(intro music) >> Narrator: "theCUBE's" live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (gentle music) >> Hey everyone, welcome back to "theCUBE," the leader in live and emerging tech coverage. As you well know, we are live at MWC23 in Barcelona, Spain. Lisa Martin with Dave Nicholson. Day three of our coverage, as you know, 'cause you've been watching the first two days. A lot of conversations about ecosystem, a lot about disruption in the telco industry. We're going to be talking about Open RAN. You've heard some of those great conversations, the complexities, the opportunities. Two guests join Dave and me. Abdullah Abuzaid, Technical Product Manager at Dell, and Gil Hellmann, VP Telecom Solutions Engineering and Architecture at Wind River. Welcome to the program guys. >> Thank you. >> Nice to be here. >> Let's talk a little bit about Dell and Wind River. We'll each ask you both the same question, and talk to us about how you're working together to really address the complexities that organizations are having when they're considering moving from a closed environment to an open environment. >> Definitely. Thank you for hosting us. By end of the day, the relationship between Dell and Wind River is not a new. We've been collaborating in the open ecosystem for long a time enough. And that's one of the, our partnership is a result of this collaboration where we've been trying to make more efficient operation in the ecosystem. The open environment ecosystem, it has the plus and a concern. The plus of simplicity, choice of multiple vendors, and then the concern of complexity managing these vendors. Especially if we look at examples for the Open RAN ecosystem, dealing with multiple vendors, trying to align them. It bring a lot of operational complexity and TCO challenges for our customers, from this outcome where we build our partnership with Wind River in order to help our customer to simplify, or run deployment, operation, and lifecycle management and sustain it. >> And who are the customers, by the way? >> Mainly the CSP customers who are targeting Open RAN and Virtual RAN deployments. That digital transformation moving towards unified cloud environment, or a seamless cloud experience from Core to RAN, these are the customers we are working with them. >> You'll give us your perspective, your thoughts on the partnership, and the capabilities that you're enabling, the CSPs with that. >> Sure. It's actually started last year here in Barcelona, when we set together, and started to look at the, you know, the industry, the adoption of Open RAN, and the challenges. And Open RAN brings a lot of possibilities and benefit, but it does bring a lot of challenges of reintegrating what you desegregate. In the past, you purchase everything from one vendor, they provide the whole solution. Now you open it, you have different layers. So if you're looking at Open RAN, you have, I like to look at it as three major layers, the management, application, and the infrastructure. And we're starting to look what are the challenges. And the challenges of integration, of complexity, knowledge that operator has with cloud infrastructure. And this is where we basically, Dell and Winder River set together and say, "How can we ease this? "How we can make it simpler?" And we decided to partner and bring a joint infrastructure solution to market, that's not only integrated at a lab at the factory level, but it basically comes with complete lifecycle management from the day zero deployment, through the day two operation, everything done through location, through Dell supported, working out of the box. So basically taking this whole infrastructure layer integration pain out, de-risking everything, and then continuing from there to work with the ecosystem vendor to reintegrate, validate the application, on top of this infrastructure. >> So what is the, what is the Wind River secret sauce in this, in this mix, for folks who aren't familiar with what Wind River does? >> Yes, absolutely. So Wind River, for many, many don't know, we're in business since 1981. So over 40 years. We specialize high performance, high reliability infrastructure. We touch every aspect of your day and your life. From the airplane that you fly, the cars, the medical equipment. And if we go into the telco, most of the telco equipment that it's not virtualized, not throughout the fight today, using our operating system. So from all the leading equipment manufacturers and even the smaller one. And as the world started to go into desegregation in cloud, Wind River started to look at this and say, "Okay, everything is evolving. Instead of a device that included the application, the hardware, everything fused together, it's now being decomposed. So instead of providing the operating environment to develop and deploy the application to the device manufacturer, now we're providing it basically to build the cloud. So to oversimplify, I call it a cloud OS, okay. It's a lot more than OS, it's an operating environment. But we took basically our experience, the same experience that, you know, we used in all those years with the telco equipment manufacturer, and brought it into the cloud. So we're basically providing solution to build an on-premises scalable cloud from the core all the way to the far edge, that doesn't compromise reliability, doesn't compromise performance, and address all the telco needs. >> So I, Abdullah, maybe you can a answer this. >> Yeah. >> What is the, what does the go-to-market motion look like, considering that you have two separate companies that can address customers directly, separately. What does that, what does that look like if you're approaching a possible customer who is, who's knocking on the door? >> How does that work? >> Exactly. And this effort is a Dell turnkey sales service offering, or solution offering to our customers. Where Dell, in collaboration with Wind River, we proactively validate, integrate, and productize the solution as engineered system, knock door on our customer who are trying to transform to Open RAN or open ecosystem. We can help you to go through that seamless experience, by pre-validating with whatever workload you want to introduce, enable zero touch provisioning, and during the day one deployment, and ensure we have sustainable lifecycle management throughout the lifecycle of the product in, in operate, in operational network, as well as having a unified single call of support from Dell side. >> Okay. So I was just going to ask you about support. So I'm a CSP, I have the solution, I go to Dell for support. >> Exactly. >> Okay. So start with Dell, and level one, level two. And if there are complex issues related to the cloud core itself, then Wind River will be on our back supporting us. >> Talk a little bit about a cust, a CSP example that is, is using the technology, and some of the outcomes that they're able to achieve. I'd love to get both of your perspectives on that. >> Vodafone is a great example. We're here in Barcelona. Vodafone is the first ora network in Europe, and it's using our joint solution. >> What are some of the, the outcomes that it's helping them to achieve? >> Faster time to market. As you see, they already started to deploy the ORAN in commercial network, and very successful in the trials that they did last year. We're also not stopping there. We're evolving, working with them together to improve like stuff around energy efficiency. So continue to optimize. So the outcome, it's just simplifying it, and you know, ready to go. Using experience that we have, Wind River is powering the first basically virtualized RAN 5G network in the world. This is with Verizon. We're at the very large scale. We started this deployment in late '20 and '19, the first site. And then through 2020 to 2022, we basically rolled in large scale. We have a lot of experience learning from it, which what we brought into the table when we partnered with Dell. A lot of experience from how you deploy at scale. Many sites from a central location, updates, upgrade. So the whole day two operation, and this is coming to bearing the solution that basically Vodafone is deploying now, and which allowed them... If I, if I look at my engagement with Verizon, started years before we started. And it took quite some time until we got stuff running. And if you look at the Vodafone time schedule, was significantly compressed compared to the Verizon first deployment. And I can tell you that there are other service providers that were announced here by KDI, for example. It's another one moving even faster. So it's accelerating the whole movement to Ora. >> We've heard a lot of acceleration talk this week. I'd love to get your perspective, Abdullah, talking about, you know, you, you just mentioned two huge names in Telco, Vodafone and Verizon. >> Yep. >> Talk a little bit about Dell's commitment to helping telecommunications companies really advance, accelerate innovation so that all of us on the other end have this thing that just works wherever we are 24 by 7. >> Not exactly. And this, we go back to the challenges in Open ecosystem. Managing multiple vendors at the same time, is a challenge for our customers. And that's why we are trying to simplify their life cycle by have, by being a trusted partner, working with our customer through all the journey. We started with Dish in their 5G deployment. Also with Vodafone. We're finding the right partners working with them proactively before getting into, in front of the customer to, we've done our homework, we are ready to simplify the process for you to go for it. If you look at the RAN in particular, we are talking with the 5g. We have ran the simplification, but they still have on the other side, limited resources and skillset can support it. So, bringing a pro, ahead of time engineer system, with a zero touch of provisioning enablement, and sustainable life cycle management, it lead to the faster time to market deployment, TCO savings, improved margins for our customers, and faster business revenue for their end users. >> Solid outcomes. >> And, and what you just just described, justifies the pain associated with disaggregating and reintegrating, which is the way that Gill referenced it, which I think is great because you're not, you're not, you're not re-aggregating, (laughs) you're reintegrating, and you're creating something that's better. >> Exactly. >> Moving forward. Otherwise, why would you do it? >> Exactly. And if you look at it, the player in the ecosystem, you have the vendors, you have the service integrators, you have the automation enablers, but kind of they are talking in silos. Everyone, this is my raci, this is what I'm responsible for. I, I'm not able, I don't want to get into something else while we are going the extra mile by working proactively in that ecosystem to... Let's bring brains together, find out what's one plus one can bring three for our customers, so we make it end-to-end seamless experience, not only on the technical part, but also on the business aspect side of it. >> So, so the partnership, it's about reducing the pen. I will say eliminating it. So this is the, the core of it. And you mentioned getting better coverage for your phone. I do want to point out that the phones are great, but if you look at the premises of a 5G network, it's to enable a lot more things that will touch your life that are beyond the consumer and the phone. Stuff like connected vehicles. So for example, something as simple as collision avoidance, the ability for the car that goes in front of you to be able to see what's happening and broadcast this information to the car behind that have no ability to see it. And basically affect our life in a way that makes our driving safer. And for this, you need a ultra low, reliable low latency communication. You need a 5G network. >> I'm glad you brought that up, because you know, we think about, "Well we just have to be connected all the time." But those are some of the emerging technologies that are going to be potentially lifesaving, and, and really life transforming that you guys are helping to enable. So, really great stuff there, but so much promise coming down the road. What's next for Dell and Wind River? And, and when you're in conversations with prospective CSP's, what is the superpower that you deliver together? I'd love to get both of your perspectives. >> So, if you look at it, number one, customers look at it, last savings and their day-to-day operation. In 5G nature, we are talking the introduction of ORAN. This is still picking up. But there is a mutualization and densification of ORAN. And this is where we're talking on monetizing my deployment. Then the third phase, we're talking sustainability and advanced service introduction. Where I want to move not only ORAN, I want to bring the edge at the same side, I want to define the advanced use cases of edge, where it enables me with this pre-work being done to deliver more services and better SLA services. By end of the day, 5G as a girl mentioned earlier, is not about a good better phone coverage, or a better speed robot, but what customized SLA's I can deliver. So it enables me to deliver different business streams to my end users. >> Yeah. >> So yeah. I will say there are two pens. One, it's the technology side. So for an example, energy efficiency. It's a very big pin point. And sustainability. So we work a lot around this, and basically to advance this. So if you look at the integrated solution today, it's very highly optimized for resource consumption. But to be able to more dynamically be able to change your power profile without compromising the SLA. So this is one side. The other side, it's about all those applications that will come to the 5G network to make our life better. It's about integrating, validating, certifying those applications. So, it's not just easy to deploy an ORAN network, but it's easy to deploy those applications. >> I'd be curious to get your perspective on the question of ROI in this, in this space. Specifically with the sort of the macro headwinds (clears throat) the economies of the world are facing right now, if you accept that. What does the ROI timeline look like when you're talking about moving towards ORAN, adopting VRAN, an amazing, you know, a plethora of new services that can be delivered, but will these operators have the appetite to take that, make that investment and take on that risk based upon the ROI time horizon? Any thoughts on that? >> Yeah. So if you look at the early days or ORAN introduction in particular, most of the entrepreneurs of ORAN and Virtual RAN ran into the challenges of not only the complexity of open ecosystem, but the integration, is like the redos of the work. And that's where we are trying to address it via pre-engineered system or building an engineer system proactively before getting it to the customers. Per our result or outcomes we get, we are talking about 30 to 50% savings on the optics. We are talking 110 ROI for our customers, simply because we are reducing the redos, the time spent to discover and explore. Because we've done that rework ahead of time, we found the optimization issues. Just for example, any customer can buy the same components from any multiple vendors, but how I can bring them together and give, deliver for me the best performance that I can fully utilize, that's, that's where it brings the value for our customer, and accelerate the deployment and the operation of the network. >> Do you have anything to add before we close in the next 30 seconds? >> Yeah. Yeah. (laughs) >> Absolutely. I would say, we start to see the data coming from two years of operation at scale. And the data supports performance. It's the same or better than traditional system. And the cost of operation, it's as good or better than traditional. Unfortunately, I can't provide more specific data. But the point is, when something is unknown in the beginning, of course you're more afraid, you take more conservative approach. Now the data starts to flow. And from here, the intention needs to go even better. So more efficiency, so cost less than traditional system, both to operate as well as to build up. But it's definitely the data that we have today says, the, ORAN system is at part, at the minimum. >> So, definite ROI there. Guys, thank you so much for joining Dave and me talking about how you're helping organizations not just address the complexities of moving from close to open, but to your point, eliminating them. We appreciate your time and, and your insights. >> Thank you. >> All right. For our guests and for Dave Nicholson, I'm Lisa Martin. You're watching "theCUBE," the leader in live and emerging tech coverage. Live from MWC23. We'll be back after a short break. (outro music)

(cheerful music) >> Welcome to theCUBE's continuing coverage of AMD's 4th Generation EPYC launch. I'm Dave Nicholson, and I'm here in our Palo Alto studios talking to Greg Gibby, senior product manager, data center products from AMD, and Mohan Rokkam, technical marketing engineer at Dell. Welcome, gentlemen. >> Mohan: Hello, hello. >> Greg: Thank you. Glad to be here. >> Good to see each of you. Just really quickly, I want to start out. Let us know a little bit about yourselves. Mohan, let's start with you. What do you do at Dell exactly? >> So I'm a technical marketing engineer at Dell. I've been with Dell for around 15 years now and my goal is to really look at the Dell powered servers and see how do customers take advantage of some of the features we have, especially with the AMD EPYC processors that have just come out. >> Greg, and what do you do at AMD? >> Yeah, so I manage our software-defined infrastructure solutions team, and really it's a cradle to grave where we work with the ISVs in the market, so VMware, Nutanix, Microsoft, et cetera, to integrate the features that we're putting into our processors and make sure they're ready to go and enabled. And then we work with our valued partners like Dell on putting those into actual solutions that customers can buy and then we work with them to sell those solutions into the market. >> Before we get into the details on the 4th Generation EPYC launch and what that means and why people should care. Mohan, maybe you can tell us a little about the relationship between Dell and AMD, how that works, and then Greg, if you've got commentary on that afterwards, that'd be great. Yeah, Mohan. >> Absolutely. Dell and AMD have a long standing partnership, right? Especially now with EPYC series. We have had products since EPYC first generation. We have been doing solutions across the whole range of Dell ecosystem. We have integrated AMD quite thoroughly and effectively and we really love how performant these systems are. So, yeah. >> Dave: Greg, what are your thoughts? >> Yeah, I would say the other thing too is, is that we need to point out is that we both have really strong relationships across the entire ecosystem. So memory vendors, the software providers, et cetera, we have technical relationships. We're working with them to optimize solutions so that ultimately when the customer buys that, they get a great user experience right out of the box. >> So, Mohan, I know that you and your team do a lot of performance validation testing as time goes by. I suspect that you had early releases of the 4th Gen EPYC processor technology. What have you been seeing so far? What can you tell us? >> AMD has definitely knocked it out of the park. Time and again, in the past four generations, in the past five years alone, we have done some database work where in five years, we have seen five exit performance. And across the board, AMD is the leader in benchmarks. We have done virtualization where we would consolidate from five into one system. We have world records in AI, we have world records in databases, we have world records in virtualization. The AMD EPYC solutions has been absolutely performant. I'll leave you with one number here. When we went from top of Stack Milan to top of Stack Genoa, we saw a performance bump of 120%. And that number just blew my mind. >> So that prompts a question for Greg. Often we, in industry insiders, think in terms of performance gains over the last generation or the current generation. A lot of customers in the real world, however, are N - 2. They're a ways back, so I guess two points on that. First of all, the kinds of increases the average person is going to see when they move to this architecture, correct me if I'm wrong, but it's even more significant than a lot of the headline numbers because they're moving two generations, number one. Correct me if I'm wrong on that, but then the other thing is the question to you, Greg. I like very long complicated questions, as you can tell. The question is, is it okay for people to skip generations or make the case for upgrades, I guess is the problem? >> Well, yeah, so a couple thoughts on that first too. Mohan talked about that five X over the generation improvements that we've seen. The other key point with that too is that we've made significant process improvements along the way moving to seven nanocomputer to now five nanocomputer and that's really reducing the total amount of power or the performance per watt the customers can realize as well. And when we look at why would a customer want to upgrade, right? And I want to rephrase that as to why aren't you? And there is a real cost of not upgrading. And so when you look at infrastructure, the average age of a server in the data center is over five years old. And if you look at the most popular processors that were sold in that timeframe, it's 8, 10, 12 cores. So now you've got a bunch of servers that you need in order to deliver the applications and meet your SLAs to your end users, and all those servers pull power. They require maintenance. They have the opportunity to go down, et cetera. You got to pay licensing and service and support costs and all those. And when you look at all the costs that roll up, even though the hardware is paid for just to keep the lights on, and not even talking about the soft costs of unplanned