>> Thank you for joining us today for this session entitled, Deploy any Workload as a Service, When General Purpose Technology isn't Enough. This session today will be on our HPE GreenLake platform. And my name is Mark Seamans, and I'm a member of our GreenLake cloud services team. And I'll be kind of leading you through the material today which will include both a slide presentation as well as an interactive demo to get some experience in terms of how the process goes for interacting with your initial experience with our GreenLake system. So, let's go ahead and get started. One of the things that we've noticed over the last decade and I'm sure that you have as well has been the tremendous focus on accelerating business while concurrently trying to increase agility and to reduce costs. And one of the ways a lot of businesses have gone about doing that has been leveraging a cloud based technology set. And in many cases, that's involved moving some of the workloads to the public cloud. And so with that much said, though, while organizations have been able to enjoy that cost control and the agility associated with the public cloud. What we've seen is that the easy to move workloads have been moved but there's a significant amount as much as 70% in many cases of workloads that organizations run which still remain on prem. And there's reasons for that. Some cases it's due to data privacy and security concerns. Other times it's due to latency of really needing high-performance access to data. And the other times, it's really just related to the interconnected nature of systems and that you need to have a whole bunch of systems which form an overall experience and they need to be located close together. So, one of the challenges that we've worked with customers and have actually developed our GreenLake solution to address is this idea of trying to achieve this cloud-like experience for all of your apps and data in a way that leverages the best of the public cloud with also that same type of experience delivered on premise. So as you think about some of the challenges, again, we touched on this that customers are trying to address. One of the ones is this idea of agility, being able to move quickly and to be able to take a set of IT resources that you have and deploy them for different use cases and different models. So, it's one of the things as we built GreenLake, we really had a strong focus on is how do we provide a common foundation, a common framework to deliver that kind of agility. The next one is this term on the top right called scale. And one of the words you may hear is you hear cloud talked about regularly is this notion of what's called elasticity and the ability to have something stretch and get larger kind of on an on demand basis. That's another challenge and premise that we've really tried to work through. And you'll see how we've addressed that. Now, obviously, as you do this, you can achieve scale if you just put a ton of equipment in place much more maybe than you need at any given time but with that comes a lot of costs. And so as you think about wanting to have an agile and flexible system, what you'd also like is something where the costs flexes as your needs grow and it's elastic and that it can get larger and then it can get smaller as needed as well. So, we'll talk about how we do that with our GreenLake solution. And then finally it's complexity, it's trying to abstract away the vision for people of having to be aware of all the complexity it takes to build these systems and provide a single interface, a single experience for people to manage all of their IT assets. So we do that through this solution called HPE GreenLake and really we call it the cloud that comes to you. And as you think about what we're really trying to do here is take the notion of a cloud from being a place where people have thought about the public cloud and turning that to an idea of the cloud being an experience. And so it's regardless of whether it's in the public cloud or running on premise or as is the case with GreenLake, whether it's a mixture of those and maybe even a mixture of multiple public clouds with on-prem experience, the cloud now becomes something you experience and that you leverage as opposed to a place where you have an account and that can include edge computing combined with co-location or data center based computing. It could include equipment stored in your own data center and certainly it can include resources in the public cloud. So, let's take a look at how we go about delivering the experience and what some of those benefits are as we put these solutions in place. So, as you think about why you'd want to do this and the benefits you get from GreenLake, what we've seen in terms of both working with customers and actually having studies done with analysts is the benefits are numerous, but they come in areas that are shown here, one time to deployment. And that once you get this flexible and easily to manage environment in place with what we'll show you are these prebuilt, pre-configured and managed as a service solutions, your time to deployment for putting new workloads in place can shrink dramatically. The next in terms of having these pre-configured solutions and combining both the hardware and software technology with a set of managed services through our GreenLake managed services team, what you can do is dramatically reduce the risk of putting a new workload in place. So for example, if you wanted to deploy virtual desktop infrastructure and maybe you haven't done that in the past, you can leverage a GreenLake VDI solution along with GreenLake management services to very predictably and very reliably put that solution in place. So you're up and running focusing on the needs of your users with incredibly lowered risk, because this was built on a pre-validated and a pre-certified foundation. Obviously, I talked earlier about the idea with GreenLake is that you have flexibility in terms of scaling up your use of the resources, even though they're computers that may be in your data center or a colo, and also scaling them back down. So if you have workloads over time, that may be even an end of month cycle or an end to quarter cycle where certain workloads get larger and then would get smaller again, the ability with GreenLake on a consumption billing basis is there where your costs can flow as your use of the systems flow. And again, I'll show you a screen in just a few minutes, that kind of illustrates what that looks like. And then the last piece is the single pane of glass for control and insight into what's going on. And what we mean by that is not just what's going on from a cost perspective, but also what's going on from a system utilization perspective. You'll see in one of the screens I'll show that there's a system utilization report of all of your GreenLake resources that you can view at any time. And so what you can get visibility to, for example, with storage capacity as your storage capacity is being consumed over time as you generate more data, the system will tell you, hey, you're getting up to about 60, 70% utilized. And then at that point, we would be able to work with you to automatically deploy even though you won't be paying for it yet, additional storage capacity so it's ready as your needs grow to encompass that. So in terms of what are some of these services that we deliver as part of GreenLake? Well, they range and you see here a portfolio of services that we offer. If you start at the bottom, it's simple things, right? Things like compute as a service, and I'll show you examples of that today, networking as a service, hyper-converged infrastructure as a service. And then if we work our way up the stack, we move from kind of basic services to platform services, things like VMware and containers as a service. And then if we go to the top layer of this, we actually can offer complete solutions for targeted workloads. So if your need was for example, to run machine learning and AI, and you wanted to have a complete environment put in place that you could leverage for machine learning and AI and use it and consume it on a consumption as a service basis, we've got our MLOps solution that delivers that. And similarly, I mentioned earlier, VDI for virtual desktops or a solution for SAP HANA. So, the solutions range from very basic compute at the foundation all the way up to complete workload solutions that you can achieve. And the portfolio of what these are is expanding all the time. And as you'll see, you can go out to our hpe.com site and see a complete catalog of all the GreenLake services that are available. So let's take a minute and let's drill in like on that MLOps solution. And we can take a look at how that fits together and what makes that up. So, if you think about GreenLake for MLOps, it's a fast path for data scientists, and it's really oriented around the needs of data scientists within your organization who have a desire to be able to get in and start to analyze data for advantage in your business. So, what comes with an MLOps solution from GreenLake starts at the left side of the slide here with a fully curated hardware platform, including GPU based nodes, data science, optimized hardware, all the storage that you're going to need to run at scale and that performance to make these workloads work. And so that's one piece of it is a curated hardware stack for machine learning. Next in the software component, we pre-validated a whole bunch of the common stack elements that you would need. So beyond operating systems, but things for doing continuous integration, for things like TensorFlow and Jupyter notebooks are already pre-validated and delivered with this solution. So, the tools that your data scientists will need come with this, ready to go, out of the box. And then finally, as this solution gets delivered, there's a services component to it beyond just us installing this full thing and delivering a complete solution to you. But the GreenLake management services options where our services teams can work side by side with data scientists to assist them in getting up to speed on the solution, to leveraging the tools, to understanding best practices if you want those, if you want that assistance for deploying MLOps and the whole thing's delivered as a service. As similar, we similar solutions for other workloads like SAP HANA that would leverage again, different compute building blocks, but always in a way that's done for workload optimized solutions, best practice and that build up that stack. And so your experience in consuming this is always consistent, but what's running under the hood isn't just a generic solution that you might see in for example, a public cloud environment, it's a best practice, hardware optimized, software optimized environment built for each one of the workloads that we can deploy. So I like to do at this point is actually show you what's the process like for actually specifying a GreenLake solution. And maybe we'll take a look at compute as our example today. So, what I've got here is a browser experience, I'm just in my web browser, I'm on the hpe.com website and what I'd like to do. I mean the GreenLake section and I've actually clicked on this services menu and I'm going to go ahead and scroll down. And one of the things you can see here is that catalog of GreenLake services that I referenced. So, just like we showed you on the slide, this is that catalog of services that you can consume. I'm going to go to compute and we'll go about quoting a GreenLake compute solution. So we see when I clicked on that, one of the options I have is to get a price in my inbox. And I'll click on that to go in here to our GreenLake quick quote environment where if in my case here for our demonstration, I'll specify that I'd like to purchase to add to my GreenLake environment some additional general compute capability for some workloads that I might like to run. If I click on this, I go in and you notice here that I'm not going to specify server types. I'm really going to tell the system about the types of workloads that I'd like to run and the characteristics of those workloads. So for example, my workload choices would be adaptable performance or maybe densely optimized compute for highly scalable and high performance computing requirements. So, I'll select adaptable performance. I have a choice of processor types, my case, I'll pick Intel. And I then say, how many servers for the workloads that I want to run would be part of the solution. Again, in my case, maybe we'll quote a 20 server configuration. Now, as we think about the plans here, what you can see is we're really looking at the different options in terms of a balanced performance and price option which is the recommended option. But if I knew that the workloads I were going to run were more performance optimized, I could simply click on that option. And in the system under the hood does all the work to reconfigure the system. I'm not having to pick individual server options as you see. So once I picked between cost optimized balance or performance, I can go in here and select the rest of the options. Now, we'll start at the top right and you see here from a services perspective, this is where it specifies how much services content and in services assistance I'd like all the way from just doing proactive metering of my solution all the way through being able to do actual workload deployment and assistance with me physically managing the equipment myself. The other piece I'll focus on is this variable usage. And this comes back to how much of the variable time, variable capacity of additional capacity, what I like to have available in my data center for this solution. So if I know that my flex could be larger in the future of the capacity, I want to flex up and down. I might pick a slightly larger amount of flex capacity at my location as part of this solution. With that, I'd select that workload. And the less steps would be, I could click on get price and this whole thing will be packaged up and shipped to you in terms of the price of the solution. And any other details that you might like to see. And I encourage you to go out to hpe.com and to go through this process yourself for one of the workloads that might be of interest for you to get a flavor of that experience. So if we move forward, once you've deployed your GreenLake solution, one of the things you see here is that single pane of glass experience in terms of managing the system, right? We've got a single panel that all in one place provides you access to your cost information for billing, and what's driving that billing, your middle and the middle of the top center, you can see we've got information on the capacity planning but then we can actually drill in and actually look at additional things like services we offer around continuous compliance, capacity planning data for you to build and see how things like storage or filling, cost control information with recommendations around how you could reduce or minimize your costs based on the usage profile that you have. So, all of this is a fully integrated experience that can span components running both on-premise and also incorporating services that could be in the public cloud. Now, when we think about who's using this and why is this becoming attractive? You can imagine just looking at this capability that this ability to blend public cloud capabilities with on-premise or in a co-location, private data center capabilities provides tremendous power and provides tremendous flexibility for users. And so we're seeing this adopted broadly as kind of a new way, people are looking to take the advantages of cloud, but bring them into a much more self-managed or on-premise experience. And so some example, customers here include deployments in the automotive field, both at Porsche or over on the right at Zenseact, which is the autonomous driving division of Volvo where they're doing research with tremendous amounts of data to produce the best possible autonomous driving experience. And then in the center, Danfoss who is one of the world's leading manufacturers of both electric and hydraulic control components. And so as they produce components themselves, that drive an optimized management of physical infrastructure, power, liquids and cooling, they're leveraging GreenLake for the same type of control and best practice deployment of their data centers and of their IT infrastructure. So again, somebody who's innovating in their own world taking advantage of compute innovations to get the benefits of the cloud and the flexibility of a cloud-like environment but running within their own premise. And it's not just those three customers clearly. I mean, what we're seeing is, as you see on the slide, it's a unique solution in the market today. It provides the true benefits of the cloud, but with your own on-premise experience, it provides expertise in terms of services to help you take best advantage of it. And if you look at the adoption by customers, over a thousand customers in 50 countries have now deployed GreenLake based solutions as the foundation on which they're building their next generation IT architecture. So, there's a lot of unique capabilities that as we built GreenLake, that we have that really make this a single pane of glass and a very, very unified and elegant experience. So as we kind of wrap up, there's three things I want to call your attention to, one, GreenLake, which we focused a lot on today. I'd also like to call your attention to the point next services, which are an extension of those GreenLake services that I talked about earlier but there's a much broader portfolio of what Pointnext can do in delivering value for your organization. And then again, HPE financial services who much like what we do with GreenLake in this as a service consumption environment can provide a lot of financial flexibility in other models and other use cases. So, I'd encourage you to take time to learn about each of those three areas. And then there's obviously many many resources available online. And again, there's some that are listed here but it kind of as a single point takeaway from this slide, I encourage you to go to hpe.com. If you're interested in GreenLake, click on our GreenLake icon and you can take yourself through that quoting experience for what would be interesting and certainly as well for our compute solutions, there's a tremendous amount of information about the leading solutions that HPE brings to market. So with that, I hope that's been an informative set of experience. I'm thanking you for spending a little bit of time with us today and hopefully you'll take some time to learn more about GreenLake and how it might be a benefit for you within your organization. Thanks again.

>> Announcer: From around the globe, it's "theCUBE", covering HPE Discover Virtual Experience, brought to you by HPE. >> Hi, and welcome to "theCUBE"'s coverage of HPE Discover, 2020, The virtqual Experience. I'm Stu Miniman. Of course this year, we're getting to talk to HPE, their customers and their partners where they are around the globe. We've said many times this, we're together even while we're apart, having to dig into a really important partnership with HPE and VMware. Welcome into the program, first time guest on the program, Krista Satterthwaite. She is the Vice President of Product Management for Compute, with Hewlett Packard Enterprise and welcome back to the program. Lee Caswell, he is the Vice President of Product Marketing for hyper converged infrastructure, at VMware. Of course, we're talking about vSphere and how that gets bundled into everything else. Krista and Lee, thanks so much for joining us. >> Thanks for having us. >> All right, so, Krista, let's start with you. So, I'd like to know a little bit about your background. And of course, the the HP and HPE relationship with VMware, goes back to, the earliest days, but give us a little bit about, where in the portfolio you focus on and how VMware fits in. >> Oh, sure, sure. So I've been with HPE for 24 years now. And I'm leading the business for Alliance and Synergy. And talking a little bit about the relationship with VMware. So we've been partnering for 19 years, and we have over 200, 000 joint customers together. And I'm actually often asked about the partnership and how we partner, and we really partner across all fronts. So it's from the innovation, to the CO engineering, to working with specific customers on what solutions are good for them to servicing our customers. So we're really working across the board and a lot of customers we work with closely, are really impressed with how closely we're working together because that's what they look for. >> And and Lee it's an interesting relationship to watch, obviously, the long history Krista talked about on the Compute side. But the VMware HPE partnership is more than just the Compute, maybe give us a little bit of a view inside, the joint engineering, joint go-to market efforts that you do. >> Yeah, you bet. I mean, customers always sit up straight when we talk together, because, both of our companies are just raw engines of innovation. And they look forward to not just the capabilities that we're bringing, but also the seamless way that we integrate that and make that seamless and easy for customers to digest. So, certainly on the server front, through vSphere, that's been a long standing participation, the VMware cloud Foundation, then this fully Software-Defined stack became a really interesting way for us to go and partner and show joint value to customers who are trying to basically get more speed, particularly speed. We're going to talk about a lot of that today, and then finally, VMware cloud foundation that we've opened up into storage systems. So there's certainly a hyper converged element of it. But now what we do with nimble three part and now primeira is a really interesting way for us to take the vVols technology that we have and extend a common operating model. So really just interesting innovation for customers to take advantage of, as they look to innovate themselves. >> Krista, from a research standpoint, we were really early in watching, new models of building out storage, and we said, the pendulum is swung back to pull it much closer to Compute. You talked about you've got a broad portfolio in Compute, Synergy has some really interesting ways to be able to compose things and leverage software capabilities, so maybe give us a little bit as to how HPE differentiates in the market. Because, VMware does partner with lots of people but what separates these point solutions from everything else out in the market. >> Sure, and Synergy is a great example because what we're seeing is a really, really high interest on, on Synergy with VCF. And the reason for that is because customers want a software-defined infrastructure, that they can compose, Compute, storage and networking, as they need to, to address any workload they have. And they want to do that with a partner like VMware and VCF. So what we see is customers choosing those two things together, and building their hybrid cloud environments on those two. When I think of some of the customers that we have, all given a specific example. So, Banco Santander is one of the largest banking groups in the world, and they are really trying to drive innovation across all of their locations that are in North America, South America, Europe, Asia. They're trying to drive innovation across, they have a big project. And they selected Synergy and VCF as