking about the why of Nutanix. Like why do we exist? Why have we survived? Why will we continue to survive and thrive? And it's simpler than an NQ or category name, the word hyper-convergence, I think we are all complicated. Just thinking about what is it that we need to talk about today that really makes it relevant, that makes you take back something from this conference. That Nutanix is an obvious innovation, it's very obvious what we do is not very complicated. Because the more things change, the more they remain the same, so can we draw some parallels from life, from what's going on around us in our own personal lives that makes this whole thing very natural as opposed to "Oh, it's hyper-converged, it's a category, it's analysts and pundits and media." I actually think it's something new. It's not that different, so I want to start with some of that today. And if you look at our personal lives, everything that we had, has been digitized. If anything, a lot of these gadgets became apps, they got digitized into a phone itself, you know. What's Nutanix? What have we done in the last seven, eight years, is we digitized a lot of hardware. We made everything that used to be single purpose hardware look like pure software. We digitized storage, we digitized the systems manager role, an operations manager role. We are digitizing scriptures, people don't need to write scripts anymore when they automate because we can visually design automation with [com 00:15:36]. And we're also trying to make a case that the cloud itself is not just a physical destination. That it can be digitized and must be digitized as well. So we learn that from our personal lives too, but it goes on. Look at music. Used to be tons of things, if you used to go to [inaudible 00:15:55] Records, I'm sure there were European versions of [inaudible 00:15:57] Records as well, the physical things around us that then got digitized as well. And it goes on and on. We look at entertainment, it's very similar. The idea that if you go to a movie hall, the idea that you buy these tickets, the idea that we'd have these DVD players and DVDs, they all got digitized. Or as [inaudible 00:16:20] want to call it, virtualized, actually. That is basically happening in pretty much new things that we never thought would look this different. One of the most exciting things happening around us is the car industry. It's getting digitized faster than we know. And in many ways that we'd not even imagined 10 years ago. The driver will get digitized. Autonomous cars. The engine is definitely gone, it's a different kind of an engine. In fact, we'll re-skill a lot of automotive engineers who actually used to work in mechanical things to look at real chemical things like battery technologies and so on. A lot of those things that used to be physical are now in software in the car itself. Media itself got digitized. Think about a physical newspaper, or physical ads in newspapers. Now we talk about virtual ads, the digital ads, they're all over on websites and so on is our digital experience now. Education is no different, you know, we look back at the kind of things we used to do physically with physical things. Their now all digital. The experience has become that digital. And I can go on and on. You look at retail, you look at healthcare, look at a lot of these industries, they all are at the cusp of a digital disruption. And in fact, if you look at the data, everybody wants it. We all want a digital transformation for industries, for companies around us. In fact, the whole idea of a cloud is a highly digitized data center, basically. It's not just about digitizing servers and storage and networks and security, it's about virtualizing, digitizing the entire data center itself. That's what cloud is all about. So we all know that it's a very natural phenomenon, because it's happening around us and that's the obviousness of Nutanix, actually. Why is it actually a good thing? Because obviously it makes anything that we digitize and we work in the digital world, bring 10X more productivity and decision making efficiencies as well. And there are challenges, obviously there are challenges, but before I talk about the challenges of digitization, think about why are things moving this fast? Why are things becoming digitally disrupted quicker than we ever imagined? There are some reasons for it. One of the big reasons is obviously we all know about Moore's Law. The fact that a lot of hardware's been commoditized, and we have really miniaturized hardware. Nutanix today runs on a palm-sized server. Obviously it runs on the other end of the spectrum with high-end IBM power systems, but it also runs on palm-sized servers. Moore's Law has made a tremendous difference in the way we actually think about consuming software itself. Of course, the internet is also a big part of this. The fact that there's a bandwidth glut, there's Trans-Pacific cables and Trans-Atlantic cables and so on, has really connected us a lot faster than we ever imagined, actually, and a lot of this was also the telecom revolution of the '90s where we really produced a ton of glut for the internet itself. There's obviously a more subtle reason as well, because software development is democratizing. There's consumer-grade programming languages that we never imagined 10, 15, 20 years ago, that's making it so much faster to write- >> Speaker 1: 15-20 years ago that's making it so much faster to write code, with this crowdsourcing that never existed before with Githubs and things like that, open source. There's a lot more stuff that's happening that's outside the boundary of a corporation itself, which is making things so much faster in terms of going getting disrupted and writing things at 10x the speed it used to be 20 years ago. There is obviously this technology at the tip of our fingers, and we all want it in our mobile experience while we're driving, while we're in a coffee shop, and so on; and there's a tremendous focus on design on consumer-grade simplicity, that's making digital disruption that much more compressed in some of sense of this whole cycle of creative disruption that we talk about, is compressed because of mobility, because of design, because of API, the fact that machines are talking to machines, developers are talking to developers. We are going and miniaturizing the experience of organizations because we talk about micro-services and small two-pizza teams, and they all want to talk about each other using APIs and so on. Massive influence on this digital disruption itself. Of course, one of the reasons why this is also happening is because we want it faster, we want to consume it faster than ever before. And our attention spans are reducing. I like the fact that not many people are watching their cell phones right now, but you can imagine the multi-tasking mode that we are all in today in our lives, makes us want to consume things at a faster pace, which is one of the big drivers of digital disruption. But most importantly, and this is a very dear slide to me, a lot of this is happening because of infrastructure. And I can't overemphasize the importance of infrastructure. If you look at why did Google succeed, it was the ninth search engine, after eight of them before, and if you take a step back at why Facebook succeeded over MySpace and so on, a big reason was infrastructure. They believed in scale, they believed in low latency, they believed in being able to crunch information, at 10x, 100x, bigger scale than anyone else before. Even in our geopolitical lives, look at why is China succeeding? Because they've made infrastructure seamless. They've basically said look, governance is about making infrastructure seamless and invisible, and then let the businesses flourish. So for all you CIOs out there who actually believe in governance, you have to think about what's my first role? What's my primary responsibility? It's to provide such a seamless infrastructure, that lines of business can flourish with their applications, with their developers that can write code 10x faster than ever before. And a lot of these tenets of infrastructure, the fact of the matter is you need to have this always-on philosophy. The fact that it's breach-safe culture. Or the fact that operating systems are hardware agnostic. A lot of these tenets basically embody what Nutanix really stands for. And that's the core of what we really have achieved in the last eight years and want to achieve in the coming five to ten years as well. There's a nuance, and obviously we talk about digital, we talk about cloud, we talk about everything actually going to the cloud and so on. What are the things that could slow us down? What are the things that challenge us today? Which is the reason for Nutanix? Again, I go back to this very important point that the reason why we think enterprise cloud is a nuanced term, because the word "cloud" itself doesn't solve for a lot of the problems. The public cloud itself doesn't solve for a lot of the problems. One of the big ones, and obviously we face it here in Europe as well, is laws of the land. We have bureaucracy, which we need to deal with and respect; we have data sovereignty and computing sovereignty needs that we need to actually fulfill as well, while we think about going at breakneck speed in terms of disrupting our competitors and so on. So there's laws of the land, there's laws of physics. This is probably one of the big ones for what the architecture of cloud will look like itself, over the coming five to ten years. Our take is that cloud will need to be more dispersed than they have ever imagined, because computing has to be local to business operations. Computing has to be in hospitals and factories and shop floors and power plants and on and on and on... That's where you really can have operations and computing really co-exist together, cause speed is important there as well. Data locality is one of our favorite things; the fact that computing and data have to be local, at least the most relevant data has to be local as well. And the fact that electrons travel way faster when it's actually local, versus when you have to have them go over a Wide Area Network itself; it's one of the big reasons why we think that the cloud will actually be more nuanced than just some large data centers. You need to disperse them, you need to actually think about software (cloud is about software). Whether data plane itself could be dispersed and even miniaturized in small factories and shop floors and hospitals. But the control plane of the cloud is centralized. And that's the way you can have the best of both worlds; the control plane is centralized. You think as if you're managing one massive data center, but it's not because you're really managing hundreds or thousands of these sites. Especially if you think about edge-based computing and IoT where you really have your tentacles in tens of thousands of smaller devices and so on. We've talked about laws of the land, which is going to really make this digital transformation nuanced; laws of physics; and the third one, which is really laws of entropy. These are hackers that do this for adrenaline. These are parochial rogue states. These are parochial geo-politicians, you know, good thing I actually left the torture sign there, because apparently for our creative designer, geo-politics is equal to torture as well. So imagine one bad tweet can actually result in big changes to the way we actually live in this world today. And it's important. Geo-politics itself is digitized to a point where you don't need a ton of media people to go and talk about your principles and what you stand for and what you strategy for, for running a country itself is, and so on. And these are all human reasons, political reasons, bureaucratic reasons, compliance and regulations reasons, that, and of course, laws of physics is yet another one. So laws of physics, laws of the land, and laws of entropy really make us take a step back and say, "What does cloud really mean, then?" Cause obviously we want to digitize everything, and it all should appear like it's invisible, but then you have to nuance it for the Global 5000, the Global 10000. There's lots of companies out there that need to really think about GDPR and Brexit and a lot of the things that you all deal with on an everyday basis, actually. And that's what Nutanix is all about. Balancing what we think is all about technology and balancing that with things that are more real and practical. To deal with, grapple with these laws of the land and laws of physics and laws of entropy. And that's where we believe we need to go and balance the private and the public. That's the architecture, that's the why of Nutanix. To be able to really think about frictionless control. You want things to be frictionless, but you also realize that you are a responsible citizen of this continent, of your countries, and you need to actually do governance of things around you, which is computing governance, and data governance, and so on. So this idea of melding the public and the private is really about melding control and frictionless together. I know these are paradoxical things to talk about like how do you really have frictionless control, but that's the life you all lead, and as leaders we have to think about this series of paradoxes itself. And that's what Nutanix strategy, the roadmap, the definition of enterprise cloud is really thinking about frictionless control. And in fact, if anything, it's one of the things is also very interesting; think about what's disrupting Nutanix as a company? We will be getting disrupted along the way as well. It's this idea of true invisibility, the public cloud itself. I'd like to actually bring on board somebody who I have a ton of respect for, this leader of a massive company; which itself is undergoing disruption. Which is helping a lot of its customers undergo disruption as well, and which is thinking about how the life of a business analyst is getting digitized. And what about the laws of the land, the laws of physics, and laws of entropy, and so on. And we're learning a lot from this partner, massively giant company, called IBM. So without further ado, Bob Picciano. >> Bob Picciano: Thanks, >> Speaker 1: Thank you so much, Bob, for being here. I really appreciate your presence here- >> Bob Picciano: My pleasure! >> Speaker 1: And for those of you who actually don't know Bob, Bob is a Senior VP and General Manager at IBM, and is all things cognitive and obviously- >> Speaker 1: IBM is all things cognitive. Obviously, I learn a lot from a lot of leaders that have spent decades really looking at digital disruption. >> Bob: Did you just call me old? >> Speaker 1: No. (laughing) I want to talk about experience and talking about the meaning of history, because I love history, actually, you know, and I don't want to make you look old actually, you're too young right now. When you talk about digital disruption, we look at ourselves and say, "Look we are not extremely invisible, we are invisible, but we have not made something as invisible as the public clouds itself." And hence as I. But what's digital disruption mean for IBM itself? Now, obviously a lot of hardware is being digitized into software and cloud services. >> Bob: Yep. >> Speaker 1: What does it mean for IBM itself? >> Bob: Yeah, if you allow me to take a step back for a moment, I think there is some good foundational understanding that'll come from a particular point of view. And, you talked about it with the number of these dimensions that are affecting the way businesses need to consider their competitiveness. How they offer their capabilities into the market place. And as you reflected upon IBM, you know, we've had decades of involvement in information technology. And there's a big disruption going on in the information technology space. But it's what I call an accretive disruption. It's a disruption that can add value. If you were to take a step back and look at that digital trajectory at IBM you'd see our involvement with information technology in a space where it was all oriented around adding value and capability to how organizations managed inscale processes. Thinking about the way they were going to represent their businesses in a digital form. We came to call them applications. But it was how do you open an account, how do you process a claim, how do you transfer money, how do you hire an employee? All the policies of a company, the way the people used to do it mechanically, became digital representations. And that foundation of the digital business process is something that IBM helped define. We invented the role of the CIO to help really sponsor and enter in this notion that businesses could re represent themselves in a digital way and that allowed them to scale predictably with the qualities of their brand, from local operations, to regional operations, to international operations, and show up the same way. And, that added a lot of value to business for many decades. And we thrived. Many companies, SAP all thrived during that span. But now we're in a new space where the value of information technology is hitting a new inflection point. Which is not about how you scale process, but how you scale insight, and how you scale wisdom, and how you scale knowledge and learning from those operational systems and the data that's in those operational systems. >> Speaker 1: How's it different from 1993? We're talking about disruption. There was a time when IBM reinvented itself, 20-25 years ago. >> Bob: Right. >> Speaker 1: And you said it's bigger than 25 years ago. Tell us more. >> Bob: You know, it gets down. Everything we know about that process space right down to the very foundation, the very architecture of the CPU itself and the computer architecture, the von Neumann architecture, was all optimized on those relatively static scaled business processes. When you move into the notion where you're going to scale insight, scale knowledge, you enter the era that we call the cognitive era, or the era of intelligence. The algorithms are very different. You know the data semantically doesn't integrate well across those traditional process based pools and reformation. So, new capabilities like deep learning, machine learning, the whole field of artificial intelligence, allows us to reach into that data. Much of it unstructured, much of it dark, because it hasn't been indexed and brought into the space where it is directly affecting decision making processes in a business. And you have to be able to apply that capability to those business processes. You have to rethink the computer, the circuitry itself. You have to think about how the infrastructure is designed and organized, the network that is required to do that, the experience of the applications as you talked about have to be very natural, very engaging. So IBM does all of those things. So as a function of our transformation that we're on now, is that we've had to reach back, all the way back from rethinking the CPU, and what we dedicate our time and attention to. To our services organization, which is over 130,000 people on the consulting side helping organizations add digital intelligence to this