downtime, and, "I'm not meeting your SLAs," et cetera, it's very expensive to keep those servers running. Now, if you refresh, and now you have processors that have 32, 64, 96 cores, now you can consolidate that infrastructure and reduce your total power bill. You can reduce your CapEx, you reduce your ongoing OpEx, you improve your performance, and you improve your security profile. So it really is more cost effective to refresh than not to refresh. >> So, Mohan, what has your experience been double clicking on this topic of consolidation? I know that we're going to talk about virtualization in some of the results that you've seen. What have you seen in that regard? Does this favor better consolidation and virtualized environments? And are you both assuring us that the ROI and TCO pencil out on these new big, bad machines? >> Greg definitely hit the nail on the head, right? We are seeing tremendous savings really, if you're consolidating from two generations old. We went from, as I said, five is to one. You're going from five full servers, probably paid off down to one single server. That itself is, if you look at licensing costs, which again, with things like VMware does get pretty expensive. If you move to a single system, yes, we are at 32, 64, 96 cores, but if you compare to the licensing costs of 10 cores, two sockets, that's still pretty significant, right? That's one huge thing. Another thing which actually really drives the thing is we are looking at security, and in today's environment, security becomes a major driving factor for upgrades. Dell has its own setups, cyber-resilient architecture, as we call it, and that really is integrated from processor all the way up into the OS. And those are some of the features which customers really can take advantage of and help protect their ecosystems. >> So what kinds of virtualized environments did you test? >> We have done virtualization across primary codes with VMware, but the Azure Stack, we have looked at Nutanix. PowerFlex is another one within Dell. We have vSAN Ready Nodes. All of these, OpenShift, we have a broad variety of solutions from Dell and AMD really fits into almost every one of them very well. >> So where does hyper-converged infrastructure fit into this puzzle? We can think of a server as something that contains not only AMD's latest architecture but also latest PCIe bus technology and all of the faster memory, faster storage cards, faster nicks, all of that comes together. But how does that play out in Dell's hyper-converged infrastructure or HCI strategy? >> Dell is a leader in hyper-converged infrastructure. We have the very popular VxRail line, we have the PowerFlex, which is now going into the AWS ecosystem as well, Nutanix, and of course, Azure Stack. With all these, when you look at AMD, we have up to 96 cores coming in. We have PCIe Gen 5 which means you can now connect dual port, 100 and 200 gig nicks and get line rate on those so you can connect to your ecosystem. And I don't know if you've seen the news, 200, 400 gig routers and switchers are selling out. That's not slowing down. The network infrastructure is booming. If you want to look at the AI/ML side of things, the VDI side of things, accelerator cards are becoming more and more powerful, more and more popular. And of course they need that higher end data path that PCIe Gen 5 brings to the table. GDDR5 is another huge improvement in terms of performance and latencies. So when we take all this together, you talk about hyper-converged, all of them add into making sure that A, with hyper-converged, you get ease of management, but B, just 'cause you have ease of management doesn't mean you need to compromise on anything. And the AMD servers effectively are a no compromise offering that we at Dell are able to offer to our customers. >> So Greg, I've got a question a little bit from left field for you. We covered Supercompute Conference 2022. We were in Dallas a couple of weeks ago, and there was a lot of discussion of the current processor manufacturer battles, and a lot of buzz around 4th Gen EPYC being launched and what's coming over the next year. Do you have any thoughts on what this architecture can deliver for us in terms of things like AI? We talk about virtualization, but if you look out over the next year, do you see this kind of architecture driving significant change in the world? >> Yeah, yeah, yeah, yeah. It has the real potential to do that from just the building blocks. So we have our chiplet architecture we call it. So you have an IO die and then you have your core complexes that go around that. And we integrate it all with our infinity fabric. That architecture allows you, if we wanted to, replace some of those CCDs with specific accelerators. And so when we look two, three, four years down the road, that architecture and that capability already built into what we're delivering and can easily be moved in. We just need to make sure that when you look at doing that, that the power that's required to do that and the software, et cetera, and those accelerators actually deliver better performance as a dedicated engine versus just using standard CPUs. The other things that I would say too is if you look at emerging workloads. So data center modernization is one of the buzzwords in cloud native, right? And these container environments, well, AMD'S architecture really just screams support for those type of environments, right? Where when you get into these larger core accounts and the consolidation that Mohan talked about. Now when I'm in a container environment, that blast radius so a lot of customers have concerns around, "Hey, having a single point of failure and having more than X number of cores concerns me." If I'm in containers, that becomes less of a concern. And so when you look at cloud native, containerized applications, data center modernization, AMD's extremely well positioned to take advantage of those use cases as well. >> Yeah, Mohan, and when we talk about virtualization, I think sometimes we have to remind everyone that yeah, we're talking about not only virtualization that has a full-blown operating system in the bucket, but also virtualization where the containers have microservices and things like that. I think you had something to add, Mohan. >> I did, and I think going back to the accelerator side of business, right? When we are looking at the current technology and looking at accelerators, AMD has done a fantastic job of adding in features like AVX-512, we have the bfloat16 and eight features. And some of what these do is they're effectively built-in accelerators for certain workloads especially in the AI and media spaces. And in some of these use cases we look at, for example, are inference. Traditionally we have used external accelerator cards, but for some of the entry level and mid-level use cases, CPU is going to work just fine especially with the newer CPUs that we are seeing this fantastic performance from. The accelerators just help get us to the point where if I'm at the edge, if I'm in certain use cases, I don't need to have an accelerator in there. I can run most of my inference workloads right on the CPU. >> Yeah, yeah. You know the game. It's an endless chase to find the bottleneck. And once we've solved the puzzle, we've created a bottleneck somewhere else. Back to the supercompute conversations we had, specifically about some of the AMD EPYC processor technology and the way that Dell is packaging it up and leveraging things like connectivity. That was one of the things that was also highlighted. This idea that increasingly connectivity is critically important, not just for supercomputing, but for high-performance computing that's finding its way out of the realms of Los Alamos and down to the enterprise level. Gentlemen, any more thoughts about the partnership or maybe a hint at what's coming in the future? I know that the original AMD announcement was announcing and previewing some things that are rolling out over the next several months. So let me just toss it to Greg. What are we going to see in 2023 in terms of rollouts that you can share with us? >> That I can share with you? Yeah, so I think look forward to see more advancements in the technology at the core level. I think we've already announced our product code name Bergamo, where we'll have up to 128 cores per socket. And then as we look in, how do we continually address this demand for data, this demand for, I need actionable insights immediately, look for us to continue to drive performance leadership in our products that are coming out and address specific workloads and accelerators where appropriate and where we see a growing market. >> Mohan, final thoughts. >> On the Dell side, of course, we have four very rich and configurable options with AMD EPYC servers. But beyond that, you'll see a lot more solutions. Some of what Greg has been talking about around the next generation of processors or the next updated processors, you'll start seeing some of those. and you'll definitely see more use cases from us and how customers can implement them and take advantage of the features that. It's just exciting stuff. >> Exciting stuff indeed. Gentlemen, we have a great year ahead of us. As we approach possibly the holiday seasons, I wish both of you well. Thank you for joining us. From here in the Palo Alto studios, again, Dave Nicholson here. Stay tuned for our continuing coverage of AMD's 4th Generation EPYC launch. Thanks for joining us. (cheerful music)

>> Voice Over: From around the globe. It's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Okay. Welcome back everyone. To theCUBE's coverage of IBM Think 2021 virtual. I'm John Furrier, host of theCUBE. We've got a great segment here on the power of hybrid cloud and AI. And I'm excited to have Rob Thomas, Senior Vice President of IBM's cloud and Data platform, CUBE alumni. Been on going back years and years talking about data. Rob, great to see you, a leader at IBM. Thanks for joining. >> John. Great to see you hope everybody is safe and well and great to be with you again. >> Yeah, love the progress, love the Hybrid Cloud distributed computing, meets operating systems, meets modern applications at the center of it is the new cloud equation. And of course data continues to be the value proposition as the platform. And as you quoted many times and I love your favorite quote. There's no AI without IA. So you got to have the architecture. So that still rings true today and it's just so evergreen and so relevant and cooler than ever with machine learning and AI operations. So let's just jump in. IBM's announced, host a new products and updates at Think. Tell us what you're most excited about and what should people pay attention to. >> Maybe I'll connect two thoughts here. There is no AI without IA, still true today. Meaning, customers that want to do AI need an information architecture. There was an IDC report just last year that said, "Despite all the progress on data, still 90% of data in organizations is either unused or underutilized." So what's amazing is after all the time we've been talking John, we're still really just getting started. Then that kind of connects to another thought, which is I still believe that AI is not going to replace managers, but managers that use AI will replace the managers that do not. And I'd say that's the backdrop for all the announcements that we're doing this week. It's things like auto SQL. How do you actually automate the creation of SQL queries in a large distributed data warehouse? It's never been done before, now we're doing it. It's things like Watson Orchestrate which is super powers in the hands of any business user, just to ask for something to get done. Just ask for a task to get completed. Watson Orchestrator will do that for you. It's maximo mobile. So anybody working in the field now has access to an AI system on their device for how they're managing their assets. So this is all about empowering people and users that use these products are going to have an advantage over the users that are not, that's what I'm really excited about. >> So one of the things that's coming out as Cloud Pak for Data, AI powered automation these are kind of two that you kind of touched upon the SQL thing their. Cloud Pak is there, you got it for Data and this automation trend. What is that about? Why is it important? Can you share with us the relevance of those two things? >> Let's talk broadly about automation. There's two huge markets here. There's the market for RPA business process, $30 billion market. There's the market for AIOps, which is growing 22%, that's on its way to $40 billion. These are enormous markets. Probably the biggest bet IBM has made in the last year is in automation. Explicitly in Watson AIOps. Last June in Think we announced Watson AIOps, then we did the acquisition of Instana, then we announced our intent to acquire Turbonomic. At this point, we're the only company that has all the pieces for automating how you run your IT systems. That's what I mean when I say AIOps. So really pleased with the progress that we've made there. But again, we're just getting started. >> Yeah. Congratulations on the Turbonomic. I was just commenting on that when that announced. IBM buying into the Cloud and the Hybrid cloud is interesting because the shift has happened. It's Public Cloud, it's on premises as Edge. Those two things as a system, it's more important ever than the modernization of the apps that you guys are talking about and having the under the cover capabilities. So as Cloud and Data merge, this kind of control plane concept, this architecture, as you'd said IA. You can't have AI without IA. What is that architecture look like? Can you break down the elements of what's involved? I know there's predictive analytics, there's automation and security. What are the pillars of this architecture? What are the four concepts? If you can explain that. >> Yeah, let's start with the basics. So Hybrid Cloud is about you build your software runs once and you run it anywhere you want, any public cloud,any private cloud. That assumes containers are important to the future of software. We are a hundred percent convinced that is true. OpenShift is the platform that we build on and that many software companies in the world are now building on because it gives you portability for your applications. So then you start to think about if you have that common fabric for Hybrid Cloud, how do you deliver value to customers in addition to the platform? To me, that's four big things. It's automation, we talked about that. It's security, it's predictions. How do you actually make predictions on your data? And then it's modernization. Meaning, how do you actually help customers modernize their applications and get to the Cloud? So those are the things we always talk about, automate, secure, modernize, predict. I think those are the four most important things for every company that's thinking about Cloud and AI. >> Yeah, it's interesting. I love the security side is one of the big conversations in AIOps and day two operations or whatever it's called is shifting left, getting security into the Cloud native kind of development pipeline. But speaking of secure, you have a customer that was talking about this Dow Chemical. About IB empowering Dow zero trust architecture. Could you explain that deal and how that's working? Because that's again, huge enterprise customer, very big scale at scale, zero trust is big, part of it. What is this? >> Let's start with the basics. So what is zero trust mean? It means to have a secure business, you have to start with the assumption that nothing can be trusted. That means you have to think about all aspects of your security practice. How do you align on a security strategy? How do you protect your data assets? How do you manage security threats? So we always talk about a line, protect, manage back to modernize, which is how do you bring all your systems forward to do this? That's exactly what we're doing with the Dow as you heard in that session, which is they've kind of done that whole journey from how they built a security strategy that was designed with zero trust in mind, they're protecting data assets, they're managing cyber threats in real time with a relatively low number of false positives which are the issue that most companies have. They're a tremendous example of a company that jumped on this and has had a really big impact. And they've done it without interfering with their business operations, meaning anybody can lock everything down but then you can't really run your business if you're doing that. They've done it, I think in a really intelligent way. >> That's awesome. We always talk about the big waves. You always give great color commentary on the trends. Right now though, the tsunami seems to be a confluence of many things coming together. What are some of the big trends in waves you're seeing now specifically on the tech side, on the technology side, as well as the business side right now? 'Cause coming out of post COVID, it's pretty clear cloud-native is powering a new growth strategy for customers. Dow was one of them, you just commented on it but there's a bigger wave happening here, both on the tech theater and in the business theater. Can you share your views on and your opinions and envision on these trends? >> I think there's three profound trends that are actually pretty simple to understand. One is, technology is going to decentralize again. We've always gone from centralized architectures to decentralized. Mainframe was centralized, internet mobile decentralized. The first version of public cloud was centralized, meaning bringing everything to one place. Technology is decentralized and again, with Hybrid Cloud, with Edge, pretty straight forward I think that's a trend that we can ride and lead for the next decade. Next is around automation that we talked about. There was a McKinsey report that said, "120 billion hours a year are going to be automated with things like Watson Orchestrator, Watson AIOps." What we're doing around Cloud Pak for automation, we think that time is now. We think you can start to automate in your business today and you may have seen the--example where we're doing customer care and they're now automating 70% of their inbound customer inquiries. It's really amazing. And then the third is around data. The classical problem, I mentioned 90% is still unused or underutilized. This trend on data is not about to slow down because the data being collected is still multiplying 10 X every year and companies have to find a way to organize that data as they collected. So that's going to be a trend that continues. >> You know, I just kind of pinched myself sometimes and hearing you talk with some of our earlier conversations in theCUBE, people who have been on this data mindset have really been successful because it's evolving and growing and it's changing and it's adding more input into the system and the technology is getting better. There's more cloud scales. You mentioned automation and scale are huge. And I think this really kind of wakes everyone up. And certainly the pandemic has woken everyone up to the fact that this is driving new experiences for users and businesses, right? So this is, and then those experiences become expectations. This is the classic UX paradigm that grows from new things. So I got to ask you, with the pandemic what is the been the most compelling ways you seen people operate, create new expectations? Because new things are coming, new big things, and new incremental things are happening. So evolution and revolutionary capabilities. Can you share some examples and your thoughts? >> We've collected a decent bit of data on this. And what's interesting is how much AI has accelerated since the pandemic started. And it's really in five areas, it's customer care that we talked about, virtual agents, customer service, how you do that. It's employee experience. So somewhere to customer care but how do you take care of your employees using AI? Third is around AIOps, we talked about that. Fourth is around regulatory compliance and fifth is around financial planning and budgeting. These are the five major use cases of AI that are getting into production in companies over the last year that's going to continue to accelerate. So I think it's actually fairly clarifying now that we really understand these are the five big things. I encourage anybody watching, pick one of these, get started, then pick the second, then pick the third. If you are not doing all five of these, 12, 18, 24 months from now, you are going to be behind. >> So give us an example of some things that have surprised you in the pandemic and things that blew you away. Like, wow, I didn't see that coming. Can you share on things that you've seen evolve? Cause you're a year ahead of the business units of Cloud and Data, big part of IBM and you see customer examples. Just quickly share some notable use cases or just anecdotal examples of just things that jumped out at you that said, "Wow, that's going to be a double-down moment or that's not going to be anymore." Exposes, the pandemic exposes the good, bad and the ugly. I mean, people got caught off guard, some got a tailwind, some had a headwind, some are retooling. What's your thoughts on what you can you share any examples? >> Like everybody, many things have surprised me in the last year. I am encouraged at how fast many companies were able to adjust and adapt for this world. So that's a credit to all the resiliency that they built into their processes, their systems and their people over time. Related to that, the thing that really sticks out to me again, is this idea of using AI to serve your customers and to serve your employees. We had a hundred customers that went live with one of those two use cases in the first 35 days of the pandemic. Just think about that acceleration. I think without the pandemic, for those hundred it might've taken three years and it happened in 35 days. It's proof that the technology today is so powerful. Sometimes it just takes the initiative to get started and to do something. And all those companies have really benefited from this. So it's great to see. >> Great. Rob, great to have you on. Great to have your commentary on theCUBE. Could you just quickly share in 30 seconds, what is the most important thing people should pay attention to and Think this year from your perspective? What's the big aha moment that you think they could walk away with? >> We have intentionally made this a very technology centric event. Just go look at the demos, play with the technology. I think you will be impressed and start to see, let's say a bit of a new IBM in terms of how we're making technology accessible and easy for anybody to use. >> All right. Rob Thomas, Senior Vice President of IBM cloud and Data platform. Great to have you on and looking forward to seeing more of you this year and hopefully in person. Thanks for coming on theCUBE virtual. >> Thanks, John. >> Okay. I'm John Furrier with theCUBE. Keep coverage of IBM Think 2021. Thank you for watching. (soft music)