a service GreenLake model to help them transform their business. And they're really excited because what they think this is providing to them is a reduced data center space, reduced power consumption, and reduced costs. And all of that with automation, more automation than they've had in the past, more flexibility than they've had in the past. >> Yeah, I'm so glad you brought up the GreenLake, because, those other service models, cloud obviously has been a big discussion for the last few years. Lee, VMware is no stranger to working in multi and hybrid cloud environments. Give us a little bit about what you're hearing from your customers, you mentioned the GreenLake solution. How does that fit in the, overall, VMware multi cloud offering? >> Well, we all know these are uncertain Time's right? And customers in uncertain times are looking for flexibility. How do they go and basically, invest smartly, look to come out of uncertain times stronger. And what we're finding is that flexibility... Starting at, we're really impressed with this Synergy platform by the way. The idea of being able to flexibly configure, Compute and storage to tie into external arrays from that and to have the VMware cloud foundation as a unifying Software-Defined data center concept that's available on-prem and then extends into the hybrid cloud. This basically gives investment protection to customers who are looking for how to invest in, you've mentioned GreenLake as well. And I just mentioned that innovation on GreenLake is about true consumption-based purchasing models, if you will. And that's different than just a financial engineering aspect. I mean, that's real innovation and real technical innovation in terms of how customers can go and apply infrastructure. At the time that they need it, relative to the compelling business models. >> I'll chime in there too, I will tell you a little story about when I first presented the GreenLake model, at that time, it wasn't called GreenLake. But I presented it to a bunch of customers about 100 customers in an advisory council. And I have never had so many people come up to me afterwards, trying to figure out how they can get that for themselves, as I did when I had that presentation. What really resonated with people is that they wanted to take advantage of the latest and greatest technologies, but they didn't have big budgets. And when they did take advantage of those technologies, one of the challenges has been growth. So when they need to expand, that's another procurement cycle. You have to wait, you have to stand it all up. With GreenLake, you actually have that added capacity on site, and then also payfor what you use. So they were attracted to All of those things. And I feel like right now, in the environment we're in, many people had big, big projects, things they wanted to do. And they may have plan those capital expenditure for that, but that money may not be there. So GreenLake is one of those things that can help overcome that challenge. And what we found is when people use GreenLake, we don't see many people go back. So, I was talking with the GreenLake light team, and I said, what happens if they decide not to do GreenLake and they kind of pause, and they're like, "Well, we really haven't run into that very often." So it's very, very popular and customers were really happy with it. >> Yeah, talking about innovation and helping customers take advantage of new technologies. Lee, maybe we'll start with you and Krista, definitely want your input. Been a lot of feedback about vSphere seven. Of course, one of the big pieces of that, is how cloud native containerization Kubernetes can be pulled into the virtualization platforms. So we're talking a lot about VCF, Lee, that's the, the way to get it, the Kubernetes piece today. Tell us a little bit about that, what you're hearing from customers and then, Krista, I'd like to understand how that fits into the HPE offerings. >> Yeah, the data we have, shows that 95% of new applications, are being developed on containers. Why? Because it's the speed of development. And so, at VMware, we've re architected vSphere for the first time that in the last five years. And look carefully at what VMware integrates into the hypervisor, because that's what we believe is going to be really benefiting from performance, efficiency and management. And so we've integrated Kubernetes directly into the hypervisor itself. And then through our Tanzu portfolio, introduce an upstream, compatible, Kubernetes development environment so that we have developer-ready infrastructure. And that's really important because at the speed of new applications, basically, you need to be able to respond quickly to those. And what VMware has always offered, which is a resilient underlying infrastructure with an intrinsic security model built in. And separately important, when containers are being spun up more quickly, destroyed more quickly. They're being portable now they're portable across the hybrid cloud, those models mean that you need, and you get the value right from this integrated model that leverages all of the experience and knowledge that people have around how to run this center and this sphere. So really exciting. And it's available in VCF 4.0 with Tanzu and Synergy. >> Yeah. And I will say that it's very exciting because I actually see the interest I see customers asking about and inquiring about it. I can, definitely second everything that Lee just said. I think Lee you're going to see a really fast transition over because there's so much value added in. >> Excellent. Okay, Krista, while I've got you on the Compute piece, Lee said that 95% of new applications are being built on containerization. How has that, impacted architecture in how you're working with customers? >> Yeah, so what I find is that customers, are very interested in containers. What we're doing is we're helping them from a services standpoint, a consulting standpoint. Many of these customers are adopting for the first time trying to figure out how they could leverage containers in their environment. From our standpoint, it's making sure that we have the right platforms and we're advising and consulting and helping customers get there. Excellent. Lee, Krista talked about Santander, wondering if you've got any customer examples you'd like to share. >> Yeah, great one is Porsche, I love the Porsche example, just because Porsche, just The epitome of speed. And so the idea of this flexibility. The way you're finding, is the flexibility starting from, let's say, from a Synergy, and flexible on hardware allocation? And then with VCF now being able to be flexible across the hybrid cloud, and now with VCF 4.0, with Tanzu, the flexibility of introducing new modern application support, and finally layering GreenLake on top of that, which Porsche is also using, it gives you this idea that, especially in uncertain times, but regardless, the changing business environment where everyone's responding to app development, pressures, timelines, and innovation, we've got a really interesting model now for customers to invest responsibly and be able to respond quickly. >> Excellent. Krista, I guess the other piece, onto Discover, any updates in the portfolio expanding the VMware solution that you can share? >> Yeah. Yeah, so I'd like to talk a little bit about our pre validated Synergy VCF solution stack with built in automation. So we've literally gotten rid of hundreds of steps, pre and post deployment. So we could speed deployment by five times. So we're talking to point in hours instead of weeks. So we're really, really excited about that. We're working together to make sure we're making things easier for customers, making that journey to a hybrid cloud. Very, very simple. So we're really happy to offer that to customers. >> Right, Lee, any final words you can share on HPE partnership? >> Yeah. what I might say is that the pace of innovation from our companies is so great. That really VMware Cloud Foundation is a way in our joint effort and joint delivery, is a way for customers to assimilate all of this innovation. So that day zero, it's guaranteed to work And then day two, you can lifecycle manage all the individual components from a common SVC manager interface. That's the value that we're bringing together today. Is that, listen, putting all this in place can seem daunting until the VMware cloud Foundation, with Synergy with all of the joint value we have basically makes it manageable, so that you can go and basically stop looking down at infrastructure. Look up at the ass. >> All right, Krista, I'll let you have the final word and final takeaways from HPE Discover. >> Okay, sure, thanks. Together, what we're trying to do is simplify that journey to Hybrid Cloud, makes sure that customers can innovate faster, provide stable operations and reduce their costs. >> Well, Krista and Lee, thank you so much for joining us. Congratulations on the progress. Looking forward to watching down the road. >> All right, thank you Stu. >> Thank you Stu. >> All right, stay tuned for lots more coverage from "theCUBE", HPE Discover 2020 Virtual Experience. I'm Stu Miniman, thanks for watching. (cool music)

>> From the SiliconAngle media office, in Boston, Massachusetts, it's theCUBE. Now, here's your host, Dave Vellante. >> Hello everyone, and welcome to this Cube Conversation. You know, the auto industry was a, if not the dominant force in the 20th century economy, and clearly, you see it in the headlines today. I mean all you got to do is look at Tesla. The stock is absolutely on fire, Tesla's market value is actually greater than that of Ford and GM combined. Even though its revenues are about one 12th of those two combined. The macro discussion today is really heating up around ESG, which stands for environmental social governance. So, electric vehicles are really picking up momentum, and maybe that's the tailwind for Tesla, but consumers are pragmatic, the electric is still more expensive than internal combustion-powered vehicles, so we'll see how that plays out. One of the things we talk about a lot on theCUBE is the software content in automobiles. In many ways, these vehicles are code on wheels, so that's part of the hype factor, too. But you know, I've always argued that the incumbent auto makers are actually in a pretty reasonable position to compete. While autonomous vehicles, they may disrupt the incumbents, and even though right now Silicon Valley is ahead of Detroit and Japan and Germany and Korea, there's an ecosystem that is evolving to support traditional auto makers. Now, one of those players is Tactile Mobility. The vast majority of data created around autonomous vehicles today is visual-based with LIDAR as a key enabler. But a human driver, you think about it, they don't just rely on sight, they're able to feel the road, the bumps, the curves, and the impacts of things like weather. In fact, it's estimated that more than 20% of vehicle crashes in the US each year are weather-related. And intelligent cars, they really still can't predict road conditions ahead. Tactile offers software that uses sensors that already live in the vehicles to predict and feel road conditions like black ice and potholes to improve safety. And with me to talk about these trends and his company is Amit Nisenbaum, who's the CEO of Tactile Mobility, Amit, thanks so much for coming on theCUBE. >> Thank you Dave very much for having me. >> Yeah, so really, it was a great opportunity, when I heard you were in town, invited you out, and really appreciate you coming out to our Marlborough studios, but let me start with, why your founders launched Tactile Mobility. >> Well, Dave, it's a very interesting story, I think, for our company, as well for other entrepreneurs to learn from it, because actually, the company's been around for about eight years, and it all started from a conundrum from a question that was posed to our founder, Boaz Mizrachi, which was about how do you take a vehicle from point A to point B at a set speed, with minimum gas consumption, using only the software and data coming off the vehicle sensors that are run of the mill sensors? And that question started this whole company, he believed that it's only an optimization question, meaning all of the data is out there, meaning data about the conditions of the road, the grates, the curvatures, the conditions and the health of the vehicle, meaning engine efficiency, tire health, et cetera et cetera. And what he found out was that actually neither this nor that has existed. So it was way more complicated than a mere optimization question, it's about how do you generate that data about the vehicle and the road? And he launched the company in order to go after those two data sets. He was able to solve that, or to address that question, and to take a vehicle and to show that you can take a vehicle from point A to point B at a set speed while minimizing fuel consumption, up to 10%. By the time that he has done that, gas prices dropped, and the question was what's next, and fortunately enough, the industry and the hype around autonomous vehicles has come around, and that has been the next frontier for our company, and that's what we been focusing on since then, but not only on that but on also other aspects, which I'll be happy to speak about. >> That is an awesome story of a pivot, you see this all the time with startups, it's kind of survive until you can thrive, and then something happens that's a tailwind, great technology that the visionary can see how to reapply it, and a little bit of luck involved, maybe, okay, so you-- >> Stamina. >> Stamina, right, you got to have a strong heart and stomach to be a startup. Okay, and you joined just a couple years ago, what attracted you to Tactile? >> Well I've been in this industry, actually in the cross section of the two industries of automotive and energy for about 12 years now, starting from a company called Better Place that you might have heard of, I was one of the first 10 employees there, and those two industries have been near and dear to my heart ever since. I like big questions, I like big challenges, I like big plays that have the potential to make a real difference, so the fact that the Tactile Mobility, at the time it was called MobiWize, it was in this industry was a big plus, but also the fact that the offering is not really the vanilla flavor offering, everybody's doing LIDAR and radar and cameras, all of a sudden there is someone else that is saying "Wait a minute, there is that "neglected segment, that additional set "of sensors, the sense of tactility that all of us "are using when we're driving, "and computers will need that as well. "How about that, this is something "that nobody pays attention to." And that really caught my attention. >> So I kind of hinted at this in my little narrative up front, the hype was all around autonomous, but let's face it, level five autonomous, it's, we're talking at least 2030, maybe further, but everybody drives some form of autonomous vehicle today, if you purchase a new vehicle, and that's really the space that you play in, so what are the big trends that you see, and what's the problem that you're solving? >> Yeah, so first of all, you're absolutely right, when people speak about autonomous vehicles, they imagine themself a car, a vehicle with big red button and that's it, that's what is called level five. However, there are four levels below that that lead to that, and today most of the vehicles leaving the assembly line are either level two or level three. That's why we're also saying that we're in the business of smart and autonomous vehicles, and the challenges there, if you're looking at the vehicles themself, are challenges of how do we make those vehicles both safer, as well as more enjoyable to ride? And the ability to address both of those together is actually not as simple as one might think, so that's what we're focusing on, and that's the trend, the trend of no compromises, that you go both for safety, as well as a user experience, that's on the vehicle side. Having said that, being a data company that has a proprietary software stack, that allows it to generate that data, the tactile data, the data about the dynamic between the vehicle and the road, allows us also to take that data to the cloud, and in the cloud to split that dynamic into two separate models. One we model independently the vehicle, the vehicle health, and the other one is we're turning each one of the vehicles to become like a probe that feels the road conditions and maps the location of bumps, cracks, oil spills, black ice, et cetera et cetera, and by that we are able to crowd source the data and create new layer of the map, road conditions there. Going back to the question that was posed about how do you take that vehicle from point A to point B, in minimum fuel, here you go, we have those two types of data, and now we can use it in other verticals as well. >> Well that's very interesting, so a lot of people say "Oh, autonomous vehicles, it's all about real time, "you can't do anything in the cloud," and you actually, you're refuting that, because you're building essentially a map of what's happening on the roads, whether it's a pothole or a bump or a curve, et cetera. And so essentially you're doing that in the cloud, modeling that in the cloud and then what, bringing it down in real time, right? >> Yeah, so first of all, the first use case is indeed to bring it back to the vehicles and so the vehicle, and the vehicles around it, will know what's ahead of them. Use cases, there are about preconditioning vehicle systems, for instance, you're approaching a pothole, probably you want, you meaning the vehicle, would like to tune the suspension to become harder or softer. You're approaching black ice, probably you want, you, the vehicle, would like to slow down, so that's one use case, but there are other use cases. Other use cases around, for instance, road authorities and municipalities, we do have customers around the globe, road authorities and municipalities, that are subscribed to our data services, the road condition data services, that allow them to better plan maintenance, as well as dispatch crews to locations of hazards in real time. >> Yeah, so I remember when I was a kid, we had a CB, that's how you communicated what was ahead. "Hey, watch out, there's a pothole up ahead." >> Great technology. >> Now we're doing that, and now does that essentially require some kind of peer to peer network, or? >> So we're agnostic of the technology, we're the data layer behind all of that. These days, everything, or most of the use cases, are still running on vehicle to cloud to vehicle, or to anybody else, but there are companies that are working on vehicle to vehicle. >> So you mentioned a stack, what does your stack look like, can you describe that a little bit? >> Two parts, one is embedded software, that sits on one of the vehicle computers, one of the ECUs, and the other one is the cloud component, the component, the embedded software that sits on one of the vehicle ECUs usually either the gateway, or one of the vehicle dynamics ECUs, or maybe ADAS ECU, et cetera, it takes in real time, mounds of data for multiple existing nonvisual sensors, such as wheel speed from all four wheels, wheel angle, position of the gas pedal, torque of the brake pedal and much much more, ingest all of that, create a unified signal that describes in real time the dynamic between the vehicle and the road, that signal is very very noisy, so we apply signal processing methodologies to clean it, and then we apply on top of it algorithms and AI and all of that in real time, in order to derive insights about the vehicle road dynamics. You probably ask yourself, "Give me a concrete example" or something like that, 'cause it's kind of amorphous. The killer app these days with OEMs, vehicle manufacturers, is what is called available grip level. It's basically a signal to the vehicle computer about how drastically can the vehicle accelerate, decelerate, or change direction, all different types of acceleration, before it will start to skid. Think about it as the performance envelope of the vehicle. Nobody but us can model this using software only in any condition, and this type of data has multiple use cases in the vehicle, happy to tell you more about those, question is if we have time. >> We do, but I want to make a point. The software only, the thing, if I understand it correctly, the OEM doesn't have to change any hardware that, you're using the existing sensors of the vehicle, of which there are certainly dozens if not hundreds, to actually take advantage of this, right, you don't have to do any kind of hardware changes, is that correct? >> We're a data and data analytics and AI company. >> Yeah, so if you wanted to add some color and double click on some examples, that would be great. >> Sure, so going back to the available grip level type of data, of insight, I call it, think about adaptive cruise control, the function that allows a vehicle to drive at a set speed, however, to avoid colliding into the front vehicle. So today, it seems like all of the data is there for ACC, adaptive cruise control, to be effective, you know the distance from the vehicle, probably using a radar, you know the relative velocity between the two vehicles, so you have all of the information, however you don't know, you, again, the vehicle computer, how hard the vehicle can brake given how slippery the road is, given how healthy or worn out the tires are, et cetera et cetera. That means that the vehicle computer needs to err on the safe side and keep the large distance in order to allow safe braking. What's wrong with that? Going back to the question about the trend before, first of all it's not natural to the driver. We keep a certain distance for a certain reason, and when the distance is too large, it just doesn't feel natural to us. That's one thing. However, on the other side, it's also not safe, how is that? You keep too large of a distance, someone at the end will cut you in. And ironically, you kept a large distance to stay safe, all of a sudden you're worse off. So being able to allow the vehicle to know really, what is the tight distance, safe distance to stay from the vehicle, allows that vehicle to be more enjoyable to ride, as well as safe. >> So take that example, because today, I can sort of personalize that adaptive cruise control and say "Okay, I want one bar, two bar, three bar," but that's it, and I sometimes say "Whoa, is three bar right, is two bar right?" And you're right, sometimes I go "Eh, it's too far, "I think I'll cut it down to two bar or one bar." You're saying with your software, the system is intelligent enough to optimize that, to keep me safe, but also keep me having comfortable driving. >> Absolutely true, actually those three bars is kind of a psychological exercise, right? Because the shortest bar is that large distance. When they tell you two bars or three bars, it's kind of like "Do you want to keep a large, "very large, or extra large distance," right? Because they will never allow you to keep shorter distance shorter than what is really really the bare minimum in order to brake at the worst case scenario. >> Even if it's safe. And that's really where your software comes in, okay. Now Porsche is an investor in the company, presumably it's a customer, right? >> No, they actually said publicly that they're a customer as well. >> Okay, great, so talk about how customers are using this, and what the adoption cycle looks like, and maybe give us some