notion of a digital business. Because, the two things are really a confluence of what will make this vision successful. >> Speaker 1: It looks like massive amounts of change for half a million people who work with the company. >> Bob: That's right. >> Speaker 1: I'm sure there are a lot of large customers out here, who will also read into this and say, "If IBM feels disrupted ... >> Bob: Uh hm >> Speaker 1: How can we actually stay not vulnerable? Actually there is massive amounts of change around their own competitive landscape as well. >> Bob: Look, I think every company should feel vulnerable right. If you're at this age, this cognitive era, the age of digital intelligence, and you're not making a move into being able to exploit the capabilities of cognition into the business process. You are vulnerable. If you're at that intersection, and your competitor is passing through it, and you're not taking action to be able to deploy cognitive infrastructure in conjunction with the business processes. You're going to have a hard time keeping up, because it's about using the machines to do the training to augment the intelligence of our employees of our professionals. Whether that's a lawyer, or a doctor, an educator or whether that's somebody in a business function, who's trying to make a critical business decision about risk or about opportunity. >> Speaker 1: Interesting, very interesting. You used the word cognitive infrastructure. >> Bob: Uh hm >> Speaker 1: There's obviously computer infrastructure, data infrastructure, storage infrastructure, network infrastructure, security infrastructure, and the core of cognition has to be infrastructure as well. >> Bob: Right >> Speaker 1: Which is one of the two things that the two companies are working together on. Tell us more about the collaboration that we are actually doing. >> Bob: We are so excited about our opportunity to add value in this space, so we do think very differently about the cognitive infrastructure that's required for this next generation of computing. You know I mentioned the original CPU was built for very deterministic, very finite operations; large precision floating point capabilities to be able to accurately calculate the exact balance, the exact amount of transfer. When you're working in the field of AI in cognition. You actually want variable precision. Right. The data is very sparse, as opposed to the way that deterministic or scorecastic operations work, which is very dense or very structured. So the algorithms are redefining the processes that the circuitry actually has to run. About five years ago, we dedicated a huge effort to rethink everything about the chip and what we made to facilitate an orchestra of participation to solve that problem. We all know the GPU has a great benefit for deep learning. But the GPU in many cases, in many architectures, specifically intel architectures, it's dramatically confined by a very small amount of IO bandwidth that intel allows to go on and off the chip. At IBM, we looked at all 686 roughly square millimeters of our chip and said how do we reuse that square area to open up that IO bandwidth? So the innovation of a GPU or a FPGA could really be utilized to it's maximum extent. And we could be an orchestrator of all of the diverse compute that's going to be necessary for AI to really compel these new capabilities. >> Speaker 1: It's interesting that you mentioned the fact that you know power chips have been redefined for the cognitive era. >> Bob: Right, for Lennox for the cognitive era. >> Speaker 1: Exactly, and now the question is how do you make it simple to use as well? How do you bring simplicity which is where ... >> Bob: That's why we're so thrilled with our partnership. Because you talked about the why of Nutanix. And it really is about that empowerment. Doing what's natural. You talked about the benefits of calm and being able to really create that liberation of an information technology professional, whether it's in operations or in development. Having the freedom of action to make good decisions about defining the infrastructure and deploying that infrastructure and not having to second guess the physical limitations of what they're going to have to be dealing with. >> Speaker 1: That's why I feel really excited about the fact that you have the power of software, to really meld the two forms together. The intel form and the power form comes together. And we have some interesting use cases that our CIO Randy Phiffer is also really exploring, is how can a power form serve as a storage form for our intel form. >> Bob: Sure. >> Speaker 1: It can serve files and mocks and things like that. >> Bob: Any data intensive application where we have seen massive growth in our Lennox business, now for our business, Lennox is 20% of the revenue of our power systems. You know, we started enabling native Lennox distributions on top of little Indian ones, on top of the power capabilities just a few years ago, and it's rocketed. And the reason for that if for any data intensive application like a data base, a no sequel database or a structured data base, a dupe in the unstructured space, they typically run about three to four times better price performance on top of Lennox on power, than they will on top of an intel alternative. >> Speaker 1: Fascinating. >> Bob: So all of these applications that we're talking about either create or consume a lot of data, have to manage a lot of flexibility in that space, and power is a tremendous architecture for that. And you mentioned also the cohabitation, if you will, between intel and power. What we want is that optionality, for you to utilize those benefits of the 3X better price performance where they apply and utilize the commodity base where it applies. So you get the cost benefits in that space and the depth and capability in the space for power. >> Speaker 1: Your tongue in cheek remark about commodity intel is not lost on people actually. But tell us about... >> Speaker 1: Intel is not lost on people actually. Tell us about ... Obviously we digitized Linux 10, 15 years ago with [inaudible 00:40:07]. Have you tried to talk about digitizing AIX? That is the core of IBM's business for the last 20, 25, 30 years. >> Bob: Again, it's about this ability to compliment and extend the investments that businesses have made during their previous generations of decision making. This industry loves to talk about shifts. We talked about this earlier. That was old, this is new. That was hard, this is easy. It's not about shift, it's about using the inflection point, the new capability to extend what you already have to make it better. And that's one thing that I must compliment you, and the entire Nutanix organization. It's really empowering those applications as a catalog to be deployed, managed, and integrated in a new way, and to have seamless interoperability into the cloud. We see the AIX workload just having that same benefit for those businesses. And there are many, many 10's of thousands around the world that are critically dependent on every element of their daily operations and productivity of that operating platform. But to introduce that into that network effect as well. >> Speaker 1: Yeah. I think we're looking forward to how we bring the same cloud experience on AIX as well because as a company it keeps us honest when we don't scoff at legacy. We look at these applications the last 10, 15, 20 years and say, "Can we bring them into the new world as well?" >> Bob: Right. >> Speaker 1: That's what design is all about. >> Bob: Right. >> Speaker 1: That's what Apple did with musics. We'll take an old world thing and make it really new world. >> Bob: Right. >> Speaker 1: The way we consume things. >> Bob: That governance. The capability to help protect against the bad actors, the nefarious entropy players, as you will. That's what it's all about. That's really what it takes to do this for the enterprise. It's okay, and possibly easier to do it in smaller islands of containment, but when you think about bringing these class of capabilities into an enterprise, and really helping an organization drive both the flexibility and empowerment benefits of that, but really be able to depend upon it for international operations. You need that level of support. You need that level of capability. >> Speaker 1: Awesome. Thank you so much Bob. Really appreciate you coming. [crosstalk 00:42:14] Look forward to your [crosstalk 00:42:14]. >> Bob: Cheers. Thank you. >> Speaker 1: Thanks again for all of you. I know that people are sitting all the way up there as well, which is remarkable. I hope you can actually see some of the things that Sunil and the team will actually bring about, talk about live demos. We do real stuff here, which is truly live. I think one of the requests that I have is help us help you navigate the digital disruption that's upon you and your competitive landscape that's around you that's really creating that disruption. Thank you again for being here, and welcome again to Acropolis. >> Speaker 3: Ladies and gentlemen, please welcome Chief Product and Development Officer, Nutanix Sunil Potti. >> Sunil Potti: Okay, so I'm going to just jump right in because I know a bunch of you guys are here to see the product as well. We are a lot of demos lined up for you guys, and we'll try to mix in the slides, and the demos as well. Here's just an example of the things I always bring up in these conferences to look around, and say in the last few months, are we making progress in simplifying infrastructure? You guys have heard this again and again, this has been our mantra from the beginning, that the hotter things get, the more differentiated a company like Nutanix can be if we can make things simple, or keep things simple. Even though I like this a lot, we found something a little bit more interesting, I thought, by our European marketing team. If you guys need these tea bags, which you will need pretty soon. It's a new tagline for the company, not really. I thought it was apropos. But before I get into the product and the demos, to give you an idea. Every time I go to an event you find ways to memorialize the event. You meet people, you build relationships, you see something new. Last night, nothing to do with the product, I sat beside someone. It was a customer event. I had no idea who I was sitting beside. He was a speaker. How many of you guys know him, by the way? Sir Ranulph Fiennes. Few hands. Good for you. I had no idea who I was sitting beside. I said, "Oh, somebody called Sir. I should be respectful." It's kind of hard for me to be respectful, but I tried. He says, "No, I didn't do anything in the sense. My grandfather was knighted about 100 years ago because he was the governor of Antigua. And when he dies, his son becomes." And apparently Sir Ranulph's dad also died in the war, and so that's how he is a sir. But then I started looking it up because he's obviously getting ready to present. And the background for him is, in my opinion, even though the term goes he's the World's Greatest Living Explorer. I would have actually called it the World's Number One Stag, and I'll tell you why. Really, you should go look it up. So this guy, at the age of 21, gets admitted to Special Forces. If you're from the UK, this is as good as it gets, SAS. Six, seven years into it, he rebels, helps out his local partner because he doesn't like a movie who's building a dam inside this pretty village. And he goes and blows up a dam, and he's thrown out of that Special Forces. Obviously he's in demolitions. Goes all the way. This is the '60's, by the way. Remember he's 74 right now. The '60's he goes to Oman, all by himself, as the only guy, only white guy there. And then around the '70's, he starts truly exploring, truly exploring. And this is where he becomes really, really famous. You have to go see this in real life, when he sees these videos to really appreciate the impact of this guy. All by himself, he's gone across the world. He's actually gone across Antarctica. Now he tells me that Antarctica is the size of China and India put together, and he was prepared for -50 to 60 degrees, and obviously he got -130 degrees. Again, you have to see the videos, see his frostbite. Two of his fingers are cut off, by the way. He hacksawed them himself. True story. And then as he, obviously, aged, his body couldn't keep up with him, but his will kept up with him. So after a recent heart attack, he actually ran seven marathons. But most importantly, he was telling me this story, at 65 he wanted to do something different because his body was letting him down. He said, "Let me do something easy." So he climbed Mount Everest. My point being, what is this related to Nutanix? Is that if Nutanix is a company, without technology, allows to spend more time on life, then we've accomplished a piece of our vision. So keep that in mind. Keep that in mind. Now comes the boring part, which is the product. The why, what, how of Nutanix. Neeris talked about this. We have two acts in this company. Invisible Infrastructure was what we started off. You heard us talk about it. How did we do it? Using one-click technologies by converging infrastructure, computer storage, virtualization, et cetera, et cetera. What we are now about is about changing the game. Saying that just like we'd applicated what powers Google and Amazon inside the data center, could we now make them all invisible? Whether it be inside or outside, could we now make clouds invisible? Clouds could be made invisible by a new level of convergence, not about computer storage, but converging public and private, converging CAPEX and OPEX, converging consumption models. And there, beyond our core products, Acropolis and Prism, are these new products. As you know, we have this core thesis, right? The core thesis says what? Predictable workloads will stay inside the data center, elastic workloads will go outside, as long as the experience on both sides is the same. So if you can genuinely have a cloud-like experience delivered inside a data center, then that's the right a- >> Speaker 1: Genuinely have a cloud like experience developed inside the data center. And that's the right answer of predictable workloads. Absolutely the answer of elastic workloads, doesn't matter whether security or compliance. Eventually a public cloud will have a data center right beside your region, whether through local partner or a top three cloud partner. And you should use it as your public cloud of choice. And so, our goal is to ensure that those two worlds are converged. And that's what Calm does, and we'll talk about that. But at the same time, what we found in late 2015, we had a bunch of customers come to us and said "Look, I love this, I love the fact that you're going to converge public and private and all that good stuff. But I have these environments and these apps that I want to be delivered as a service but I want the same operational tooling. I don't want to have two different environments but I don't want to manage my data centers. Especially my secondary data centers, DR data centers." And that's why we created Xi, right? And you'll hear a lot more about this, obviously it's going to start off in the U.S but very rapidly launch in Europe, APJ globally in the next 9-12 months. And so we'll spend some quality time on those products as well today. So, from the journey that we're at, we're starting with the score cloud that essentially says "Look, your public and private needs to be the same" We call that the first instantiation of your cloud architectures and we're essentially as a company, want to build this enterprise cloud operating system as a fabric across public and private. But that's just the starting point. The starting point evolves to the score architecture that we believe that the cloud is being dispersed. Just like you have a public and a private cloud in the core data centers and so forth, you'll need a similar experience inside your remote office branch office, inside your DR data centers, inside your branches, and it won't stop there. It'll go all the way to the edge. All we're already seeing this right? Not just in the army where your forward operating bases in Afghanistan having a three note cluster sitting inside a tent. But we're seeing this in a variety of enterprise scenarios. And here's an example. So, here's a customer, global oil and gas company, has couple of primary data centers running Nutanix, uses GCP as a core public cloud platform, has a whole bunch of remote offices, but it also has this interesting new edge locations in the form of these small, medium, large size rigs. And today, they're in the process of building a next generation cloud architecture that's completely dispersed. They're using one node, coming out on version 5.5 with Nutanix. They're going to use two nodes, they're going to throw us three nods, multicultural architectures. Day one, they're going to centrally manage it using Prism, with one click upgrades, right? And then on top of that, they're also now provisioning using Calm, purpose built apps for the various locations. So, for example, there will be a re control app at the edge, there's an exploration data lag in Google and so forth. My point being that increasingly this architecture that we're talking about is happening in real time. It's no longer just an existing cellular civilization data center that's being replatformed to look like a private cloud and so forth, or a hybrid cloud. But the fact that you're going into this multi cloud era is getting excel bated, the more someone consumes AWL's GCP or any public cloud, the more they're excel bating their internal transformation to this multi cloud architecture. And so that's what we're going to talk about today, is this construct of ONE OS and ONE Click, and when you think about it, every company has a standard stack. So, this is the only slide you're going to see from me today that's a stack, okay? And if you look at the new release coming out, version 5.5, it's coming out imminently, easiest way to say it is that it's got a ton of functionality. We've jammed as much as we can onto one slide and then build a product basically, okay? But I would encourage you guys to check out the release, it's coming out shortly. And we can go into each and every feature here, we'd be spending a lot of time but the way that we look at building Nutanix products as many of you know, it is not feature at a time. It's experience at a time. And so, when you really look at Nutanix using a lateral view, and that's how we approach problems with our customers and partners. We think about it as a life cycle, all the way from learning to using, operating, and then getting support and experiences. And today, we're going to go through each of these stages with you. And who better to talk about it than our local version of an architect, Steven Poitras please come up on stage. I don't know where you are, Steven come on up. You tucked your shirt in? >> Speaker 2: Just for you guys today. >> Speaker 1: Okay. Alright. He's sort of putting on his weight. I know you used a couple of tight buckles there. But, okay so Steven so I know we're looking for the demo here. So, what we're going to do