(soft music) >> Voice Over: From around the globe. It's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Okay. Welcome back everyone. To theCUBE's coverage of IBM Think 2021 virtual. I'm John Furrier, host of theCUBE. We've got a great segment here on the power of hybrid cloud and AI. And I'm excited to have Rob Thomas, Senior Vice President of IBM's cloud and Data platform, CUBE alumni. Been on going back years and years talking about data. Rob, great to see you, a leader at IBM. Thanks for joining. >> John. Great to see you hope everybody is safe and well and great to be with you again. >> Yeah, love the progress, love the Hybrid Cloud distributed computing, meets operating systems, meets modern applications at the center of it is the new cloud equation. And of course data continues to be the value proposition as the platform. And as you quoted many times and I love your favorite quote. There's no AI without IA. So you got to have the architecture. So that still rings true today and it's just so evergreen and so relevant and cooler than ever with machine learning and AI operations. So let's just jump in. IBM's announced, host a new products and updates at Think. Tell us what you're most excited about and what should people pay attention to. >> Maybe I'll connect two thoughts here. There is no AI without IA, still true today. Meaning, customers that want to do AI need an information architecture. There was an IDC report just last year that said, "Despite all the progress on data, still 90% of data in organizations is either unused or underutilized." So what's amazing is after all the time we've been talking John, we're still really just getting started. Then that kind of connects to another thought, which is I still believe that AI is not going to replace managers, but managers that use AI will replace the managers that do not. And I'd say that's the backdrop for all the announcements that we're doing this week. It's things like auto SQL. How do you actually automate the creation of SQL queries in a large distributed data warehouse? It's never been done before, now we're doing it. It's things like Watson Orchestrate which is super powers in the hands of any business user, just to ask for something to get done. Just ask for a task to get completed. Watson Orchestrator will do that for you. It's Maximo Mbo. So anybody working in the field now has access to an AI system on their device for how they're managing their assets. So this is all about empowering people and users that use these products are going to have an advantage over the users that are not, that's what I'm really excited about. >> So one of the things that's coming out as Cloud Pak for Data, AI powered automation these are kind of two that you kind of touched upon the SQL thing their. Cloud Pak is there, you got it for Data and this automation trend. What is that about? Why is it important? Can you share with us the relevance of those two things? >> Let's talk broadly about automation. There's two huge markets here. There's the market for RPA business process, $30 billion market. There's the market for AIOps, which is growing 22%, that's on its way to $40 billion. These are enormous markets. Probably the biggest bet IBM has made in the last year is in automation. Explicitly in Watson AIOps. Last June in Think we announced Watson AIOps, then we did the acquisition of Instana, then we announced our intent to acquire Turbonomic. At this point, we're the only company that has all the pieces for automating how you run your IT systems. That's what I mean when I say AIOps. So really pleased with the progress that we've made there. But again, we're just getting started. >> Yeah. Congratulations on the Turbonomic. I was just commenting on that when that announced. IBM buying into the Cloud and the Hybrid cloud is interesting because the shift has happened. It's Public Cloud, it's on premises as Edge. Those two things as a system, it's more important ever than the modernization of the apps that you guys are talking about and having the under the cover capabilities. So as Cloud and Data merge, this kind of control plane concept, this architecture, as you'd said IA. You can't have AI without IA. What is that architecture look like? Can you break down the elements of what's involved? I know there's predictive analytics, there's automation and security. What are the pillars of this architecture? What are the four concepts? If you can explain that. >> Yeah, let's start with the basics. So Hybrid Cloud is about you build your software runs once and you run it anywhere you want, any public cloud,any private cloud. That assumes containers are important to the future of software. We are a hundred percent convinced that is true. OpenShift is the platform that we build on and that many software companies in the world are now building on because it gives you portability for your applications. So then you start to think about if you have that common fabric for Hybrid Cloud, how do you deliver value to customers in addition to the platform? To me, that's four big things. It's automation, we talked about that. It's security, it's predictions. How do you actually make predictions on your data? And then it's modernization. Meaning, how do you actually help customers modernize their applications and get to the Cloud? So those are the things we always talk about, automate, secure, modernize, predict. I think those are the four most important things for every company that's thinking about Cloud and AI. >> Yeah, it's interesting. I love the security side is one of the big conversations in AIOps and day two operations or whatever it's called is shifting left, getting security into the Cloud native kind of development pipeline. But speaking of secure, you have a customer that was talking about this Dow Chemical. About IB empowering Dow zero trust architecture. Could you explain that deal and how that's working? Because that's again, huge enterprise customer, very big scale at scale, zero trust is big, part of it. What is this? >> Let's start with the basics. So what is zero trust mean? It means to have a secure business, you have to start with the assumption that nothing can be trusted. That means you have to think about all aspects of your security practice. How do you align on a security strategy? How do you protect your data assets? How do you manage security threats? So we always talk about a line, protect, manage back to modernize, which is how do you bring all your systems forward to do this? That's exactly what we're doing with the Dow as you heard in that session, which is they've kind of done that whole journey from how they built a security strategy that was designed with zero trust in mind, they're protecting data assets, they're managing cyber threats in real time with a relatively low number of false positives which are the issue that most companies have. They're a tremendous example of a company that jumped on this and has had a really big impact. And they've done it without interfering with their business operations, meaning anybody can lock everything down but then you can't really run your business if you're doing that. They've done it, I think in a really intelligent way. >> That's awesome. We always talk about the big waves. You always give great color commentary on the trends. Right now though, the tsunami seems to be a confluence of many things coming together. What are some of the big trends in waves you're seeing now specifically on the tech side, on the technology side, as well as the business side right now? 'Cause coming out of post COVID, it's pretty clear cloud-native is powering a new growth strategy for customers. Dow was one of them, you just commented on it but there's a bigger wave happening here, both on the tech theater and in the business theater. Can you share your views on and your opinions and envision on these trends? >> I think there's three profound trends that are actually pretty simple to understand. One is, technology is going to decentralize again. We've always gone from centralized architectures to decentralized. Mainframe was centralized, internet mobile decentralized. The first version of public cloud was centralized, meaning bringing everything to one place. Technology is decentralized and again, with Hybrid Cloud, with Edge, pretty straight forward I think that's a trend that we can ride and lead for the next decade. Next is around automation that we talked about. There was a McKinsey report that said, "120 billion hours a year are going to be automated with things like Watson Orchestrator, Watson AIOps." What we're doing around Cloud Pak for automation, we think that time is now. We think you can start to automate in your business today and you may have seen the C QVS example where we're doing customer care and they're now automating 70% of their inbound customer inquiries. It's really amazing. And then the third is around data. The classical problem, I mentioned 90% is still unused or underutilized. This trend on data is not about the slow down because the data being collected is still multiplying 10 X every year and companies have to find a way to organize that data as they collected. So that's going to be a trend that continues. >> You know, I just kind of pinched myself sometimes and hearing you talk with some of our earlier conversations in theCUBE, people who have been on this data mindset have really been successful because it's evolving and growing and it's changing and it's adding more input into the system and the technology is getting better. There's more cloud scales. You mentioned automation and scale are huge. And I think this really kind of wakes everyone up. And certainly the pandemic has woken everyone up to the fact that this is driving new experiences for users and businesses, right? So this is, and then those experiences become expectations. This is the classic UX paradigm that grows from new things. So I got to ask you, with the pandemic what is the been the most compelling ways you seen people operate, create new expectations? Because new things are coming, new big things, and new incremental things are happening. So evolution and revolutionary capabilities. Can you share some examples and your thoughts? >> We've collected a decent bit of data on this. And what's interesting is how much AI has accelerated since the pandemic started. And it's really in five areas, it's customer care that we talked about, virtual agents, customer service, how you do that. It's employee experience. So somewhere to customer care but how do you take care of your employees using AI? Third is around AIOps, we talked about that. Fourth is around regulatory compliance and fifth is around financial planning and budgeting. These are the five major use cases of AI that are getting into production in companies over the last year that's going to continue to accelerate. So I think it's actually fairly clarifying now that we really understand these are the five big things. I encourage anybody watching, pick one of these, get started, then pick the second, then pick the third. If you are not doing all five of these, 12, 18, 24 months from now, you are going to be behind. >> So give us an example of some things that have surprised you in the pandemic and things that blew you away. Like, wow, I didn't see that coming. Can you share on things that you've seen evolve? Cause you're a year ahead of the business units of Cloud and Data, big part of IBM and you see customer examples. Just quickly share some notable use cases or just anecdotal examples of just things that jumped out at you that said, "Wow, that's going to be a double-down moment or that's not going to be anymore." Exposes, the pandemic exposes the good, bad and the ugly. I mean, people got caught off guard, some got a tailwind, some had a headwind, some are retooling. What's your thoughts on what you can you share any examples? >> Like everybody, many things have surprised me in the last year. I am encouraged at how fast many companies were able to adjust and adapt for this world. So that's a credit to all the resiliency that they built into their processes, their systems and their people over time. Related to that, the thing that really sticks out to me again, is this idea of using AI to serve your customers and to serve your employees. We had a hundred customers that went live with one of those two use cases in the first 35 days of the pandemic. Just think about that acceleration. I think without the pandemic, for those hundred it might've taken three years and it happened in 35 days. It's proof that the technology today is so powerful. Sometimes it just takes the initiative to get started and to do something. And all those companies have really benefited from this. So it's great to see. >> Great. Rob, great to have you on. Great to have your commentary on theCUBE. Could you just quickly share in 30 seconds, what is the most important thing people should pay attention to and Think this year from your perspective? What's the big aha moment that you think they could walk away with? >> We have intentionally made this a very technology centric event. Just go look at the demos, play with the technology. I think you will be impressed and start to see, let's say a bit of a new IBM in terms of how we're making technology accessible and easy for anybody to use. >> All right. Rob Thomas, Senior Vice President of IBM cloud and Data platform. Great to have you on and looking forward to seeing more of you this year and hopefully in person. Thanks for coming on theCUBE virtual. >> Thanks, John. >> Okay. I'm John Furrier with theCUBE. Keep coverage of IBM Think 2021. Thank you for watching. (soft music)

>>Hello everybody. I am Toshihiko Nishimura from Stanford. University is there to TTT out here, super aging, global OMIM global transportation group about infections, uh, or major point of concerns. In addition, this year, we have the COVID-19 pandemic. As you can see here, while the why the new COVID-19 patients are still increasing, meanwhile, case count per day in the United state, uh, beginning to decrease this pandemic has changed our daily life to digital transformation. Even today, the micro segmentation is being conducted online and doctor and the nurse care, uh, now increase to telemedicine. Likewise, the drug development process is in need of major change paradigm shift, especially in vaccine in drug development for COVID-19 is, should be safe, effective, and faster >>In the >>Anastasia department, which is the biggest department in school of medicine. We have Stanford, a love for drug device development, regulatory science. So cold. Say the DDT RDS chairman is Ron Paul and this love leaderships are long mysel and stable shaper. In the drug development. We have three major pains, one exceedingly long duration that just 20 years huge budget, very low success rate general overview in the drug development. There are Discoverly but clinical clinical stage, as you see here, Tang. Yes. In clinical stage where we sit, say, what are the programs in D D D R S in each stages or mix program? Single cell programs, big data machine learning, deep learning, AI mathematics, statistics programs, humanized animal, the program SNS program engineering program. And we have annual symposium. Today's the, my talk, I do like to explain limitation of my science significance of humanized. My science out of separate out a program. I focused on humanized program. I believe this program is potent game changer for drug development mouse. When we think of animal experiment, many people think of immediately mouse. We have more than 30 kinds of inbred while the type such as chief 57, black KK yarrow, barber C white and so on using QA QC defined. Why did the type mice 18 of them gave him only one intervention using mouse, genomics analyzed, computational genetics. And then we succeeded to pick up fish one single gene in a week. >>We have another category of gene manipulated, mice transgenic, no clout, no Kamal's group. So far registered 40,000 kind as over today. Pretty critical requirement. Wrong FDA PMDA negative three sites are based on arteries. Two kinds of animal models, showing safety efficacy, combination of two animals and motel our mouse and the swine mouse and non-human primate. And so on mouse. Oh, Barry popular. Why? Because mouse are small enough, easy to handle big database we had and cost effective. However, it calls that low success rate. Why >>It, this issue speculation, low success rate came from a gap between preclinical the POC and the POC couldn't stay. Father divided into phase one. Phase two has the city FDA unsolved to our question. Speculation in nature biology using 7,372 new submissions, they found a 68 significant cradle out crazy too, to study approved by the process. And in total 90 per cent Radia in the clinical stages. What we can surmise from this study, FDA confirmed is that the big discrepancy between POC and clinical POC in another ward, any amount of data well, Ms. Representative for human, this nature bio report impacted our work significantly. >>What is a solution for this discrepancy? FDA standards require the people data from two species. One species is usually mice, but if the reported 90% in a preclinical data, then huge discrepancy between pretty critical POC in clinical POC. Our interpretation is data from mice, sometime representative, actually mice, and the humor of different especially immune system and the diva mice liver enzyme are missing, which human Liba has. This is one huge issue to be taught to overcome this problem. We started humanized mice program. What kind of human animals? We created one humanized, immune mice. The other is human eyes, DBA, mice. What is the definition of a humanized mice? They should have human gene or human cells or human tissues or human organs. Well, let me share one preclinical stages. Example of a humanized mouse that is polio receptor mice. This problem led by who was my mentor? Polio virus. Well, polio virus vaccine usually required no human primate to test in 13 years, collaboration with the FDA w H O polio eradication program. Finally FDA well as w H O R Purdue due to the place no human primate test to transgenic PVL. This is three. Our principle led by loss around the botch >>To move before this humanized mouse program, we need two other bonds donut outside your science, as well as the CPN mouse science >>human hormone, like GM CSF, Whoah, GCSF producing or human cytokine. those producing emoji mice are required in the long run. Two maintain human cells in their body under generation here, South the generation here, Dr. already created more than 100 kinds based on Z. The 100 kinds of Noe mice, we succeeded to create the human immune mice led the blood. The cell quite about the cell platelets are beautifully constituted in an mice, human and rebar MAs also succeeded to create using deparent human base. We have AGN diva, humanized mouse, American African human nine-thirty by mice co-case kitchen, humanized mice. These are Hennessy humanized, the immune and rebar model. On the other hand, we created disease rebar human either must to one example, congenital Liba disease, our guidance Schindel on patient model. >>The other model, we have infectious DDS and Waddell council Modell and GVH Modell. And so on creature stage or phase can a human itemize apply. Our objective is any stage. Any phase would be to, to propose. We propose experiment, pose a compound, which showed a huge discrepancy between. If Y you show the huge discrepancy, if Y is lucrative analog and the potent anti hepatitis B candidate in that predict clinical stage, it didn't show any toxicity in mice got dark and no human primate. On the other hand, weighing into clinical stage and crazy to October 15, salvage, five of people died and other 10 the show to very severe condition. >>Is that the reason why Nicole traditional the mice model is that throughout this, another mice Modell did not predict this severe side outcome. Why Zack humanized mouse, the Debar Modell demonstrate itself? Yes. Within few days that chemistry data and the puzzle physiology data phase two and phase the city requires huge number of a human subject. For example, COVID-19 vaccine development by Pfizer, AstraZeneca Moderna today, they are sample size are Southeast thousand vaccine development for COVID-19. She Novak UConn in China books for the us Erica Jones on the Johnson in unite United Kingdom. Well, there are now no box us Osaka Osaka, university hundred Japan. They are already in phase two industry discovery and predict clinical and regulatory stage foster in-app. However, clinical stage is a studious role because that phases required hugely number or the human subject 9,000 to 30,000. Even my conclusion, a humanized mouse model shortens the duration of drug development humanize, and most Isabel, uh, can be increase the success rate of drug development. Thank you for Ron Paul and to Steven YALI pelt at Stanford and and his team and or other colleagues. Thank you for listening.