examples of how it's being applied. >> So customers, you mean OEMs, car manufacturers. So the way that they use it, I just described it now, the adoption cycle, we in this industry unfortunately cycles are long. We work years to create relationships with the car manufacturers to allow them to learn about our capabilities, to validate the integrity of our software. They also most commonly run RFPs or RFQs in order to choose the right technology, and I'm glad to say that we're winning again and again and again, and then there is the integration cycle, which by itself is a few years in length. So the cycle altogether is long, however, we found that our approach is quite effective, and the approach, not necessarily the technology, yes, but also the way that we approach those OEMs. We are quite, if I may say, humble. We know that we're not the car engineers, the typical car engineers. We actually know very little about cars, what we know, we know data very well and we know AI very well. And when we come to them, we say "We're not trying to replace your engineers, "we're not trying to do what you do, "we're trying to tackle the same problems "that you weren't able to tackle before "from a very different angle," and that works very well. >> So, you talked about the integration cycle of a couple, or maybe even longer, how long is the design cycle for these things, is it also years, or? >> So, the design cycle from our perspective is much much more agile, actually we are working in the Agile framework in terms of the development of the software itself, but you're asking about the design, much faster, but when I said a few years, a couple of years, I meant per OEM to design together, to allow them to feel that we're designing, meaning customizing the software to their needs, as well as implementing it, that's the length. >> But what they get is a competitive advantage, so Porsche as a leader, obviously, and an early adopter, is going to be able to now commercialize this technology, and of course it'll be embedded, but now it'll be a feature that the car salesperson will highlight, and maybe they market it, maybe they don't, but that gives them a competitive differentiation, right? So are you seeing that other OEMs are starting to really get this, and sort of leaning in, or what's your experience? >> Yes, it's the typical technology adoption curve, there are the early adopters, and there are the mainstream and the late adopters, I'm glad to say that these days we're not only working with the early adopters, but also more with the mainstream. I encourage you to stay tuned, I believe that in the coming month or two, we'll have a big announcement about another major OEM that has chosen us commercially for mass production, and we are in quite advanced stages with OEMs both in Europe and North America, starting also to spin out to Asia. >> And is the business model, is it a subscription model, is it a one time payment from the OEM, how's it work? >> That's another thing that made me excited about the company, going back to your question from before, it's quite diverse, I would say. For the OEMs, that's software that we embed in their vehicle, it's software licensing. However, the data that we generate and then upload to the cloud and repurpose it with the OEMs themself, but also as I said before, road authorities, municipalities, fleet managers, insurance companies, I didn't have a chance to touch on all of the verticals. That's a subscription model, so the two models working together, it's actually quite an attractive, valuable position for us and for our investors. >> So there's software license, and then there's data as a service. And so there's also adjacent industries that you can go after, you just mentioned a couple, so when you think about the total available market, which obviously, any CEO is going to do, TAM expansion is part of your job, but so what's that vision, what does that look like? >> So in terms of the size itself, it's measured in the trillions, it's very very big. In terms of the different verticals, the ones that I tapped on are the first ones, but even within those, these days we're really trying to stay razor focused on the OEMs and road authorities and municipalities. We have fleets and fleet managers that are coming to us with requests for the data that we call vehicle DNA, that's the data about the vehicle health, et cetera, and that's the third vertical that we're starting to address these days, but we're only 25 people, growing to 40, we're trying to be very very agile, that's from one end, and from the other end, now that we showed our value to the car manufacturers, we're going for the force multipliers, meaning partnerships with the channels, with the T1s, the suppliers to the OEMs themself. >> And let's see, you've been around eight years, you've been there two years, right, and then I think you did a raise of roughly, what, nine million to date? >> In October 2019, we announced the latest round of nine million dollars from Porsche, as well as some other investors, yes. >> Great, okay, so I mean not a ton of money, but you guys are small, and so, little bit more on the companies, 20, going to 40, you're well capitalized, but today, you see people raising 250 million, what do you sense as your capital needs, I mean you're obviously actively raising money, and doing what a CEO does, but can you share with us your milestones for the next 12, 18 months? >> First of all, we were fortunate, and fortune has something to do with it, I think that being disciplined is another thing, to have revenue already. So our capital needs, we're still not profitable, and we're growing fast, so we need to raise in order to support that growth, but we're quite diligent about that. Also, true, companies have raised tens and hundreds of millions of dollars. First of all, not all companies in this industry are created equal, we're not a hardware company, we're a software and data. We're also not trying to do a fully integrated offering like, let's say Zuks or something like that, which requires way way more money. And actually, I'm quite glad that we're raising as we need, but not more than that, because what you raise, you need to return tenfold, so we have enough in order to support the growth of the company in years to come. >> Well the OEM model is very sales efficient as well, so it's not like in software companies today, are hiring people to do inside sales, outside sales, enterprise sales, and so it's a different business. Well Amit, first of all, congratulations, a really interesting story, really appreciate you coming out to our studios here in Marlborough and sharing your story, and best of luck to you. >> Thank you very much, Dave, it's been a pleasure coming here, and I'm glad that you invited me. >> Great, and thank you everybody for watching, this is Dave Vellante with theCUBE, we'll see you next time. (techno music)

>>Live from Las Vegas, you covering splunk.com 19 brought to you by Splunk.. >>Okay. Welcome back everyone. That's the cubes live coverage in Las Vegas for Splunk's dot com user conference 10 years is their anniversary. It's cubes seventh year. I'm John Farah, your host with a great guest here. Joe Partlow, CTO of rely AQuESTT recently on the heels of vying thread care and Marcus, Carrie and team. Congratulations. They'd come on. Yeah. Yeah. It's been a been a fun month. So obviously security. We love it. Let's take a minute to talk about what you guys do. Talk about what your company does that I've got some questions for you. Yeah. So you know, obviously with the increasing cyber threats, uh, you know, uh, security companies had a lot or customers had a lot of tools. Uh, it's easy to get overwhelmed, um, really causes a lot of confusion. So really what we're trying to do is we have a platform called gray matter that is really kind of how we deliver security model management, which what that means is that's bringing together people, process technology in a way that's easy to kind of make sense of all the noise. >>Um, yeah, there's, there a, a lot of features in there that would help monitor the health, uh, the incident response, the hunt, um, any kind of features that you would need from a security. So you guys are a managed service, you said four? >> Yeah. Yeah, a different, a little different than a traditional MSSP. We um, you'll work very close with, uh, the customers. Uh, we work in their environment, we're working side by side with them, uh, in their tools and we're really maturing and getting better visibility in their environment to get that MSSP for newer. >> Right. That's where you guys are. M S S VP >> on steroids. A little bit different. >> Alright. Well you guys got some things going on. You got a partnership with Splunk for the dotcom sock. Oh yeah. Talk about that with set up out here. And what's it showing? Yeah, that's been a great experience. >>Uh, we, we work very close with the Splunk, uh, team. Uh, we monitored Splunk corporate, uh, from a work with skirt team monitoring them. Uh, so when.call came around, it was kind of a natural progression of Hey, uh, you know, Joel and team on their side said, Hey, how do we kind of build up the team and do a little bit extra and I'll see any way that we can help secure.com. Uh, it was really cool. I give credit to the team, both teams, uh, standing up a, uh, new Splunk install, getting everything stood up really in the last few weeks, uh, making sure that every, uh, everybody at the pavilion and the conference in general is protected and we're watching for any kind of threat. >> So it's, it's been great working with the Splunk team. So is that normal procedure that the bad guys want to target? >>The security congresses? This is gonna make a state visit more of graffiti kind of mentality. It's an act kind of lift, fun, malicious endpoints that they want to get out of here. Oh yeah. There's, there's a little bit of a, you know, let's do it for fun and mess with the conference a little bit. So we'll want to make sure that, that that's what happened. So is my end point protected here? My end points, my phone and my laptop. Uh, not the user specific but any of the conference provided demo stations. Okay. So or structure for the equipment, not me personally. You are not monitoring your personal okay. I give up my privacy years ago. Yes. This is a interesting thing to talk about working with spunk because you know, I hear all the time and again we're looking at this from an industry wide perspective. >>I hear we've got a sock, they got a slot. So these socks are popping up yesterday. Operation centers. What is, what is the state of the art for that now? Is it best practice to have a mega Monster's sock or is it distributed, is it decentralized? What's the current thinking around how to deploy Sox surgery operations center or centers? Yeah, we certainly grow with a decentralized model. We need to follow the sun. So we've got operations centers here in Vegas, Tampa and Dublin. Uh, really making sure that we've got the full coverage. Uh, but it is working very close with the Splunk socks. So they've got a phenomenal team and we work with them side by side. Uh, obviously we are providing a lot of the, uh, the tier one, tier two heavy lift, and then we escalate to Splunk team. They're obviously gonna know Splunk corporate better than we will. >>So, uh, we work very close hand in hand. So you guys acquired threat care and Marcus carries now in the office of CTO, which you're running. Yes. How is that going to shape rely a quest and the Europe business? >> Yeah, the acquisition has been extremely, uh, you know, uh, exciting for us. Uh, you know, after meeting Marcus, uh, I've known of Marcus, he's a very positive influence in the community, uh, but having worked with him, the vision for threat care and the vision for Lioncrest really closely aligned. So where we want to take, uh, the future of security testing, testing controls, making sure upstream controls are working, uh, where threats they're wanting to go for. That was very much with what we aligned more so it made sense to partner up. So, uh, very excited about that and I think we will roll that into our gray matter platform has another capability. >>Uh, gray matter, love the name by the way. I mean, first of all, the security companies have the best names or mission control gray matter, you know, red Canary, Canary in the coal mine. All good stuff. All fun. But you know, you guys work hard so I know the price gotta be good. I gotta ask you around the product vision around the customers and how they're looking at security because you know, it's all fun games. They'll, someone's hacking their business trash or this ransomware going on. Data protection has become a big part of it. What are customers telling you right now in terms of their, their fears and aspirations? What do they need? What's on the agenda? Guests for customers right now? Yeah. I think kind of the two biggest fears, um, and then the problems that we're trying to address is one, just a lack of visibility. >>Uh, customers have so many things on their network, a lot of mergers and acquisitions. So, uh, unfortunately with a lot of times the security team is the last one to know when something pops up. Uh, so anything that we can do to increase visibility and that and that, a lot of times we work very closely with Splunk or send that they have out to make sure that it happens. And then the other thing I think is, you know, most people want to get more proactive. Uh, you know, salmon logging by nature is very reactive. So when he tried to get out in front of those threats a little bit more, so anything that we can do to try to get more proactive, uh, may certainly going to be on their, their top of mind. Well, the machine learning toolkits, getting a lot of buzz here at the show, that's a really big deal. >>I think the other thing that I'm seeing I to get your reaction to is this concept of diverse data. That's my word, not Splunk's, but the idea of bringing in more data sets actually helps machine learning that's pretty much known by data geeks, but in making data addressable because data seems to be the one thing that is all doing a lot of the automation that's takes that headway heavy lift and also provides heavy lifting capabilities to set data up to look at stuff. So data is pretty critical. Data addressability data diversity, you got to have the data and it's gotta be addressable in real time and through tools like fabric search and other things. What's your reaction to that and thoughts around that? No, I agree 100%. Uh, you know, obviously most enterprise customers have a diverse set of data. So trying to search across those data sets, normalize that data, it's, it's a huge task. >>Um, but to get the visibility that we need, we really need to be able to search these multiple data sets and bring those into make sense. Whether you're doing threat hunting or responding to alerts. Um, or you need it from a compliance standpoint, being able to deal with those diverse data sets, uh, is is a key key issue. You know, the other thing I wanna get your thoughts on this one that we've been kind of commenting, I've kind of said a ticket position on this gonna from an opinion standpoint, but it's kind of obvious but it's not necessarily true. But my point is with the data volume going up so massive, that puts the tips, the scales and the advantage for the adversaries. Ransomware's a great example of it and you know, as little ransomware now is towns and cities, these ransomware attacks just one little vector, but with the data volume data is the surface area, not just devices. >>Oh yeah. So how is the data piece of it and the adversarial advantage, you think that that makes them stronger, more surface area? Yeah, definitely. And that's something that where we're leaning on machine learning for a lot is if you really kind of make sense of that data, a lot of times you want to baseline that environment and just find it what's normal in the environment, what's not normal. And once you to find that out, then we can start saying, all right, is this malicious or not? Uh, you know, some things that uh, yeah, maybe PowerShell or something and one environment is a huge red flag that Hey, we've been compromised in another one. Hey, that's just a good administrator automating his job. So making sense of that. Um, and then also just the sheer volume of data that we, that we see customers dealing with. >>Very easy to hide in if you're doing an attack, uh, from an adversary standpoint. So being able to see across that and make sure that you can at scale SyFy that data and find actionable event. You guys, I was just talking with a friend that I've known from the cloud, world, cloud native world. We're talking about dev ops versus the security operations and those worlds are coming together. There are more operational things than developer things, but yet CSOs that we talked to are fully investing in developer teams. So it's not so much dev ops dogma, if you will. But we gotta do dev ops, right? You know, see the CIC D pipeline. Okay, I get that. But developers play a critical role in this feature security architecture, but at the end of the day, it's still operations. So this is the new dev ops or sec ops or whatever it's called these days. >>What's your, how, how do customers solve this problem? Because it is operational, whether it's industrial IOT or IOT or cloud native microservices to on premise security practices with end points. I mean, I, the thing we see that, that kind of gets those teams the most success is making sure they're working with those teams. So having security siloed off by itself. Um, I think we've kind of proven in the past that doesn't work right? So get them involved with their development teams, get them involved with their net ops or, or, you know, sec ops teams, making sure they're working together so that security teams can be an enabler. Uh, they don't want to be the, uh, the team that says no to everything. Um, but at the end of the day, you know, most companies are not in the business of security. They're in the business of making widgets or selling widgets or whatever it is. >>So making sure that the security, yeah, yeah, that's an app issue. Exactly. Making sure that they're kind of involved in that life cycle so that, not that they can, you know, define what that needs to be, but at least be aware of, Hey, this is something we need to watch out for or get visibility into and, and keep the process moving. All right. Let's talk about Splunk. Let's set up their role in the enterprise. I'll see enterprise suite 6.0 is a shipping general availability. How are you guys deploying and optimizing Splunk for customers? What are some of the killer use cases that's there and new ones emerging? Yeah, we've, we provide, you know, really kind of three core areas. First one customers, you're one is obviously making sure that the platform is healthy. So a lot of times we'll go into a, a customer that, uh, you know, maybe they, they, there's one team has turned over or they rapidly expanded and, and in a quickly, you kind of overwhelming the system that's there. >>So making sure that the, the architecture is correct, maintained, patched, upgraded, and they're, they're really taking advantage of the power of Splunk. Uh, from an engineering standpoint. Uh, also another key area is building content. So as we were discussing earlier, making sure that we've got the visibility and all that data coming in, we've got to make sure that, okay, are we pursuing that data correctly? Are we creating the appropriate alerts and dashboards and reports and we can see what's going on. Um, and then the last piece is actually taking, you know, see you taking action on that. So, uh, from an incident response standpoint, watching those alerts and watching that content flyer and making sure that we're escalating and working with the customer security team, they'd love to get your thoughts. Final question on the, um, first of all, great, great insight. They'll, I love that. >>As customers who have personal Splunk, we buy our data is number one third party app for blogs work an app, work app workloads, and in cloud as well as more clients than you have rely more on cloud. AWS for instance, they have security hub, they're deploying some of this to lean on cloud providers, hyperscale cloud providers for security, but that doesn't diminish the roles flung place. So there's a lot of people that are debating, well, the cloud is going to eat Splunk's lunch. And so I don't think that's the case. I want to get your thoughts of it because they're symbionic. Oh yeah. So what's your thoughts on the relationship to the cloud providers, to the Splunk customer who's also going to potentially moves to the cloud and have a hybrid cloud environment? Yeah, and now I would agree there's, you know, there are going to exist side by side for a long time. >>Uh, most environments that we see are hybrid environments. While most organizations do have a cloud first initiative, there's still a lot of on premise stuff. So Splunk is still going to be a, a key cornerstone of just getting that data. Where I do see is maybe a, you know, in those platforms, um, kind of stretching the reach of Splunk of, Hey, let's, let's filter and parse this stuff maybe closer to the source and make sure that we're getting the actionable things into our Splunk ES dashboards and things like that so that we can really make sure that we're getting the good stuff. And maybe, you know, the stuff that's not actionable, we're, we've up in our AWS environment. Um, and that's, that's a lot of the technology that Splunk's coming out with. It's able to search those other environments is going to be really key I think for that where you don't have to kind of use up all your licensing and bring that non-actionable data in, but you still able to search across. >>But that doesn't sound like core Splunk services more. That's more of an operational choice there. Less of a core thing. You mentioned that you think splints to sit side by side for the clouds. What, what gives you that insight? What's, what's, uh, what's telling you that that's gonna happen? What's the, yeah, you still need the core functionality of Splunk running with spark provides is a, you know, it's a great way to bring data and it parses it, uh, extremely well. Um, having those, uh, you know, correlate in correlation engines and searches. Um, that's, that's very nice to have that prepackaged doing that from scratch. Uh, you can certainly, there's other tools that can bring data in, but that's a heavy riff to try to recreate the wheel so to speak. We're here with Joe Parlo, CTO, really a quest, a pardon with Splunk setting up this dotcom SOC for the exhibits and all the infrastructure. >>Um, final question, what's the coolest thing going on at dotcom this year? What's, what should customers or geeks look at that's cool and relevant that you think should be top line? Top couple of things. Yeah, I, I, uh, one of the things I like the most out of the keynote was, uh, the whole, uh, Porsche use case with that. The AR augmentation on my pet bear was really, really cool. Um, and then obviously the new features are coming out with, with VFS and some of another pricing model. So definitely exciting time to be a partner of Splunk. Alright, Joe, thanks for them. John furrier here with the cube live in Las Vegas day two of three days of coverage.com. Their 10th year anniversary, our seventh year covering the Silicon angle, the cube. I'm Sean furrier. Thanks for watching. We'll be right back.