is, the first step most of you guys know this, is we've been quite successful with CE, it's been a great product. How many of you guys like CE? Come on. Alright. I know you had a hard time downloading it yesterday apparently, there's a bunch of guys had a hard time downloading it. But it's been a great way for us not just to get you guys to experience it, there's more than 25,000 downloads and so forth. But it's also a great way for us to see new features like IEME and so forth. So, keep an eye on CE because we're going to if anything, explode the way that we actually use as a way to get new features out in the next 12 months. Now, one thing beyond CE that we did, and this was something that we did about ... It took us about 12 months to get it out. While people were using CE to learn a lot, a lot of customers were actually getting into full blown competitive evals, right? Especially with hit CI being so popular and so forth. So, we came up with our own version called X-Ray. >> Speaker 2: Yup. >> Speaker 1: What does X-Ray do before we show it? >> Speaker 2: Yeah. Absolutely. So, if we think about back in the day we were really the only ACI platform out there on the market. Now there are a few others. So, to basically enable the customer to objectively test these, we came out with X-Ray. And rather than talking about the slide let's go ahead and take a look. Okay, I think it's ready. Perfect. So, here's our X-Ray user interface. And essentially what you do is you specify your targets. So, in this case we have a Nutanix 80150 as well as some of our competitors products which we've actually tested. Now we can see on the left hand side here we see a series of tests. So, what we do is we go through and specify certain workloads like OLTP workloads, database colocation, and while we do that we actually inject certain test cases or scenarios. So, this can be snapshot or component failures. Now one of the key things is having the ability to test these against each other. So, what we see here is we're actually taking a OLTP workload where we're running two virtual machines, and then we can see the IOPS OLTP VM's are actually performing here on the left hand side. Now as we're actually go through this test we perform a series of snapshots, which are identified by these red lines here. Now as you can see, the Nutanix platform, which is shown by this blue line, is purely consistent as we go through this test. However, our competitor's product actually degrades performance overtime as these snapshots are taken. >> Speaker 1: Gotcha. And some of these tests by the way are just not about failure or benchmarking, right? It's a variety of tests that we have that makes real life production workloads. So, every couple of months we actually look at our production workloads out there, subset those two cases and put it into X-Ray. So, X-Ray's one of those that has been more recently announced into the public. But it's already gotten a lot of update. I would strongly encourage you, even if you an existing Nutanix customer. It's a great way to keep us honest, it's a great way for you to actually expand your usage of Nutanix by putting a lot of these real life tests into production, and as and when you look at new alternatives as well, there'll be certain situations that we don't do as well and that's a great way to give us feedback on it. And so, X-Ray is there, the other one, which is more recent by the way is a fact that most of you has spent many days if not weeks, after you've chosen Nutanix, moving non-Nutanix workloads. I.e. VMware, on three tier architectures to Atrio Nutanix. And to do that, we took a hard look and came out with a new product called Xtract. >> Speaker 2: Yeah. So essentially if we think about what Nutanix has done for the data center really enables that iPhone like experience, really bringing it simplicity and intuitiveness to the data center. Now what we wanted to do is to provide that same experience for migrating existing workloads to us. So, with Xtract essentially what we've done is we've scanned your existing environment, we've created design spec, we handled the migration process ... >> Steven: ... environment, we create a design spec. We handle for the migration process as well as the cut over. Now, let's go ahead and take a look in our extract user interface here. What we can see is we have a source environment. In this case, this is a VC environment. This can be any VC, whether it's traditional three tier or hypherconverged. We also see our Nutanix target environments. Essentially, these are our AHV target clusters where we're going to be migrating the data and performing the cut over to you. >> Speaker 2: Gotcha. Steven: The first thing that we do here is we go ahead and create a new migration plan. Here, I'm just going to specify this as DB Wave 2. I'll click okay. What I'm doing here is I'm selecting my target Nutanix cluster, as well as my target Nutanix container. Once I'll do that, I'll click next. Now in this case, we actually like to do it big. We're actually going to migrate some production virtual machines over to this target environment. Here, I'm going to select a few windows instances, which are in our database cluster. I'll click next. At this point, essentially what's occurring is it's going through taking a look at these virtual machines as well as taking a look at the target environment. It takes a look at the resources to ensure that we actually have enough, an ample capacity to facilitate the workload. The next thing we'll do is we'll go ahead and type in our credentials here. This is actually going to be used for logging into the virtual machine. We can do a new device driver installation, as well as get any static IP configuration. Well specify our network mapping. Then from there, we'll click next. What we'll do is we'll actually save and start. This will go through create the migration plan. It'll do some analysis on these virtual machines to ensure that we can actually log in before we actually start migrating data. Here we have a migration, which has been in progress. We can see we have a few virtual machines, obviously some Linux, some Windows here. We've cut over a few. What we do to actually cut over these VMS, is go ahead select the VMS- Speaker 2: This is the actual task of actually doing the final stage of cut over. Steven: Yeah, exactly. That's one of the nice things. Essentially, we can migrate the data whenever we want. We actually hook into the VADP API's to do this. Then every 10 minutes, we send over a delta to sync the data. Speaker 2: Gotcha, gotcha. That's how one click migration can now be possible. This is something that if you guys haven't used this, this has been out in the wild, just for a month or so. Its been probably one of our bestselling, because it's free, bestselling features of the recent product release. I've had customers come to me and say, "Look, there are situations where its taken us weeks to move data." That is now minutes from the operator perspective. Forget where the director, or the VP, it's the line architecture and operator that really loves these tools, which is essentially the core of Nutanix. That's one of our core things, is to make sure that if we can keep the engineer and the architect truly happy, then everything else will be fine for us, right? That's extract. Then we have a lot of things, right? We've done the usual things, there's a tunnel functionality on day zero, day one, day two, kind of capabilities. Why don't we start with something around Prism Central, now that we can do one click PC installs? We can do PC scale outs, we can go from managing thousands of VMS, tens of thousands of VMS, while doing all the one click operations, right? Steven: Yep. Speaker 2: Why don't we take a quick look at what's new in Prism Central? Steven: Yep. Absolutely. Here, we can see our Prism element interface. As you mentioned, one of the key things we added here was the ability to deploy Prism Central very simply just with a few clicks. We'll actually go through a distributed PC scale of deployment here. Here, we're actually going to deploy, as this is a new instance. We're going to select our 5.5 version. In this case, we're going to deploy a scale out Prism Central cluster. Obviously, availability and up-time's very critical for us, as we're mainly distributed systems. In this case we're going to deploy a scale-out PC cluster. Here we'll select our number of PC virtual machines. Based upon the number of VMS, we can actually select our size of VM that we'd deploy. If we want to deploy 25K's report, we can do that as well. Speaker 2: Basically a thousand to tens of thousands of VM's are possible now. Steven: Yep. That's a nice thing is you can start small, and then scale out as necessary. We'll select our PC network. Go ahead and input our IP address. Now, we'll go to deploy. Now, here we can see it's actually kicked off the deployment, so it'll go provision these virtual machines to apply the configuration. In a few minutes, we'll be up and running. Speaker 2: Right. While Steven's doing that, one of the things that we've obviously invested in is a ton of making VM operations invisible. Now with Calm's, what we've done is to up level that abstraction. Two applications. At the end of the day, more and more ... when you go to AWS, when you go to GCP, you go to [inaudible 01:04:56], right? The level of abstractions now at an app level, it's cloud formations, and so forth. Essentially, what Calm's able to do is to give you this marketplace that you can go in and self-service [inaudible 01:05:05], create this internal cloud like environment for your end users, whether it be business owners, technology users to self-serve themselves. The process is pretty straightforward. You, as an operator, or an architect, or [inaudible 01:05:16] create these blueprints. Consumers within the enterprise, whether they be self-service users, whether they'll be end business users, are able to consume them for a simple marketplace, and deploy them on whether it be a private cloud using Nutanix, or public clouds using anything with public choices. Then, as a single frame of glass, as operators you're doing conversed operations, at an application centric level between [inaudible 01:05:41] across any of these clouds. It's this combination of producer, consumer, operator in a curated sense. Much like an iPhone with an app store. It's the core construct that we're trying to get with Calm to up level the abstraction interface across multiple clouds. Maybe we'll do a quick demo of this, and then get into the rest of the stuff, right? Steven: Sure. Let's check it out. Here we have our Prism Central user interface. We can see we have two Nutanix clusters, our cloudy04 as well as our Power8 cluster. One of the key things here that we've added is this apps tab. I'm clicking on this apps tab, we can see that we have a few [inaudible 01:06:19] solutions, we have a TensorFlow solution, a [inaudible 01:06:22] et cetera. The nice thing about this is, this is essentially a marketplace where vendors as well as developers could produce these blueprints for consumption by the public. Now, let's actually go ahead and deploy one of these blueprints. Here we have a HR employment engagement app. We can see we have three different tiers of services part of this. Speaker 2: You need a lot of engagement at HR, you know that. Okay, keep going. Steven: Then the next thing we'll do here is we'll go and click on. Based upon this, we'll specify our blueprint name, HR app. The nice thing when I'm deploying is I can actually put in back doors. We'll click clone. Now what we can see here is our blueprint editor. As a developer, I could actually go make modifications, or even as an in-user given the simple intuitive user interface. Speaker 2: This is the consumers side right here, but it's also the [inaudible 01:07:11]. Steven: Yep, absolutely. Yeah, if I wanted to make any modifications, I could select the tier, I could scale out the number of instances, I could modify the packages. Then to actually deploy, all I do is click launch, specify HR app, and click create. Speaker 2: Awesome. Again, this is coming in 5.5. There's one other feature, by the way, that is coming in 5.5 that's surrounding Calm, and Prism Pro, and everything else. That seems to be a much awaited feature for us. What was that? Steven: Yeah. Obviously when we think about multi-tenant, multi-cloud role based access control is a very critical piece of that. Obviously within the organization, we're going to have multiple business groups, multiple units. Our back's a very critical piece. Now, if we go over here to our projects, we can see in this scenario we just have a single project. What we've added is if you want to specify certain roles, in this case we're going to add our good friend John Doe. We can add them, it could be a user or group, but then we specify their role. We can give a developer the ability to edit and create these blueprints, or consumer the ability to actually provision based upon. Speaker 2: Gotcha. Basically in 5.5, you'll have role based access control now in Prism and Calm burned into that, that I believe it'll support custom role shortly after. Steven: Yep, okay. Speaker 2: Good stuff, good stuff. I think this is where the Nutanix guys are supposed to clap, by the way, so that the rest of the guys can clap. Steven: Thank you, thank you. Okay. What do we have? Speaker 2: We have day one stuff, obviously there's a ton of stuff that's coming in core data path capabilities that most of you guys use. One of the most popular things is synchronous replication, especially in Europe. Everybody wants to do [Metro 01:08:49] for whatever reason. But we've got something new, something even more enhanced than Metro, right? Steven: Yep. Speaker 2: Do you want to talk a little bit about it? Steven: Yeah, let's talk about it. If we think about what we had previously, we started out with a synchronous replication. This is essentially going to be your higher RPO. Then we moved into Metro cluster, which was RPO zero. Those are two ins of the gamete. What we did is we introduced new synchronous replication, which really gives you the best of both worlds where you have very, very decreased RPO's, but zero impact in line mainstream performance. Speaker 2: That's it. Let's show something. Steven: Yeah, yeah. Let's do it. Here, we're back at our Prism Element interface. We'll go over here. At this point, we provisioned our HR app, the next thing we need to do is to protect that data. Let's go here to protection domain. We'll create a new PD for our HR app. Speaker 2: You clearly love HR. Steven: Spent a lot of time there. Speaker 2: Yeah, yeah, yeah. Steven: Here, you can see we have our production lamp DBVM. We'll go ahead and protect that entity. We can see that's protected. The next thing we'll do is create a schedule. Now, what would you say would be a good schedule we should actually shoot for? Speaker 2: I don't know, 15 minutes? Steven: 15 minutes is not bad. But I ... Section 7 of 13 [01:00:00 - 01:10:04] Section 8 of 13 [01:10:00 - 01:20:04] (NOTE: speaker names may be different in each section) Speaker 1: ... 15 minutes. Speaker 2: 15 minutes is not bad, but I think the people here deserve much better than that, so I say let's shoot for ... what about 15 seconds? Speaker 1: Yeah. They definitely need a bathroom break, so let's do 15 seconds. Speaker 2: Alright, let's do 15 seconds. Speaker 1: Okay, sounds good. Speaker 2: K. Then we'll select our retention policy and remote cluster replicate to you, which in this case is wedge. And we'll go ahead and create the schedule here. Now at this point we can see our protection domain. Let's go ahead and look at our entities. We can see our database virtual machine. We can see our 15 second schedule, our local snapshots, as well as we'll start seeing our remote snapshots. Now essentially what occurs is we take two very quick snapshots to essentially see the initial data, and then based upon that then we'll start taking our continuous 15 second snaps. Speaker 1: 15 seconds snaps, and obviously near sync has less of impact than synchronous, right? From an architectural perspective. Speaker 2: Yeah, and that's a nice thing is essentially within the cluster it's truly pure synchronous, but externally it's just a lagged a-sync. Speaker 1: Gotcha. So there you see some 15 second snapshots. So near sync is also built into five-five, it's a long-awaited feature. So then, when we expand in the rest of capabilities, I would say, operations. There's a lot of you guys obviously, have started using Prism Pro. Okay, okay, you can clap. You can clap. It's okay. It was a lot of work, by the way, by the core data pad team, it was a lot of time. So Prism Pro ... I don't know if you guys know this, Prism Central now run from zero percent to more than 50 percent attach on install base, within 18 months. And normally that's a sign of true usage, and true value being supported. And so, many things are new in five-five out on Prism Pro starting with the fact that you can do data[inaudible 01:11:49] base lining, alerting, so that you're not capturing a ton of false positives and tons of alerts. We go beyond that, because we have this core machine-learning technology power, we call it cross fit. And, what we've done is we've used that as a foundation now for pretty much all kinds of operations benefits such as auto RCA, where you're able to actually map to particular [inaudible 01:12:12] crosses back to who's actually causing it whether it's the network, a computer, and so forth. But then the last thing that we've also done in five-five now that's quite different shading, is the fact that you can now have a lot of these one-click recommendations and remediations, such as right-sizing, the fact that you can actually move around [inaudible 01:12:28] VMs, constrained VMs, and so forth. So, I now we've packed a lot of functionality in Prism Pro, so why don't we spend a couple of minutes quickly giving a sneak peak into a few of those things. Speaker 2: Yep, definitely. So here we're back at our Prism Central interface and one of the things we've added here, if we take a look at one of our clusters, we can see we have this new anomalies portion here. So, let's go ahead and select that and hop into this. Now let's click on one of these anomaly events. Now, essentially what the system does is we monitor all the entities and everything running within the system, and then based upon that, we can actually determine what we expect the band of values for these metrics to be. So in this scenario, we can see we have a CPU usage anomaly event. So, normal time, we expect this to be right around 86 to 100 percent utilization, but at this point we can see this is drastically dropped from 99 percent to near zero. So, this might be a point as an administrator that I want to go check out this virtual machine, ensure that certain services and applications are still up and running. Speaker 1: Gotcha, and then also it changes the baseline based on- Speaker 2: Yep. Yeah, so essentially we apply machine-learning techniques to this, so the system will dynamically adjust based upon the value adjustment. Speaker 1: Gotcha. What