>>Okay, >>listen, we're gearing up for the start of the snowflake Data Cloud Summit, and we wanna go back to the early roots of Snowflake. We've got some of the founding engineers here. Abdul Monir, Ashish Motive, Allah and Alison Lee There three individuals that were at snowflake in the early years and participated in many of the technical decisions that led to the platform and is making snowflake famous today. Folks, great to see you. Thanks so much for taking some time out of your busy schedules. Hey, it's gotta be really gratifying. Thio, See this platform that you've built, you know, taking off and changing businesses. So I'm sure it was always smooth sailing. Right? There were. There were no debates. Wherever. >>I've never seen an engineer get into the bed. >>Alright, So seriously so take us back to the early days. You guys, you know, choose whoever wants to start. But what was it like early on? We're talking 2013 here, right? >>When I think back to the early days of Snowflake, I just think of all of us sitting in one room at the time. You know, we just had an office that was one room with, you know, 12 or 13 engineers sitting there clacking away on our keyboards, uh, working really hard, turning out code, uh, punctuated by you know, somebody asking a question about Hey, what should we do about this, or what should we do about that? And then everyone kind of looking up from their keyboards and getting into discussions and debates about the work that we're doing. >>So so Abdul it was just kind of heads down headphones on, just coating or e think there was >>a lot of talking and followed by a lot of typing. Andi, I think there were periods of time where where you know, anyone could just walk in into the office and probably out of the office and all the here is probably people, uh, typing away at their keyboards. And one of my member vivid, most vivid memories is actually I used to sit right across from Alison, and there's these huge to two huge monitor monitors between us and I would just here typing away in our keyboard, and sometimes I was thinking and and and, uh and all that type and got me nervous because it seemed like Alison knew exactly what what, what she needed to do, and I was just still thinking about it. >>So she she was just like bliss for for you as a developer engineer was it was a stressful time. What was the mood? So when you don't have >>a whole lot of customers, there's a lot of bliss. But at the same time, there was a lot of pressure on us to make sure that we build the product. There was a time line ahead of us. We knew we had to build this in a certain time frame. Um, so one thing I'll add to what Alison and Abdulle said is we did a lot of white boarding as well. There are a lot of discussions, and those discussions were a lot of fun. They actually cemented what we wanted to build. They made sure everyone was in tune, and and there we have it. >>Yes, so I mean, it is a really exciting time doing any start up. But when you know when you have to make decisions and development, invariably you come to a fork in the road. So I'm curious as to what some of those forks might have been. How you guys decided You know which fork to take. Was there a Yoda in the room that served as the Jedi master? I mean, how are those decisions made? Maybe you could talk about that a little bit. >>Yeah, that's an interesting question. And I think one of a Zai think back. One of the memories that that sticks out in my mind is is this, uh, epic meeting and one of our conference rooms called Northstar. Many of our conference rooms are named after ski resorts because the founders, they're really into skiing. And that's why that's where the snowflake name comes from. So there was this epic meeting and I'm not even sure exactly what topic we were discussing. I think it was It was the sign up flow and and there were a few different options on the table and and and one of the options that that people were gravitating Teoh, one of the founders, didn't like it and and on, and they said a few times that there's this makes no sense. There's no other system in the world that does it this way, and and I think one of the other founders said, uh, that's exactly why we should do it this way. And or at least seriously, consider this option. So I think there was always this, um, this this, uh, this tendency and and and this impulse that that we needed to think big and think differently and and not see the world the way it is but the way we wanted it to be and then work our way backwards and try to make it happen. >>Alison, Any fork in the road moments that you remember. >>Well, I'm just thinking back to a really early meeting with sheesh! And and a few of our founders where we're debating something probably not super exciting to a lot of people outside of hardcore database people, which was how to represent our our column metadata. Andi, I think it's funny that you that you mentioned Yoda because we often make jokes about one of our founders. Teary Bond refer to him as Yoda because he hasn't its tendency to say very concise things that kind of make you scratch your head and say, Wow, why didn't I think of that? Or you know, what exactly does that mean? I never thought about it that way. So I think when I think of the Yoda in the room, it was definitely Terry, >>uh, excuse you. Anything you can add to this, this conversation >>I'll agree with Alison on the you're a comment for short. Another big fork in the road, I recall, was when we changed. What are meta store where we store our own internal metadata? We used >>to use >>a tool called my sequel and we changed it. Thio another database called Foundation TV. I think that was a big game changer for us. And, you know, it was a tough decision. It took us a long time. For the longest time, we even had our own little branch. It was called Foundation DB, and everybody was developing on that branch. It's a little embarrassing, but, you know, those are the kind of decisions that have altered altered the shape of snowflake. >>Yeah. I mean, these air, really, you know, down in the weeds, hardcore stuff that a lot of people that might not be exposed to What would you say was the least obvious technical decision that you had to make it the time. And I wanna ask you about the most obvious to. But what was the what was the one that was so out of the box? I mean, you kind of maybe mentioned it a little bit before, but what if we could double click on that? >>Well, I think one of the core decisions in our architectures the separation of compute and storage on Do you know that is really court architecture. And there's so many features that we have today, um, for instance, data sharing zero copy cloning that that we couldn't have without that architecture. Er, um and I think it was both not obvious. And when we told people about it in the early days, there was definitely skepticism about being able to make that work on being able Thio have that architecture and still get great performance. >>Anything? Yeah, anything that was, like, clearly obvious, that is, Maybe that maybe that was the least and the most that that separation from computing story because it allowed you toe actually take advantage of cloud native. But But was there an obvious one that, you know, it's sort of dogma that you, you know, philosophically lived behind. You know, to this day, >>I think one really obvious thing, um is the sort of no tuning, no knobs, ease of use story behind snowflake. Andi and I say it's really obvious because everybody wants their system to be easy to use. But then I would say there are tons of decisions behind that, that it's not always obvious three implications of of such a choice, right, and really sticking to that. And I think that that's really like a core principle behind Snowflake that that led to a lot of non obvious decisions as a result of sticking to that principle. So, yeah, I >>think to add to that now, now you've gotten us thinking I think another really interesting one was was really, um, should we start from scratch or or should we use something that already exists and and build on top of that? And I think that was one of these, um, almost philosophical kind of stances that we took that that a lot of the systems that were out there were the way they were because because they weren't built for the for the platforms that they were running on, and the big thing that we were targeting was the cloud. And so one of the big stances we took was that we were gonna build it from scratch, and we weren't gonna borrow a single line of code from many other database out there. And this was something that really shocked a lot of people and and many times that this was pretty crazy and it waas. But this is how you build great products. >>That's awesome. All right. She should give you the last word. We got, like, just like 30 seconds left to bring us home >>Your till date. Actually, one of those said shocks people when you talk to them and they say, Wow, you're not You're not really using any other database and you build this entirely yourself. The number of people who actually can build a database from scratch are fairly limited. The group is fairly small, and so it was really a humongous task. And as you mentioned, you know, it really changed the direction off how we design the database. What we what does the database really mean? Tow us right the way Snowflake has built a database. It's really a number of organs that come together and form the body and That's also a concept that's novel to the database industry. >>Guys, congratulations. You must be so proud. And, uh, there's gonna be awesome watching the next next decade, so thank you so much for sharing your stories. >>Thanks, dude. >>Thank you.

>> Okay, listen, we're gearing up for the start of the Snowflake Data Cloud Summit and we want to go back to the early roots of Snowflake. We got some of the founding engineers here, Abdul Muneer, Ashish Modivala, and Alison Lee. They're three individuals that were at Snowflake in the early years and participated in many of the technical decisions that led to the platform that is making Snowflake famous today. Folks, great to see you. Thanks so much for taking some time out of your busy schedules. >> Than you for having us. >> Same. >> Hey, it's got to be really gratifying to see this platform that you've built, you know, taking off and changing businesses. So, I'm sure it was always smooth sailing, right? There were no debates, were there ever? >> Never. >> Now, I've never seen an engineer get into a debate. (laughter) >> All right, so seriously though, so take us back to the early days, you guys, you know, choose whoever wants to start but, what was it like early on? We're talking 2013 here, right? >> That's right. >> When I think back to the early days of Snowflake, I just think of all of us sitting in one room at the time you know, we just had an office that was one room with you know, 12 or 13 engineers sitting there, clacking away at our keyboards, working really hard, churning out code, punctuated by, you know, somebody asking a question about, "Hey, what should we do about this? Or what should we do about that?" And then everyone kind of looking up from their keyboards and getting into discussions and debates about, about the work that we were doing. >> So Abdul, it was just kind of heads down, headphones on, just coding, or >> I think there was a lot of talking and followed by a lot of typing. And, and I think there were periods of time where, you know, anyone could just walk in into the office and probably out of the office and all they'd hear is probably people typing away at their keyboards. And one of my vivid, most vivid memories is is actually I used to sit right across from Alison and there's these huge two, two huge monitors monitors between us. And I would just hear her typing away at our keyboard. And sometimes I was thinking and and all that typing got me nervous because it seemed like Alison knew exactly what, what she needed to do, and I was just still thinking about it. >> So Ashish was this like bliss for you as a developer, an engineer, or was it, was it a stressful time? What was the mood? >> When you don't have a whole lot of customers there's a lot of bliss, but at the same time, there's a lot of pressure on us to make sure that we build the product. There was a timeline ahead of us, we knew we had to build this in a certain timeframe. So one thing I'll add to what Alison and Abdul said is we did a lot of white boarding as well. There were a lot of discussions and those discussions were a lot of fun. They actually cemented what we wanted to build. They made sure that everyone was in tune and there we have it. >> (Dave) Yeah, so, I mean, it is a really exciting time doing any startup. When you have to make decisions in development and variably you come to a fork in the road. So I'm curious as to what some of those forks might've been, how you guys decided, you know, which fork to take. Was there a Yoda in the room that served as the Jedi master? I mean, how are those decisions made? Maybe you could talk about that a little bit. >> Yeah. That's an interesting question. And I think one of, as I think back, one of the memories that, that sticks out in my mind is this epic meeting in one of our conference rooms called North star. And many of our conference rooms are named after ski resorts because the founders are really into skiing and that's why, that's where the Snowflake names comes from. So there was this epic meeting and and I'm not even sure exactly what topic we were discussing. I think it was, it was the signup flow and there were a few different options on the table. and one of the options that, that people were gravitating to one of the founders didn't like it. And they said a few times that there's this makes no sense, there's no other system in the world that does it this way. And I think one of the other founders said that's exactly why we should do it this way. And, or at least seriously considered this option. So I think there was always this this tendency and this impulse that that we needed to think big and think differently and not see the world the way it is but the, the way we wanted it to be and then work our way backwards and try to make it happen. >> Alison, any fork in the road moments that you remember? >> Well, I'm just thinking back to a really early meeting with Ashish and a few of our founders where we were debating something, probably not super exciting to a lot of people outside of hardcore database people which was how to represent our column metadata. And I think it's funny that you, that you mentioned Yoda because we often make jokes about one of our founders Terry and referred to him as Yoda, because he has this tendency to say very concise things that kind of make you scratch your head and say, "Wow why didn't I think of that?" Or, you know, what exactly does that mean? I never thought about it that way. So I think when I think of the Yoda in the room, it was definitely Terry. >> Ashish, anything you can add to this conversation? >> I'll agree with Alison on the Yoda comment, for sure. Another big fork in the road I recall was when we changed one of our meta store where we store our on internal metadata. We used to use a tool called MySQL and we changed it to another database called FoundationDB, I think that was a big game changer for us. And, you know, it was a tough decision, it took us a long time. For the longest time we even had our own little branch it was called FoundationDB and everybody who was developing on that branch. It's a little embarrassing, but, you know, those are the kinds of decisions that alter the shape of Snowflake. >> Yeah, I mean, these are really, you know, down in the weeds hardcore stuff that a lot of people might not be exposed to. What would you say was the least obvious technical decision that you had to make at the time? And I want to ask you about the most obvious too, but what was the one that was so out of the box? I mean, you kind of maybe mentioned it a little bit before but I wonder if we could double click on that? >> Well, I think one of the core decisions in our architecture is the separation of compute and storage. And, you know, that is really core to our architecture, and there are so many features that we have today for instance, data sharing, zero copy cloning, that we couldn't have without that architecture. And I think it was both not obvious, and when we told people about it in the early days there was definitely skepticism about being able to make that work and being able to have that architecture and still get great performance. >> Exactly. >> Yeah. Anything that was like clearly obvious that maybe that, maybe that was the least and the most that, that separation from compute and store, because it allowed you to actually take advantage of Cloud native. But was there an obvious one that you know, is it sort of dogma that you, you know philosophically live by, you know, to this day? >> I think one really obvious thing is the sort of no tuning, no knobs, ease of use story behind Snowflake. And I say, it's really obvious because everybody wants their system to be easy to use. But then I would say there were tons of decisions behind that, that it's not always obvious, the implications, of such a choice, right? And really sticking to that. And I think that that's really like a core principle behind Snowflake, that led to a lot of non-obvious decisions as a result of sticking to that principle. >> So >> I think, to add to that, now you've grabbed us thinking. I think another really interesting one was really, should we start from scratch or should we use something that already exists and build on top of that? And I think that was one of these almost philosophical kind of stances that we took, that a lot of the systems that were out there were the way they were, because, because they weren't built for the, for the platforms that they were running on. And the big thing that we were targeting was the Cloud. And so one of the big stances we took was that we were going to build from scratch. And we weren't going to borrow a single line of code from many other database out there. And this was something that really shocked a lot of people and many times that this was pretty crazy, and it was, but this is how you build great products. >> That's awesome. All right Ashish, I should give you the last word. We got like just like 30 seconds left, bring us home. >> Till date, actually one of those said shocks people when you talk to them and they say, "Wow, you are naturally using any other database, and you build this entirely yourself." The number of people who actually can build a database from scratch are fairly limited, the group is fairly small. And so it was really a humongous task, and as you've mentioned, you know, it really changed the direction of how we designed a database. What we, what does the database really mean to us, right? The way Snowflake has built a database, it's really a number of organs that come together and form the body. And that's also a concept that's novel to the database industry. >> Guys, congratulations, you must be so proud and it's going to be awesome watching the next decade. So thank you so much for sharing your stories. >> Thanks too. >> Thank you. >> Thank you.