>>Live from Las Vegas. It's the cube covering splunk.com 19 brought to you by Splunk. >>Hey, welcome back. Everyone's the cubes coverage here in Las Vegas for Splunk's dot com I'm John, the host of the cube. This is Splunk's 10th year user conference is the cube seventh year. We've been riding on the same wave with Splunk over the years and just watching the phenomenal growth and changes at the level of data at scale we've been covering. We can remember I said from day one data at the center of this, not just log files is now gone. Beyond that, we're here with Carrie Pailin, the CMO, chief marketing officer for Splunk. Welcome to the cube. Thanks for coming on. Thank you so much. It's great to be here. The folks that know us know about spunk. Notice the color changes in the background, the popping kink, burning yellow, orange underneath, new branding. You're new to Splunk story, career in technology. Um, this is exciting. And then portfolio, there's all the news is a phenomenal good news flow. >>Very relevant, right on Mark. Data is now creating value and datas like software. It's enabling value. Splunk software and solution platform has done that and this new new grounds to take. But you're now setting the agenda for the brand and the company tell us, I mean, it's a marketer's dream. What can I say? It's a, you know, I joined nine months ago and when I was interviewing for the role, I remember Doug Merritt saying to me, Hey, you know, we might be the only $2 billion enterprise software company that nobody's ever heard of. Amy said, I want to go solve for that. Right? Like the folks who know Splunk and our customers, they love us, our product is awesome and our culture is awesome, but the world doesn't know about us yet and we haven't invested there. So I want to go take the brand to the next level. >>And I want the world to understand what data use cases are out there that are so broad and so vast. And we believe that every problem ultimately can be solved through data or almost every problem. And we wanted to set the stage for that with this new brand campaign. Yeah. Just on a personal note. And following the journey of Splunk, a scrappy startup goes public and growth modes. When you're a growth Moe is hard to kind of lay down foundational things like branding and whatnot. But now sponsor leader, we did a poll within our community and for cloud and on premise security, Splunk's the number one supplier for just laws with workloads. And then now cloud security is kicking in. So the relationship to Amazon, Google cloud platform and Azure is a critical part of Splunk is now the leader. So leaders have to do things like make sure that their brand's good. >>This is what you're doing. Take us behind the scenes of the branding, the things you chose and data for everything. Yeah. D the little small nuance data to everything. Um, and the reason behind that was we believe you can bring and we can enable our customers to bring data to every question, every decision and every action to create meaningful outcomes. And the use cases are vast and enormous. We talked about some of them before the show started, but helping look at global law enforcement, get ahead of human trafficking through SPOHNC and spelunking. What's going on across all sorts of data sources, right? Helping zone Haven, which is our first investment from Splunk ventures, which startup that's actually helping firefighters figure out burn burn patterns with fire wildfires. But also when temperatures and humidity change where sensors are, they can alert firefighters 30 to 45 minutes earlier than they would usually do that. >>And then they can also help influence evacuation patterns. I mean it's, it's remarkable what folks are doing with data today and it's really at the, at the core of solving some of the world's biggest issues. It's hard to tell a story for a company that solves some of the use cases. Yes. Because depending on who you talk to, that's the company. This is what we should be telling them. I know you do this over here, so when you're horizontally creating this kind of value, yeah, it's hard to kind of brand that because it will get a lot of opinions because you're doing a lot of different things. There's not like one vertical. That's right. So this is the challenge that most B to B marketers will fall on the trip. We do this because we have a lot of customers in this one segment. But yes, you guys are hitting so much more. >>How did you deal with that? Ha, we had a lot of talks about it, a lot of discussions, a lot of debate and I love diversity of thought. It usually drives the right outcomes, but we had a lot of this, this is not an easy answer. If it had been, it would have been done years ago and we really talked about setting the stage for where, you know, I love the Wayne Gretzky quote about skate to where the puck is going and that's what he always did and that's why he was so good. We believe there will ultimately be a data platform of platforms and we believe Splunk is that platform, right? And so that's where the industry's going. We wanted to cast a net that would take us there so that this is the beginning of a brand evolution for us and not a total rebrand, but it's setting the stage for a category creation that we believe is coming in the industry. >>A few. You guys are smart and I think my observation would be looking at some of our 10 years of reporting and sharing some on digital is that all the conversations around data is impacting the real world. Yes. You see Mark Zuckerberg and on Capitol Hill having the answer to the date of debacles, he has cybersecurity attacks, national security, um, ransomware taking down cities and towns. This is a real impact. Forest fires disrupting rolling blackouts. So technology's impacting real world lives. That's right. This is really new to tech. I mean usually behind the scenes, you know, coding, but not anymore. We're the front lines of real societal, global. Yes. Jade is at the forefront and it's really exciting. It's also frightening, right? Because we believe data presents the greatest opportunity for humanity, but also some of the greatest threats. And so hence our ability to really dig in on data security. >>It's important to do that while we're actually also surfacing data to solve real world issues. You've been in the industry for a while and when you came to Splunk, boasts a couple of things that surprised you as you, you had some thoughts going in, you knew Splunk. Yes. What are some of the things that surprised you when you got here? Oh, I mean, in such a good way. A few things, you know. Well, here's the story. Three days into being at Splunk, my dad got very ill and I wasted him to Austin for heart surgery and he actually didn't make it. Um, and so it's been a rough year to say the least. And uh, the way that Splunk's culture, I knew about it before I came, but the way that this company treated me, like I had been here 10 years, uh, when I'd really only been an employee three days was something I'll never forget. >>And it's, it's special. Um, and so I believe that companies are successful if they are smart and healthy and in Splunk has the healthy and droves and not just the compassion and the empathy, but you know, a very transparent culture. We debate things, we talk about things, we support each other. We are accountable. And I believe that's a big part of why we've grown so fast because our culture is incredibly healthy and very, um, collaborative as a team. I'm sorry for your loss. Thank you. Um, you mentioned the culture is a big part of Splunk. Yes. In talking to some of the folks that spoke over the years, there's no, I will, I'll totally say this. There's no shortage of opinions, so have not volunteered. These are robustness. Yes. Diversity of thoughts, very actionable communities. How do you, um, how do you look at that? Because that's a, could be a force, a force multiplier. >>Yes. For the brand. How are you going to tie in to everything with the community? How are you going to harness that energy? Yeah. So it's coming and the reality is data to everything is actually a set up to tell the stories of everyone who is using data today. And so the community is going to be one of the first places we go to surface. Some of those amazing stories. Um, and some of the things you see here at the show are actually showcasing that in the keynote today we heard from zone Haman and Porsche and so many others around their use cases. But the community is where it all begins and that's the lifeblood of our sort of spunkiness and a something that we don't take for granted once. One second. Sorry about the Barack Obama. Yeah. Directions with him and his interest in Splunk. Yeah. So we had our big re rebrand a reveal last month we had an event and it was for C suite type of folks. >>That was a very intimate event and we wanted somebody to keynote that and headline that that really brought to life the whole notion that you can bring data to everything. And president Obama was the first POTUS that actually use data in his campaign strategy. He's very open about that. He's the first president to appoint a chief data scientist to the white house. He's actually exceptionally geeky and very data-driven. And so when we asked him to come and headline this, he actually was really excited about it. Um, and you know, in, in great fashion, his communications team was really strict on curating the questions that we had for him. And he was so cute. He showed up to the event and he said, look, um, I'm so thrilled to be here. I love what you guys are doing and you can ask me anything. It's just like ready to go. >>And he was so wonderful and teed up this, this notion of day bringing data to everything so brilliantly. He's kicking, dig and be ad live all the time. He's very colorful as well as personality. Yes. He's kind of nerdy and you know, he was very open and OpenGov too. One of the things that I remember and when big data really started rolling into the scene around 2009, 2010 yes. You saw that opening up data registries from cities and towns and actually created innovation from health care medical supplies? Yes. Yes. So this has been a big part of it. Huge. You guys are doing some things out here and I see the exhibits we're using the day you're doing demos. How do you see you guys helping society with that? Because if you get to the next level, you've got some great use cases. Yes, the public sector is a big part of some news here. >>Fed ramp is one little technicality, but you got some certification, but government's modernizing now. So you know post Obama, you're seeing modernization of procurement roll with cloud, certainly cyber security. Amazon with the CIA, department of defense, role of data in the military and public sector. Yes, education. This is going to be a disruptive enabler for faults on the public impact. I mean, look, there's, you know, Doug touched on this a little bit this morning, the reality in our press conference, but the reality is if you do it right, opening up datasets to communities of people that can do better together and you can get this collective momentum going. For instance, in healthcare, I mean I'm a little bit of a health care nerd and I don't know if you've watched the PBS special on the Mayo clinic, it's spectacular. But one of the reasons the Mayo has been amazing for years is because their doctors all work off the same systems in every discipline in that facility and they can learn more holistically about a patient. >>And I think about the impact that data could have if we could open up those data sets across every health provider for one person or the same illness with every major institution across the U S collaborating and sharing and what we could actually do to make real impact and strides against some of the diseases that are really crippling society today. So I think that the good that we can do with data, if we open up those data sets and do it in a way that, that it's safe. It's remarkable the progress we can make. You know, one of the from machine learning has been a big success story. Machine learning toolkit. Customers are raving about it. Opening up the data creates better machine learning. AI creates better business value. That's right. That's that part of how you guys see things rolling out. Sure. I mean, as a marketer we use AI today and it's really more machine learning. >>It's sad pattern recognition. But we use, uh, you know, my last stand as a CMO, the last company I was at, we use an AI bot to augment our sales headcount for following up on leads. And it looked like a human being. I mean, same thing for Splunk. I mean, the more we can see pattern recognition, proffer up insights, the better off we are to help out our customers. And so Tim Teles team is driving that hard and fast into our innovation curve with everything that we do. Innovation culture, big time here, right? Huge, huge and one of the reasons I came to Splunk is when I interviewed with Tim and I said, Hey, how are you doing on recruiting engineers in the Valley? We all know that that is liquid gold, and he said that he had hired 370 odd engineers in less than a year and from really big brands like Airbnb and I thought, all right, there's some really cool innovation going on here. >>If some of the best engineers in the Valley really want to come work here and they want to work for a great leader, and Tim and his team are that. so.com is 10 years now this year has been riding the wave together. It's been fun. Your first, my very first dotcom. Yes. Your thoughts on this, on this community, this event. Share your, your thoughts. I mean I'm blown away and this is a team sport. I'm so proud of the events team, the creative team, the sales teams, everybody who's come together to make this event so spectacular. It's just sort of mind numbing that a company of our size can put on such an experience for our user community, but I'm also thrilled with the engagement. We have over 300 sessions this week and most of them are user and customer use, case driven and the stories they are telling are magnificent. >>They're doing this all with Splunk, so it's pretty special. And the ecosystem and the app showcase is pretty hot here. You're seeing real applications, people writing code on top of Splunk? Yes, it's, it's, I'm sorry I don't use this word often. I'm 48 but it's rad. It's so cool. Yes. Harry, thanks so much for coming on the cube and sharing your insights. Absolutely. Final thoughts for the people who aren't here at the event, watching on camera, what, how would you encapsulate.com this year? What's the top story that needs to be told? I mean, look, the reality is that we are bringing data to way more than just security and it ops, which has been our core use cases forever, and they will continue to be, but folks are that are not incredibly data literate or through Splunk bringing data to everything and solving some big gnarly issues in the world. And it's pretty exciting stuff. So check us out. All right. Thanks. Gnarly red. Cool. I need a surf board, Jerry. Thanks for coming on Friday. Thank you so much. Coverage here@thetenth.com I'm Jennifer with the cube, bringing you all the action here in Las Vegas. Three days of cubed wall to wall coverage. We've got one more after this short break.

>> Live, from Washington, DC it's theCUBE. Covering AWS Public Sector Summit 2018. Brought to you buy Amazon Web Services and it's ecosystem partners. >> Hey, welcome back everyone. We're live here in Washington, DC with theCUBE's exclusive coverage of Amazon Web Services Public Sector Summit. I'm John Furrier with Stu Miniman. It's a huge show, it's like the reinvent for public sector and it's really booming. Our theCUBE allumnis on Josh Stella, CEO of Fugue. And Peter O'Donoghue, Vice President of Service Application Services at Unisys. You guys are back for the third time. We first interviewed you guys last year here in that reinvent, as well. Good to you back, thanks for joining us again. >> Thanks for having us back on. >> Thanks yeah, great. >> I love to connect the dots. It's almost like the trajectory. And we were talking yesterday about Cloud and how Amazon and other Cloud players, and Stew brought up a term called having experience. And then we were talking about this economies scale. This is really where people who have done it over time, have got their requisite, experience, scar tissue, and learnings. Some jump to try to deliver everything at once. You guys have been together for a while working together. What's the update on the trajectory as you guys go Cloud first? What's the status, what's goin' on? >> You guys made an announcement this week right? >> Sure, yeah, yeah. So, yeah we at Unisys are super excited to announce our new Cloud offering called Cloud Forte. And your point about takin' the lessons from experience and really embedding those into a capability, that's really what Cloud Forte is about. I think, ya know, at a very high level Cloud Forte it's got two major kind of sets of capabilities. One is like subscription services, which is around management and governance of AWS. And actually we've designed it to solve like really tricky problems, that our public sector and frankly our commercial clients are really struggling with. And the second set of services are really professional services, that allow for any need to facilitate and catalyze adoption at scale. And actually they go head on addressing some of the trickiest problems in that space, as well. >> Well, take a minute and just explain, what does the product do? What's the value proposition of this new service? >> Okay. Well, at the management and governance tier, let me tell you what the problems that it solves. I can go into all the minutiae, but I think we could be here a while right? It solves some big problems. Problem one that it solves is, commercially, public sector, and actually federal wise organizations have a tough time managing the finances of AWS Cloud consumption. Actually having the transparency and visibility, and being able to comply with the Antideficiency Act, being able to manage funding, and also being able to tie it back to contracts and contract line owners sounds trivial enough, but it's really a thorn in the side of a lot of folks really trnna adopt Cloud. I would say the second element is what we're calling our command bundle. And the command bundle really kind of, it deliberately kind of solves the... It feels the gap of the shared responsibility model. I think we all here are deeply aware of what that means. But, that's really kind of the air gap, if you will, between while AWS it supports out of the box, and quite frankly what customers need to support. So, things like, classic things like service catalog management, patch management, back up and recovery, IT operations, incident management, asset management. All those things. We've built and we've constructed basically in a flexible framework. A light weight framework that allows folks to do, to go fast. But also has that enterprise level of governance that people people expect to see from the cloud. One of the key elements of our command bundle is what Josh's organization provides, is the Fugue policy engine. So, we find that in order to provide Cloud, it's really important to be able to have those guardrails. To provide basically a nanny like supervisor to make sure that what's deployed is compliant. And actually what's deployed and what's running in production, stays compliant with security policy. So, that's really what command is all about. >> Josh, how about what's under the hood? We've had a lot of conversation on policy and automation. It's third year in on our conversations. What's going on under the hood, what's happening with the things that you guys are doing with Unisys? >> Yeah, so when we last talked they hadn't announced this yet, so we couldn't quite explain what we're working on together. But, we're working with Unisys and other organizations to provide that full automation of the entire infrastructure layer. And it's just fire and forget infrastructure on Cloud. So, one of the things we're seeing consistently is people are really starting to struggle. The markets really maturing around the need to fully automate remediation of problems, detection and remediation. Where the old model of use a monitoring solution, throws a ticket over the wall, search for the pilot tickets. You might have hours, days, weeks, where you're exposed and your data leaks. And Fugue fixes that in under a minute. So, that's what we've been workin' on together and we love the partnership because Unisys has experience in the engagement on the federal side of the market. And Fugue is baked in to just provide all that goodness. >> What's the impact of that? Because you compared kind of the old way to the new way you guys are doing. Just kind of give some categorical or anecdotal color behind what the impact is from that. What does it do, save people's lives, saves time, money. What's the impact? >> Yeah, I'll tell ya the impact and I'll describe a use case. So, we're working with another customer and they came to us and said, in our hosted environments on AWS we have over 500 events a day, where configuration has drifted. And every one of those we have to investigate. We have to come up with a plan. Then we have to execute the plan. Then we have to write a report on how it will never happen again, 500 a day. So, with Fugue, every one of those just is automatically fixed and reported within about 30 seconds to a minute. So, the impact of this is a team of three completely overwhelmed folks, who were looking to hire 10 people to try to, as their Cloud presence group, they just had to staff a larger and larger Cloud services desk. Actually the three people that they have are now on to doing other work. Because it's just automated. >> So, Peter help connect the dots for us, for your customers on the federal side because we know there's been push back. Sometimes customer, oh automation sounds great, but ah wait, on the government side I've got regulations, I've got processes, I've got hurdles that we might need to do. So, how do we get beyond those? >> Well, I think that's a great question. I would say that, so as I was talking about the Cloud Forte offering that, there's a set of offerings in the professional services domain too. We actually have our accelerated bundle, right? And actually one of the things that we, we really believe as important as folks to adopt Cloud is, in order to leverage Cloud most effectively, you really need a mind shift. So, we have like two of the legs of our offerings went around the order of chain management. And kind of making that major transformation for human capital. And actually what really good looks like is folks who actually think Cloud natively, right? So, we find the most successful clients are folks who've kind of made that leap. The other kind of dimension is is around process and process change. And we see ITIL has been super affective and has been kind of a stone wall of enterprise IT for a long time. But, we see that as folks move to the Cloud one of the strong recommendations we make and we have process offerings, is how do we renew... My management in governance process is to actually embrace more DevOps thinking, embrace more of everything as code thinking, including policy. Because what we find is, as I think you're hinting at right, is as folks move to the Cloud you can kind of have like almost a goldilocks scenario. Where, like on one hand I've taken the really heavy weight processes and tools from my data center into my thinking, and I've got now kind of a Porsche 911, but I've put donut wheels on it and I can't move very quickly, and I'm kind of frustrated with it, right? On the other extreme, I've got like the SharePoint era of 2005, 2006 where it is the wild west. It's pandemonium, and God only knows what's goin' on right there. So, what we're trynna do is is really looking for effective enterprise and having transparent governance, making sure that the great lessons learned of before are there. But, we have like a light weight extensible frame work that we have the nanny guardrails on it, so we can understand where this policy drifts. >> And the beauty of this is ya know the APIs giveth and the APIs taketh away. The APIs are why we can go so fast, but it's also why it's really easy to hurt yourself. That's what Fugue is there for. We let you go just as fast, and when can show that all those processes, like in ITIL having a CMDB, that's a side affect of running Fugue. You can query Fugue and you've got your configuration data. >> How you made them go fast, I get that. But how do you protect from breaking, what's the other half? >> Yeah, sure, so the Fugue approach, and Unisys are doing some other things on top of this. But, the Fugue approach is you cannot deploy something unless it is both correct and meets policy and compliance. >> That's the guardrails you're talking about. >> That's the guardrails. And unlike anything else, Fugue tells you exactly how you got it wrong, why, and how to fix it. So, it's not just a big no, at the end of the process. It's hey, on 147 you're not allowed to have unencrypted volumes so change that. Then