else? Speaker 2: Yep. So the other thing here that we mentioned was capacity planning. So if we go over here, we can take a look at our runway. So in this scenario we have about 30 days worth of runway, which is most constrained by memory. Now, obviously, more nodes is all good for everyone, but we also want to ensure that you get the maximum value on your investment. So here we can actually see a few recommendations. We have 11 overprovision virtual machines. These are essentially VMs which have more resources than are necessary. As well as 19 inactives, so these are dead VMs essentially that haven't been powered on and not utilized. We can also see we have six constrained, as well as one bully. So, constrained VMs are essentially VMs which are requesting more resources than they actually have access to. This could be running at 100 percent CPU utilization, or 100 percent memory, or storage utilization. So we could actually go in and modify these. Speaker 1: Gotcha. So these are all part of the auto remediation capabilities that are now possible? Speaker 2: Yeah. Speaker 1: What else, do you want to take reporting? Speaker 2: Yeah. Yeah, so I know reporting is a very big thing, so if we think about it, we can't rely on an administrator to constantly go into Prism. We need to provide some mechanism to allow them to get emailed reports. So what we've done is we actually autogenerate reports which can be sent via email. So we'll go ahead and add one of these sample reports which was created today. And here we can actually get specific detailed information about our cluster without actually having to go into Prism to get this. Speaker 1: And you can customize these reports and all? Speaker 2: Yep. Yeah, if we hop over here and click on our new report, we can actually see a list of views we could add to these reports, and we can mix and match and customize as needed. Speaker 1: Yeah, so that's the operational side. Now we also have new services like AFS which has been quite popular with many of you folks. We've had hundreds of customers already on it live with SMB functionality. You want to show a couple of things that is new in five-five? Speaker 2: Yeah. Yep, definitely. So ... let's wait for my screen here. So one of the key things is if we looked at that runway tab, what we saw is we had over a year's worth of storage capacity. So, what we saw is customers had the requirement for filers, they had some excess storage, so why not actually build a software featured natively into the cluster. And that's essentially what we've done with AFS. So here we can see we have our AFS cluster, and one of the key things is the ability to scale. So, this particular cluster has around 3.1 or 3.16 billion files, which are running on this AFS cluster, as well as around 3,000 active concurrent sessions. Speaker 1: So basically thousands of concurrent sessions with billions of files? Speaker 2: Yeah, and the nice thing with this is this is actually only a four node Nutanix cluster, so as the cluster actually scales, these numbers will actually scale linearly as a function of those nodes. Speaker 1: Gotcha, gotcha. There's got to be one more bullet here on this slide so what's it about? Speaker 2: Yeah so, obviously the initial use case was realistically for home folders as well as user profiles. That was a good start, but it wasn't the only thing. So what we've done is we've actually also introduced important and upcoming release of NFS. So now you can now use NFS to also interface with our [crosstalk 01:16:44]. Speaker 1: NFS coming soon with AFS by the way, it's a big deal. Big deal. So one last thing obviously, as you go operationalize it, we've talked a lot of things on features and functions but one of the cool things that's always been seminal to this company is the fact that we all for really good customer service and support experience. Right now a lot of it is around the product, the people, the support guys, and so forth. So fundamentally to the product we have found ways using Pulse to instrument everything. With Pulse HD that has been allowed for a little bit longer now. We have fine grain [inaudible 01:17:20] around everything that's being done, so if you turn on this functionality you get a lot of information now that we built, we've used when you make a phone call, or an email, and so forth. There's a ton of context now available to support you guys. What we've now done is taken that and are now externalizing it for your own consumption, so that you don't have to necessarily call support. You can log in, look at your entire profile across your own alerts, your own advisories, your own recommendations. You can look at collective intelligence now that's coming soon which is the fact that look, here are 50 other customers just like you. These are the kinds of customers that are using workloads like you, what are their configuration profiles? Through this centralized customer insights portal you going to get a lot more insight, not just about your own operations, but also how everybody else is also using it. So let's take a quick look at that upcoming functionality. Speaker 2: Yep. Absolutely. So this is our customer 360 portal, so as [inaudible 01:18:18] mentioned, as a customer I can actually log in here, I can get a high-level overview of my existing environment, my cases, the status of those cases, as well as any relevant announcements. So, here based upon my cluster version, if there's any updates which are available, I can then see that here immediately. And then one of the other things that we've added here is this insights page. So essentially this is information that previously support would leverage to essentially proactively look out to the cluster, but now we've exposed this to you as the customer. So, clicking on this insights tab we can see an overview of our environment, in this case we have three Nutanix clusters, right around 550 virtual machines, and over here what's critical is we can actually see our cases. And one of the nice things about this is these area all autogenerated by the cluster itself, so no human interaction, no manual intervention was required to actually create these alerts. The cluster itself will actually facilitate that, send it over to support, and then support can get back out to you automatically. Speaker 1: K, so look for customer insights coming soon. And obviously that's the full life cycle. One cool thing though that's always been unique to Nutanix was the fact that we had [inaudible 01:19:28] security from day one built-in. And [inaudible 01:19:31] chunk of functionality coming in five-five just around this, because every release we try to insert more and more security capabilities, and the first one is around data. What are we doing? Speaker 2: Yeah, absolutely. So previously we had support for data at rest encryption, but this did have the requirement to leverage self-encrypting drives. These can be very expensive, so what we've done, typical to our fashion is we've actually built this in natively via software. So, here within Prism Element, I can go to data at rest encryption, and then I can go and edit this configuration here. Section 8 of 13 [01:10:00 - 01:20:04] Section 9 of 13 [01:20:00 - 01:30:04] (NOTE: speaker names may be different in each section) Steve: Encryption and then I can go and edit this configuration here. From here I could add my CSR's. I can specify KMS server and leverage native software base encryption without the requirement of SED's. Sunil: Awesome. So data address encryption [inaudible 01:20:15] coming soon, five five. Now data security is only one element, the other element was around network security obviously. We've always had this request about what are we doing about networking, what are we doing about network, and our philosophy has always been simple and clear, right. It is that the problem in networking is not the data plan. Problem in networking is the control plan. As in, if a packing loss happens to the top of an ax switch, what do we do? If there's a misconfigured board, what do we do? So we've invested a lot in full blown new network visualization that we'll show you a preview of that's all new in five five, but then once you can visualize you can take action, so you can actually using our netscape API's now in five five. You can optovision re lands on the switch, you can update reps on your load balancing pools. You can update obviously rules on your firewall. And then we've taken that to the next level, which is beyond all that, just let you go to AWS right now, what do you do? You take 100 VM's, you put it in an AWS security group, boom. That's how you get micro segmentation. You don't need to buy expensive products, you don't need to virtualize your network to get micro segmentation. That's what we're doing with five five, is built in one click micro segmentation. That's part of the core product, so why don't we just quickly show that. Okay? Steve: Yeah, let's take a look. So if we think about where we've been so far, we've done the comparison test, we've done a migration over to a Nutanix. We've deployed our new HR app. We've protected it's data, now we need to protect the network's. So one of the things you'll see that's new here is this security policies. What we'll do is we'll actually go ahead and create a new security policy and we'll just say this is HR security policy. We'll specify the application type, which in this case is HR. Sunil: HR of course. Steve: Yep and we can see our app instance is automatically populated, so based upon the number of running instances of that blueprint, that would populate that drop-down. Now we'll go ahead and click next here and what we can see in the middle is essentially those three tiers that composed that app blueprint. Now one of the important things is actually figuring out what's trying to communicate with this within my existing environment. So if I take a look over here on my left hand side, I can essentially see a few things. I can see a Ha Proxy load balancer is trying to communicate with my app here, that's all good. I want to allow that. I can see some sort of monitoring service is trying to communicate with all three of the tiers. That's good as well. Now the last thing I can see here is this IP address which is trying to access my database. Now, that's not designed and that's not supposed to happen, so what we'll do is we'll actually take a look and see what it's doing. Now hopping over to this database virtual machine or the hack VM, what we can see is it's trying to perform a brute force log in attempt to my MySQL database. This is not good. We can see obviously it can connect on the socket, however, it hasn't guessed the right password. In order to lock that down, we'll go back to our policies here and we're going to click deny. Once we've done that, we'll click next and now we'll go to Apply Now. Now we can see our newly created security policy and if we hop back over to this VM, we can now see it's actually timing out and what this means is that it's not able to communicate with that database virtual machine due to micro segmentation actively blocking that request. Sunil: Gotcha and when you go back to the Prism site, essentially what we're saying now is, it's as simple as that, to set up micro segmentation now inside your existing clusters. So that's one click micro segmentation, right. Good stuff. One other thing before we let Steve walk off the stage and then go to the bathroom, but is you guys know Steve, you know he spends a lot time in the gym, you do. Right. He and I share cubes right beside each other by the way just if you ever come to San Jose Nutanix corporate headquarters, you're always welcome. Come to the fourth floor and you'll see Steve and Sunil beside each other, most of the time I'm not in the cube, most of the time he's in the gym. If you go to his cube, you'll see all kinds of stuff. Okay. It's true, it's true, but the reason why I brought this up, was Steve recently became a father, his first kid. Oh by the way this is, clicker, this is how his cube looks like by the way but he left his wife and his new born kid to come over here to show us a demo, so give him a round of applause. Thank you, sir. Steve: Cool, thanks, Sunil. That was fun. Sunil: Thank you. Okay, so lots of good stuff. Please try out five five, give us feedback as you always do. A lot of sessions, a lot of details, have fun hopefully for the rest of the day. To talk about how their using Nutanix, you know here's one of our favorite customers and partners. He normally comes with sunglasses, I've asked him that I have to be the best looking guy on stage in my keynotes, so he's going to try to reduce his charm a little bit. Please come on up, Alessandro. Thank you. Alessandro R.: I'm delighted to be here, thank you so much. Sunil: Maybe we can stand here, tell us a little bit about Leonardo. Alessandro R.: About Leonardo, Leonardo is a key actor of the aerospace defense and security systems. Helicopters, aircraft, the fancy systems, the fancy electronics, weapons unfortunately, but it's also a global actor in high technology field. The security information systems division that is the division I belong to, 3,000 people located in Italy and in UK and there's several other countries in Europe and the U.S. $1 billion dollar of revenue. It has a long a deep experience in information technology, communications, automation, logical and physical security, so we have quite a long experience to expand. I'm in charge of the security infrastructure business side. That is devoted to designing, delivering, managing, secure infrastructures services and secure by design solutions and platforms. Sunil: Gotcha. Alessandro R.: That is. Sunil: Gotcha. Some of your focus obviously in recent times has been delivering secure cloud services obviously. Alessandro R.: Yeah, obviously. Sunil: Versus traditional infrastructure, right. How did Nutanix help you in some of that? Alessandro R.: I can tell something about our recent experience about that. At the end of two thousand ... well, not so recent. Sunil: Yeah, yeah. Alessandro R.: At the end of 2014, we realized and understood that we had to move a step forward, a big step and a fast step, otherwise we would drown. At that time, our newly appointed CEO confirmed that the IT would be a core business to Leonardo and had to be developed and grow. So we decided to start our digital transformation journey and decided to do it in a structured and organized way. Having clear in mind our targets. We launched two programs. One analysis program and one deployments programs that were essentially transformation programs. We had to renew ourselves in terms of service models, in terms of organization, in terms of skills to invest upon and in terms of technologies to adopt. We were stacking a certification of technologies that adopted, companies merged in the years before and we have to move forward and to rationalize all these things. So we spent a lot of time analyzing, comparing technologies, and evaluating what would fit to us. We had two main targets. The first one to consolidate and centralize the huge amount of services and infrastructure that were spread over 52 data centers in Italy, for Leonardo itself. The second one, to update our service catalog with a bunch of cloud services, so we decided to update our data centers. One of our building block of our new data center architecture was Nutanix. We evaluated a lot, we had spent a lot of time in analysis, so that wasn't a bet, but you are quite pioneers at those times. Sunil: Yeah, you took a lot of risk right as an Italian company- Alessandro R.: At this time, my colleague used to say, "Hey, Alessandro, think it over, remember that not a CEO has ever been fired for having chose IBM." I apologize, Bob, but at that time, when Nutanix didn't run on [inaudible 01:29:27]. We have still a good bunch of [inaudible 01:29:31] in our data center, so that will be the chance to ... Audience Member: [inaudible 01:29:37] Alessandro R.: So much you must [inaudible 01:29:37] what you announced it. Sunil: So you took a risk and you got into it. Alessandro R.: Yes, we got into, we are very satisfied with the results we have reached. Sunil: Gotcha. Alessandro R.: Most of the targets we expected to fulfill have come and so we are satisfied, but that doesn't mean that we won't go on asking you a big discount ... Sunil: Sure, sure, sure, sure. Alessandro R.: On price list. Sunil: Sure, sure, so what's next in terms of I know there are some interesting stuff that you're thinking. Alessandro R.: The next- Section 9 of 13 [01:20:00 - 01:30:04] Section 10 of 13 [01:30:00 - 01:40:04] (NOTE: speaker names may be different in each section) Speaker 1: So what's next, in terms of I know you have some interesting stuff that you're thinking of. Speaker 2: The next, we have to move forward obviously. The name Leonardo is inspired to Leonardo da Vinci, it was a guy that in terms of innovation and technology innovation had some good ideas. And so, I think, that Leonardo with Nutanix could go on in following an innovation target and following really mutual ... Speaker 1: Partnership. Speaker 2: Useful partnership, yes. We surely want to investigate the micro segmentation technologies you showed a minute ago because we have some looking, particularly by the economical point of view ... Speaker 1: Yeah, the costs and expenses. Speaker 2: And we have to give an alternative to the technology we are using. We want to use more intensively AHV, again as an alternative solution we are using. We are selecting a couple of services, a couple of quite big projects to build using AHV talking of Calm we are very eager to understand the announcement that they are going to show to all of us because the solution we are currently using is quite[crosstalk 01:31:30] Speaker 1: Complicated. Speaker 2: Complicated, yeah. To move a step of automation to elaborate and implement[inaudible 01:31:36] you spend 500 hours of manual activities that's nonsense so ... Speaker 1: Manual automation. Speaker 2: (laughs) Yes, and in the end we are very interested also in the prism features, mostly the new features that you ... Speaker 1: Talked about. Speaker 2: You showed yesterday in the preview because one bit of benefit that we received from the solution in the operations field means a bit plus, plus to our customer and a distinctive plus to our customs so we are very interested in that ... Speaker 1: Gotcha, gotcha. Thanks for taking the risk, thanks for being a customer and partner. Speaker 2: It has been a pleasure. Speaker 1: Appreciate it. Speaker 2: Bless you, bless you. Speaker 1: Thank you. So, you know obviously one OS, one click was one of our core things, as you can see the tagline doesn't stop there, it also says "any cloud". So, that's the rest of the presentation right now it's about; what are we doing, to now fulfill on that mission of one OS, one cloud, one click with one support experience across any cloud right? And there you know, we talked about Calm. Calm is not only just an operational experience for your private cloud but as you can see it's a one-click experience where you can actually up level your apps, set up blueprints, put SLA's and policies, push them down to either your AWS, GCP all your [inaudible 01:33:00] environments and then on day one while you can do one click provisioning, day two and so forth you will see new and new capabilities such as, one-click migration and mobility seeping into the product. Because, that's the end game for Calm, is to actually be your cloud autonomy platform right? So, you can choose the right cloud for the right workload. And talk about how they're building a multi cloud architecture using Nutanix and partnership a great pleasure to introduce my other good Italian friend Daniele, come up on stage please. From Telecom Italia Sparkle. How are you sir? Daniele: Not too bad thank you. Speaker 1: You want an espresso, cappuccino? Daniele: No, no later. Speaker 1: You all good? Okay, tell us a little about Sparkle. Daniele: Yeah, Sparkle is a fully owned subsidy of Telecom Italia group. Speaker 1: Mm-hmm (affirmative) Daniele: Spinned off in 2003 with the mission to develop the wholesale and multinational corporate and enterprise business abroad. Huge network, as you can see, hundreds of thousands of kilometers of fiber optics spread between; south east Asia to Europe to the U.S. Most of it proprietary part of it realized on some running cables. Part of them proprietary part of them bilateral part of them[inaudible 01:34:21] with other operators. 