>> Okay listen, we're gearing up for the start of the Snowflake Data Cloud Summit. And we want to go back to the early roots of Snowflake. We got some of the founding engineers here, Abdul Munir, Ashish Motivala and Allison Lee. They're three individuals that were at Snowflake, in the early years and participated in many of the technical decisions. That led to the platform and is making Snowflake famous today. Folks great to see you. Thanks so much for taking some time out of your busy schedules. >> Thank you for having us- >> Same. >> It's got to be really gratifying to see this platform that you've built, taking off and changing businesses. So I'm sure it was always smooth sailing, right? There were no debates, where there ever? >> I've never seen an engineer get into a debate. >> Yeah alright, so seriously. So take us back to the early days, you guys choose whoever wants to start, but what was it like, early on we're talking 2013 here, right? >> That's right. >> When I think back to the early days of Snowflake. I just think of all of us sitting in one room at the time, we just had an office that was one room with 12 or 13 engineers sitting there, clacking away at our keyboards, working really hard, churning out code punctuated by somebody asking a question about hey, what should we do about this? Or what should we do about that? And then everyone kind of looking up from their keyboards and getting into discussions and debates about the work that we were doing. >> So, Abdul was it just kind of heads down, headphones on just coding or? >> I think there was a lot of talking and followed by a lot of typing. And I think there were periods of time where anyone could just walk in into the office and probably out of the office and all they'd hear is probably people typing away their keyboards. And one of my most vivid memory is actually I used to sit right across from Allison and there was these two huge monitors between us. And I would just hear her typing away at her keyboard. And sometimes I was thinking and all that typing got me nervous because it seemed like Allison knew exactly what she needed to do. And I was just still thinking about it. >> So Ashish was this like bliss for you as a developer or an engineer? Or was it a stressful time? What was the mood? >> Then when you don't have a whole lot of customers, there's a lot of bliss, but at the same time, there's a lot of pressure on us to make sure that we build the product. There was a timeline ahead of us. We knew we had to build this in a certain timeframe. So one thing I'll add to what Allison and Abdul said is, we did a lot of whiteboarding as well. There were a lot of discussions and those discussions were a lot of fun. They actually cemented what we wanted to build. They made sure everyone was in tune and there we have it. >> Yeah, it is a really exciting time. We can do it any start-up. When you have to make decisions in development and variably you come to a fork in the road. So I'm curious as to what some of those forks might've been, how you guys decided which fork to take. Was there a Yoda in the room that served as the Jedi Master? How are those decisions made? Maybe you could talk about that a little bit. >> That's an interesting question. And as I think back one of the memories that sticks out in my mind is this epic meeting in one of our conference rooms called Northstar and many of our conference rooms are named after ski resorts because the founders are really into skiing. And that's where the Snowflake name comes from. So there was this epic meeting and I'm not even sure exactly what topic we were discussing. I think it was the sign up flow and there were a few different options on the table. And one of the options that people were gravitating to, one of the founders didn't like it. And they said a few times that this makes no sense. There's no other system in the world that does it this way. And I think one of the other founders said, that's exactly why we should do it this way or at least seriously consider this option. So, I think there was always this tendency and this impulse that we needed to think big and think differently and not see the world the way it is, but the way we wanted it to be and then work our way backwards and try to make it happen. >> Allison, any fork in the road moments that you remember? >> Well, I'm just thinking back to a really early meeting with Ashish and a few of our founders where we're debating something probably not super exciting to a lot of people outside of hardcore database people, which was how to represent our column metadata. And I think it's funny that you that you mentioned Yoda, because we often make jokes about one of our founders Thierry and referred to him as Yoda, because he has this tendency to say very concise things that kind of make you scratch your head and say, wow, why didn't I think of that? Or what exactly does that mean? I never thought about it that way. So, when I think of the Yoda in the room, it was definitely Thierry, >> Ashish is there anything you can add to this conversation? >> I'll agree with Allison on the Yoda comment for sure. Another big fork in the road I recall was when we changed one of our meadow store, where we store and are willing to try and metadata. We used to use a tool called my SQL and we changed it to another database called foundation DV. I think that was a big game changer for us. And it was a tough decision. It took us a long time, for the longest time we even had our own little branch it was called foundation DV and everybody was developing on that branch, it's a little embarrassing but those are the kinds of decisions that have altered the shape of Snowflake. >> Yeah, these are really down in the weeds hardcore stuff that a lot of people might not be exposed to. What would you say was the least obvious technical decision that you had to make at the time? And I want to ask you about the most obvious too, but what was the one that was so out of the box? You kind of maybe mentioned it a little bit before, but I wonder if we could double click on that? >> Well, I think one of the core decisions in our architecture is the separation of compute and storage that is really core to our architecture. And there's so many features that we have today, for instance data sharing, zero-copy cloning, that we couldn't have without that architecture. And I think it was both not obvious. And when we told people about it in the early days, there was definitely skepticism about being able to make that work and being able to have that architecture and still get great performance. >> Exactly- >> Yeah, anything that was like clearly obvious, maybe that was the least and the most that separation from compute and store, 'cause it allowed you to actually take advantage of cloud native, but was there an obvious one that is it sort of dogma that you philosophically live behind to this day? >> I think one really obvious thing is the sort of no tuning, no knobs, ease of use story behind Snowflake. And I say it's really obvious because everybody wants their system to be easy to use. But then I would say there were tons of decisions behind that, that it's not always obvious the implications of such a choice, right? And really sticking to that. And I think that that's really like a core principle behind Snowflake that led to a lot of non-obvious decisions as a result of sticking to that principle. >> To wrap to that now you've gotten us thinking, I think another really interesting one was really, should we start from scratch or should we use something that already exists and build on top of that. And I think that was one of these almost philosophical kind of stances that we took, that a lot of the systems that were out there were the way they were because they weren't built for the platforms that they were running on. And the big thing that we were targeting was the cloud. And so one of the big stances we took was that we were going to build it from scratch and we weren't going to borrow a single line of code from any other database out there. And this was something that really shocked a lot of people and many times that this was pretty crazy. And it was, but this is how you build great products. >> That's awesome, all right, Ashish give your last word, we got like just 30 seconds left take, bring us home. >> Till date actually one of those that shocks people when you talk to them and they say, wow, you're not really using any other database? And you build this entirely yourself? The number of people who actually can build a database from scratch are fairly limited. The group is fairly small. And so it was really a humongous task. And as you've mentioned, it really changed the direction of how we designed the database. What does the database really mean to us, right? The way Snowflake has built a database, it's really a number of organs that come together and form the body. And that's also a concept that's novel to the database industry. >> Guys congratulations, you must be so proud and it's going to be awesome watching the next decade. So thank you so much for sharing your stories. >> Thanks Dave. >> Thank you- >> Thank you.

>> Narrator: From around the globe, its theCUBE! With digital coverage of enterprise data automation. An event series brought to you by Io-Tahoe. >> Okay, we're back, welcome back to Data Automated, Ajay Vohora is CEO of Io-Tahoe. Ajay, good to see you, how are things in London? >> Things are doing well, things are doing well, we're making progress. Good to see you, hope you're doing well, and pleasure being back here on theCUBE. >> Yeah, it's always great to talk to you, we're talking enterprise data automation, as you know, within our community we've been pounding the whole DataOps conversation. A little different, though, we're going to dig into that a little bit, but let's start with, Ajay, how are you seeing the response to COVID, and I'm especially interested in the role that data has played in this pandemic. >> Yeah, absolutely, I think everyone's adapting, both socially and in business, the customers that I speak to, day in, day out, that we partner with, they're busy adapting their businesses to serve their customers, it's very much a game of ensuring that we can serve our customers to help their customers, and the adaptation that's happening here is trying to be more agile, trying to be more flexible, and there's a lot of pressure on data, lot of demand on data to deliver more value to the business, to serve that customer. >> Yeah, I mean data, machine intelligence and cloud are really three huge factors that have helped organizations in this pandemic, and the machine intelligence or AI piece, that's what automation is all about, how do you see automation helping organizations evolve, maybe faster than they thought they might have to? >> For sure, I think the necessity of these times, there's, as they say, there's a lot of demand on doing something with data, data, a lot of businesses talk about being data-driven. It's interesting, I sort of look behind that when we work with our customers, and it's all about the customer. My peers, CEOs, investors, shareholders, the common theme here is the customer, and that customer experience starts and ends with data. Being able to move from a point that is reacting to what the customer is expecting, and taking it to that step forward where you can be proactive to serve what that customer's expectation to, and that's definitely come alive now with the current time. >> Yeah, so as I said, we were talking about DataOps a lot, the idea being DevOps applied to the data pipeline, but talk about enterprise data automation, what is it to you and how is it different from DataOps? >> Yeah, great question, thank you. I think we're all familiar with, got more and more awareness around DevOps as it's applied to processes, methodologies that have become more mature over the past five years around DevOps, but managing change, managing application life cycles, managing software development, DevOps has been great, but breaking down those silos between different roles, functions, and bringing people together to collaborate. And we definitely see that those tools, those methodologies, those processes, that kind of thinking, lending itself to data with DataOps is exciting, we're excited about that, and shifting the focus from being IT versus business users to, who are the data producers and who are the data consumers, and in a lot of cases it can sit in many different lines of business. So with DataOps, those methods, those tools, those processes, what we look to do is build on top of that with data automation, it's the nuts and bolts of the algorithms, the models behind machine learning, the functions, that's where we invest our R&D. And bringing that in to build on top of the methods, the ways of thinking that break down those silos, and injecting that automation into the business processes that are going to drive a business to serve its customer. It's a layer beyond DevOps, DataOps, taking it to that point where, way I like to think about it is, is the automation behind the automation. We can take, I'll give you an example of a bank where we've done a lot of work to move them into accelerating their digital transformation, and what we're finding is that as we're able to automate the jobs related to data, and managing that data, and serving that data, that's going into them as a business automating their processes for their customer. So it's definitely having a compound effect. >> Yeah, I mean I think that DataOps for a lot of people is somewhat new, the whole DevOps, the DataOps thing is good and it's a nice framework, good methodology, there is obviously a level of automation in there, and collaboration across different roles, but it sounds like you're talking about sort of supercharging it if you will, the automation behind the automation. You know, organizations talk about being data-driven, you hear that thrown around a lot. A lot of times people will sit back and say "We don't make decisions without data." Okay, but really, being data-driven is, there's a lot of aspects there, there's cultural, but there's also putting data at the core of your organization, understanding how it affects monetization, and as you know well, silos have been built up, whether it's through M&A, data sprawl, outside data sources, so I'm interested in your thoughts on what data-driven means and specifically how Io-Tahoe plays there. >> Yeah, sure, I'd be happy to put that through, David. We've come a long way in the last three or four years, we started out with automating some of those simple, to codify, but have a high impact on an organization across a data lake, across a data warehouse. Those data-related tasks that help classify data. And a lot of our original patents and IP portfolio that were built up is very much around there. Automating, classifying data across different sources, and then being able to serve that for some purpose. So originally, some of those simpler challenges that we help our customers solve, were around data privacy. I've got a huge data lake here, I'm a telecoms business, so I've got millions of subscribers, and quite often a chief data office challenge is, how do I cover the operational risk here, where I've got so much data, I need to simplify my approach to automating, classifying that data. Reason is, can't do that manually, we can't throw people at it, and the scale of that is prohibitive. Quite often, if you were to do it manually, by the time you've got a good picture of it, it's already out of date. So in starting with those simple challenges that we've been able to address, we've then gone on and built on that to see, what else do we serve? What else do we serve for the chief data officer, chief marketing officer, and the CFO, and in these times, where those decision-makers are looking for, have a lot of choices in the platform options that they take, the tooling, they're very much looking for that Swiss army knife, being able to do one thing really well is great, but more and more, where that cost pressure challenge is coming in, is about how do we offer more across the organization, bring in those business, lines of business activities that depend on data, to not just with IT. >> So we like, in theCUBE sometimes we like to talk about okay, what is it, and then how does it work, and what's the business impact? We kind of covered what it is, I'd love to get into the tech a little bit in terms of how it works, and I think we have a graphic here that gets into that a little bit. So guys, if you could bring that up, I wonder, Ajay, if you could tell us, what is the secret sauce behind Io-Tahoe, and if you could take us through this slide. >> Ajay: Sure, I mean right there in the middle, the heart of what we do, it is the intellectual property that were built up over time, that takes from heterogeneous data sources, your Oracle relational database, your mainframe, your data lake, and increasingly APIs and devices that produce data. And now creates the ability to automatically discover that data, classify that data, after it's classified then have the ability to form relationship across those different source systems, silos, different lines of business, and once we've automated that, then we can start to do some cool things, such as put some context and meaning around that data. So it's moving it now from being data-driven, and increasingly where we have really smart, bright people in our customer organizations who want to do some of those advanced knowledge tasks, data scientists, and quants in some of the banks that we work with. The onus is on them, putting everything we've done there with automation, classifying it, relationship, understanding data quality, the policies that you can apply to that data, and putting it in context. Once you've got the ability to power a professional who's using data, to be able to put that data in context and search across the entire enterprise estate, then they can start to do some exciting things, and piece together the tapestry, the fabric, across their different system. Could be CRM, ELP systems, such as SAP, and some of the newer cloud databases that we work with, Snowflake is a great one. >> Yeah, so this is, you're describing sort of one of the reasons why there's so many stovepipes in