once the infrastructure is provision, so it must be correct up front, once it's provisioned Fugue will never let it drift again. Again, within 30 seconds to a minute we've seen it needs changed, and we've fixed it. And what that means is... >> Intelligence. >> It is. >> You bring intelligence do it, ya fix it, again this the, this is why I love the automation whole Cloud thing. The non believers don't understand the value of this. I call them the Cloud non believers because this is just game changing. You mentioned the point about the efficiency of people not having to bulk up manual labor to lock down and just open up so many security holes. Peter, I've got to ask you, I hate to put you on the spot here, what's it like now working with Fugue? You guys have done a lot of work together. What's the outcomes? Tell us about the experience. And what is it about their solution that really helps you out? >> Okay, sure. Well, I mean I think the most obvious ya know, response there is is the fact that we've baked it in, and it's part of the solution, it's one of the core tenants, and components within our command bundle. That in itself is a major part of our strategy. What we find in our customers, ya know we do find clients actually kind of range in where they are in terms of their Cloud adoption. And we're also finding with our Cloud Forte bundle folks actually will adopt different parts of it at different times. But, actually we do find clients are very interested... Actually, I think our best clients are folks who actually have been been playing with CI/CD and they've been playing with Cloud. But, they've actually kind of started to see that the sprawl affect is actually starting to happen. And they're looking to have speed, but also security at the same time. We find that the integration of Fugue, and that just, that kind of, that insane Cloud native thinking, and this kind of like ability to speak AWS natively as a native language is really important differentially, when we bring a joint solution to our client. >> How many of the scale pieces created? Josh I want to give you that final word on your, give us an update on your business. What's goin' on? What's the value possession look like now? Obviously, automation we're believers, we just talked about that. But, where's it go next? What's up with Fugue? >> Sure, so what's up for Fugue, all kinds of things over the next quarter or two that we'll be releasing. That I can't quite talk about yet, or my product lead will kill me. But, one of the things we've put a ton of work into is around pre-building libraries of policy for our customers. So, Nist 800-53 for federal we've implemented a lot as policy now. PCI, HIPPA, all kinds of standards, so that when they purchase Fugue they just get these out of the box. It's amazing to watch somebody who's been on Cloud for a little while bring up the Fugue compose or a visualization engine, go discover all their infrastructure, and then do import HIPPA, and find all the little red dots of where they're actually, have been running wrong, fix it all in less than an hour, and not worry about it again. So, we're doing a lot of business in federal. We're doing a lot of business with partners. And we're also doing a lot of business in commercial now, mostly on the larger enterprise side. The value prop is really around that controlling sprawl over time and automated remediation. There's lots of kinds of automation that are partial, unless the system like Fugue does can fix everything, if there are any gaps in that, you're back to manual world. So, it's a kind of binary scenario, so yeah. >> You kind of never give it up, unless you can fully let go of it. >> That's right, that's right. >> Awesome, well congratulations on the part, you want to... >> Can I pull string on that though, I mean I think this another great concrete example of why we like working with you guys. It's part of our business obviously, I would say one of the major blockers getting folks to the Cloud is what do we do with ATOs that folks already have? And how do I bring those security credidations into the Cloud? So, if you think of you know where I think the industry is going to go next, is automation frameworks that allow me to quickly figure out what I inherit, what controls or balance I need to address as I move to the Cloud. But, the fact that Fugue is looking at natively kind of having as a primary citizen of their policies, this idea of those Nist controls, that's going to help provide transparency and visibility. So, that's actually going to be key part of being able to shorten the time to get to an ATO. >> Well, that certainly accelerates the discovery piece. >> Absolutely. >> Then ya kind of understand what ya have first and then you attack it with automation. >> Exactly. >> And everything seems more efficient, that's the goal right? >> Yeah, so this is why you know the true believer there's concrete reality there. Which is I can demonstrate, but I can demonstrate in real time that I'm complying all the time. I mean we've never really had that before, right? >> Yes. I mean again, this wave is coming. And love the commentary again. Public sector is very interesting, it's just being disrupted heavily and at a highly accelerated rate. You guys are doing a great job. Good to see ya Josh, Peter great to see you. CUBE coverage here in Washington, DC. Bringing all the action expected from us, I'm John Furrier with Stu Miniman. Stay with us, we'll be right back with more after this short break. 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>> Speaker: From the SiliconANGLE Media Office in Boston, Massachusetts, it's TheCube. Now, here's your host, Stu Miniman. >> I'm Stu Miniman, and this is a special Cube conversation here in our Boston area studio. Happy to welcome to the program Bobby Allen, who's the chief technology officer and chief evangelist at CloudGenera. Bobby thanks so much for joining us. >> Thank you Stu, thanks for having us. >> Alright so Bobby we had a great conversation with your CEO Brian Kelly talking about CloudGenera, helping customers if, in my own words I'll say, there's this great mess of the cloud and service providers and data centers and things are changing all the time. And here's a great tool to help people understand this. Now, I've had people asking me for years, it's like "Hey, I've got my app, "or I'm building a new app, where do I do this?" And I've always said well, there are certain things that are really easy. If it's going to be up for a really short period of time, and it's something there, it's like you're not going to spend the time to rack and stack and build and do this. hey, Cloud was great for that. And on the other end of the spectrum now, the public clouds might disagree, but if I have something that's just like it's going to be cooking along and it's not changing and it's there, the rent versus buy analogy once again goes towards kind of doing it in a hosted or my own data center. But there's a whole lot of stuff in the middle, That is, well, it depends. There's there's this uncertainty in the world and that's where you live, so bring us in a little bit as to some of the thinking as to how CloudGenera helps and where let's get into it. >> That's a great question Stu. So, we feel like the market is actually changed, in the sense that information is coming faster and faster, there's more and more information that people are inundated and honestly overwhelmed by. And so when people ask us for more information, we typically tell them you don't need more information in our opinion, you really want to move from information to clarity to insight, "What should I actually do?" And so to go back to the real estate analogy you talked about, I think people think of cloud as a house. Cloud is at least a neighborhood if not a state, and you need to figure out where should I live within that state or that neighborhood. So, let's take AWS for example. AWS is a vendor that has many, many, many services, but also different flavors of how you can run things. So before people would look at CloudGenera as a company that can compare different execution venues. Do I want to run this in Amazon or Azure or Google? Still we increasingly get people that want to understand which flavor of Amazon should I do? Do I do the multi-tenant, do I do the dedicated, do I do the VMware cloud on AWS? And those are all valid choices for us. And so for us, we don't really care where a customer wants to evaluate. Let's define what you need and map that to the relevant or interesting options in the marketplace, and then take the guesswork out of it so you have some data-driven decision making. >> Yeah, I love that because I have been covering Amazon for many years, and boy I go to the show and it was like "Alright, I thought I got my arms around Aurora and now there's the serverless based Aurora, and there's 17 different database options inside of Amazon so, oh boy," and then, right. Let's not even talk about all the compute instances. I think it's more complicated to pick a compute instance in the public cloud than it is if I was going to put something in my own rack these days. >> Bobby: Yes, yes it is. >> So, but that being said I want to for a second before we talk about the public cloud, talk to your viewpoint, how are you helping customers in kind of the service provider to data center world. And because that's a complicated and very I have to say fragmented space. >> It is. >> How does CloudGenera help there? >> So CloudGenera deals with the consumers, so ones who actually want to benefit from the technology themselves, but also from the service provider side. So if you're Joe's Cloud Shack, or regional cloud provider or Vmware service provider, anyone who is offering technology services, you may want to know number one, how do you compare with the large hyperscale providers, and then number two, how can you showcase your valued proposition next to those. So maybe Amazon and Azure and Google are on the top of peoples' minds, but how do your services compare to those? So in our platform you can actually show a Joe's Cloud Shack next to an Amazon next to something like a Synergy or SimpliVity. So options inside and outside the data center that you thought about and then ones that you didn't can all be kind of presented in a fair way, so you take the guesswork out of how they compare to each other. >> Yeah, it's interesting. One of the big raging debates we've had out there is, "Oh I wish I had a cloud concierge." And it's like well, it's not a utility, and therefore, I could stand up something in my data center or I could put a Paz in my environment or there's so many layers in the stack and so much nuance that it's the paradox of choice I think that most people have. So, maybe walk us through a customer. When do they tend to come to you, what are some of those patterns, and what are the things that really help get accelerated when they use a platform like yours? >> So, some of the things that people think about are they have workloads that they want to move maybe they want to exit a data center, or what really happens commonly is there's a new leader in town. New CIO comes in, "We're going to have a cloud-first strategy." And we're not opposed to that. The biggest principle for us is do you understand why you're doing, and whether this is the right time, the when? Because if you don't do the right thing at the right time for the right reason there's a hole in your strategy. And so what we look at is, okay what is it that you're trying to move or change or transform, What are the things that are interesting to you or strategic, and then let's look at putting those things together. Now when you define what you need, you shouldn't define what you need in terms of where you're going, right. I don't decide my venue based on the airline I want to get on, I decide I need to be in Vegas for this conference at this time, and then I see the airline that can get me there on time for the best price, hopefully. And we take that same approach when it comes to helping customers. Let's talk about what you need in a vendor agnostic way that's divorced from the options in the market. Because your needs are not impacted by Amazon or Azure or HPE or Dell. And so then, after we define your expectations and your requirements let's map those to the things that you're curious about, or that your leadership says are strategic, and then let's make sure that we understand what we call the concept of logical equivalence. The spirit of your requirement may be called x in one provider and y in a different one, are they really the same as a tomato to-mah-to, or are they really two different types of, excuse me, services or entities altogether? So let's, let's evaluate then, how well your needs are met by these different vendors. Is it just a semantics issue or are these really two different things? Yes, they're both different types of block storage but the requirements are different. The latency is different, the redundancy is different, the pricing is certainly different. How close are these things to meeting the spirit of what you asked for? And the other parts too that I'll just offer that we see a lot is people are concerned overly about cost. How much does it cost? And we feel like the problem is not a problem of cost, it's a problem of value. People go to look for cost calculators but really what they need are value calculators, right? I take a Porsche and an F-150. An F-150 is a bigger vehicle but the Porsche is more expensive for a reason. There's a different experience than just space. And so the reality is people don't mind paying more if they know what they're paying for. Transparency is really the key. >> On that cost piece though, how much of the total equation do you look at? So I think about, my data center there's everything like the power, space, and all those pieces, if I go to a service provider, if it's my stuff, if I still have to manage it, versus some of the operational expenses. How much of kind of the, I hate to say total cost, but how much of that spread do you look at? >> We try to be pretty comprehensive, Stu. So, if you go to a public provider for example you're not paying for power but you're paying for a certainly hourly charge typically on an (mumbling) basis that accommodates a lot of the things that I'll say are platform or hypervisor and below. Now where I think a lot of the other people that are in this space maybe fall short, and our opinion is that they don't look at things above the hypervisor. If I move a workload to an AWS, they may have some great services I can take advantage of. The labor and the licensing and the other considerations that we consider to be carryover costs are things that I still need to accommodate. If I put a workload in Amazon, someone still needs to patch the OS, maybe manage the database, maybe audit security. Those are things that have labor and licensing and software considerations that we try to look at. So we try to be as comprehensive as possible, but we also look at SLA, we also look at security, so you may need to bring another manage services or consulting or software packages to fill those other gaps, so we try to be as holistic and comprehensive as possible. >> What other kind of patterns and data do you bring for CloudGenera? So thinking things either from a vertical standpoint or kind of size of company. I just think there's been certain movements in virtualization and containers and the like where there's been kind of that data and how do I understand what's going to make sense for me, so. Does CloudGenera get into any of that? >> We do get into some of that. So we try again not to force anything down someone's throat. We try to look at where you are, but also understand that there are some patterns. So for example, when we talk about different industry verticals it's very aligned to security and compliance for example. So we know that there are certain providers that are interesting but not ready for primetime because they don't have HIPAA, high tech, high trust, things that are typically relevant for the healthcare industry, so we're very quickly able to say this is something that may not be right for you just yet. Or if you have certain regional concerns, maybe you're looking at GDPR in Europe, you're looking at IRAP in Australia, we can, again, typically guide them to, this provider has some very interesting services but they don't have the security or the SLA that you need. So we try to do that to kind of whittle it down. The other thing that we're seeing though, Stu, is that honestly, many enterprises are biting off more than they can chew. They try to do too much at once, and so some of the things that we talked about, even off camera, is I would ask the question "Does the industry have a POT problem? "Are we trying to do too much at once?" And when I say POT I'm using that to represent the acronym of, to me, three pieces that we need to break this down to. Number one is parity, number two is optimization, and then number three is transformation. Many enterprises in our opinion are trying to eat an elephant with a spoon. They have no idea how to get there and they really don't understand what is too much in terms of the cost, and so when they're evaluating how much they can handle, how much change is too much, in terms of people, process, and technology, the thing to us is, what does parity look like? And that may mean a lift and shift in some cases, it may not, but you at least have to define what success looks like if you take what you're doing in your data center and move that somewhere else. But then, the middle ground is optimization. How do I take the spirit of what I'm doing, move it to that venue and then kind of clean it up or optimize it a little bit, and then once I'm there and I can evaluate the unintended consequences of change, what are the things that I didn't think about? The impacts to my people, the retraining, the other software package I need to put in place for monitoring and management, and so forth. Once I have a handle on that, then I can finally move from optimization to transformation, but that's not, that's not glamorous. That's not interesting. People don't want to talk about that. They want to go whole hog and change everything all at once and we get into trouble doing that. >> Bobby you've given me flashbacks. I worked in the storage industry for a decade, and migrations, you still kind of wake up in the middle of the night, screaming a little bit because it's always challenging, there's always all of those things to work through. You think you've gone through all of your checklists and then, oh wait, something didn't work. Database migrations, big discussion going on there. From Wikibon David Floyer has just been like, it's so many horror stories. People get there but it's, if you don't have to, maybe you don't want to, but there's so many reasons why you want to, so, I guess I want to highlight, we're not telling people not to change, and moving faster and getting on board, some modernization's a good thing, everywhere. You've got a virtualization environment, there's lots you can do today that we couldn't do two or four years ago. So, how do we get over this POT problem then? >> I think part of it is, so again going back to the moving analogy, if I'm going to move, Stu, it would be foolish for me to move without getting an estimate. And there are times when an estimate should be able to come in my house and tell me "It's actually better for you to sell that piano "than to try to move it, 'cause it's not worth it." I would want someone, if I were CIO in an enterprise today, to tell me, "Don't waste your time focusing on this, "this is really where you need to focus your time "because this is going to be the Pareto principle "that saves you the time and the money." The reality is bringing someone who's benefited from the land mines and the pitfalls, so in our opinion, bringing whether that's an SI, consultancy, a data service company like CloudGenera that's benefited from a lot of the things we've seen in the industry, don't hit things on your own that other people have stumbled on, right? Benefit from others' mistakes to allow you to take a look at the whole thing. So the challenge that I think we're having, Stu, is that we're proficient in talking about these things, there aren't enough use cases in terms of mature of cloud transformations to really look back at anecdotal data this comprehensive. We're still figuring a lot of this stuff out, and I know people don't want to hear that, but that's my opinion. >> So, Bobby, is there some place when I'm filling out these forms that I put in here's the skill set my team has, and a little alarm goes off and says, "Hey, time to do some retraining, some reskilling, "maybe bringing on some new people "to handle some of these new areas." How do you handle that side of it? >> I think part of it is honestly, and this may sound a little trite, I think people that are willing to raise their hand and say that we need some help or that "We don't have this all figured out," or that "There are some things that we need to bring in "a little bit of help to help us get that estimate "before we look to move everything," that's really the skill set you want to have. People that are not saying, "I'm the (mumbles) "juggernaut of everything cloud," because those people don't exist yet in my opinion. There are people that have pockets of expertise in things that they have really deep knowledge about, but we need to mix that with, I think, a healthy appreciation for the fact that there's still a lot of things that we're learning about together. The other part of that, Stu, is it's a community and it's a network. You may know storage migrations, I may know database migrations, let's put our heads together about how we can work together as an enterprise and make sure that we minimize impact to the users, because at the end of the day, that's really the challenge, is not to do a cool project, it's to deliver value to the business, and that's what I think we're loosing sight of with all this cool technology sometimes. >> Alright, so Bobby you've got over a thousand people using the tool. What are some of the big areas that people are like, "Oh wow, this is the stuff that's saving me "either lots of time, lots of money, saving my business, "and heck if I'm running the show, keeps my job"? >> I think storage is a big one. So people are oftentimes unaware that there are so many different ways that you can run storage in a given provider. So Amazon for example has four to six different ways you can just run block storage in their particular multi-tenant cloud, and people aren't aware of that. So there's a case that we did for a major bank. We showed them that a terabyte of storage in Amazon can run from 300 dollars up to 26 thousand dollars depending on the level or performance that you want to hit. Egress is another one, so what does the network behavior look like in those applications? Because people often will estimate the resources but not the traffic. What are the estimates to have a level of parity around security. So I don't have HIPAA compliance or SOP compliance in this particular provider. What is it going to take me to get to that level of parity that I need to have, because if I save money, Stu, but I have to spend all that on my lawyer because my data got accessed, then I've still got a problem, I've just kind of moved that down the road. So lots of things out there that I believe we're hiding in plain sight. Again, information is out there that we just don't have the filters to find. What I would say is a lot of people think that cloud is a commodity, we're not there yet. There're providers to this day, I can't give any names to protect the innocent, but the same service is literally triple in one provider what it costs in another one for almost exactly the same service. And there're examples like that that have been out there for years, we just can't see them. >> So, Bobby, last question, if somebody wanted to get started with CloudGenera, is there like a trial version, or how would somebody get involved? >> Yeah, so a couple things that are really interesting. So there's a try now button on our website that lets you kind of answer a few questions and actually get a sample mini-assessment, download a sample report, and actually see the type of analysis that we provide, number one. Number two, CloudGenera is a software company but also a services company. If you want to purchase the software, great, and we actually have trials that we can set up for you to do that. We also do what we call proofs of value. If you want to engage our team to come in and do five to ten applications to see how those might look with our analysis, and then they go at scale and look at your whole CMDB. We want to make sure we're meeting the needs of the business and not trying to boil the ocean if they're not ready for that yet. >> Bobby Allen, CTO and chief evangelist to CloudGenerate, thanks so much for joining me. So much happening in the cloud world. Be sure to check out thecube.net for all of our coverage, as well as wikibon.com for all the research. Thanks for watching theCUBE, I'm Stu Miniman.