37 countries in which we have offices in the world, 700 employees, lean and clean company ... Speaker 1: Wow, just 700 employees for all of this. Daniele: Yep, 1.4 billion revenues per year more or less. Speaker 1: Wow, are you a public company? Daniele: No, fully owned by TIM so far. Speaker 1: So, what is your experience with Nutanix so far? Daniele: Well, in a way similar to what Alessandro was describing. To operate such a huge network as you can see before, and to keep on bringing revenues for the wholesale market, while trying to turn the bar toward the enterprise in a serious way. Couple of years ago the management team realized that we had to go through a serious transformation, not just technological but in terms of the way we build the services to our customers. In terms of how we let our customer feel the Sparkle experience. So, we are moving towards cloud but we are moving towards cloud with connectivity attached to it because it's in our cord as a provider of Telecom services. The paradigm that is driving today is the on-demand, is the dynamic and in order to get these things we need to move to software. Most of the network must become invisible as the Nutanix way. So, we decided instead of creating patchworks onto our existing systems, infrastructure, OSS, BSS and network systems, to build a new data center from scratch. And the paradigm being this new data center, the mantra was; everything is software designed, everything must be easy to manage, performance capacity planning, everything must be predictable and everything to be managed by few people. Nutanix is at the moment the baseline of this data center for what concern, let's say all the new networking tools, meaning as the end controllers that are taking care of automation and programmability of the network. Lifecycle service orchestrator, network orchestrator, cloud automation and brokerage platform and everything at the moment runs on AHV because we are forcing our vendors to certify their application on AHV. The only stack that is not at the moment AHV based is on a specific cloud platform because there we were really looking for the multi[inaudible 01:37:05]things that you are announcing today. So, we hope to do the migration as soon as possible. Speaker 1: Gotcha, gotcha. And then looking forward you're going to build out some more data center space, expose these services Daniele: Yeah. Speaker 1: For the customers as well as your internal[crosstalk 01:37:21] Daniele: Yeah, basically yes for sure we are going to consolidate, to invest more in the data centers in the markets on where we are leader. Italy, Turkey and Greece we are big data centers for [inaudible 01:37:33] and cloud, but we believe that the cloud with all the issues discussed this morning by Diraj, that our locality, customer proximity ... we think as a global player having more than 120 pops all over the world, which becomes more than 1000 in partnerships, that the pop can easily be transformed in a data center, so that we want to push the customer experience of what we develop in our main data centers closer to them. So, that we can combine traditional infrastructure as a service with the new connectivity services every single[inaudible 01:38:18] possibly everything running. Speaker 1: I mean, it makes sense, I mean I think essentially in some ways to summarize it's the example of an edge cloud where you're pushing a micro-cloud closer to the customers edge. Daniele: Absolutely. Speaker 1: Great stuff man, thank you so much, thank you so much. Daniele: Pleasure, pleasure. Thank you. Speaker 1: So, you know a couple of other things before we get in the next demo is the fact that in addition to Calm from multi-cloud management we have Zai, we talked about for extended enterprise capabilities and something for you guys to quickly understand why we have done this. In a very simple way is if you think about your enterprise data center, clearly you have a bunch of apps there, a bunch of public clouds and when you look at the paradigm you currently deploy traditional apps, we call them mode one apps, SAP, Exchange and so forth on your enterprise. Then you have next generation apps whether it be [inaudible 01:39:11] space, whether it be Doob or whatever you want to call it, lets call them mode two apps right? And when you look at these two types of apps, which are the predominant set, most enterprises have a combination of mode one and mode two apps, most public clouds primarily are focused, initially these days on mode two apps right? And when people talk about app mobility, when people talk about cloud migration, they talk about lift and shift, forklift [inaudible 01:39:41]. And that's a hard problem I mean, it's happening but it's a hard problem and ends up that its just not a one time thing. Once you've forklift, once you move you have different tooling, different operation support experience, different stacks. What if for some of your applications that mattered ... Section 10 of 13 [01:30:00 - 01:40:04] Section 11 of 13 [01:40:00 - 01:50:04] (NOTE: speaker names may be different in each section) Speaker 1: What if, for some of your applications that matter to you, that are your core enterprise apps that you can retain the same toolimg, the same operational experience and so forth. And that is what we achieve to do with Xi. It is truly making hybrid invisible, which is a next act for this company. It'll take us a few years to really fulfill the vision here, but the idea here is that you shouldn't think about public cloud as a different silo. You should think of it as an extension of your enterprise data centers. And for any services such as DR, whether it would be dev test, whether it be back-up, and so-forth. You can use the same tooling, same experience, get a public cloud-like capability without lift and shift, right? So it's making this lift and shift invisible by, soft of, homogenizing the data plan, the network plan, the control plan is what we really want to do with Xi. Okay? And we'll show you some more details here. But the simplest way to understand this is, think of it as the iPhone, right? D has mentioned this a little bit. This is how we built this experience. Views IOS as the core, IP, we wrap it up with a great package called the iPhone. But then, a few years into the iPhone era, came iTunes and iCloud. There's no apps, per se. That's fused into IOS. And similarly, think about Xi that way. The more you move VMs, into an internet-x environment, stuff like DR comes burnt into the fabric. And to give us a sneak peek into a bunch of the com and Xi cable days, let me bring back Binny who's always a popular guys on stage. Come on up, Binny. I'd be surprised in Binny untucked his shirt. He's always tucking in his shirt. Binny Gill: Okay, yeah. Let's go. Speaker 1: So first thing is com. And to show how we can actually deploy apps, not just across private and public clouds, but across multiple public clouds as well. Right? Binny Gill: Yeah, basically, you know com is about simplifying the disparity between various public clouds out there. So it's very important for us to be able to take one application blueprint and then quickly deploy in whatever cloud of your choice. Without understanding how one cloud is different. Speaker 1: Yeah, that's the goal. Binny Gill: So here, if you can see, I have market list. And by the way, this market list is a great partner community interest. And every single sort of apps come up here. Let me take a sample app here, Hadoop. And click launch. And now where do you want me to deploy? Speaker 1: Let's start at GCP. Binny Gill: GCP, okay. So I click on GCP, and let me give it a name. Hadoop. GCP. Say 30, right. Clear. So this is one click deployment of anything from our marketplace on to a cloud of your choice. Right now, what the system is doing, is taking the intent-filled description of what the application should look like. Not just the infrastructure level but also within the merchant machines. And it's creating a set of work flows that it needs to go deploy. So as you can see, while we were talking, it's loading the application. Making sure that the provisioning workflows are all set up. Speaker 1: And so this is actually, in real time it's actually extracting out some of the GCP requirements. It's actually talking to GCP. Setting up the constructs so that we can actually push it up on the GCP personally. Binny Gill: Right. So it takes a couple of minutes. It'll provision. Let me go back and show you. Say you worked with deploying AWS. So you Hadoop. Hit address. And that's it. So again, the same work flow. Speaker 1: Same process, I see. Binny Gill: It's going to now deploy in AWS. Speaker 1: See one of the keys things is that we actually extracted out all the isms of each of these clouds into this logical substrate. Binny Gill: Yep. Speaker 1: That you can now piggy-back off of. Binny Gill: Absolutely. And it makes it extremely simple for the average consumer. And you know we like more cloud support here over time. Speaker 1: Sounds good. Binny Gill: Now let me go back and show you an app that I had already deployed. Now 13 days ago. It's on GCP. And essentially what I want to show you is what is the view of the application. Firstly, it shows you the cost summary. Hourly, daily, and how the cost is going to look like. The other is how you manage it. So you know one click ways of upgrading, scaling out, starting, deleting, and so on. Speaker 1: So common actions, but independent of the type of clouds. Binny Gill: Independent. And also you can act with these actions over time. Right? Then services. It's learning two services, Hadoop slave and Hadoop master. Hadoop slave runs fast right now. And auditing. It shows you what are the important actions you've taken on this app. Not just, for example, on the IS front. This is, you know how the VMs were created. But also if you scroll down, you know how the application was deployed and brought up. You know the slaves have to discover each other, and so on. Speaker 1: Yeah got you. So find game invisibility into whatever you were doing with clouds because that's been one of the complaints in general. Is that the cloud abstractions have been pretty high level. Binny Gill: Yeah. Speaker 1: Yeah. Binny Gill: Yeah. So that's how we make the differences between the public clouds. All go away for the Indias of ... Speaker 1: Got you. So why don't we now give folks ... Now a lot of this stuff is coming in five, five so you'll see that pretty soon. You'll get your hands around it with AWS and tree support and so forth. What we wanted to show you was emerging alpha version that is being baked. So is a real production code for Xi. And why don't we just jump right in to it. Because we're running short of time. Binny Gill: Yep. Speaker 1: Give folks a flavor for what the production level code is already being baked around. Binny Gill: Right. So the idea of the design is make sure it's not ... the public cloud is no longer any different from your private cloud. It's a true seamless extension of your private cloud. Here I have my test environment. As you can see I'm running the HR app. It has the DB tier and the Web tier. Yeah. Alright? And the DB tier is running Oracle DB. Employee payroll is the Web tier. And if you look at the availability zones that I have, this is my data center. Now I want to protect this application, right? From disaster. What do I do? I need another data center. Speaker 1: Sure. Binny Gill: Right? With Xi, what we are doing is ... You go here and click on Xi Cloud Services. Speaker 1: And essentially as the slide says, you are adding AZs with one click. Binny Gill: Yeps so this is what I'm going to do. Essentially, you log in using your existing my.nutanix.com credentials. So here I'm going to use my guest credentials and log in. Now while I'm logging in what's happening is we are creating a seamless network between the two sides. And then making the Xi cloud availability zone appear. As if it was my own. Right? Speaker 1: Gotcha. Binny Gill: So in a couple of seconds what you'll notice this list is here now I don't have just one availability zone, but another one appears. Speaker 1: So you have essentially, real time now, paid a one data center doing an availability zone. Binny Gill: Yep. Speaker 1: Cool. Okay. Let's see what else we can do. Binny Gill: So now you think about VR setup. Now I'm armed with another data center, let's do DR Center. Now DR set-up is going to be extremely simple. Speaker 1: Okay but it's also based because on the fact that it is the same stack on both sides. Right? Binny Gill: It's the same stack on both sides. We have a secure network lane connecting the two sides, on top of the secure network plane. Now data can flow back and forth. So now applications can go back and forth, securely. Speaker 1: Gotcha, okay. Let's look at one-click DR. Binny Gill: So for one-click DR set-up. A couple of things we need to know. One is a protection rule. This is the RPO, where does it apply to? Right? And the connection of the replication. The other one is recovery plans, in case disaster happens. You know, how do I bring up my machines and application work-order and so on. So let me first show you, Protection Rule. Right? So here's the protection rule. I'll create one right now. Let me call it Platinum. Alright, and source is my own data center. Destination, you know Xi appears now. Recovery point objective, so maybe in a one hour these snapshots going to the public cloud. I want to retain three in the public side, three locally. And now I select what are the entities that I want to protect. Now instead of giving VMs my name, what I can do is app type employee payroll, app type article database. It covers both the categories of the application tiers that I have. And save. Speaker 1: So one of the things here, by the way I don't know if you guys have noticed this, more and more of Nutanix's constructs are being eliminated to become app-centric. Of course is VM centric. And essentially what that allows one to do is to create that as the new service-level API/abstraction. So that under the cover over a period of time, you may be VMs today, maybe containers tomorrow. Or functions, the day after. Binny Gill: Yep. What I just did was all that needs to be done to set up replication from your own data center to Xi. So we started off with no data center to actually replication happening. Speaker 1: Gotcha. Binny Gill: Okay? Speaker 1: No, no. You want to set up some recovery plans? Binny Gill: Yeah so now set up recovery plan. Recovery plans are going to be extremely simple. You select a bunch of VMs or apps, and then there you can say what are the scripts you want to run. What order in which you want to boot things. And you know, you can set up access these things with one click monthly or weekly and so on. Speaker 1: Gotcha. And that sets up the IPs as well as subnets and everything. Binny Gill: So you have the option. You can maintain the same IPs on frame as the move to Xi. Or you can make them- Speaker 1: Remember, you can maintain your own IPs when you actually use the Xi service. There was a lot of things getting done to actually accommodate that capability. Binny Gill: Yeah. Speaker 1: So let's take a look at some of- Binny Gill: You know, the same thing as VPC, for example. Speaker 1: Yeah. Binny Gill: You need to possess on Xi. So, let's create a recovery plan. A recovery plan you select the destination. Where does the recovery happen. Now, after that Section 11 of 13 [01:40:00 - 01:50:04] Section 12 of 13 [01:50:00 - 02:00:04] (NOTE: speaker names may be different in each section) Speaker 1: ... does the recovery happen. Now, after that you have to think of what is the runbook that you want to run when disaster happens, right? So you're preparing for that, so let me call "HR App Recovery." The next thing is the first stage. We're doing the first stage, let me add some entities by categories. I want to bring up my database first, right? Let's click on the database and that's it. Speaker 2: So essentially, you're building the script now. Speaker 1: Building the script- Speaker 2: ... on the [inaudible 01:50:30] Speaker 1: ... but in a visual way. It's simple for folks to understand. You can add custom script, add delay and so on. Let me add another stage and this stage is about bringing up the web tier after the database is up. Speaker 2: So basically, bring up the database first, then bring up the web tier, et cetera, et cetera, right? Speaker 1: That's it. I've created a recovery plan. I mean usually it's complicated stuff, but we made it extremely simple. Now if you click on "Recovery Points," these are snapshots. Snapshots of your applications. As you can see, already the system has taken three snapshots in response to the protection rule that we had created just a couple minutes ago. And these are now being seeded to Xi data centers. Of course this takes time for seeding, so what I have is a setup already and that's the production environment. I'll cut over to that. This is my production environment. Click "Explore," now you see the same application running in production and I have a few other VMs that are not protected. Let's go to "Recovery Points." It has been running for sometime, these recover points are there and they have been replicated to Xi. Speaker 2: So let's do the failover then. Speaker 1: Yeah, so to failover, you'll have to go to Xi so let me login to Xi. This time I'll use my production account for logging into Xi. I'm logging in. The first thing that you'll see in Xi is a dashboard that gives you a quick summary of what your DR testing has been so far, if there are any issues with the replication that you have and most importantly the monthly charges. So right now I've spent with my own credit card about close to 1,000 bucks. You'll have to refund it quickly. Speaker 2: It depends. If the- Speaker 1: If this works- Speaker 