organizations, 'cause data is kind of locked into these silos and applications, and I also want to point out that previously, to do discovery, to do that classification that you talked about, form those relationships, to glean context from data, a lot of that, if not most of that, in some cases all of that would've been manual. And of course it's out of date so quickly, nobody wants to do it because it's so hard, so this again is where automation comes into the idea of really becoming data-driven. >> Sure, I mean the efforts, if I look back maybe five years ago, we had a prevalence of data lake technologies at the cutting edge, and those have started to converge and move to some of the cloud platforms that we work with, such as Google and AWS. And I think very much as you've said it, those manual attempts to try and grasp what is such a complex challenge at scale, quickly runs out of steam, because once you've got your fingers on the details of what's in your data estate, it's changed. You've onboarded a new customer, you've signed up a new partner, a customer has adopted a new product that you've just launched, and that slew of data keeps coming, so it's keeping pace with that, the only answer really here is some form of automation. And what we've found is if we can tie automation with what I said before, the expertise, the subject matter experience that sometimes goes back many years within an organization's people, that augmentation between machine learning, AI, and that knowledge that sits inside the organization really tends to allot a lot of value in data. >> Yeah, so you know well, Ajay, you can't be as a smaller company all things to all people, so the ecosystem is critical. You're working with AWS, you're working with Google, you got Red Hat, IBM as partners. What is attracting those folks to your ecosystem, and give us your thoughts on the importance of ecosystem. >> Yeah, that's fundamental, I mean when I came into Io-Tahoe here as CEO, one of the trends that I wanted us to be part of was being open, having an open architecture that allowed one thing that was close to my heart, which was as a CEO, a CIO, well you've got a budget vision, and you've already made investments into your organization, and some of those are pretty long term bets, they could be going out five, 10 years sometimes, with a CRM system, training up your people, getting everybody working together around a common business platform. What I wanted to ensure is that we could openly plug in, using APIs that were available, to a lot of that sunk investment, and the cost that has already gone into managing an organization's IT, for business users to perform. So, part of the reason why we've been able to be successful with some of our partners like Google, AWS, and increasingly a number of technology players such as Red Hat, MongoDB is another one that we're doing a lot of good work with, and Snowflake, there is, those investments have been made by the organizations that are our customers, and we want to make sure we're adding to that, and then leveraging the value that they've already committed to. >> Okay, so we've talked about what it is and how it works, now I want to get into the business impact, I would say what I would be looking for, from this, would be can you help me lower my operational risk, I've got tasks that I do, many are sequential, some are in parallel, but can you reduce my time to task, and can you help me reduce the labor intensity, and ultimately my labor cost, so I can put those resources elsewhere, and ultimately I want to reduce the end to end cycle time, because that is going to drive telephone number ROI, so am I missing anything, can you do those things, maybe you can give us some examples of the ROI and the business impact. >> Yeah, I mean the ROI, David, is built upon three things that I've mentioned, it's a combination of leveraging the existing investment with the existing estate, whether that's on Microsoft Azure, or AWS, or Google, IBM, and putting that to work, because the customers that we work with have made those choices. On top of that, it's ensuring that we have got the automation that is working right down to the level of data, at a column level or the file level. So we don't deal with metadata, it's being very specific, to be at the most granular level. So as we run our processes and the automation, classification, tagging, applying policies from across different compliance and regulatory needs an organization has to the data, everything that then happens downstream from that is ready to serve a business outcome. It could be a customer who wants that experience on a mobile device, a tablet, or face to face, within a store. And being able to provision the right data, and enable our customers to do that for their customers, with the right data that they can trust, at the right time, just in that real time moment where a decision or an action is being expected, that's driving the ROI to be in some cases 20x plus, and that's really satisfying to see, that kind of impact, it's taking years down to month, and in many cases months of work down to days, and some cases hours, the time to value. I'm impressed with how quickly out of the box, with very little training a customer can pick up our tool, and use features such as search, data discovery, knowledge graph, and identifying duplicates, and redundant data. Straight off the bat, within hours. >> Well it's why investors are interested in this space, I mean they're looking for a big, total available market, they're looking for a significant return, 10x is, you got to have 10x, 20x is better. So that's exciting, and obviously strong management, and a strong team. I want to ask you about people, and culture. So you got people process technology, we've seen with this pandemic that the processes are really unpredictable, and the technology has to be able to adapt to any process, not the reverse, you can't force your process into some static software, so that's very very important, but at the end of the day, you got to get people on board. So I wonder if you could talk about this notion of culture, and a data-driven culture. >> Yeah, that's so important, I mean, current times is forcing the necessity of the moment to adapt, but as we start to work our way through these changes and adapt and work with our customers to adapt to these changing economic times, what we're seeing here is the ability to have the technology complement, in a really smart way, what those business users and IT knowledge workers are looking to achieve together. So, I'll give you an example. We have quite often with the data operations teams, in the companies that we are partnering with, have a lot of inbound inquiries on a day to day level, "I really need this set of data because I think it can help "my data scientists run a particular model," or "What would happen if we combine these two different "silos of data and get some enrichment going?" Now those requests can sometimes take weeks to realize, what we've been able to do with the power of (audio glitches) technology, is to get those answers being addressed by the business users themselves, and now, with our customers, they're coming to the data and IT folks saying "Hey, I've now built something in a development environment, "why don't we see how that can scale up "with these sets of data?" I don't need terabytes of it, I know exactly the columns and the feats in the data that I'm going to use, and that cuts out a lot of wastage, and time, and cost, to innovate. >> Well that's huge, I mean the whole notion of self-service in the lines of business actually feeling like they have ownership of the data, as opposed to IT or some technology group owning the data because then you've got data quality issues, or if it doesn't line up with their agenda, you're going to get a lot of finger pointing, so that is a really important piece of it. I'll give you a last word, Ajay, your final thoughts if you would. >> Yeah, we're excited to be on this path, and I think we've got some great customer examples here, where we're having a real impact in a really fast pace, whether it's helping them migrate to the cloud, helping them clean up their legacy data lake, and quite often now, the conversation is around data quality. As more of the applications that we enable to work more proficiently could be data, RPA, could be robotic process automation, a lot of the APIs that are now available in the cloud platforms, a lot of those are dependent on data quality and being able to automate for business users, to take accountability of being able to look at the trend of their data quality over time and get those signaled, is really driving trust, and that trust in data is helping in turn, the IT teams, the data operations teams they partner with, do more, and more quickly. So it comes back to culture, being able to apply the technology in such a way that it's visual, it's intuitive, and helping just like DevOps has with IT, DataOps, putting the intelligence in at the data level, to drive that collaboration. We're excited. >> You know, you remind me of something, I lied, I don't want to go yet, if it's okay. I know we're tight on time, but you mentioned a migration to the cloud, and I'm thinking about the conversation with Paula from Webster Bank. Migrations are, they're a nasty word for organizations, and we saw this with Webster, how are you able to help minimize the migration pain and why is that something that you guys are good at? >> Yeah, I mean there are many large, successful companies that we've worked with, Webster's a great example. Where I'd like to give you the analogy where, you've got a lot of bright people in your teams, if you're running a business as a CEO, and it's a bit like a living brain. But imagine if those different parts of your brain were not connected, that would certainly diminish how you're able to perform. So, what we're seeing, particularly with migration, is where banks, retailers, manufacturers have grown over the last 10 years, through acquisition, and through different initiatives to drive customer value. That sprawl in their data estate hasn't been fully dealt with. It's sometimes been a good thing to leave whatever you've acquired or created in situ, side by side with that legacy mainframe, and your Oracle ERP. And what we're able to do very quickly with that migration challenge is shine a light on all the different parts of data application at the column level, or at the file level if it's a data lake, and show an enterprise architect, a CDO, how everything's connected, where there may not be any documentation. The bright people that created some of those systems have long since moved on, or retired, or been promoted into other roles, and within days, being able to automatically generate and keep refreshed the states of that data, across that landscape, and put it into context, then allows you to look at a migration from a confidence that you're dealing with the facts, rather than what we've often seen in the past, is teams of consultants and business analysts and data analysts, spend months getting an approximation, and a good idea of what it could be in the current state, and try their very best to map that to the future target state. Now with Io-Tahoe being able to run those processes within hours of getting started, and build that picture, visualize that picture, and bring it to life. The ROI starts off the bat with finding data that should've been deleted, data that there's copies of, and being able to allow the architect, whether it's we have working on GCP, or in migration to any of the clouds such as AWS, or a multicloud landscape, quite often now. We're seeing, yeah. >> Yeah, that visi-- That visibility is key to sort of reducing operational risk, giving people confidence that they can move forward, and being able to do that and update that on an ongoing basis means you can scale. Ajay Vohora, thanks so much for coming to theCUBE and sharing your insights and your experiences, great to have you. >> Thank you David, look forward to talking again. >> All right, and keep it right there everybody, we're here with Data Automated on theCUBE, this is Dave Vellante, and we'll be right back right after this short break. (calm music)

>>It's the queue covering the virtual vertical Big Data Conference 2020. Brought to you by vertical. >>Hello, everybody. Welcome to the new Normal. You're watching the Cube, and it's remote coverage of the vertical big data event on digital or gone Virtual. My name is Dave Volante, and I'm here with Colin Mahoney, who's a senior vice president at Micro Focus and the GM of Vertical Colin. Well, strange times, but the show goes on. Great to see you again. >>Good to see you too, Dave. Yeah, strange times indeed. Obviously, Safety first of everyone that we made >>a >>decision to go Virtual. I think it was absolutely the right all made it in advance of how things have transpired, but we're making the best of it and appreciate your time here, going virtual with us. >>Well, Joe and we're super excited to be here. As you know, the Cube has been at every single BDC since its inception. It's a great event. You just you just presented the key note to your to your audience, You know, it was remote. You didn't have that that live vibe. And you have a lot of fans in the vertical community But could you feel the love? >>Yeah, you know, it's >>it's hard to >>feel the love virtually, but I'll tell you what. The silver lining in all this is the reach that we have for this event now is much broader than it would have been a Z you know, you know, we brought this event back. It's been a few years since we've done it. We're super excited to do it, obviously, you know, in Boston, where it was supposed to be on location, but there wouldn't have been as many people that could participate. So the silver lining in all of this is that I think there's there's a lot of love out there we're getting, too. I have a lot of participants who otherwise would not have been able to participate in this. Both live as well. It's a lot of these assets that we're gonna have available. So, um, you know, it's out there. We've got an amazing customers and of practitioners with vertical. We've got so many have been with us for a long time. We've of course, have a lot of new customers as well that we're welcoming, so it's exciting. >>Well, it's been a while. Since you've had the BDC event, a lot of transpired. You're now part of micro focus, but I know you and I know the vertical team you guys have have not stopped. You've kept the innovation going. We've been following the announcements, but but bridge the gap between the last time. You know, we had coverage of this event and where we are today. A lot has changed. >>Oh, yeah, a lot. A lot has changed. I mean, you know, it's it's the software industry, right? So nothing stays the same. We constantly have Teoh keep going. Probably the only thing that stays the same is the name Vertical. Um and, uh, you know, you're not spending 10 which is just a phenomenal released for us. So, you know, overall, the the organization continues to grow. The dedication and commitment to this great form of vertical continues every single release we do as you know, and this hasn't changed. It's always about performance and scale and adding a whole bunch of new capabilities on that front. But it's also about are our main road map and direction that we're going towards. And I think one of the things have been great about it is that we've stayed true that from day one we haven't tried to deviate too much and get into things that are barred to outside your box. But we've really done, I think, a great job of extending vertical into places where people need a lot of help. And with vertical 10 we know we're going to talk more about that. But we've done a lot of that. It's super exciting for our customers, and all of this, of course, is driven by our customers. But back to the big data conference. You know, everybody has been saying this for years. It was one of the best conferences we've been to just so really it's. It's developers giving tech talks, its customers giving talks. And we have more customers that wanted to give talks than we had slots to fill this year at the event, which is another benefit, a little bit of going virtually accommodate a little bit more about obviously still a tight schedule. But it really was an opportunity for our community to come together and talk about not just America, but how to deal with data, you know, we know the volumes are slowing down. We know the complexity isn't slowing down. The things that people want to do with AI and machine learning are moving forward in a rapid pace as well. There's a lot talk about and share, and that's really huge part of what we try to do with it. >>Well, let's get into some of that. Um, your customers are making bets. Micro focus is actually making a bet on one vertical. I wanna get your perspective on one of the waves that you're riding and where are you placing your bets? >>Yeah, No, it's great. So, you know, I think that one of the waves that we've been writing for a long time, obviously Vertical started out as a sequel platform for analytics as a sequel, database engine, relational engine. But we always knew that was just sort of takes that we wanted to do. People were going to trust us to put enormous amounts of data in our platform and what we owe everyone else's lots of analytics to take advantage of that data in the lots of tools and capabilities to shape that data to get into the right format. The operational reporting but also in this day and age for machine learning and from some pretty advanced regressions and other techniques of things. So a huge part of vertical 10 is just doubling down on that commitment to what we call in database machine learning and ai. Um, And to do that, you know, we know that we're not going to come up with the world's best algorithms. Nor is that our focus to do. Our advantage is we have this massively parallel platform to ingest store, manage and analyze the data. So we made some announcements about incorporating PM ML models into the product. We continue to deepen our python integration. Building off of a new open source project we started with uber has been a great customer and partner on This is one of our great talks here at the