>> Announcer: Live from Barcelona, Spain. It's theCUBE, covering Cisco Live 2018. Brought to you by Cisco, Veeam, and theCUBE's ecosystem partners. >> Hello everyone. Welcome back to theCUBE's live coverage here, exclusive coverage of Cisco Live 2018 in Europe. We're in Barcelona, Spain for theCUBE Day one wrap of our two days of wall-to-wall coverage. I'm John Furrier with my co-host Stu Miniman, and we're going to break down day one, Stu? >> I can go for a couple more hours, who else we got? >> But Stu, we'll go live for a marathon session. No, let's wrap it up. We got a full day tomorrow, got some great guests here. At the keynote, Cisco laying out their vision and the story's kind of coming together, and I think Cisco has clarity. So my takeaway, I learned a lot. I learned that Cisco is not just talking, they're walking. They got a lot of work to do. I think that the signs of great progress with Cisco, Stu: one is Rowan put out a great keynote that looks forward not back. They didn't lean on their base and saying we're going to milk this cow until it's dead, meaning the networking engineers and the position. They're looking forward and putting a vision out there that says here's how the network will transform applications and they had a lot of use cases from IoT to multi-cloud and more. And two, they're cracking the code on IoT because they bought Jasper, which is back haul, essentially using cellular to the classic OT market, which is a classic end-to-end. To me, that was a revelation to me and I think that might be the unique creative thinking that could bring IoT into IT and transform the highly unsecure IoT WiFi IP market because anyone can throw a smart light bulb or whatever device. Full processing, multi-threading capabilities, and that can be hijacked and taken over and spewing malware and ransomware and everything else in between. >> John, if anything what I critique a little bit is he gives the vision of 2050. Go to a show like Amazon, they're like hey builders, here's what we have for you today that's really cool. And I think, we heard a lot from Cisco today, the cool things they have. Big acquisitions like AppD. We've talked a lot about, in the IoT discussion today, you talked about it was a $1.4 billion acquisition they made in that space. Here in the DevNet Zone, they're not talking about the future, they're talking about what they're building today. >> Well Stu-- Stu, you know how I feel about this. I kind of roll my eyes when I get that kind of futuristic with no meat on the bone. If you're going to have sizzle, you better have some steak on the grill. That's the critique for me is I'm looking and squinting through the hype and use cases. Oh, we got the future's going to be upon us to reality. What do they got now? That's the progress that I see and the signals that are showing to me are DevNet, active transformation of classic network engineer operator to programmer, one. Two, Susie Wee pointed out a new concept that we love called Net DevOps, which is programming the network for microservices and these new services with Kubernetes as the linchpin. Heard a little bit about Google, so in line with Google. Of course, Cisco's got billion dollar partners in the ecosystem. The certainly great fertilizer if you will, for this growth. They got a lot of things coming together. I think the challenge for Cisco and the strategic imperative that I see for the management team is show progress now. Now you've got the vision, that's the sizzle. Show the stink, that's what's happening now if they can bring that Amazon like mojo, I would think they'd hit a home run. >> John, we've got the Learning Lab behind you in DevNet area here. It's the first time in two whole days I haven't seen it packed and that's just because 15 minutes ago the World of Solutions reception opened. They've got snacks, they've got beer and wine, the music's going over there, so everybody's kind of moved over there but this area's been hopping. A day before the rest of the show really started, before the key notes. Absolutely, I'd love to have Susie talk about the four year transformation internally. We'd watched some of the people inside Cisco beating the drum, talking about making change. Cisco's made investment in Open Source. They've tried to move the needle some, but this developer wave, absolutely, they need to be a part of it. I think back to John Chambers talking about all the adjacencies, some of the failed acquisitions, flip acquisition, some the set top box type stuff. IoT, is the message they've had. I think you laid it out well. They had a good vision upfront but the market needed to mature some. Now we're ready for this to be real. Partner ecosystem, absolutely. Cisco is still a behemoth in this space and they've got strong partnerships a lot of way. There's a lot of transitions. There's some things they need to be careful about how they make the moves, but absolutely, there's interesting times here. >> Stu, you and I always love to talk about this because the network is where the bottleneck has always been. You mentioned in one of the questions, I forget who the guest was, what's going on with some of defined networking? Well, guess what, microservices changes that game. With Kubernetes now as a integration layer, it kind of splits the line between app developers and under the hood software engineering, all the way down to network engineering. Those are okay personas, but now you have policy programmability at the network level that services could take advantage of Those app developers that are slinging APIs, doing no JS, they're used to IOs. They're used to programming these functions. This kind of feels a little bit like serverless is coming to the table. I haven't heard that word here, but kind of getting that vibe. >> Absolutely, we haven't heard serverless. We have talked about containers some. Obviously, we talked about Kubernetes in area we've won, but the multi-cloud is still a little bit early for where Cisco plays at that M and O piece of it, Cisco has had a number of plays over the years and they make an acquisition. We'll see how it is. My friends in the networking space, the line is the single pain of glass, John, is spelled P-A-I-N. I'm glad I didn't hear that term from Cisco. >> John: I heard it once only. >> In general, they understand some of the challenges. They touch a lot of the pieces and they're not being overly dogmatic. They're not bashing the public Cloud. Yes, they have a lot more revenue in the data centers in the service providers, but they're not coming out here as a Cloud denier. >> That's a great point for a couple things. You know how I feel about multi-cloud. I think multi-cloud's BS right now. I think it's one of those moon shots down the road and I don't think anything's going to happen in multi-cloud for awhile. Your "True Private Cloud" report on Wikibon.com kind of validates that. The thing about the pain of class, Cisco actually has a lot of that on the management side. What needs to happen is that pain of glass management has to move up the stacks, Stu. This is where I think the test will be for them. That's going to be key. The thing that I did not hear that I'm surprised about is I didn't hear anything about data-driven anything. There's a lot of stuff being talked about. Programmable networking, kind of implies data. You even heard the IoT general manager talk about IoT feeds AI. I think AI's fed by data. Certainly, IoT supports data. I didn't hear about how their data is driving either policy, automation, not enough of that. I think that's a weak area, I'll say, they've got to do some work on. >> John, some of that I think is just terminology cause if you look inside the intent-based networking pieces that Cisco talks about, David Goeckeler this morning in the key note. He said it's about learning and security. Learning, it's all about data. How do we train those models? They didn't throw out the AI and MO buzzwords out there, but underneath, that's what's happening. It is about data, just networking people don't talk about data nearly as much as the compute or storage people. You're right, serverless, how will that impact the network? Because underneath infrastructure matters. Teagan's going to have to move around a lot more. I would've expected to hear some mention of it. >> Well, you made a good point, I agree with you. I love this intent-based networking. It really changes the conversation. If you say, what is that, what is intent in context? Huge conversation point, huge area to explore. This truly will make an adaptive network, a flexible network. It'll make it programmable. That's what people want. App developers need to have the services on the network side and they need the automation. Really, really key point. Any other learnings for you, Stu? >> Really John, it's going through that shift in model as we talked about in the intro. Cisco heavily moving towards that software model. Riaz who they brought in, heavy software background. You've got that balance of Cisco has strong history. They are trusted. Network provider, Trust and risk are absolutely the number one things that customers hear about. Security is something they bang on, but they need to undergo those transformations. People like Susie, like Riaz, coming in, helping to drive what's happening there. It's been nice to see very different from when the last time I came to Cisco, very heavy gear, and people plugging and running around, dealing with all those challenges. You think back to customers always-- What do they spend, 70 to 80% on keeping the lights on? Most of the activities we talk about here aren't the, oh, how do we keep the lights on? It's about growing the business and transforming the business, which is the imperative for CIOs today. >> The other thing I liked today is we had storage on, IBM and NetApp with a Cisco partner and ecosystem managing executives. Here's the thing that I learned and I'm happy to see this. You see storage going through the haves and have nots. There is a line going on, maybe its NV, NVFE over-- >> Stu: NVME over Fabrics. >> MVME over Fabric is causing a line that's going to define history, either on the wrong side of history or the right side. We're seeing storage start-ups struggling. We're seeing a lot of companies that we knew that went public, going out of business, start-ups cratering. But there's winners. Hearing the Cisco guys with NetApp and IBM, you're starting to see the storage vents who continue to make it, doing well and they're differentiating. What Cisco has actually done masterfully in my opinion, is they've balanced the ecosystem with the storage guys so that they can let everyone win. It's like a race car. Do you want the Lamborghini or the Ferrari or Porsche? You have different versions of storage. Each one can stand on their own and use Cisco and the better mousetrap wins, the better engine, will win for the use cases of the storage guys. Seeing kind of some swim lanes for storage. That's a good sign, Stu, for Cisco. >> Yeah, absolutely. That's how Cisco really drove that wave of converged infrastructure. I heard from lots of the partners at the (mumbles). CI, even though it's not the sexiest thing anymore cause it's over eight years old now, we've been talking about it, billions of dollars, that's what drove UCS, Cisco has a little bit of fear that they missed out on some of the core verbalization so they're not going to miss the container trend. They're not going to miss microservices. They're all over these pieces. But absolutely, they understand the value of ecosystems and they're very smart about how they target that. >> I agree with you, they got the container magic going on. DevNet certainly is looking good from a developer's standpoint. We will be covering the DevNet Create Event, which is a non-Cisco ecosystem. It's a new territory that Susie Wee has taken down, which is to get real Cloud native developers that aren't necessarily in the ecosystem, so that's going to be a positive. The thing I want to ask you, Stu, to end day one wrap up because this is kind of coming up as the NVME over Fabric. What's the impact of Cisco because we see the impact on the market place, with David Floyer would be chiming away if he was here, but I'd like to get your thoughts because you covered it closely, how is that going to help Cisco? Does it hurt Cisco, does it enable them, is it a game changer? What's the impact of NVME over Fabric? >> Cisco, remember not just a networking company, they're a compute supplier with UCS here. They have the M5, they have their latest that they have. Cisco's all over this, they're involved. It's how do I really bring that HPC kind of environment we've been talking about in the networking space. RDMA options out there. iWARP and Roce and NVME over Fabrics is going to be able to give me even higher speed, really low latency, getting scuzzy out of the way, which has been something that we've been trying to do for over a decade now in the storage world. I don't think-- We talked to Eric Herzog this morning and I really agree with him. This is evolutionary and this is not something that's catching anyone by surprise. It's not like-- >> It's on their radar. >> We're going from wire to wireless, or hey, this is now ethernet instead of token ring. >> So not a massive shift. >> It is similar to disk and Flash. It's absolutely, it's the next generation and there will be companies that implement it better, but we've all seen it coming. All the big guys are involved in it. Cisco, it relates to them and their ecosystem, and you expect them to not be a huge shift. >> One of the things we did not hear about. It's not a main theme here, it's certainly an undercurrent. It's certainly mainstream in the tech industry, both on the enterprise and emerging tech, certainly on AI and software, Stu, is the role of open source software. Not a lot going on here. I looked for sessions, I didn't see any birds of a feather or any meetups around open source. I know it's a DevNet show, Cisco show. DevNet creates a little bit more open source with Cloud found. We've interviewed folks like that and others. But if they're going to be talking to Google, and we're talking about Kubernetes, you cannot ignore the role of open source in the Cisco ecosystem. Your thoughts. Miss, not relevant to the show, kind of the back burner? Maybe Cisco's boiling something up? What's happening with their role and impact with open source? >> John, we heard that there's a presentation tomorrow in STO, they're working with Google on that. I'm not surprised not to see heavy open source in here. It would fit into the Cloud messaging, absolutely Cisco. On that Kubernetes train. We talked about in the containers that ecosystem when Docker announced the networking pieces, Cisco was right up there, wanted to make sure they're there. Cisco's doing it. John, they've had middling success to where they've been able to roll that into their products. We've covered a lot of it because we're big proponents of it but the typical customer here, I don't think that they're like oh hey, I didn't see this. There's other places where those communities, the builders and the contributors in those environments know where Cisco goes. >> Cisco's got billions of dollars they've got to focus on that I agree, but open source is important. You know, Stu, we think Kubernetes could possibly unlock the multi-cloud path. We're constantly watching it. I think it's important to them, they have to be there. They're talking Kubernetes. They're talking about that line in the stack that creates an app developer, very cohesive app developer ecosystem, and then under the hood, engineering, software engineering mindset. They got to play. If you're going to play with Google in multi-cloud, Google's all in open source. They want to be on Amazon, they got to be open source. They got to be there, so we'll see. We'll see how it goes. Okay, day one wrap up here. theCUBE, live in Barcelona for exclusive coverage of Cisco Live 2018. We'll be here all day tomorrow as well. Thanks for watching, I'm John Furrier with Stu Miniman for Cisco Live 2018 in Europe. Thanks for watching. (techno music)

(lively music) >> Announcer: It's the CUBE, covering SAPPHIRE NOW 2017, brought to you by SAP cloud platform and HANA Enterprise Cloud. >> Welcome back, everybody. Jeff Frick here with the CUBE with our ongoing coverage of SAP SAPPHIRE 2017 down in Orlando. Really exciting day today, day two, 'cause we got to see Hasso Plattner. Got up and gave his keynote. Joined by George Gilbert. George, great to see you. I know you've known Hasso for years and years and years. Impressions of the kfeynote. God, there is so much stuff that we can dig into. I'm looking forward to it. >> Hasso almost never disappoints, 'cause he's just got %a richness of history and of vision that goes all the way back to the beginning. He was probably the technical visionary from the very beginning. He was the guy who took them from the first super integrated mainframe ERP package all the way to the client server age with R3, and now beyond into sort of in-memory, cloud ready, and with machine learning and iOT baked in. >> But he really speaks like a developer. You can really tell that he likes the technology, he understands the technology, he's kind of a no-BS guy. Some of the Q&A afterwards, people were trying to trip him up and challenge him on stuff. And he would either say, "I don't know," or, "I don't believe that," or, "Here's our impression." Really you could tell he's a humble guy, smart guy, and really has a grasp of what the heck is going on here. Let's jump into it. So many themes we could talk about. But the one that started out early in the conversation was, he literally said, "We need to get as quickly "to the cloud as possible." This is coming from a guy who built the company based on on prem ERP heavy lifting. And even he said today, 2017, "We need to get to the cloud as quickly as possible." >> I think there are a few things going on behind there, when you unpack it. One is, they did start building for the cloud in the early 2000's. It was meant to be a product for the mid-market. In fact, actually its first objective wasn't to be cloud-ready. The first objective was to be highly configurable so that you could bend it to the needs of many customers without customizing it, because typically with the customizations, it made it very difficult to upgrade. In making it configurable first and cloud-read second, they kind of accomplished neither. But they learned a lot. So they started on this next version, which was, okay, we're going to take an in-memory database which we're building from the ground up, 'cause Oracle wasn't building it at the time, and then we're going to build SAP ERP from scratch on top of this new database, 'cause database was so high performance that they didn't have to sepyarate analytics from transactions the way traditionally you do, you had to do in all applications. So they could simplify the app. Then, in simplifying it, they could make it easier to run in the cloud. And now, just like Oracle, just like Microsoft, they now build cloud first and on-prem second, because by building it cloud first, it sort of simplifies the assumptions that you have to make. >> Right, and he talked quite a bit about so much effort now is around integration connectors, to get stuff in and out of this thing. And that's a big focus, he said. It's not that we're ignoring it, it's just a big, hard, hairy problem that we're attacking. >> Yeah, and this is interesting and there's a lot of history behind this. Oracle, in the 90s, up until about the late 90s, their greatest success was in their industry-specific applications, where they took different modules from different vendors and stitched them together. That was how they built, like, a special solution for a consumer package goods company. But it turned out that that wasn't really workable because the different modules for the different vendors6 upgraded at different rates. So there was no way coherently to integrate them and tie them together. And SAP had said that all along. They were, like, this wasn't going to work. Fast forward to the last five-plus years, SAP started buying products from a bunch of different vendors, Ariba, SuccessFactors, Concur, Hybris. So you're, like, "Aren't they doing the same thing "Oracle did 10 year, 15 years before?" But no, and this is what Hasso was talking about today, which was, once those apps are in the cloud, you only have to build the integration points once. It's not like when it's on every customer's data center, you have to build integrations that work for every version that every customer has. So I think that's what he was talking about. You put it all in the cloud, you integrate it once. >> Another thing that he talked, he really, he spoke in tweets. (mumbles) goes to buy Twitter feed, I was basically, like, bang, bang, bang as he was talking. He talked about databases, and databases in the cloud. Nobody cares, right? It's a classic theme we hear over and over. "We presume it works. "We just want it to work." You know, it should just work. Nobody really cares what the underlying database is. >> But he was, in those cases, referring to these purchased apps, Concur, SuccessFactors, Ariba, Hybris. He was, like, "Some of them work on SQLServer, "some of 'em work on Oracle. "But you know what? "Until we get around to upgrading them to HANA, "it doesn't matter because you, the customer, "don't know that." If they were on prem and you had to support all those different databases, it might be a different story. But he's, like, "We'd rather give you the functionality "that's baked into them now "and get around to upgrading the databases later." >> Another thing that came up, and he actually reference the conversation with Michael Dell from yesterday's keynote, about the evolution of compute horsepower. You know, you had CPUs and CPUs kind of topped out. Then you had multicore CPUs. Now we have GPUs that he said you can put 10s or 100s of 1,000s on the board at one time. Basically he's smart guy, he's down the road a few steps from delivering today's product, saying that, you know, we're basically living in a era of unlimited free compute and kind of asymptotically approaching. But that's where we are. And how does that really change the way that we look now at new application development. I thought that was a pretty interesting thing. >> And sort of big advances in software architecture come from when you have a big change in the relative cost of compute memory, network storage. So as you were saying, cost of compute is approaching zero. But the same time, the cost of memory relative to storage is coming way down. So not only do you have these really beefy clusters with lots of compute, but you also have lots of memory. He was talking about something like putting 16 terabytes of memory in a server and putting 64 servers in a cluster, and all of a sudden, I can't do that math, being that I was a humanities major, but all of a sudden, you're talking about huge databases where you can crunch through this stuff very, very fast because it's all, you have lots of processors running in parallel and you have lots of memory. >> It's pretty interesting. He made an interesting statement. He used a sailor reference. He said, "You know, we are through the big waves "and now we're in the smooth water," and really saying that all this heavy lifting and now that this cloud architecture is here and we have this phenomenal compute and store technology, that he can kind of take a breath and really refresh a look out into the future as to, how do we build modern apps that have intelligence with basically unlimited resources, and how does that change the way that we go forward? I thought that was an interesting point of view, especially 'cause he has been at it for decades. >> You know, I think he was probably looking back to some of the arrows he had in his back from having done an in-memory database essentially before anyone else did for mission critical apps. I think when he's saying we're out of the choppy water and into the smooth water, because we now have the hardware that lets us run essentially these very resource-intensive databases and the apps on 'em, so that we no longer have to worry, are we overtaxing the infrastructure? Is it too expensive to outfit the hardware for a customer? So his, when he talks about rethinking the apps, he, like, "We don't have to have separate analytical systems "from the transaction systems. "And not only that. "We can simplify because we don't have to have" what he's calling aggregates. In other words, we don't have to, we don't, let's say, take an order and all the line items in an order, and then pre-aggregate all the orders. It's, like, we do that on the fly. And that simplifies things a lot. Then, not only that. Because we have all this memory, we can do, like, machine learning very inexpensively. >> A whole another chapter in his keynote was about modern software design. A lot of really interesting things, especially in the context of SAP, which was a big, monolithic application, hard to learn, hard to understand, hard to manage. I remember a start, that were were (mumbles) using is a core V to C commerce engine. And to add 16 colors of shirts times 10 neck sizes and 10 sleeve sizes was just a nightmare. You're not going to have some merchant that works at Macy's to put that into the system. But he talked about intelligent design, which is pretty interesting. We're hearing that more and more in a lot of work done over at Stanford, intelligent design. He's talking about no manuals. He's, like, "If I can't figure it out, "I need to understand." He talked about intelligent applications that continue to learn as the applications get more data. And specifically, the fact that machines don't get bored testing 100s or 1,000s or even millions of scenarios and grinding through those things to get the intelligence to start to learn about what's going on. So a very different kind of an application, both development, delivery approach, than what we think of historically as R3. >> Yeah, like the design thinking was, they have