2: IF the demo works. Speaker 1: Yeah, if it works, okay. As you see, there are no VMs right now here. If I go to the recovery points, they are there. I can click on the recovery plan that I had created and let's see how hard it's going to be. I click "Failover." It says three entities that, based on the snapshots, it knows that it can recovery from source to destination, which is Xi. And one click for the failover. Now we'll see what happens. Speaker 2: So this is essentially failing over my production now. Speaker 1: Failing over your production now. [crosstalk 01:52:53] If you click on the "HR App Recovery," here you see now it started the recovery plan. The simple recovery plan that we had created, it actually gets converted to a series of tasks that the system has to do. Each VM has to be hydrated, powered on in the right order and so on and so forth. You don't have to worry about any of that. You can keep an eye on it. But in the meantime, let's talk about something else. We are doing failover, but after you failover, you run in Xi as if it was your own setup and environment. Maybe I want to create a new VM. I create a VM and I want to maybe extend my HR app's web tier. Let me name it as "HR_Web_3." It's going to boot from that disk. Production network, I want to run it on production network. We have production and test categories. This one, I want to give it employee payroll category. Now it applies the same policies as it's peers will. Here, I'm going to create the VM. As you can see, I can already see some VMs coming up. There you go. So three VMs from on-prem are now being filled over here while the fourth VM that I created is already being powered. Speaker 2: So this is basically realtime, one-click failover, while you're using Xi for your [inaudible 01:54:13] operations as well. Speaker 1: Exactly. Speaker 2: Wow. Okay. Good stuff. What about- Speaker 1: Let me add here. As the other cloud vendors, they'll ask you to make your apps ready for their clouds. Well we tell our engineers is make our cloud ready for your apps. So as you can see, this failover is working. Speaker 2: So what about failback? Speaker 1: All of them are up and you can see the protection rule "platinum" has been applied to all four. Now let's look at this recovery plan points "HR_Web_3" right here, it's already there. Now assume the on-prem was already up. Let's go back to on-prem- Speaker 2: So now the scenario is, while Binny's coming up, is that the on-prem has come back up and we're going to do live migration back as in a failback scenario between the data centers. Speaker 1: And how hard is it going to be. "HR App Recovery" the same "HR App Recovery", I click failover and the system is smart enough to understand the direction is reversed. It's also smart enough to figure out "Hey, there are now the four VMs are there instead of three." Xi to on-prem, one-click failover again. Speaker 2: And it's rerunning obviously the same runbook but in- Speaker 1: Same runbook but the details are different. But it's hidden from the customer. Let me go to the VMs view and do something interesting here. I'll group them by availability zone. Here you go. As you can see, this is a hybrid cloud view. Same management plane for both sides public and private. There are two availability zones, the Xi availability zone is in the cloud- Speaker 2: So essentially you're moving from the top- Speaker 1: Yeah, top- Speaker 2: ... to the bottom. Speaker 1: ... to the bottom. Speaker 2: That's happening in the background. While this is happening, let me take the time to go and look at billing in Xi. Speaker 1: Sure, some of the common operations that you can now see in a hybrid view. Speaker 2: So you go to "Billing" here and first let me look at my account. And account is a simple page, I have set up active directory and you can add your own XML file, upload it. You can also add multi-factor authentication, all those things are simple. On the billing side, you can see more details about how did I rack up $966. Here's my credit card. Detailed description of where the cost is coming from. I can also download previous versions, builds. Speaker 1: It's actually Nutanix as a service essentially, right? Speaker 2: Yep. Speaker 1: As a subscription service. Speaker 2: Not only do we go to on-prem as you can see, while we were talking, two VMs have already come back on-prem. They are powered off right now. The other two are on the wire. Oh, there they are. Speaker 1: Wow. Speaker 2: So now four VMs are there. Speaker 1: Okay. Perfect. Sometimes it works, sometimes it doesn't work, but it's good. Speaker 2: It always works. Speaker 1: Always works. All right. Speaker 2: As you can see the platinum protection rule is now already applied to them and now it has reversed the direction of [inaudible 01:57:12]- Speaker 1: Remember, we showed one-click DR, failover, failback, built into the product when Xi ships to any Nutanix fabric. You can start with DSX on premise, obviously when you failover to Xi. You can start with AHV, things that are going to take the same paradigm of one-click operations into this hybrid view. Speaker 2: Let's stop doing lift and shift. The era has come for click and shift. Speaker 1: Binny's now been promoted to the Chief Marketing Officer, too by the way. Right? So, one more thing. Speaker 2: Okay. Speaker 1: You know we don't stop any conferences without a couple of things that are new. The first one is something that we should have done, I guess, a couple of years ago. Speaker 2: It depends how you look at it. Essentially, if you look at the cloud vendors, one of the key things they have done is they've built services as building blocks for the apps that run on top of them. What we have done at Nutanix, we've built core services like block services, file services, now with Calm, a marketplace. Now if you look at [inaudible 01:58:14] applications, one of the core building pieces is the object store. I'm happy to announce that we have the object store service coming up. Again, in true Nutanix fashion, it's going to be elastic. Speaker 1: Let's- Speaker 2: Let me show you. Speaker 1: Yeah, let's show it. It's something that is an object store service by the way that's not just for your primary, but for your secondary. It's obviously not just for on-prem, it's hybrid. So this is being built as a next gen object service, as an extension of the core fabric, but accommodating a bunch of these new paradigms. Speaker 2: Here is the object browser. I've created a bunch of buckets here. Again, object stores can be used in various ways: as primary object store, or for secondary use cases. I'll show you both. I'll show you a Hadoop use case where Hadoop is using this as a primary store and a backup use case. Let's just jump right in. This is a Hadoop bucket. AS you can see, there's a temp directory, there's nothing interesting there. Let me go to my Hadoop VM. There it is. And let me run a Hadoop job. So this Hadoop job essentially is going to create a bunch of files, write them out and after that do map radius on top. Let's wait for the job to start. It's running now. If we go back to the object store, refresh the page, now you see it's writing from benchmarks. Directory, there's a bunch of files that will write here over time. This is going to take time. Let's not wait for it, but essentially, it is showing Hadoop that uses AWS 3 compatible API, that can run with our object store because our object store exposes AWS 3 compatible APIs. The other use case is the HYCU backup. As you can see, that's a- Section 12 of 13 [01:50:00 - 02:00:04] Section 13 of 13 [02:00:00 - 02:13:42] (NOTE: speaker names may be different in each section) Vineet: This is the hycu back up ... As you can see, that's a back-up software that can back-up WSS3. If you point it to Nutanix objects or it can back-up there as well. There are a bunch of back-up files in there. Now, object stores, it's very important for us to be able to view what's going on there and make sure there's no objects sprawled because once it's easy to write objects, you just accumulate a lot of them. So what we wanted to do, in true Nutanix style, is give you a quick overview of what's happening with your object store. So here, as you can see, you can look at the buckets, where the load is, you can look at the bucket sizes, where the data is, and also what kind of data is there. Now this is a dashboard that you can optimize, and customize, for yourself as well, right? So that's the object store. Then we go back here, and I have one more thing for you as well. Speaker 2: Okay. Sounds good. I already clicked through a slide, by the way, by mistake, but keep going. Vineet: That's okay. That's okay. It is actually a quiz, so it's good for people- Speaker 2: Okay. Sounds good. Vineet: It's good for people to have some clues. So the quiz is, how big is my SAP HANA VM, right? I have to show it to you before you can answer so you don't leak the question. Okay. So here it is. So the SAP HANA VM here vCPU is 96. Pretty beefy. Memory is 1.5 terabytes. The question to all of you is, what's different in this screen? Speaker 2: Who's a real Prism user here, by the way? Come on, it's got to be at least a few. Those guys. Let's see if they'll notice something. Vineet: What's different here? Speaker 3: There's zero CVM. Vineet: Zero CVM. Speaker 2: That's right. Yeah. Yeah, go ahead. Vineet: So, essentially, in the Nutanix fabric, every server has to run a [inaudible 02:01:48] machine, right? That's where the storage comes from. I am happy to announce the Acropolis Compute Cloud, where you will be able to run the HV on servers that are storage-less, and add it to your existing cluster. So it's a compute cloud that now can be managed from Prism Central, and that way you can preserve your investments on your existing server farms, and add them to the Nutanix fabric. Speaker 2: Gotcha. So, essentially ... I mean, essentially, imagine, now that you have the equivalent of S3 and EC2 for the enterprise now on Premisis, like you have the equivalent compute and storage services on JCP and AWS, and so forth, right? So the full flexibility for any kind of workload is now surely being available on the same Nutanix fabric. Thanks a lot, Vineet. Before we wrap up, I'd sort of like to bring this home. We've announced a pretty strategic partnership with someone that has always inspired us for many years. In fact, one would argue that the genesis of Nutanix actually was inspired by Google and to talk more about what we're actually doing here because we've spent a lot of time now in the last few months to really get into the product capabilities. You're going to see some upcoming capabilities and 55X release time frame. To talk more about that stuff as well as some of the long-term synergies, let me invite Bill onstage. C'mon up Bill. Tell us a little bit about Google's view in the cloud. Bill: First of all, I want to compliment the demo people and what you did. Phenomenal work that you're doing to make very complex things look really simple. I actually started several years ago as a product manager in high availability and disaster recovery and I remember, as a product manager, my engineers coming to me and saying "we have a shortage of our engineers and we want you to write the fail-over routines for the SAP instance that we're supporting." And so here's the PERL handbook, you know, I haven't written in PERL yet, go and do all that work to include all the network setup and all that work, that's amazing, what you are doing right there and I think that's the spirit of the partnership that we have. From a Google perspective, obviously what we believe is that it's time now to harness the power of scale security and these innovations that are coming out. At Google we've spent a lot of time in trying to solve these really large problems at scale and a lot of the technology that's been inserted into the industry right now. Things like MapReduce, things like TenserFlow algorithms for AI and things like Kubernetes and Docker were first invented at Google to solve problems because we had to do it to be able to support the business we have. You think about search, alright? When you type in search terms within the search box, you see a white screen, what I see is all the data-center work that's happening behind that and the MapReduction to be able to give you a search result back in seconds. Think about that work, think about that process. Taking and pursing those search terms, dividing that over thousands of [inaudible 02:05:01], being able to then search segments of the index of the internet and to be able to intelligent reduce that to be able to get you an answer within seconds that is prioritized, that is sorted. How many of you, out there, have to go to page two and page three to get the results you want, today? You don't because of the power of that technology. We think it's time to bring that to the consumer of the data center enterprise space and that's what we're doing at Google. Speaker 2: Gotcha, man. So I know we've done a lot of things now over the last year worth of collaboration. Why don't we spend a few minutes talking through a couple things that we're started on, starting with [inaudible 02:05:36] going into com and then we'll talk a little bit about XI. Bill: I think one of the advantages here, as we start to move up the stack and virtualize things to your point, right, is virtual machines and the work required of that still takes a fair amount of effort of which you're doing a lot to reduce, right, you're making that a lot simpler and seamless across both On-Prem and the cloud. The next step in the journey is to really leverage the power of containers. Lightweight objects that allow you to be able to head and surface functionality without being dependent upon the operating system or the VM to be able to do that work. And then having the orchestration layer to be able to run that in the context of cloud and On-Prem We've been very successful in building out the Kubernetes and Docker infrastructure for everyone to use. The challenge that you're solving is how to we actually bridge the gap. How do we actually make that work seamlessly between the On-Premise world and the cloud and that's where our partnership, I think, is so valuable. It's cuz you're bringing the secret sauce to be able to make that happen. Speaker 2: Gotcha, gotcha. One last thing. We talked about Xi and the two companies are working really closely where, essentially the Nutanix fabric can seamlessly seep into every Google platform as infrastructure worldwide. Xi, as a service, could be delivered natively with GCP, leading to some additional benefits, right? Bill: Absolutely. I think, first and foremost, the infrastructure we're building at scale opens up all sorts of possibilities. I'll just use, maybe, two examples. The first one is network. If you think about building out a global network, there's a lot of effort to do that. Google is doing that as a byproduct of serving our consumers. So, if you think about YouTube, if you think about there's approximately a billion hours of YouTube that's watched every single day. If you think about search, we have approximately two trillion searches done in a year and if you think about the number of containers that we run in a given week, we run about two billion containers per week. So the advantage of being able to move these workloads through Xi in a disaster recovery scenario first is that you get to take advantage of the scale. Secondly, it's because of the network that we've built out, we had to push the network out to the edge. So every single one of our consumers are using YouTube and search and Google Play and all those services, by the way we have over eight services today that have more than a billion simultaneous users, you get to take advantage of that network capacity and capability just by moving to the cloud. And then the last piece, which is a real advantage, we believe, is that it's not just about the workloads you're moving but it's about getting access to new services that cloud preventers, like Google, provide. For example, are you taking advantage like the next generation Hadoop, which is our big query capability? Are you taking advantage of the artificial intelligence derivative APIs that we have around, the video API, the image API, the speech-to-text API, mapping technology, all those additional capabilities are now exposed to you in the availability of Google cloud that you can now leverage directly from systems that are failing over and systems that running in our combined environment. Speaker 2: A true converged fabric across public and private. Bill: Absolutely. Speaker 2: Great stuff Bill. Thank you, sir. Bill: Thank you, appreciate it. Speaker 2: Good to have you. So, the last few slides. You know we've talked about, obviously One OS, One Click and eCloud. At the end of the day, it's pretty obvious that we're evaluating the move from a form factor perspective, where it's not just an OS across multiple platforms but it's also being distributed genuinely from consuming itself as an appliance to a software form factor, to subscription form factor. What you saw today, obviously, is the fact that, look you know we're still continuing, the velocity has not slowed down. In fact, in some cases it's accelerated. If you ask my quality guys, if you ask some of our customers, we're coming out fast and furious with a lot of these capabilities. And some of this directly reflects, not just in features, but also in performance, just like a public cloud, where our performance curve is going up while our price-performance curve is being more attractive over a period of time. And this is balancing it with quality, it is what differentiates great companies from good companies, right? So when you look at the number of nodes that have been shipping, it was around ten more nodes than where we were a few years ago. But, if you look at the number of customer-found defects, as a percentage of number of nodes shipped it is not only stabilized, it has actually been coming down. And that's directly reflected in the NPS part. That most of you guys love. How many of you guys love your Customer Support engineers? Give them a round of applause. Great support. So this balance of velocity, plus quality, is what differentiates a company. And, before we call it a wrap, I just want to leave you with one thing. You know, obviously, we've talked a lot about technology, innovation, inspiration, and so forth. But, as I mentioned, from last night's discussion with Sir Ranulph, let's think about a few things tonight. Don't take technology too seriously. I'll give you a simple story that he shared with me, that puts things into perspective. The year was 1971. He had come back from Aman, from his service. He was figuring out what to do. This was before he became a world-class explorer. 1971, he had a job interview, came down from Scotland and applied for a role in a movie. And he failed that job interview. But he was selected from thousands of applicants, came down to a short list, he was a ... that's a hint ... he was a good looking guy and he lost out that role. And the reason why I say this is, if he had gotten that job, first of all I wouldn't have met him, but most importantly the world wouldn't have had an explorer like him. The guy that he lost out to was Roger Moore and the role was for James Bond. And so, when you go out tonight, enjoy with your friends [inaudible 02:12:06] or otherwise, try to take life a little bit once upon a time or more than once upon a time. Have fun guys, thank you. Speaker 5: Ladies and gentlemen please make your way to the coffee break, your breakout sessions will begin shortly. Don't forget about the women's lunch today, everyone is welcome. Please join us. You can find the details in the mobile app. Please share your feedback on all sessions in the mobile app. There will be prizes. We will see you back here and 5:30, doors will open at 5, after your last breakout session. Breakout sessions will start sharply at 11:10. Thank you and have a great day. Section 13 of 13 [02:00:00 - 02:13:42]