event. So you know, we're continuing to do that, and it turns out that when it comes to anything analytics machine learning, certainly so much of what you have to do is actually prepare the big shape the data get the data in the right format, apply the model, fit the model test a model operationalized model and is a great platform to do that. So that's a huge bet that were, um, continuing to ride on, taking advantage of and then some of the other things that we've just been seeing. You continue. I'll take object. Storage is an example on, I think Hadoop and what would you point through ultimately was a huge part of this, but there's just a massive disruption going on in the world around object storage. You know, we've made several bets on S three early we created America Yang mode, which separates computing story. And so for us that separation is not just about being able to take care of your take advantage of cloud economics as we do, or the economics of object storage. It's also about being able to truly isolate workloads and start to set the sort of platform to be able to do very autonomous things in the databases in the database could actually start self analysing without impacting many operational workloads, and so that continues with our partnership with pure storage. On premise, we just announced that we're supporting beyond Google Cloud now. In addition to Amazon, we supported on we've got a CFS now being supported by are you on mode. So we continue to ride on that mega trend as well. Just the clouds in general. Whether it's a public cloud, it's a private cloud on premise. Giving our customers the flexibility and choice to run wherever it makes sense for them is something that we are very committed to. From a flexibility standpoint. There's a lot of lock in products out there. There's a lot of cloud only products now more than ever. We're hearing our customers that they want that flexibility to be able to run anywhere. They want the ease of use and simplicity of native cloud experiences, which we're giving them as well. >>I want to stay in that architectural component for a minute. Talk about separating compute from storage is not just about economics. I mean apart Is that you, you know, green, really scale compute separate from storage as opposed to in chunks. It's more efficient, but you're saying there's other advantages to operational and workload. Specificity. Um, what is unique about vertical In this regard, however, many others separate compute from storage? What's different about vertical? >>Yeah, I think you know, there's a lot of differences about how we do it. It's one thing if you're a cloud native company, you do it and you have a shared catalog. That's key value store that all of your customers are using and are on the same one. Frankly, it's probably more of a security concern than anything. But it's another thing. When you give that capability to each customer on their own, they're fully protected. They're not sharing it with any other customers. And that's something that we hear a lot of insights from our customers. They want to be able to separate compute and storage. But they want to be able to do this in their own environment so that they know that in their data catalog there's no one else is. You share in that catalog, there's no single point of failure. So, um, that's one huge advantage that we have. And frankly, I think it just comes from being a company that's operating on premise and, uh, up in the cloud. I think another huge advantages for us is we don't know what object storage platform is gonna win, nor do we necessarily have. We designed the young vote so that it's an sdk. We started with us three, but it could be anything. It's DFS. That's three. Who knows what what object storage formats were going to be there and then finally, beyond just the object storage. We're really one of the only database companies that actually allows our customers to natively operate on data in very different formats, like parquet and or if you're familiar with those in the Hadoop community. So we not only embrace this kind of object storage disruption, but we really embrace the different data formats. And what that means is our customers that have data pipelines that you know, fully automated, putting this information in different places. They don't have to completely reload everything to take advantage of the Arctic analytics. We can go where the data is connected into it, and we offer them a lot of different ways to take advantage of those analytics. So there are a couple of unique differences with verdict, and again, I think are really advance. You know, in many ways, by not being a cloud native platform is that we're very good at operating in different environments with different formats that changing formats over time. And I don't think a lot of the other companies out there that I think many, particularly many of the SAS companies were scrambling. They even have challenges moving from saying Amazon environment to a Microsoft azure environment with their office because they've got so much unique Band Aid. Excuse me in the background. Just holding the system up that is native to any of those. >>Good. I'm gonna summarize. I'm hearing from you your Ferrari of databases that we've always known. Your your object store agnostic? Um, it's any. It's the cloud experience that you can bring on Prem to virtually any cloud. All the popular clouds hybrid. You know, aws, azure, now Google or on Prem and in a variety of different data formats. And that is, I think, you know, you need the combination of those I think is unique in the marketplace. Um, before we get into the news, I want to ask you about data silos and data silos. You mentioned H DFs where you and I met back in the early days of big data. You know, in some respects, you know, Hadoop help break down the silos with distributing the date and leave it in place, and in other respects, they created Data Lakes, which became silos. And so we have. Yet all these other sales people are trying to get to, Ah, digital transformation meeting, putting data at their core virtually obviously, and leave it in place. What's your thoughts on that in terms of data being a silo buster Buster, How does verdict of way there? >>Yeah, so And you're absolutely right, I think if even if you look at his due for all the new data that gets into the do. In many ways, it's created yet another large island of data that many organizations are struggling with because it's separate from their core traditional data warehouse. It's separate from some of the operational systems that they have, and so there might be a lot of data in there, but they're still struggling with How do I break it out of that large silo and or combine it again? I think some some of the things that verdict it doesn't part of the announcement just attend his migration tools to make it really easy. If you do want to move it from one platform to another inter vertical, but you don't have to move it, you can actually take advantage of a lot of the data where it resides with vertical, especially in the Hadoop brown with our external table storage with our building or compartment natively. So we're very pragmatic about how our customers go about this. Very few customers, Many of them tried it with Hadoop and realize that didn't work. But very few customers want a wholesale. Just say we're going to throw everything out. We're gonna get rid of our data warehouse. We're gonna hit the pause button and we're going to go from there. Just it's not possible to do that. So we've spent a lot of time investing in the product, really work with them to go where the data is and then seamlessly migrate. And when it makes sense to migrate, you mentioned the performance of America. Um, and you talked about it is the variety. It definitely is. And one other thing that we're really proud of this is that it actually is not a gas guzzler. Easy either One of the things that we're seeing, a lot of the other cloud databases pound for pound you get on the 10th the hardware vertical running up there. You get over 10 x performance. We're seeing that a lot, so it's Ah, it's not just about the performance, but it's about the efficiency as well. And I think that efficiency is really important when it comes to silos. Because there's there's just only so much horsepower out there. And it's easier for companies to play tricks and lots of servers environment when they start up for so many organizations and cloud and frankly, looking at the bills they're getting from these cloud workloads that are running. They really conscious of that. >>Yeah. The big, big energy companies love the gas guzzlers. A lot of a lot of cloud. Cute. But let's get into the news. Uh, 10 dot io you shared with your the audience in your keynote. One of the one of the highlights of data. What do we need to know? >>Yeah, so, you know, again doubling down on these mega trends, I'll start with Machine Learning and ai. We've done a lot of work to integrate so that you can take native PM ml models, bring them into vertical, run them massively parallel and help shape you know your data and prepare it. Do all the work that we know is required true machine learning. And for all the hype that there is around it, this is really you know, people want to do a lot of unsupervised machine learning, whether it's for healthcare fraud, detection, financial services. So we've doubled down on that. We now also support things like Tensorflow and, you know, as I mentioned, we're not going to come up with the best algorithms. Our job is really to ensure that those algorithms that people coming up with could be incorporated, that we can run them against massive data sets super efficiently. So that's that's number one number two on object storage. We continue to support Mawr object storage platforms for ya mode in the cloud we're expanding to Google G CPI, Google's cloud beyond just Amazon on premise or in the cloud. Now we're also supporting HD fs with beyond. Of course, we continue to have a great relationship with our partners, your storage on premise. Well, what we continue to invest in the eon mode, especially. I'm not gonna go through all the different things here, but it's not just sort of Hey, you support this and then you move on. There's so many different things that we learn about AP I calls and how to save our customers money and tricks on performance and things on the third areas. We definitely continue to build on that flexibility of deployment, which is related to young vote with. Some are described, but it's also about simplicity. It's also about some of the migration tools that we've announced to make it easy to go from one platform to another. We have a great road map on these abuse on security, on performance and scale. I mean, for us. Those are the things that we're working on every single release. We probably don't talk about them as much as we need to, but obviously they're critically important. And so we constantly look at every component in this product, you know, Version 10 is. It is a huge release for any product, especially an analytic database platform. And so there's We're just constantly revisiting you know, some of the code base and figuring out how we can do it in new and better ways. And that's a big part of 10 as well. >>I'm glad you brought up the machine Intelligence, the machine Learning and AI piece because we would agree that it is really one of the things we've noticed is that you know the new innovation cocktail. It's not being driven by Moore's law anymore. It's really a combination of you. You've collected all this data over the last 10 years through Hadoop and other data stores, object stores, etcetera. And now you're applying machine intelligence to that. And then you've got the cloud for scale. And of course, we talked about you bringing the cloud experience, whether it's on Prem or hybrid etcetera. The reason why I think this is important I wanted to get your take on this is because you do see a lot of emerging analytic databases. Cloud Native. Yes, they do suck up, you know, a lot of compute. Yeah, but they also had a lot of value. And I really wanted to understand how you guys play in that new trend, that sort of cloud database, high performance, bringing in machine learning and AI and ML tools and then driving, you know, turning data into insights and from what I'm hearing is you played directly in that and your differentiation is a lot of the things that we talk about including the ability to do that on from and in the cloud and across clouds. >>Yeah, I mean, I think that's a great point. We were a great cloud database. We run very well upon three major clouds, and you could argue some of the other plants as well in other parts of the world. Um, if you talk to our customers and we have hundreds of customers who are running vertical in the cloud, the experience is very good. I think it would always be better. We've invested a lot in taking advantage of the native cloud ecosystem, so that provisioning and managing vertical is seamless when you're in that environment will continue to do that. But vertical excuse me as a cloud platform is phenomenal. And, um, you know, there's a There's a lot of confusion out there, you know? I think there's a lot of marketing dollars spent that won't name many of the companies here. You know who they are, You know, the cloud Native Data Warehouse and it's true, you know their their software as a service. But if you talk to a lot of our customers, they're getting very good and very similar. experiences with Bernie comic. We stopped short of saying where software is a service because ultimately our customers have that control of flexibility there. They're putting verdict on whichever cloud they want to run it on, managing it. Stay tuned on that. I think you'll you'll hear from or more from us about, you know, that going going even further. But, um, you know, we do really well in the cloud, and I think he on so much of yang. And, you know, this has really been a sort of 2.5 years and never for us. But so much of eon is was designed around. The cloud was designed around Cloud Data Lakes s three, separation of compute and storage on. And if you look at the work that we're doing around container ization and a lot of these other elements, it just takes that to the next level. And, um, there's a lot of great work, so I think we're gonna get continue to get better at cloud. But I would argue that we're already and have been for some time very good at being a cloud analytic data platform. >>Well, since you open the door I got to ask you. So it's e. I hear you from a performance and architectural perspective, but you're also alluding two. I think something else. I don't know what you can share with us. You said stay tuned on that. But I think you're talking about Optionality, maybe different consumption models. That am I getting that right and you share >>your difficult in that right? And actually, I'm glad you wrote something. I think a huge part of Cloud is also has nothing to do with the technology. I think it's how you and seeing the product. Some companies want to rent the product and they want to rent it for a certain period of time. And so we allow our customers to do that. We have incredibly flexible models of how you provision and purchase our product, and I think that helps a lot. You know, I am opening the door Ah, a little bit. But look, we have customers that ask us that we're in offer them or, you know, we can offer them platforms, brawl in. We've had customers come to us and say please take over systems, um, and offer something as a distribution as I said, though I think one thing that we've been really good at is focusing on on what is our core and where we really offer offer value. But I can tell you that, um, we introduced something called the Verdict Advisor Tool this year. One of the things that the Advisor Tool does is it collects information from our customer environments on premise or the cloud, and we run through our own machine learning. We analyze the customer's environment and we make some recommendations automatically. And a lot of our customers have said to us, You know, it's funny. We've tried managed service, tried SAS off, and you guys blow them away in terms of your ability to help us, like automatically managed the verdict, environment and the system. Why don't you guys just take this product and converted into a SAS offering, so I won't go much further than that? But you can imagine that there's a lot of innovation and a lot of thoughts going into how we can do that. But there's no reason that we have to wait and do that today and being able to offer our customers on premise customers that same sort of experience from a managed capability is something that we spend a lot of time thinking about as well. So again, just back to the automation that ease of use, the going above and beyond. Its really excited to have an analytic platform because we can do so much automation off ourselves. And just like we're doing with Perfect Advisor Tool, we're leveraging our own Kool Aid or Champagne Dawn. However you want to say Teoh, in fact, tune up and solve, um, some optimization for our customers automatically, and I think you're going to see that continue. And I think that could work really well in a bunch of different wallets. >>Welcome. Just on a personal note, I've always enjoyed our conversations. I've learned a lot from you over the years. I'm bummed that we can't hang out in Boston, but hopefully soon, uh, this will blow over. I loved last summer when we got together. We had the verdict throwback. We had Stone Breaker, Palmer, Lynch and Mahoney. We did a great series, and that was a lot of fun. So it's really it's a pleasure. And thanks so much. Stay safe out there and, uh, we'll talk to you soon. >>Yeah, you too did stay safe. I really appreciate it up. Unity and, you know, this is what it's all about. It's Ah, it's a lot of fun. I know we're going to see each other in person soon, and it's the people in the community that really make this happen. So looking forward to that, but I really appreciate it. >>Alright. And thank you, everybody for watching. This is the Cube coverage of the verdict. Big data conference gone, virtual going digital. I'm Dave Volante. We'll be right back right after this short break. >>Yeah.