this new UI called Fiori. I mean, if you go back 10, 15 years, let's say, when they started, 15 years, when they started trying to put browser-based user interfaces on what was a client server system, they had 10s and 10s of 1,000s of forms-based screens. They had to convert them one by one to work in a browser. I think what he's saying now is, they can mock up these prototypes in a simple tool and they can essentially recreate the UI. It's not going to be the exact same forms, but they can recreate the UI to the entire system so that it's much more accessible. On the machine learning front, he was talking about one example was, like, matching up invoices that you going to have to pay. So that you going to train the system with all these invoices. It learns how to essentially do the OCR, recognize the text. And it gets smarter to the point where it can do 95% of it without-- >> Human interaction. >> Yeah, human inter-. >> You know, it's interesting, we were at Service Now last week, as well. And they are using AI to do relatively mundane tasks that people don't want to do, that machines are good at, things like categorization and assignment and things that are relatively straightforward processes but very time-consuming and again, if you can get to a 70% solution, 80% solution, 90% solution, to free people up to do other things on the stuff that's relatively routine. Right, if the invoice matches the anticipated bill in the system, pay it. Does somebody really have to look at it? So I thought that was really interesting. Something I want to dig in with you, he talked a lot about data, where the data lives, data gravity. He even said that he fought against data warehousing in the 90s and lost. A lot of real passionate conversation about where is data and how should apps interact with data, and he's really against this data replication and a data lake and moving this stuff all around, but having it kind of central. Want to just get your thoughts on that history. What do you think he means now, and where's that going? >> It's a great question. There's a lot of history behind that. Not everyone would remember, but there was an article in Fortune Magazine in the late 90s, where it described him getting up in a small conference of software CEOs, enterprise software CEOs, and he said basically, "We're going to grind you into dust, "because everything comes in our system integrated. "And if you leave it up to the customer "to try and stitch all this stuff together, "it's going to be a nightmare." And that was back when everyone was thinking, "One company can't do it all." And the reality was, that was the point in time where we really had given go past go, collect $200, to every best-of-breed little software vendor. It did prove out over the next decade that the fewer integration points there were, that it meant much lower cost of ownership for the customer. Not only lower cost of ownership, but better business process integration, 'cause you had the (mumbles) integration. I bring this up because, well, actually, I was there when he said it. (laughs) But I bring it up because he's essentially saying the same thing now, which is, "We'll put all the machine learning technology, "the building blocks, in SAP. "If you need any contextual data, "bring it into our system. "You don't want to take our data out "and put it into all these other machine learning programs "'cause there's security issues, "there's, again, the breakdown "in the business process integration." He did acknowledge that with data warehouses, if you have 100s of other sources, yes, you may need a external data warehouse. But I think that he's going to find with machine learning the greatest value with the data that you use in machine learning is when you're always adding richer and richer contextual data. That contextual data means you're getting it from other sources. I don't think he's going to win this battle in terms of keeping most of it within SAP. >> It kind of bring up this other intersection that he talked about. In now delivering SAP as a cloud application, he said, "Now we have to learn how to run our application, "not our customers," a very different way of looking at the world. The other thing that piggybacks off of what you just said is, we've seen this trend towards configuration, not customization. It used to be probably, back in the days, if you had the big SI's, they loved customization, 'cause it's a huge project, multi-years. I used to talk to one of our center partners, like, "How do you manage a multi-year SAP project "when most the people that started it "probably aren't even there the day you finish it?" But he had a specific quote I wanted to call out now, what you just said, is that he said, "Only our customers have the data, "the desire, and the domain knowledge "to make the most out of it." So it's a really interesting recognition that yes, you want customers to have this configuration option. But we keep hearing more and more, it's config, not-- >> Both: Customization. >> For upgrades and all these other things, which now when you go to a cloud-based application, that becomes significant. You don't want customizations, 'cause that's just complicates everything. >> You can't. I don't know if he said this today. I guess he must have said it today. But basically, when you're in the cloud, I forgot the terminology for the different instances. But when you're in, like, the SAP cloud, you can only configure. There's essentially a set of greater constraints on you. When you go to the other end of the spectrum, let's say you run it in your own data center, you can customize it. But when you're running it, essentially sharing the infrastructure, you're constrained. You're much more constrained. And they build it for that environment first. >> Right. But at the same time, they've got the data. Again, this has come up with other SAS companies that we've talked to, is hopefully, their out of the box business process covers 90% of the basics. I think there's been a realization on the business analyst side that we think we're special, but really most of the time, order to cash is order to cash. So if you got to tweak your own internal process to match best-of-breed, do it. You're much better off than trying to shape that computing system to fill your little corner cases. >> It's funny that you mention that, because what happened in the 90s was that by far the biggest influencers in the purchase decision and the overall lifecycle of the app were the big system integrators. They could typically collect $10 in implementation and change management fees for every dollar of license that went to the software vendors. So they had a huge incentive to tell the customer, "Well, you really should customize this "around your particular needs," because they made all the money off that. >> Right, right. Another huge theme. Again, it was such a great keynote. We watch a lot of keynotes, and I have a very high bar for what I consider a great keynote. This was a great keynote by a smart guy who knows his stuff and got history. But another theme was just really about AI. He talked a little bit, which I thought was great. Nobody talks about the fact that airplanes have been flying themselves for a very long time. So it is coming. I think he even said, maybe this is the age of AI. But there always have to be some humans involved. It's not a complete hand-over of control. But it is coming, and it's coming very, very quickly. >> I actually thought that they were a little further behind than might expected, considering that it's been years now that people in software have seen this coming. But they have in the dozens of applications or functions right now that are machine learning enabled. But if you look out at their roadmap, where they get to predictive accounting, customer behavior segmentation, profile completeness for in sales, solution recommenders, model training infrastructure for the base software foundation, they have a pretty rich roadmap. But I guess I would have thought it'd be a little farther along. But then Oracle isn't really any farther along. (mumbles) has done some work for HR. For whatever reason, I think that enterprise application vendors, I think they found this challenging for two reasons. On the technical side, machine learning is very different from the traditional analytics they did, which was really essentially OLAP, you know, business intelligence. This requires the data scientists and the white lab coats and instead of backward-looking business intelligence this forward-looking predictive analytics. The other thing is, I think you sell this stuff differently, which is, when it was business intelligence, you're basically selling reporting on what happened to department heads or function leaders, whereas when you're selling predictive capabilities, it's a little more transformative and you're not selling efficiency, which is what these applications have always, that's been their value preposition. You're selling transformational outcomes, which is a different sort of selling motion. >> It's funny, I heard a funny quote the other day. We used to look backwards for the sample of the data. (laughs thinly) Now we're in real time with-- >> Both: All the data. >> Very different situation-- >> And forward-looking. >> And forward-looking as well, with the predictive. >> That's a great quote, yeah. >> Again, he touched on so many things. But one of the things he brought up is Tesla. He actually said he has two Teslas, or he has a second Tesla. And there was question and answer afterwards really about the Tesla, not as the technology platform. And he poked fun at Germans. He said Germans have problems with simplicity. He referenced, I presume, a Mercedes or a Porsche, you know, the perfectly ergonomically placed buttons and switches. He goes, "You sit in a Tesla "and it just all comes up on the touch screen. "And if you want to do an update overnight, "they update your software, "and now you have the newer version of the car," versus the Mercedes, where it takes 'em three years to redesign the buttons and switches. I thought that was interesting. Then one of the Q&A people said, "But what about the buying experience? "If you (mumbles) ever bought a Tesla, "it's a very different experience "than buying a car." How does that really apply to selling software? It was pretty interesting. He said we're not there yet. But he has clearly grasped on, it's a new world and it's a new way to interact with the customers, kind of like his no manuals comment, that Tesla is defining a new way to buy a car, experience a car, upgrade a car. >> Operate it. >> At the same time, he got the crazy mode, fanatical mode, like, ludicrous mode, so that he could stop and tell the Porsche guys that you're falling behind further every single day. So I thought, really interesting, bringing that kind of consumer play and kind of a cutting edge automotive example into what was historically pretty stodgy enterprise software space. >> You know, it's funny, I listened when you're saying that. That was almost like the day one objective from SalesForce, which was, we want an enterprise app like Sebol, but we want an eBay-like, or Yahoo-like experience. And that did change the experience for buying it and for operating it. I think that was almost 20 years ago, where that was Marc Benioff's objective and he's saying it's easier to do that for CRM, but it's now time to bring that to ERP. >> The other thing he brought in which I was happy, being a Bay Area resident, is the Sharks. Because he's a part owner of San Josey Sharks, obviously it's SAP Center now, also known as the Shark Tank. It used to be owned by another technology company. But he made just a funny thing. "I like hockey, so I should like SAP," and he was talking about the analysis of how often the logos come up on the telecast et cetera. But the thing that struck me is, he said the analysis is actually now faster than the game. Pretty interesting way to think about this data in flow, in that the analysis coming out of the game that feeds Vegas, it feeds all these stat lines, it feeds fantasy, it feeds all this stuff, it feeds the advertising purchase and the ROI on my logo, is it in the corner, is it on the ice, is it in the middle, is actually moving faster than the hockey game. And hockey is a pretty fast game. Very different world in which we live, even on the mar-tech side. >> That was an example of one of the machine learning-type apps, because I think in their case, they were using, I think, Google image recognition technology to parse out essentially all the logos and see what type of impact your brand made relative to your purchase. >> I mean, I could go on and on. I've so many notes. Again, I live tweeted a lot of it, you know, he's just such a humble guy. He's a smart guy. He comes at it with a technology background, but he said we're a little bit slower than we'd like, he talked about some things taking longer than he thought they would. But he also now sees around the corner, that we are very quickly going to be in this age of infinite compute, and we are already in an age of, no one's reading manuals. Just seemed very kind of customer-centric, we're no longer the super-smart Germans that, "We'll do it our way or the highway, "and you will adapt your process to us," but really customer-centric point of view, design thinking, talked about sharing their roadmap as far out in advance as possible. I think he specifically, when he got questioned on design thinking, he's, like, "You know, the studies show that a collaborative effort "yields better results. "It's no longer, 'We're the smartest guy in the room "'and we're going to do it this way "'and you're going to adapt.'" So really progressive. >> And he talked about, with Concur, he said their UI is so easy that you really don't need a manual. In fact, if you do, you failed. And I think what he's trying to say is, we're going to take that iterative prototyping capability agile development and extend it to the rest of the ERP family. With their Fiori UI and the tools that build those screens that it'll make that possible. >> You've handled CAP. We don't spend enough investment on design in UI, 'cause it is such an important piece of the puzzle. But George, we're running out of time here. I want to give you the last word. You've been paying attention to SAP for a very long time. Hasso's terrific, but then Hasso gets off the stage and he said, "I don't run the company any more. "I only make recommendations." As you look at SAP, and Bill McDermott was yesterday, are they changing? Are they just stuck in an innovator's dilemma because they just make so much money on their historical business? Or are they really changing? What's your take as they develop, where they are now, and what do you see going forward for SAP? >> Well it's a really good question. I would say, I look at the value of the business processes that they are either augmenting or automating. I hesitate to say automate because, as he said, you still want the pilot in the cockpit. >> Jeff: In proximity to take control. >> Right. And he was, like, "Look, when we do the invoice matching, "it's not like we're going to get 100% right. "We're going to get it," I think he was saying, like, in the labs right now it's, like, 94% right. So we're going to make you more productive, we're not going to eliminate that job. But when you're doing invoice matching, that's not a super high value business process. If you're doing something where you're predicting churn and making a next best offer to a customer, that's a higher value process. Or if you have a multi-touchpoint commerce solution where you can track the customer, whether it's mobile, whether he's coming via chat, whether he's in the store, and you're able to see his history or her history and what's most appropriate given their context at any one moment, that's higher value. And then it's super high value to be able to take that back upstream towards, "Okay, here's where the inventory is. "I have some in this store. "I can't fulfill that clothing item directly from the store, "but I can fulfill it from this one," or, "I have it in another warehouse," when you have that level of awareness and integration, that's high value. >> Yeah, but I want to push back a little bit on you, George, 'cause I do think the invoice ma-, if he can automatically match 94% of the invoices, that is tremendous value. I just think it's so creative when you apply this machine learning to tasks that feel relatively mundane. But if you're speeding your cash flow along, if you get 94% of your invoices done one day faster and you're a multimillion dollar business, what is the direct dollar impact on the bottom line, like, immediately? It's huge. And then you can iterate and move into other processes. I think what's termed a low value transaction is actually a lot higher value than people give it credit. It's just like again, another one we hear about all the time, automation of password reset. Some of these service desks, password reset, I heard a stat, and one of them was 70% of the calls are password reset. So if you could automate password reset, sounds kind of silly and mundane, oh my gosh, it's like 70% of your calls. It's humongous. >> I hear what you're saying. Let me give you another counter example, which was, I think he brought this up. I don't know if it was today or when Michael Dell spoke, which was that Dell's revolution wasn't that they were more efficient than doing what Compaq did. It's that they had a different business model, which was specifically, they got paid before they even procured or assembled the components. >> Or paid for them, right? >> George: Yes, yes. >> They had no inventory carry costs. >> In fact, that meant their working capital, their working capital needs were negative. In fact, the bigger they got, the more money they collected before they had to spend it. That's a different business model. That wasn't automating the invoice matching. That was, we have such good systems that we don't even have to pay for them and then assemble the stuff until after the customer gave us their credit card. >> Right, right, right. >> I think those are the things that new types of applications can make possible. >> Right. Well, we see it time and time again. It's all about scale, it's all about finding inefficiencies, and there's a lot more inefficiencies around than people give credit, as Uber showed with a lot of cars that sit in driveways and Amazon and the public clouds are showing with a lot of inefficient, not used utilization and private data centers. So the themes go on and on, and they're pretty universal. So, exciting keynote. Any last comment before we sign off for today? >> I guess we want to take a close look at Oracle next and see how their roadmap looks like in terms of applying these new technologies, iOT, machine learning, block chain. Because all of these can remake how you build a business. >> All right, that's George Gilbert from Wikibon. I'm Jeff Frick from the CUBE. We are covering ongoing coverage of SAP SAPPHIRE 2017. Thanks for watching, we'll be back with more after this short break. Thanks. (lively music)

>> Announcer: Live, from Las Vegas, it's theCUBE. Covering Interconnect 2017. Brought to you by IBM. >> Okay, welcome back everyone we're here live in Las Vegas at the Mandalay Bay, theCUBE's exclusive three day coverage of IBM Interconnect 2017, I'm John Furrier. My co-host, Dave Velliante. Our next guest is Harley Davis, who's the VP of decision management at IBM. Welcome to theCUBE. >> Thank you very much, happy to be here. >> Thanks for your time today, you've got a hot topic, you've got a hot area, making decisions in real-time with data being cognitive, enterprise strong, and data first is really, really hard. So, welcome to theCUBE. What's your thoughts? Because we were talking before we came on about data, we all love, we're all data geeks but the value of the data is all contextual. Give us your color on the data landscape and really the important areas we should shine a light on, that customers are actively working to extract those insights. >> So, you know, traditionally, decisions have really been transactional, all about taking decisions on systems of record, but what's happening now is, we have the availability of all this data, streaming it in real-time, coming from systems of record, data about the past, data about the present, and then data about the future as well, so when you take into account predictive analytics models, machine learning, what you get is kind of data from the future if I can put it that way and what's interesting is how you put it all together, look for situations of risk, opportunity, is there a fraud that's happening now? Is there going to be a lack of resources at a hospital when a patient checks in? How do we put all that context together, look into the future and apply business policies to know what to do about it in real-time and that's really the differentiating use cases that people are excited about now and like you say, it's a real challenge to put that together but it's happening. >> It's happening, and that's, I think that's the key thing and there's a couple megatrends going on right now that's really propelling this. One is machine learning, two is the big data ecosystem as we call it, the big data ecosystem has always been, okay, Hadoop was the first wave, then you saw Spark, and then you're seeing that evolving now to a whole nother level moving data at rest and data in motion is a big conversation, how to do that together, not just I'm a batch only, or real-time only, the integration of those two. Then you combine that with the power of cloud and how fast cloud computing, with compute power, is accelerating, those two forces with machine learning, and IOT, it's just amazing. >> It's all coming together and what's interesting is how you bridge the gap, how you bring it all together, how you create a single system that manages in real-time all this information coming in, how you store it, how you look at, you know, history of events, systems of record and then apply situation detection to it to generate events in real-time. So, you know, one of the things that we've been working on in the decision management lab is a system called decision server insights, which is a big real-time platform, you send a stream of events in, it gets information from systems of records, you insert analytics, predictive analytics, machine learning models into it and then you write a series of situation detection rules that look at all that information and can say right now this is what's happening, I link it in with what's likely to happen in the future, for example I can say my predictive analytics model says based on this data, executed right now, this customer, this transaction is likely, 90% likely to be a fraud and then I can take all the customer information, I can apply my rule and I can apply my business policy to say well what do I do about that? Do I let it go through anyway? Because it's okay, do I reject it? Do I send it to a human analyst? We got to put all that together. >> So that use case that you just described, that's happening today, that's state of the art today, so one of the challenges today, and we all know fraud detection's got much, much better in the last several years, it used to take, if you ever found it, it would take six months, right? And it's too late, but still a lot of false positives, that'll negate a transaction, now that's a business rule decision, right? But are we at the point where even that's going to get better and better and better? >> Well, absolutely. I mean the whole, there have been two main ways to do fraud detection in the past. The first one is kind of long scale predictive analytics that you train every few months and requires, you know, lots and lots of history of data but you don't get new use cases that come up in real-time, like you don't have the Ukrainian hacker who decides, you know, if I do a payment from this one website then I can grab a bunch of money right now and then you have the other alternative, which is having a bunch of human analysts who look for cases like that guy and put it in as business rules and what's interesting is to combine the two, to retrain the models in real-time, and still apply the knowledge that the human analysts can get in real-time, and that's happening every day in lots of companies now. >> And that idea of combining transactional data and analytics, you know, has become popularized over the last couple of years, one obvious use case there is ad-tech, right? Making offers to people, marketing, what's the state of that use case? >> Well, let's look at it from the positive perspective. What we are able to do now is take information about consumers from multiple sources, you can look at the interaction that you've had with them, let's say you're a financial services company, you get all sorts of information about a company, about a customer, sorry, from the CRM system, from the series of interactions you've had with them, from what they've looked at on your website, but you can also get additional information about them if you know them by their Twitter handle or other social media feeds, you can take information from their Twitter feeds, for example, apply some cognitive technology to extract information from that do sentiment analysis, do natural language processing, you get some sense of meaning about the tweets and then you can combine that in real-time in a system like the one I talked about to say ah, this is the moment, right here, where this guy's interested in a new car, we think he just got a promotion or a raise because he's now putting more money into the bank and we see tweets saying "oh I love that new Porsche 911, "can't wait to go look at it in the showroom," if we can put those things together in real-time, why not send him a proactive offer for a loan on a new car, or put him in touch with a dealer? >> No and sometimes as a consumer I want that, you know, when I'm looking for say, scarce tickets to a show or a play-off game or something and I want the best offer and I'm