>> Narrator: Live from Las Vegas, Nevada, it's the Cube, covering accelerate 2017, brought to you by Fortinet. Now here are your hosts, Lisa Martin and Peter Burris. >> Hi, welcome back to the cube, we are live in Las Vegas at Fortinet Accelerate 2017. I'm you host , Lisa Martin, joined by my cohost, Peter Burris, and we're really excited about or next guest. We are talking next with Derek Manky. Derek, you are-- first of all, welcome to the cube. >> Thank you very much, I'm excited to be here. >> You have a really important role in Fortinet, you are the Global Security Strategist. >> Correct, yes. >> You have a... Established yourself as a thought leader with over 15 year of cyber security expertise, and your goal is to make a positive impact towards the global war on cyber-crime, that's a big goal. >> That's a very, very big goal, but it's a big hairy goal, but it's... Critically important, I believe, I firmly believe this over my whole career, and I'm starting to see some good traction with the efforts that we're doing too. >> And it's becoming more, and more, critical every day as breaches, and hacks, are a daily occurrence, you're also the leader of FortiGuard Labs, you've got a team of over 200, tell our viewers that can't be here today, what is FortiGuard Labs, what are you doing to leverage threat intelligence to help Fortinet's customers. >> Sure, so we're trying to manage complexity, cause that's always the enemy of security, and we're trying to make it simple across the board, so we're managing security for all of our customers, 300 000 customers plus. That's a big deal, so we had to invest a lot into that in terms of how we can do that to make it simple to the end users. So what FortiGuard Labs is, is it's services we deliver to the end user, protection services across the spectrum, our whole product portfolio. So we have world-class expertise as a security vendor, 200 plus people on the team, experts in each domain. We have researchers, and experts, looking at things like industrial attacks, mobile problems, malicious websites, ripping apart, what we call reverse engineering, malware samples to find out digital fingerprints of who's creating these attacks, so we can work also in partnerships with that too. At the end of the day, we have the humans working on that, but we've also invested a ton into artificial intelligence, and machine learning, we have to comb through over 50 billion attacks in a day, and so the machines are also helping us to create a lot of this automated protection, that's all driven by our patents, by our world-class development teams, that gets down to the end user, so that they don't have to invest as much into their own security operations centers, cause that's a big OpEx, expansions to the expenditure, so we're helping to alleviate that issue, especially with this, as everybody knows, today, the big gap in cyber security, professionals, so that helps to alleviate that issue too. >> You said 50 billion attacks a day. >> That's correct sir, yes. Potential attacks. >> Oh, potential attacks. Clearly that means that increasing percentages of the total body of attacks are no longer coming from humans, they're coming from other things, >> Derek: Absolutely. >> And how's that playing out? >> It's a fascinating landscape right now. With every legitimate model, there's an illegitimate model to follow, especially with cyber crime, and what we see in the digital underground, dark web, all these sorts of things, you rewind back to the 90s, your opportunistic hacker was just trying to plot, plot, plot, a message bar on a Windows 95, or Windows 98 system at the time. Nowadays, of course, the attack surface has grown tremendously. You look back to DARPA, back in 1989, it had 60 000 system connected on the Internet, now we have IPv6, 20 plus billions connected devices, everything is a target now, especially with the Internet of Things. Smart televisions-- >> Peter: And a potential threat. >> Exactly, and a weapon. >> Exactly, and so to capitalize on that, what we're seeing now is cyber criminals developing automated systems of their own, to infect these systems, to report back to them, so they're doing a lot of that heavy work, to the heavy lifting, using their own machines to infect, and their own algorithms to infect these systems, and then from there, it'll escalate back up to them to further capitalize, and leverage those attacks. On any given minute, we're seeing between 500 000 to 700 000 hacking attempts across, and this is our own infrastructure, so we're leading in terms of firewalls in units shipped so we're able to get a good grasp on intelligence out there, what's happening, and in any given minute, well over 500 000 hacking attempts on systems worldwide. >> So every hour, 30 million. >> Derek: Yeah that's some quick math. >> Yeah, I'm amazing at multiplication. I almost got it wrong though, I have to say. 30 million hacks an hour. >> Yeah, and so our job is to identify that, we don't want to block things we shouldn't be, so there has to be a very big emphasis on quality of intelligence as well, we've done a lot with our machines to validate attacks, to be able to protect against those attacks, and not, especially when it comes to these attacks like intrusion prevention, that attack surface now, we got to be able to not just look at attacks on PCs now, so that's why that number keeps ticking up. >> Lisa: Right, proliferation of mobile, IoT. >> Derek: It's directly related, absolutely. >> So, this is clearly something that eyeballs are not going to solve. >> Not alone, so I'm very, very big advocate saying that we cannot win this war alone, just relying even on the brightest minds on the world, but we can also not just rely a hundred percent on machines to control, it's just like autonomous vehicles. You look at Tesla, and these other vehicles, and Google, what they're doing, it's a trust exercise again, you can never pass a hundred percent control to that automation. Rather you can get up to that 99 percent tile with automation, but you still need those bright minds looking at it. So to answer your questions, eyeballs alone, no, but the approach we've taken is to scale up, distribute, and use machines to identify it, to try to find that needle in a haystack, and then, escalate that to our bright minds, when we need to take a look at the big attacks that matter, and solve some more of the complex issues. >> Speaking of bright minds, you and your team, recently published an incredible blog on 2017 predictions. Wow, that's on the Fortinet blog? >> Derek: Yeah, that's correct >> We can find that? Really incredibly thorough, eye-opening, and there were six predictions, take us through maybe the top three. We talked about the proliferation of devices, the attack surface getting larger, more and more things becoming potential threats, what are the top three, maybe biggest threats that you were seeing, and is there any industry, in particular, that pops up as one of the prime targets? >> Absolutely. I'll get into some buckets on this, I think first, and foremost, what is primary now in what we're seeing is, what we're calling, autonomous malware, so this is the notion of, basically what we're just talking about to your question on what's driving this data, what's driving all these attack points. First of all, the Internet's been seeded with, what I call, ticking time bombs right now, we have 20 plus, whatever the number's going to be, all of these billions of devices that are connected, that are inherently, in my professional opinion, insecure. A lot of these devices are not following proper security development life cycles. >> Lisa: Is there accountability to begin with? >> No, not at this point. >> Right. >> Right. And that's something that DHS, and NIST, just released some guidelines on, at the end of last year, and I think we're going to see a lot of activity on accountability for that, but that has to be taken care of. Unfortunately right now, it's been seeded, this attack surfaces there, so we already have all these open avenues of attack, and that's why I call it a ticking time bomb, because it's been seeded, and now these are ripe for attack, and we're seeing attackers capitalize on this, so what we're seeing is the first indications of autonomous malware, malware that is capable of mapping out these vulnerable points. The machine's doing this, and the machine's attacking the other machines, so it's not just the eyeballs then, and the cyber criminals doing this. We saw last year, unprecedented DDoS attacks, this is directly related to Mirai BotNet. We had gone from a 600 gig to terabit plus DDoS attacks, that was unheard of before. They are leveraging all of these different IoT devices as a horsepower to attack these systems in a massive distributed denial-of-service attack. The interesting part about Mirai is that it's also using open-source intelligence as well, so this is something that humans, like a black hat attacker, would typically have to do, they would have to get reports back from one of their systems, and say, "okay, now I've found all these vulnerable systems, I'm going to attack all these systems.", but they're the glue, so they're now removing themselves as the glue, and making this completely automated, where a BotNet like Mirai is able to use Shodan, as an example, it's an open-source database, and say, "here are a whole bunch of vulnerable systems, I'm going to go attack it, and so that's to my point of view, that's the first indication of the smart-malware, because malware has always been guided by humans. But now, I think, we're starting to see a lot of, more of that intelligent attack, the offense, the intelligent offense being baked in to these pieces of malware. So I think it's going to open this whole new breed of attacks and malware, and obviously, we're in a whole new arms race when it comes to that. How can we get ahead of the bad guys, and so this is obviously what Fortinet instituting on the autonomous defense, our Security Fabric, and Fabric-ready approach, that's all about, beating them to the punch on that, having our machines, the defensive machines talk to each other, combine world-class intelligence like FortiGuard so that it can defend against those attacks, it's a though task, but I really firmly believe that this year is a year that we have the advantage, we can have the advantage as white hats to get one leg up on the black hat attackers. As I said, for 15 years at FortiGuard Labs, we have invested a ton into our AI machine, learning intelligence, so we're experts on the automation, I don't believe the black hat attackers are experts on automation. So I think for that reason, we have a really good opportunity this year, because you always hear about the black hats, another data breach, and all these things happening, they're always had the advantage, and I think, we can really turn the tables this year. >> You have some great experience working, not just in the private sector, but in the public sector as well, you've done work with NATO, with Interpol, with SERT, what is your perspective on public sector, and private sector, working together, is that essential to win this war on cyber crime? >> Absolutely, we need everybody at the table, we cannot win it, as one single vendor alone, a good example of that is, we're starting to do across the board, this is something, I firmly believe in, it's really near and dear to my heart, I've worked on it for the course of, well over six years now, and we have a lot of the existing partnerships, across organizations, so other security vendors, and experts, Cyber Threat Alliance is an excellent example, we're a founding member of that, and these are competitors, but security vendors getting together to level the playing field on intelligence, we can still really remain competitive on the solutions, and how we implement that intelligence, but at least-- it's like a Venn diagram, you look at that attack surface out there, you want to try to share all that information, so that you can deliver that to security controls, and protect against it. So, the Cyber Threat Alliance is a good example, but that's private sector. If you look at National Computer Emergency Response, law enforcement, we have made great inroads into that working with the likes of Computer Emergency Response, to give them intel. If we find bad stuff happening somewhere, we're not law enforcement, we can't go take the server down, and disrupt campaign, we can't arrest, or prosecute people, but they can, but they don't have all that expertise, and intelligence that we do, all the data points, so this is, you're starting to see a lot of this string up, and we're doing a lot of leadership in this area, and I think, it's absolutely essential. President Obama last year mentioned it, the Cyber Threat Alliance, and the public-private sector, needing to work together in one of his speeches at Stanford, and I believe it's the only way we can win this. You have to go up to the head of the snake too, if we just are always on the defense, and we're always just trying to disrupt cyber criminals, it's a slap on the wrist for them, they're going to go set up shop somewhere else. We need to be able to actually go and prosecute these guys, and we had a really good case last year, we took down, working with Interpol, and the EFCC, a 62 million dollar crime ring in the US. They went, and prosecuted the kingpin of this operation, out of Nigeria. It's an unprecedented random example, but we need to do more of that, but it's a good example of a healthy working public-private sector relationship >> What an incredible experience that you have, what you have achieved with FortiGuard Labs, what excites you most, going forward, we're just at the beginning of 2017, with what's been announced here, the partnerships that you guys have formed, what excites you most about this year, and maybe... Some of the key steps you want to take against cyber crime as Fortinet. >> Sure, so I think we want to, so Cyber Threat Alliance is a very big machine, there's a lot of exciting things happening, so that's going to be a really good initiative, that's going to carry forward momentum this year. What excites me most? Well, it's not always a good thing I guess, but if you look at all the bad news that's out there, like I said, I think it's just going to be, there's so much fuel, that's being thrown on the fire when it comes to attacks right now. Like I said, these time bombs that have been planted out there. We're going to see the year of IoT attacks for sure, a new version of Marai has already come out, they're starting to sell this, commercialize this, and it's even more advanced in terms of intelligence than the previous one, so that sort of stuff. It depends on your definition of the word, excites, of course, but these are the things that we have opportunity, and again I think going back to my first point, the white hats having, for the first time in my point of view, a leg up on the black hats, that opportunity, that really excites me. When we look at what's happening, moving forward in 2017, healthcare, I think, is going to be a very big thing in terms of attack targets, so we're going to be focused on that, in terms of attacks on, not just healthcare records, which are more valuable than financial records as an example, but medical devices, again the IoT play in healthcare, that's a big deal, we're starting to already see attacks on that. Smart cities as well, you look forward to the next three years, building management systems, a lot of people talk about SCADA industrial control, this is definitely a big attack target to a certain... Attack surface, obviously, power plants, electrical grids, but building management systems, and these automated systems that are being put in, even smart vehicles, and smart homes is another big target that's unfolding over the next year. >> Hard to air gap a home, and certainly not a city. >> Absolutely, yeah, and again it goes back to the point that a lot of these devices being installed in those homes are inherently, insecure. So that's a big focus for us, and that's a big thing FortiGuard is doing, is looking at what those attacks are, so we can defend against that at the network layer, that we can work with all of our business partners that are here at Accelerate this year, to deliver those solutions, and protect against it. >> Wow, it sounds like, and I think Peter would agree, your passion for what you do is very evident, as those bad actors are out there, and as the technologies on the baton are getting more advanced, and intelligent, as you say, it's great to hear what you, and your team are doing to help defend against that on the enterprise side, and one day on the consumer side as well. So Derek Manky, Global Security Strategist for Fortinet, thank you so much cube and sharing your expertise with us. >> It's my pleasure, any time, thank you very much. >> Well, on behalf of my cohost, Peter Burris, I'm Lisa Martin, you've been watching the Cube, and stick around, we'll be right back. 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>> Narrator: Live from San Jose, California in the heart of silicon valley, it's theCUBE! Covering QuickBooks Connect 2016. Sponsored by Intuit QuickBooks. Now here are your hosts Jeff Frick and John Walls. >> Welcome back to San Jose, California. We continue here on theCUBE our coverage of QuickBooks Connect 2016. Of course theCube is the flagship broadcast here on SiliconANGLE TV where we extract the signal from the noise and I tell you what, with our next guest, we have a lot of signal to bring you. Scott Cook, the founder and the chairman of the executive committee at Intuit. Scott, thank you for being with us. We really appreciate the time and have been looking forward to this for quite some time once we knew you were going to be on theCube. It's good to have you. >> Good to be here. >> Let's talk about just first off, look at where you are now, right? 30-some odd years. It's been quite a ride I would assume for you. >> Yeah, it started, you know Tom and I got together and then there were two of us and then we eventually had seven of us in a basement. Well they called it the garden level. But the only part of the garden you could see would be the roots and the gophers. (laughter) And then we hit bad times and the things ... We just couldn't get money. We couldn't get sales so we shrunk down to four people. Couldn't pay salaries. It was pretty ugly. And from that, to look at 5,000 people here today. 