going to five or six different websites, and somebody were to make me an offer, "hey, here are better seats for a lower price," I would be thrilled. >> So geographic information is interesting too for that, so let's say, for example, that you're, you're traveling to Napa Valley and let's say that we can detect that you just, you know, took out some money from the bank, from your ATM in Napa, now we know you're in Napa, now we know that you're a good customer of the bank, and we have a deal with a tour operator, a wine tour operator, so let's spontaneously propose a wine tour to you, give you a discount on that to keep you a good customer. >> Yeah, so relevant offers like that, as a consumer I'd be very interested in. All too often, at least lately, I feel like we're in the first and second innings of that type of, you know, system, where many of the offers that you get are just, wow, okay, for three weeks after I buy the dishwasher, I'm getting dishwasher ads, but it's getting better, you can sort of see it and feel it. >> You can see it getting a little better. I think this is where the combination of all these technologies with machine learning and predictive analytics really comes to the fore and where the new tools that we have available to data scientists, things like, you know, the data scientist experience that IBM offers and other tools, can help you produce a lot more segmented and targeted analytics models that can be combined with all the other information so that when you see that ad, you say oh, the bank really understands me. >> Harley, one of the things that people are working on right now and most customers, your customers and potential customers that we talk to is I got the insights coming, and I'm working on that, and we're pedaling as fast as we can, but I need actionable insight, this is a decision making thing, so decisions are now what people want to do, so that's what you do, so there's some stats out there that decision making can be less than 30 minutes based on good data, the life of the data, as short as six seconds, this speaks to the data in motion, humans aside of it, I might be on my mobile phone, I might be looking at some industrial equipment, whatever, I could be a decision maker in the data center, this is a core problem, what are you guys doing in this area, because this is really a core problem. Or an opportunity. >> Well this all about leveraging, you know, event driven architectures, Kafka, Spark and all the tools that work with it so that we can grab the data in real-time as it comes in, we can associate it with the rest of the context that's relevant for making a decision, so basically with action, when we talk about actionable insights, what are we talking about? We're talking about taking data in real-time, structured, unstructured data, having a framework for managing it, Kafka, Spark, something like decision server insights in ODM, whatever, applying cognitive technology to turn some of the unstructured data into structured data, applying machine learning, predictive analytics, tools like SPSS to create a kind of prediction of what happens in the future and then applying business rules, something like operational decision management, ODM, in order to apply business policies to the insights we've garnered from the rest of the cycle so that we can do something about it, that's decision manager, that's-- >> So you were saying earlier on the use case about, I get some event data, I bring it in to systems of record, I apply some rules to it, I mean, that doesn't sound very hard, I mean, it's almost as if that's happening now-- >> It's hard. >> Well it's hard, let me get, this is my whole point, this is not possible years ago so that's one point, I want to get some color from you on that because this is ungettable, most of the systems, we even go back ten, five years ago, we siloed, so now rule based stuff seems trivial, practically, okay, by some rules, but it's now possible to put this package together and I know it's hard but conceptually those are three concepts that some would say oh, why weren't we doing this before? >> It's been possible for a long time and we have, you know, we have plenty of customers who combine, you know, who do something as simple as when you get approved for a loan, that's based on a score, which is essentially a predictive analytics model combined with business rules that say approve, not approve, ask for more documentations and that's been done for years so it's been possible, what's even more enabled now is doing it in real-time, taking into account a much greater degree of information, having-- >> John: More data sources. >> Data sources, things like social media, things like sensors from IoT, connected car applications, all sorts of things like that and then retraining the models more frequently, so getting better information about the future, faster and faster. >> Give an example of some use cases that you're working with customers on because I think that's fascinating and I think I would agree with you that it's been possible before but the concepts are known, but now it's accelerating to a whole nother level. Talk about some of the use cases end-to-end that you guys have done with customers. >> Let's think about something like an airline, that wants to manage its operations and wants to help its passengers manage operational disruptions or changes. So what we want to do now is, take a series of events coming from all sorts of sources, and that can be basic operational data like the airplanes, what's the airplane, is it running late, is it not running late, is the connection running late, combining it with things about the weather, so information that we get about upcoming weather events from weather analytics models, and then turning that into predicting what's going to happen to this passenger through his journey in the future so that we can proactively notify him that he should be either, we can rebook him automatically on a flight, we can provide him, if we know he's going to be delayed, we can automatically provide him amenities, notify the staff at the airport where he's going to be blocked, because he's our platinum customer, we want to give him lounge access, we want to give him his favorite drink, so combine all this information together and that's a use case-- >> When's this going to happen? >> That's life, that's life. >> I want to fly that airline. Okay, so we've been talking a lot about-- >> Mr. American Airlines? I'm not going to put you on the spot there, hold up, that'll get you in trouble. >> Oh yeah, it's a real life use case. >> And said oh hey, you're not going to make your connection, thanks for letting me know. Okay, so, okay we were talking a lot about the way things used to be, the way things are, and the way things are going to be or actually are today, in that last example, and you talked about event driven workloads. One of the things we've been talking about, at SiliconANGLE and on theCUBE is, is workloads, with batch, interactive, Hadoop brought back batch, and now we have what you call, this event driven workloads, we call it the continuous workloads, right? >> All about data immersion, we all call it different things but it's the same thing. >> Right, and when we look at our forecast, we're like wow, this is really going to hit, it hasn't yet, but it's going to hit the steep part of the s-curve, what do you guys expect in terms of adoption for those types of workloads, is it going to be niche, is it going to be predominant? >> I think it should be predominant and I think companies want it to be predominant. What we still need, I think, is a further iteration on the technology and the ability to bring all these different things together. We have the technologies for the different components, we have machine learning technology, predictive analytics technology, business rules technology, event driven architecture technology, but putting it all together in a single framework, right now it's still a real, it's both a technology implementation challenge, and it's an organizational challenge because you have to have data scientists work with IT architects, work with operational people, work with business policy people and just organizationally, bringing everybody-- >> There's organizational gap. That's what you're talking about. >> Yeah, but every company wants it to happen, because they all see a competitive advantage in doing it this way. >> And what's some of the things that are, barriers being removed as you see them, because that is a consistent thing we're hearing, the products are getting better, but the organizational culture. >> The easy thing is the technology barriers, that's the thing, you know? That's kind of the easy thing to work on, how do we have single frameworks that bring together everything, that let you develop both the machine learning model, the business rules model, and optimization, resource optimization model in a single platform and manage it all together, that's, we're working on that, and that's going to be-- >> I'll throw a wrinkle into the conversation, hopefully a spark, pun intended. Open source and microservices and cloud native apps are coming, that are, with open source, it's actually coming in and fueling a lot more activity. This should be a helpful thing to your point about more data sources, how do you guys talk about that? Because that's something you have to be part of, enabling the inbound migration of new stuff. >> Yeah, we have, I mean, everything's part of the environment. It's been the case for a while that open source has been kind of the driver of a lot of innovation and we assimilate that, we can either assimilate it directly, help our customers use it via services, package it up and rebrand open source technology as services that we manage and we control and integrate it for, on behalf of our customers. >> Alright, last question for you. Future prediction, what's five years out? What's going to happen in your mind's eye, I'm not going to hold you, I mean IBM to this, you personally, just as you see some of this stuff unfolding, machine learning, we're expecting that to crank things up pretty quickly, I'm seeing cognitive, and cognitive to the core, really rocking and rolling here, so what's your, how'd you see the next five years playing out for decision making? >> The first thing is, I don't see Skynet ever happening, I think we're so-- >> Mark Benioff made a nice reference in the keynote about Terminator, I'm like no one pick up on that on Twitter. >> I don't think that's really, nearly impossible, as a scenario but of course what is going to happen and what we're seeing accelerating on a daily basis, is applying machine learning, cognitive technology to more and more aspects of our daily life but I see it, it's in a passive way, so when you're doing image recognition, that's passive, you have to tell the computer tell me what's in this image but you, the human, as the developer or the programmer, still has to kick that off and has to say okay, now that you've told me there's a cat in an image, what do I do about that and that's something a human still has to do and that's, you know, that's the thing that would be scary if our systems started saying we're going to do something on behalf of you because we understand humans completely and what they need so we're going to do it on your behalf, but that's not going to happen. >> So the role of the human is critical, paramount in all this. >> It's not going to go away, we decide what our business policies are and-- >> But isn't, well, autonomous vehicles are an example of that, but it's not a business policy, it's the car making a decision for us, cos we can't react fast enough. >> But the car is not going to tell you where you want to go. If it started, if you get in the car and it said I'm taking you to the doctor because you have a fever, maybe that will happen. (all laugh) >> That's kind of Skynet like. I'd be worried about that. It may make a recommendation. (all laugh) >> Hey, you want to go to the doctor, thank you, no I'm good. >> I really don't see Skynet happening but I do think we're going to get more and more intelligent observations from our systems and that's really cool. >> That's very cool. Harley, thanks so much for coming on theCUBE, sharing the insights, really appreciate it. theCUBE, getting the insights here at IBM Interconnect 2017, I'm John Furrier, stay with us for some more great interviews on day three here, in Las Vegas, more after this short break. (upbeat music)

>> Announcer: Live from Las Vegas, Nevada. It's the CUBE, covering AWS re:Invent 2016. Brought to you by AWS and its ecosystem partners. (light techno music) Now, here's your host. >> And we're back, happy to welcome back to the program, regular guest on our program, David Richards, who is the founder and CEO of WANdisco. David, anything interesting happen since last time, you know, we've talked to you? >> David: Well I kind of got, you guys are a bad omen for me. Kind of left the CUBE in New York, got off a plane, got fired, and then four days later got reinstated. Apart from that, virtually nothing's happened actually. >> Hey, you know it's good coverage in The Financial Times, and then lots of press and everything, so lots more people know about WANdisco now, right? >> David: That's right, and I don't have Tourette's, I promise. (laughs) >> Alright, David, AWS re:Invent, I mean, pretty impressive show, you know we see you in a lot of shows, many of them interesting, lots of smart people but I mean, wow this is pretty impressive. They got up on stage lots of things that I'm sure interest you, give us your take of the show so far. >> It's fascinating, I mean, this sort of must have been, I wasn't there when, you know, Steve Jobs was launching the first Mac and so on, but this kind of feels, more than just a small movement. This is a large shift in enterprise, moving from On-premises to Cloud, I think it's unquestionable that's happening. I mean, I'm sure you've covered it this week on The Cube. I've not seen it, but 32,000 people are here. Virtually every single vendor that you could ever think of is exhibiting in this exhibit hall. You can barely move about the people. Our booth traffic has just been phenomenal this week, and it really feels like this is a seismic shift in the marketplace. I know we've been saying that for a while, but it really does feel that way. >> Why do you think now, is it just, we just got here, and it's the overnight success that's been ten years in the making, or was there an event or something that really, kind of, tipped it over to where we are, because clearly, it's very different than last year. >> It, sort of, Cloud V1, and you guys have been covering this for a long time, was really companies that were born in the Cloud, it was the Airbnbs, it was the Tinders, it was the Facebooks and so on. Those companies were actually made, born in the Cloud. What's now happening, clearly, is enterprise is moving to the Cloud, and Cloud 2.0 really is about a different set of requirements, a different set of customers. There are customers with massive petabyte-scale data sets that they really can't take advantage of, they can't really scale out, it's too complex for them to build many of the applications they need to build, they now have to move to Cloud, and, you know, 32,000 people are not here just for the sake of it, they're here because they have to be here, because they're moving, obviously, to Cloud, and AWS have such a massive lead, I think, in the Cloud at the moment and Enterprise Cloud, and that's probably why so many people are here. >> David, one of the interesting things to look at at this show is, Amazon has some opinions about where data lives, how it moves, where you process it, you know, all of those kind of things. You guys are kind of opinionated on those kind of things too so, you know, give us your view on those kind of, those guys. I mean, I made a comment on Twitter, it was like, "Hey, what do we call a data lake when it's in the Cloud now?" >> Jeff: Well look, that's what happens to Clouds, they-- >> One of the big reveals in Andy Jassy's talk this morning was a truck coming across the front of the stage, and I've had so many emails saying, is this real, is this a joke, are we now really moving data in a semi from On-premises into the Cloud? And, it's kind of interesting, I think it's a little bit of a gimmick to be honest with you, I think Amazon do lots of great things, there were lots of wonderful announcements today, like opening up Alexa and allowing, you know, and some of the things they're doing with serverless computers, just phenomenal, but I think a truck to move data from On-premises to Cloud, kind of feels like we're back in the 1970s to me, whereas I was talking to a, the CIO of an automotive company a couple of weeks ago. They have a problem where, you know, to move data causes an outage in their organization today of about 30 hours. Their data growth is going to be so vast, the velocity is going to be so great in the next 12 months, that if they use the existing technology today, that they have today, would take them in the region of a month to move that data. So, trucks are great for cold, archival data, well they might be great for cold, archival data, I'm sure you could figure out a better way, like the internet to move it, but for our active transactional data, data that changes and moves, that's critical to the organization, you simply can't put it on the back of a truck and basically mail it to Amazon with a Snowball, that really doesn't work, and I think the market really needs to be educated a little bit about what's possible. >> Well, and I don't know that Amazon would necessarily disagree with you. I mean, if you look at the Snowball family, they had the Snowball Edge out there, which was realization, hey I might want compute, and even, we're going to give you that new green grass Lambda, serverless type stuff, so that you can do processing where there's no network, or I can't do anything, but, I guess, we know from a physics standpoint, I understand, you know, the internet is great, but, you know, if I want to move, you know, 100 petabytes or more of data, you know, even if I'm a Telco, that's a ton of data that I need to move. So, tell me where there's this connect. >> So, the way that WANdisco's technology works, is we continually replicate data, so where every other form of data replication is time based, it requires the concept of a clock, like, even Google, who've got Google Spanner, which is kind of active/active replication, but relies on a satellite in the sky, on atomic clocks, GPS clocks on every single server. We don't have any of that reliance, we're transactional data replication, which means if something changes, it gets replicated, and that process is continuous, which means that you can basically move data applications without any downtime or interruption to service. And that's absolutely critical for what I called earlier Cloud V2, which is the enterprises moving to Cloud, they have to be able to get there without any interruption to service. Small data, yeah, you can use that kind of technology, or non-strategic data, yeah, you can use this kind of technology. Strategic data and strategic applications, trading systems, you know, you can't be 99.99% correct if somebody's got cancer or not, right? If you're using the Cloud, or machine learning technology to figure that out, you can't be, you know, almost certain, you need to be completely certain, and that requires data to be where it's supposed to be. >> So, Amazon's a partner of yours. What's it like being a partner of Amazon's these days? Give us your point on that. >> Amazon are a phenomenal company. They have to be, right, they've just built, probably the world's most valuable enterprise technology business by a country mile in ten years. I mean, it's just, you know, zero to 10 billion in (snaps fingers) the blink of an eye is just incredible. And part of their secret is, they base everything on data, and I've learned a lot from dealing with Amazon actually, everything is data driven. You know, they have this Five Why's, I'm sure you've read about it in the media, where you have to prove, through facts and figures, not sentiment, that something is so, and that's pretty uncomfortable for a lot of people. For us, it's not, and it's, working with Amazon, their requirements, the bar is so high it's made our products much much much better. They have a well-architectured review that they go through with all their partners. They're actually great to partner with, if you're not a very good company, I would, daresay, don't bother because they'll find you out very quickly. But they're a great set of guys, very very good to partner with, it's very black and white, it's very quantitative, but, yeah, they've obviously got a huge market. >> Yeah. One of the things I love about this show is that the quality of people, you know, is phenomenal, and you get such a, I mean, a huge cross-section, not only location, size, industry, but one of the things I think that is across everybody that comes here, is they're trying new things, they're open to, you know, moving forward, iterating, learning, which has been one of the things that, you know, we kind of say what holds companies back is like, oh I'm doing it the old way. So, what's your experience been with the users? Any stories you can tell from that standpoint? >> So, right down to the bottom of the organization, they're prepared to take any idea. I mean, Amazon Web Services, for goodness' sake was basically a paper that was written and presented to Jeff Bezos, right, who said, yeah that's a good idea to Jassy and said yeah, let's go off and do it. But they, virtually every innovation in their organization is somebody coming up with an idea. They have the mechanics and machinery to listen to that idea. We do it ourselves, so, we're looking at serverless compute and using Lambda so we can have replication literally as a service that you can just call, you can call Paxos, which is our core IP, it's based on Paxos, it's called DConE, so you can call that algorithm and get a replication service. So these concepts, some of the concepts that Amazon are introducing, their ability to move so quickly to introduce new products is because they have this innovative approach where they allow people, right down to the very bottom of the organization, to come up with new ideas and approaches to doing things. And it's perfectly fine for somebody at the bottom of their organization to challenge somebody at the top of the organization. In fact, they expect it. And again, that's not comfortable for a lot of people, but I like the way that they go around their business. >> I'm looking forward to, Alexa, how's my replication doing? (laughs loudly) >> Wouldn't that be great? >> Well, it's interesting you say that, we had Malcolm Gladwell on a month or two ago, and he talked about, the most powerful organizations are the ones that let the fresh ideas bubble up from the bottom because it's the people that have not been tainted by being in part of the company, that had new and creative and innovative, and a different way of looking at it, and oftentimes they get squelched, so the fact that they let those ideas come up, and also driven by data, pretty powerful. >> It's interesting being at the show this week, and I have two types of meetings, I have meetings with companies at the forefront of this Cloud revolution, companies at the forefront of building new, innovative applications that were designed for the Cloud, and then I have other meetings with companies, vendors, who have been caught out by this. They didn't see this coming, they didn't expect, you know, this sea change to happen as quickly as it's happening and they really are fighting and scrambling to know what to do, and this is everything from, you know, the big services companies, the big traditional enterprise storage companies are really struggling to understand what they're going to do with the Cloud, and they don't have those processes and procedures inside their businesses like we do. Like, they can't change and be agile and nimble and take advantage of these new products and markets that are suddenly appearing overnight. >> Yeah, it's funny, the guy from (mumbles) was talking about, they don't want to be a system integrator anymore, right now it's services integration and really changing the way you think about putting this stuff together, it's very different. >> It is very different, and, it used to be the case that you'd get, and I know we've all lived through this, you get the enterprise sales guy that turns up in the $2,000 suit and the Porsche parked outside, and comes in and sells you, you know, a piece of software, and asks you how your wife and kids are doing and all the rest of it. Look at the audience here today. They're not going to put up with, you know, that style of enterprise sales moving forward. People are buying stuff from a marketplace. The expectation is you can choose, select, deploy, and build applications yourself, and that's how many of these companies are operating today. So it's not just the sea change in the technology, the technology's facilitating completely different and new markets. >> Jeff: Behaviors, yeah. >> David, want to give you the final word on, as you leave this show, you know, your takeaways, what you want people to know. >> Clearly we're in an era where, this is going to be an Enterprise Cloud. Cloud 2.0 is all about enterprises that are taking their data from On-premises into the Cloud. It's happening very quickly. 32,000 people are here this week, they're here for a reason, because they have to be. This is a sea change in the marketplace, and I hope, well I know WANdisco's the vanguard of moving many of those enterprises from On-premises into the Cloud very quickly. >> Alright, absolutely, definitely agree with the sea change there. David Richards, founder and still CEO of WANdisco, really appreciate you joining us again. We'll be back to wrap up our coverage of today at AWS re:Invent 2016. You're watching the CUBE. (light techno music)