8,000 employees in the company. When I started the biggest PC software company was 160 employees, and they were huge! Oh these giants! (laughter) >> How do I manage all this? >> Yeah, yeah. >> Well a quote that we've heard a couple of times today. We heard on the keynote stage. About the corporate philosophy of we fall in love with your problems, not our solutions. And is that the driving force you think? I mean, why you've made it through 33 years? >> I think yeah. Yeah, I actually think that's pretty important not just to the success of Intuit and QuickBooks and Mint and TurboTax, but to business in general. My theory is what great entrepreneurs do is they find the intersection of two circles. So think of a Venn diagram and the intersection. One circle is what are people's biggest, most important unsolved problems? Not the problems that are already solved by someone else. Find the ones that aren't solved yet. And then look for the ones that we can solve. Cause you can't solve everything. But look where we can apply the best technologies in the world. What's in that intersection? And focus there. >> And in some of the research to get ready for this. You've talked about really focusing on the important stuff. You gave a great example in that Khan Academy talk about there's really only 1 1/2 things that you should really be focusing on to really move the ship forward. And that was a very great insight. >> Yeah, you know all of of us have the desire to do too many things. You get groups. You've got 10 people in a room, they each have their ideas and it's tempting to shoot at too many targets. And those 10 targets are not of equal importance. You got to go through and kind of rigorously and be disciplined and say what's the 1 1/2 most important? And stay relentlessly focused on that. >> And then how is your role changed? As time has passed and you're no longer the CEO. Now you're chairman head of the executive board. How have you kind of learned to still keep your hands on it but in kind of a little bit more of a distant role? >> Well, first of all, thank goodness for leaders like Brad Smith, Sasan Goodarzi who heads up our small business group, that's really the host of this show. Thank goodness for great leaders like that. So my role's changed a ton. I work really on two areas now which is strategy and coaching our entrepreneurs. So strategy over to Brad and our other leaders. I'm trying to help our leaders see the future and make the big strategic calls. What's really most important? How do we know? And then work with our entrepreneurs. We're a collection of entrepreneurs basically. We've got a couple hundred entrepreneurial projects going on inside the company at any one time. And each one of those is like a little startup. I mean, they've got a customer in mind. They've got a problem they're trying to solve to improve people's lives so fundamentally. And there are challenges. So helping grow our entrepreneurs and then grow the culture around them to allow great entrepreneurs to invent things to change the world and do that from within Intuit with a huge reach to be able to get the inventions out in the hands of millions. And change the lives of tens of millions of people. >> So, over the course of the run of the company, they haven't all been home runs. >> Scott: Oh yeah. >> Right. So how have you learned from those swings and misses? And applied them to the small businesses that you're serving? Who are swinging and missing on a regular basis and you're trying to narrow that margin, right? Trying to make them more successful. >> Scott: Yeah. >> So what did you learn you think maybe through your attempts about that culture of trying basically. >> I think maybe the most important thing really dovetails with what you just said. Early on, when the company was, before we even had our first product out, we'd build a version of it and then we would bring in test audiences of it and have them test it to see if they could figure it out without us saying anything. And they couldn't. So then we'd redesign it and then we'd test again. And then we'd redesign it and test again. Over time kind of lost some of that dedication to running experiments. And it became whose opinion? And you'd build, and it was the loudest opinion in the room. Or the boss' opinion. And that produced a number of failures. Things that just didn't work. Customers didn't buy it. Or they bought it and it didn't it didn't produce the desired effect when they bought it. So the thing I've learned about life and companies is to set up a culture where you make decisions based on fast cheap experiments. That very thing you were talking about. If you got an idea, figure out, okay, what's a leap of faith assumption, let's go try it. And don't debate it. Try it. And then we learned from trying. Oh, a bunch of those don't work. And then we learned from the things. Why didn't it work? And that teaches us something we didn't know before. That maybe the fulcrum, the pivot, to a new idea. And some of those do work or most of it worked. But other pieces didn't. And we learned by doing. Not by debating in a conference room. So to set up your company so that people throughout the company can take their idea and run the experiment. That produces great entrepreneurs and great learning. A continuous stream of learning. I guess the learning begins when you first get real people trying your idea for real. >> Let me follow up. Cause the other thing you talk about is that often comes from the youngest and the newest employees. Which is completely antithesis to a kind of hierarchical structure. Where these are the people that you should be listening and giving them the opportunity within this comfortable framework to do these experiments. >> Absolutely. Sometimes the very freshest ideas come from the people farthest from the boss. Newest in the company. Closest to the customer. But typically in a hierarchy, whose got the least clout? Whose ideas are the least listened to? It'd be the new person, the young person. >> Jeff: Right. >> And so part of the genius of running a company of decision by experiment is that everyone's ideas can be run as an experiment. The boss' idea. The CEO's idea. And the person that's new. We should be testing each of those. Except in a crisis where you got to make snap decisions. And hopefully those aren't very often. You should run the company so that each good idea can be tested, regardless of where it comes from. And then the great thing is, then you get the best ideas from all your folks and they learn from doing. If their idea doesn't work, now they learn from that. Ooh, okay. I thought it was going to do X, it did Y. Why? What didn't I know? That's where learning comes from. Learning doesn't tend to come from the successes, learning comes from the things that didn't work. >> So, I think we've all seen good executives. How they operate. They hire good people, right? That's ... You have a vision and then you hire people who surround that and amplify that vision. So when you're looking for people or when you've been looking for people to work with you. What's that common thread? Or what are the traits that you've looked for the most to think that's a good fit? Or this is the person that I want on my team. In order to carry on this vision to where it's expanded to where it is today. >> Let me break that into two buckets. There are a set of things which are unique to particular career paths. So certain things from engineers might be different than certain things from a salesperson or a marketer or a finance person. So let's set that aside. Let's cover the commonalities. I think there's a few things. When you think about the people you've most loved working with or for. There are people who are great creative problem solvers. Instead of seeing a problem or barrier and giving up or being unglued by it. Can figure out okay, how're we going to solve that problem? And then there's people who are there to serve. Where it's not all about them. I've got a thing that I tell our folks that others won't care how much you know until they first know how much you care. So if one of our speakers today said it. If your first job is to serve yourself you're not going to go very far. Because who wants to work with someone who's self serving? Who wants to buy from a company that's only looking after its own front P&L? Job one is you got to serve who you're serving. The customer or the person of the company who you serve. So we look for people who are really motivated by the outside to try to do right by the customer. I think you look for people who are achievement oriented. Who get stuff done. Who make things happen. Do you want to work with somebody who always needs to be dragged along? No. You want to work with somebody who's pulling you along. Who's getting a lot done. So you go, wow, that person gets a lot done. So I think those are pretty core. Solve the creative problems. Have the passion and energy to serve, do what's right for the customer. And then get a lot done. >> And then you've talked about the curse of success. And avoiding the curse of success. And you guys have done that, obviously. So what are the kind of the lessons to say fresh? This started as a checkbook register and now the future of payments and mobile and the options are just tremendous. Bitcoin, who knows where that's going. So, as the future keeps evolving, how do you stay fresh? How do you keep the team fresh? How do you not rest on your laurels even though you have 5,000 fans walking around San Jose convention center today? >> This is a real challenge for companies. Because success turns organizations. It makes them dumb and slow. It's tempting, the thing I would avoid is it's tempting to look at your achievements. To look through the rear view mirror. And look at boy, how much we've achieved. But that only makes you self satisfied. In fact, with an organization you need to do the opposite. Look to where we want to be. Look to where we should be. And we're here. And then say, well shoot we are not very far. So for example, and I define these in customer terms. For example, we started our first product helped somebody manage a checkbook and pay bills. If you look at it really, the problem of paying bills has gotten worse. It used to be all bills came in the mail. So you had a little physical reminder. Some come in the mail, some you get by e-mail with invoices from some people. Some you go online and find a website. You pay some at a bank website. Maybe you go to the biller, you pay some. You write checks for some. It's much harder now. We have not actually got to the point. When our nirvana is you never worry about a bill. And you're never late. And you're never overdraft. The overdraft rate in the country is around 30% of households have a late payment during the year from which they get fees. And the overdraft rates, the overdraft charges can be $30, $35. We have not solved that yet. We got to look and say with all that we've done, that's what we should have done. So we've got a team working on that right now. Because we got re-focused on it. So we'll be coming out in December with stuff in there. Look at tax. Tax many people would say is one of our best businesses. And it is. Look at all we've achieved. But, look at the reality. People are still spending a lot of time on tax. Who wants to be spending time typing stuff into tax software? Does anybody? (laughter) No. There's not an accountant, there's not a consumer. We haven't solved that yet guys. There are still a hundred million people in the country typing stuff in to systems to do taxes every February, March and April. That's where we want to be. Is ultimately there is no typing in. All that information you have that goes in your tax return goes in automatically. And if you're an accountant, it all goes in for your clients automatically. So that you can focus on the high level stuff and not the drudgery. So, viewed from the lens of really what life should be. What's our aspiration? Our ideal? Keep people focused on that. And it sure has helped motivate us. I mean, we should be finding a lot of money for small businesses. And we're launching, announcing today ways that we help small businesses find more money. We should be eliminating the drudgery of running a small business. Nobody wants to do the book work. Instead, they want to do what they love to do in business. It could be working with clients. It could be the craft of doing the business. It could be selling new business. Every business person has something they love to do. And it's not doing the books. And that yet, people still have to do it. We want to have it on your phone so you don't have to do the books. It's done automatically. And you got a question, boop boop, there's the answer. >> So you mentioned the phone. Is that the next big growth opportunity? Mobile this is top priority with so many different sectors right now. >> Yeah, yeah. It's the growth today. In fact, every new feature and new benefit that Sasan Goodarzi showed today in his keynote address. Every one of 'em, he showed it on a mobile phone. Every one. It's the fastest growing. TurboTax the great consumer business. It's the fastest growing platform by far. So yeah, if you can take stuff off a desktop and put it so automatically that you can just get on your phone, say, okay, yep, do it. >> Right, right. >> Yeah, so that's where we're aiming a lot of our innovation. And these are amazing platforms. A simple example, the fastest growing form of employment in the United States and in fact, in the world is self employed. Where you think of an Uber driver or someone like that. People who work as consultants, contractors, they work for themselves. They've got to keep track of all their business expenses. Or they lose that money on their tax returns. Money out of their pocket. They got to keep track of every individual business expense which of course, they co-mingle with their personal checking, personal credit card. And they got to keep track of every mile they drive for business. And keep it separate with contemporaneous records that the IRS requires with the starting odometer reading, the ending odometer reading, and the destination and what it was for. Well you can imagine that's such a pain in the butt. So many independent business people, freelancers fail. Or they do some but not others. And that's money right out of their pocket. Thousands of dollars they don't get. They should get that they deserve. So we've devised and a team really creative work, QuickBooks Self Employed. It sits on your phone in your pocket. It reads what's coming from your bank and your credit cards and anytime you're stopped at a stop light or you've got two minutes before a meeting starts. You can go through and say oh, that was a business expense, business, business. That was personal, personal. It's that fast. And then you get complete records for your taxes. Oh then mileage. There's lots of software out there that'll track your mileage but it does by pinging the GPS. GPS takes battery. You ping the GPS all day long, what happens? Zhoom. >> Goodbye phone. >> Bye bye phone. So it's worthless. Our guys we launched that. Quickly found out that people stopped using it because it drained their battery just like everyone else. So, three clever engineers. Together with a couple others came up with a really clever idea which we've patented now. And it tracks your location without pinging your GPS all day long. So it doesn't drain your battery. So now you had complete records. It can detect when you're driving and where you started, where you finished. How many miles. Keeps perfect record, just as the IRS requires. And then you just have to tell it which are business, which are personal. And then it learns. Which one are business trips. So that over time, it knows when you're driving on business and you don't have to do anything. You get complete tax records. We've got businesses using it who get on average $7,000 of tax deductions. $7,000 of tax deductions. Because of the way it tracks. >> And you're taking advantage of the platform. You're taking advantage of the accelerometer. >> Yes. >> More importantly I think. The thing about mobile that most people don't maybe consciously think of is the way we interact with it as you said is little bits of time here, there, and everywhere. >> Scott: Yes. >> It's not the sit down thing. But I think what I think is most exciting about this show is it's a lot of talk about technology. But at the end of the day, it's really more about business. And small business. And small medium size business. And getting business done. >> Scott: Yes. >> And letting people do those dreams like the gal that was on the keynote. >> Scott: Yes. >> Letting her build her company and her franchise. And not have to worry about am I getting all the right deductions. >> That's right. I think the technology is the enabler. But it's all to enable what? What are we trying to deliver? And you saw it, in the kind of lead of slides. We're trying to fuel the success of small business. This is all about success. The technology's an enabler but that's not the center, the star of the show. The star of the show are small businesses and how they succeed. And how the suite of things that hundreds of developers and hundreds of software entrepreneurs who all build for the QuickBooks ecosystem. The new methods, and new ways to drive small business success. And at the end of the day, we don't measure ourselves with software. We measure ourselves with how much more money did we make small businesses? How much time did we save them so they could do what they love? How did we help them grow their business? Running a small business is a, and I know from starting Intuit, it absorbs who you are. You identify with that business. It is your representation to the world. To your spouse, to your in-laws. And if that business is successful, it's something about you that's irreplaceably positive. If that business is struggling, it strikes to the core. I mean, you feel bad. You look bad. So helping businesses succeed. And move them from mediocrity to success is such a home run for the psychology of this growing part of our economy. For each individual, it's your report card on yourself. And we can help make those report cards much better. That's our mission. That's how we're going to change the world so, so dramatically. People can't imagine going back. >> I'd say that you've already changed it dramatically. And it is exciting to hear about the next steps but this whole blend of strategy and execution and culture you're being commended for. It's just a great example of all those factors coming together and make great things happen for a lot of people around the globe so congratulations for that and thank you for being with us Scott. We appreciate the time here on theCube. >> Jeff, John thank you very much. This was a pleasure. >> Jeff: Thank you. >> You bet. Back with more from San Jose in just a bit. You're watching theCube here on SiliconANGLE TV. (techno music)