>> Announcer: Live from Boston, Massachusetts, it's theCube. Covering IFS World Conference 2019. Brought to you by IFS. >> Welcome back to Boston everybody you're watching theCube, the leader in live tech coverage. This is day one of the IFS World Conference. I'm Dave Vallante with my co-host Paul Gillen. Melissa Di Donato is here, she's the CEO of SUSE and Jon Roskill is the CEO of Acumatica. Folks, welcome to theCube. >> Thank you so much. >> So you guys had the power panel today? Talking about digital transformation. I got a question for all of you. What's the difference between a business and a digital business? Melissa, I'll give you first crack. >> Before a regular old business and a digital business? Everyone's digital these days, aren't they? I was interviewing the, one of the leaders in Expedia and I said, "Are you a travel company "or are you a digital company? "Like where do you lead with?" And she said to me, "No no, we're a travel company "but we use digital." So it seems like the more and more we think about what the future means how we service our customers, customers being at the core everyone's a digital business. The way you service, the way you communicate the way you support. So whether you're a business or none you're always got to be a digital business. >> You better be a digital business and so-- >> I'm going to take a slightly different tact on that which is, we talk about digital and analog businesses and analog businesses are ones that are data silos they have a lot of systems, so they think they're digital but they're disconnected. And, you know, part of a transformation is connecting all the systems together and getting them to work like one. >> But I think the confict other common thread is data, right? A digital business maybe puts data at the core and that's how they get competitive advantage but, I want to ask you guys about your respective businesses. So SUSE, obviously you compete with the big whale RedHat, you know, the big news last year IBM $34 billion. How did that or will that in your view affect your business? >> It's already affecting our business. We've seen a big big uptake in interest in SUSE and what we're doing. You know, they say that a big part of the install based customers that RedHat and IBM currently have are unhappy about the decision to be acquired by IBM. Whether they're in conflict because we're a very big heavily channel business, right? So a lot of the channel partners are not quite happy about having one of their closest competitors now be, you know, part of the inner circle if you will. And other customers are just not happy. I mean, RedHat had fast innovation, fast pace and thought leadership and now all of a sudden they're going to be buried inside of a large conglomerate and they're not happy about that. So when we look at what's been happening for us particularly since March, we became an independent company now one of the world's largest independent open source company in the world. Since IBM has been taking over from RedHat. And, you know, big big uptake. Since March we became independent we've been getting a lot of questioning. "Where are we, where are we going, what are we doing?" And, " Hey, you know, I haven't heard about SUSE a while "what are you doing now?" So it's been really good news for us really, really good news. >> I mean, we're huge fans of RedHat. We do a lot of their events and-- >> Melissa: I'm a huge fan myself. >> But I tell you, I mean, we know from first hand IBM has this nasty habit of buying companies tripling the price. Now they say they're going to leave RedHat alone, we'll see. >> Yeah, like they said they'd leave Lotus alone and all the others. >> SPSS, you saw that, Ustream, you know one of our platforms. >> What's your view, how do you think it's going to go? >> I don't think it's about cloud I think it's about services and I think that's the piece that we don't really have great visibility on. Can IBM kind of jam OpenShift into its customers you know, businesses without them even really knowing it and that's the near-term cash flow play that they're trying to, you know, effect. >> Yeah, but it's not working for them, isn't though? Because when you look at the install base 90% of their business it's been Linux open source environment and OpenShift is a tag-along. I don't know if that's a real enabler for the future rather than, you know, an afterthought from the past. >> Well, for $34 billion it better be. >> I want to ask you about the cost of shifting because historically, you know if you were IBM, you were stuck with IBM forever. What is involved in customers moving from RedHat to SUSE presumably you're doing some of those migrations style. >> We are, we are doing them more and more in fact, we're even offering migration services ourself in some applications. It depends on the application layer. >> How simple is that? >> It depends on the application. So, we've got some telco companies is very very complex 24/7, you know, high pays, big fat enterprise applications around billing, for example. They're harder to move. >> A lot of custom code. >> A lot of custom code, really deep, really rich they need, you know, constant operation because it's billing, right? Big, fat transactions, those are a little bit more complex than say, the other applications are. Nonetheless, there is a migration path and in fact, we're one of the only open source companies in the world that provides support for not just SUSE, but actually for RedHat. So, if you're a RedHat, for or a well customer that want to get off an unsupported version of RedHat you can come over to SUSE. We'll not just support your RedHat system but actually come up with a migration plan to get you into a supported version of SUSE. >> If it's a package set of apps and you have to freeze the code it's actually not that bad-- >> It's not that bad, no. >> To migrate. All right, Jon I got to ask you, so help us understand Acumatica and IFS and the relationship you're like sister companies, you both the ERP providers. How do you work together or? >> Yeah, so we're both owned by a private equity firm called EQT. IFS is generally focused on $500 million and above company so more enterprise and we're focused on core mid-market. So say, $20 million to $500 million. And so very complementary in that way. IFS is largely direct selling we're a 100% through channels. IFS is stronger in Europe, we're stronger in North America and so they see these as very complementary assets and rather than to, perhaps what's going on with the IBM, RedHat discussion here. Slam these big things together and screw them up they're trying to actually keep us independent. So they put us in a holding company but we're trying to leverage much of each other's goodness as we can. >> Is there a migration path? I mean, for customers who reach the top end of your market can they smoothly get to IFS? >> Yeah, it's not going to be like a smooth you know, turn a switch and go. But it absolutely is a migration option for customers and we do have a set of customers that are outgrowing us you know, we have a number of customers now over a billion dollars running on Acumatica and you know, for a company, we've got one that we're actually talking to about this right now operating in 41 countries global, they need 24/7 support we're not the right company to be running their ERP system. >> On your panel today guys you were talking about, a lot about digital transformations kind of lessons learned. What are the big mistakes you see companies making and kind of what's your roadmap for success? >> I think doing too much too fast. Everyone talks about the digital innovation digital transformation. It's really a business transformation with digital being the underpinning the push forward that carries the business forward, right? And I think that we make too many mistakes with regards to doing too much, too fast, too soon, that's one. Doing and adopting technology for technology's sake. "Oh, it's ML, it's AI." And everyone loves these big buzz words, right? All the code words for what technology is? So they tend to bring it on but they don't really know the outcome. Really really important at SUSE were absolutely obsessed with our customers and during a digital transformation if you remain absolutely sick of anything about your customer at the core of every decision you make and everything you do. Particularly with regards to digital transformation you want to make sure that business outcome is focused on them. Having a clear roadmap with milestones along the journey is really important and ensuring it's really collaborative. We talked this morning about digital natives you know, we're all young, aren't we? Me in particular, but, you know I think the younger generation of digital natives think a little bit differently perhaps than we were originally thinking when we were their age. You know, I depend on that thinking I depend on that integration of that thought leadership infused into companies to help really reach customers in different ways. Our customers are buying differently our customers have different expectations they have different deliverables they require and they expect to be supported in different way. And those digital natives, that young talent can really aid in that delivery of good thought leadership for our businesses. >> So Jon, we're seeing IT spending at the macro slow down a little bit. You know, a lot of different factors going on it's not a disaster, it's not falling off the cliff but definitely pre-2018 levels and one of the theories is that you had this kind of spray-and-pray kind of like Melissa was say, deal was going too fast trying everything and now we're seeing more of a narrow focus on things that are going to give a return. Do you see that happening out there? >> Yeah, definitely some, I mean people are looking for returns even in what's been a really vibrant economy but, you know, I agree with Melissa's point there's a lot of ready, shoot, aim projects out there and, you know, the biggest thing I see is the ones that aren't, the fail that aren't the ones that aren't led by the leadership. They're sort of given off to some side team often the IT team and said, "Go lead digital transformation of the company." And digital transformation you know, Melissa said this morning it's business transformation. You've got to bring the business part of it to the table and you've got to think about, it's got to be led by the CEO or the entire senior leadership team has to be on board and if not, it's not going to be successful. >> So, pragmatism would say, okay, you get some quick hits get some wins and then you got kind of the, you know, Bezos, Michael Dell mindset go big or go home, so what's your philosophy? Moonshots or, you know, quick hits? >> I always think starting you know, you've got to understand your team's capabilities. So starting is something that you can get a gauge of that you know, particularly if you're new and you're walking into an organization, you know. Melissa, I don't know how long you've been in your role now? >> Melissa: 65 days. >> Right, so there you go. So it's probably a good person to ask what, you know, what you're finding out there but I think, you know, getting a gauge of what your resources are. I mean, one of the things you see around here is there are, you know, dozens of partner firms that are, or can be brought into, you know supplement the resources you have in your own team. So being thoughtful in that is part of the approach. And then having a roadmap for what you're trying to do. Like we talked this morning about a customer that Linda had been talking about. Have been working on for six or seven years, right? And you're saying, for an enterprise a very large enterprise company taking six or seven years to turn the battleship maybe isn't that long. >> Okay, so you got the sister company going on. Do you have a commercial relationship with IFS or you just here as kind of an outside speaker and a thought leader? >> I'm here as an outside speaker thought leader. There is talk that perhaps we can you know, work together in the future we're trying to work that out right now. >> I want to ask you about open source business models. We still see companies sort of struggling to come up with, not profitable but, you know, insanely profitable business models based on open source software. What do you see coming out of all this? Is there a model that you think is going to work in the long term? >> I think the future is open source for sure and this is coming from a person who spent 25 years in proprietary software having worked for the larger piece here in vendors. 100% of my life has been dedicated to proprietary software. So whilst that's true I came at SUSE and the open source environment in a very different way as a customer running my proprietary applications on open source Linux based systems. So I come with a little bit different of a, you know, of an approach I would say. The future's open source for sure the way that we collaborate, the innovation the borderless means of which we deliver you know, leadership within our business is much much different than proprietary software. You would think as well that, you know the wall that we hide behind an open source being able to access software anywhere in a community and be able to provide thought leadership masks and hides who the developers and engineers are and instead exacerbates the thought leadership that comes out of them. So it provides for a naturally inclusive and diverse environment which leads to really good business results. We all know the importance of diversity and inclusion. I think there is definitely a place for open source in the world it's a matter providing it in such a way that creates business value that does enable and foster that growth of the community because nothing is better than having two or three or four or five million developers hacking away at my software to deliver better business value to my customers. The commercial side is going to be around the support, right? The enterprise customers would want to know that when bump goes in the night I've got someone I can pay to support my systems. And that's really what SUSE is about protecting our install base. Ensuring that we get them live, all the time every day and keep them running frictionlessly across their IT department. >> Now there's another model, the so-called open core model that holds that, the future is actually proprietary on top of an open base. So are you saying that you don't think that's a good model? >> I don't know, jury's out. Next time that you come to our event which is going to be in March, in Dublin. We're doing our SUSECON conference. Leave that question for me and I'll have an answer for you. I'm pontificating. >> Well I did and-- >> It's a date. The 12th of March. >> It's certainly working for Amazon. I mean, you know, Amazon's criticized for bogarting open source but Redshift is built on open source I think Aurora is built on open source. They're obviously making a lot of money. Your open core model failed for cloud era. Hortonworks was pure, Hortonworks had a model like, you know, you guys and RedHat and that didn't work and now that was kind of profitless prosperity of Hadoop and maybe that was sort of an over head-- >> I think our model, the future's open-source no question. It's just what level of open source within the sack do we keep proprietary or not, it's the case maybe, right? Do we allow open source in the bottom or the top or do we put some proprietary components on top to preserve and protect like an umbrella the core of which is open source. I don't know, we're thinking about that right now. We're trynna think what our future looks like. What the model should look like in the future for the industry. How can we service our customers best. At the end of the day, it's satisfying customer needs and solving business problems. If that's going to be, pure open source or open source with a little bit of proprietary to service the customer best that's what we're all going to be after, aren't we? >> So, there's no question that the innovation model is open source. I mean, I don't think that's a debate, the hard part is. Okay, how do you make money? A bit of open source for you guys. I mean, are you using open source technologies presumable you are, everybody is but-- >> So we're very open API's, who joined three years ago. We joined openapi.org. And so we've been one of the the leading ERP companies in the industry on publishing open API's and then we do a lot of customization work with our community and all of that's going on in GitHub. And so it's all open source, it's all out there for people who want it. Not everybody wants to be messing around in the core of a transaction engine and that's where you get into you know, the sort of the core argument of, you know which pieces should be people modifying? Do you want people in the kernel? Maybe, maybe not. And, you know, this is not my area of expertise so I'll defer to Melissa. Having people would be able to extend things in an open source model. Having people be able to find a library of customizations and components that can extend Acumatica, that's obviously a good thing. >> I mean, I think you hit on it with developers. I mean, that to me is the key lever. I mean, if I were a VM where I'd hire you know, 1000, 2000 open source software developers and say, "Go build next-generation apps and tools "and give it away." And then I'd say, "Okay, Michael Dell make you a hardware "run better in our software." That's a business model, you can make a lot of money-- >> 100% and we're, you know, we're going to be very acquisitive right now, we're looking for our future, right? We're looking to make a mark right now and where do we go next? How can we help predict the outcome next step in the marketplace when it pertains to, you know, the core of applications and the delivery mechanism in which we want to offer. The ease of being able to get thousands of mainframe customers with complex enterprise applications. Let's say, for example to the cloud. And a part of that is going to be the developer network. I mean, that's a really really big important segment for us and we're looking at companies. Who can we acquire? What's the business outcome? And what the developer networks look like. >> So Cloud and Edge, here got to be two huge opportunities for you, right? Again, it's all about developers. I think that's the right strategy at the Edge. You see a lot of Edge activity where somebody trying to throw a box at the Edge with the top down, in a traditional IT model. It's really the devs up, where I think-- >> It is, it is the dev ups, you're exactly right. Exactly right. >> Yeah, I mean, Edge is fascinating. That's going to be amazing what happens in the next 10 years and we don't even know, but we ship a construction edition we've got a customer that we're working with that's instrumenting all of their construction machinery on something like a thousand construction sites and feeding the sensor data into a Acumatica and so it's a way to keep track of all the machines and what's going on with them. You know, obviously shipping logistics the opportunity to start putting things like, you know, RFID tags on everything an instrument to all of that, out at the Edge. And then the issue is you get this huge amount of data and how do you process that and get the intelligence out of it and make the right decisions. >> Well, how do you? When data is plentiful, insights, you know, aren't is-- >> Yeah, well I think that's where the machine learning breakthroughs are going to happen. I mean, we've built out a team in the last three years on machine learning, all the guys who've been talking about Amazon, Microsoft, Google are all putting out machine learning engines that companies can pick up and start building models around. So we're doing one's around, you know inventory, logistics, shipping. We just release one on expense reports. You know, that really is where the innovation is happening right now. >> Okay, so you're not an inventor of AI you're going to take those technologies apply 'em to your business. >> Yeah, we don't want to be the engine builder we want to be the guys that are building the models and putting the insight for the industry on top that's our job. >> All right Melissa, we'll give you the final word and IFS World 2019, I think, is this your first one? >> It's my first one, yeah-- >> We say bumper sticker say when your truck's are pulling away or-- (laughs) >> A bumper sticker would say, "When you think about the future of open source "think about SUSE." (laughing) >> Dave: I love it. >> I'd say in the event, I mean, I'm super-impressed I think it's the group that's here is great the customers are really enthused and you know, I have zero bias so I'm just giving you my perspective. >> Yeah, I mean the ecosystem is robust here, I have to say. I think they said 400 partners and I was pleasantly surprised when I was walking around last-- >> This is your second one, isn't it? >> It's theCubes second one, my first. >> Oh your first, all right, well done. And so what do you think? Coming back? >> I would love to come back. Especially overseas, I know you guys do a bunch of stuff over seas. >> There you go, he wants to travel. >> Dublin in March? >> March the 12th. >> Dublin is a good place for sure so you're doing at the big conference? >> Yep, the big conference center and it's-- >> That is a great venue. >> And not just because the green thing but it's actually because (laughs). >> No, that's a really nice venue, it's modern It's got, I think three or four floors. >> It does, yeah yeah, we're looking forward to it. >> And then evening events at the, you know, the Guinness Storehouse. >> There you go. >> Exactly right. So we'll look forward to hosting you there. >> All right, great, see you there. >> We'll come with our tough questions for you. (laughing) >> Thanks you guys, I really appreciate your time. >> Thanks very much. >> Thank you for watching but right back, right after this short break you're watching theCube from IFS World in Boston be right back. (upbeat music)

live from Las Vegas it's the queue covering del technology's world 2019 brought to you by Dell technologies and it's ecosystem partners everyone welcome back to the cubes live coverage here in Las Vegas we are here for Dell technology rules 2019 got two sets I'm John Faraday Volante my co-host Dave day to three days of wall-to-wall coverage I've got a great guest December the president of client Solutions Group at Dell technologies Sam handles all of the big edge machines like the PCs my machine here and other cool stuff Sam thanks for joining us today appreciate it thank you guys for having me so one of the themes that we're seeing I'll see through the transformation going back when Michael went private buys EMC new puzzle pieces this is growing and scaling and one of the big surprises or not surprises is the cloud growth and them data grow that's been fueling a lot of existing businesses the client business one of them that you run yeah as do extremely well the numbers are looking good new machines you know the PC revolution continues evolving that's the state of the art what's the current state of the business give us an update hey so like you said the business is doing really well I'm excited this year we'll have our 35th birthday for Dell and the PC business the business I lead at Dell is where it all started 35 years ago in a dorm room at University of Texas now a forty three billion dollar business it is just a part of Dell so we've become a lot more but growing double digits we've seen a resurgence in the edge and I think like you said one of the things I'm seeing as I talk to companies they're almost seeing that edge is the secret weapon as we talk about all this transformation because getting great employees is the challenge if you want your business to lead in an industry and as we go talk to companies and we talked to Jen Expo we talked to Millennials we talked to Gen Z getting them armed with a great piece of technology where they can be productive in a job and help make a difference in a company or career that's what they want to go and do they want that more than drinks in the break room they want that more than volleyball courts outside and when companies are able to do that with our PC products at the edge they get great people in who helped that company be more successful so we're seeing a really good growth and we're we're dedicated to doing some exciting products for people and it's not easy to I just want to unpack the dynamics between the two worlds that go on one is making the machines go faster smaller less expensive so more horsepower lower prices higher functionality and then the integration to get that kind of a seamless works work lifestyle balance where you got consumer business all kind of blending together where you got to connect the networks you got it you can go to work at Starbucks here in once in a while you got to have all this stuff in it working together with what used to be the big iron back-end systems oh yes oh yeah so you got to you've got two jobs it's true what how do you balance that other different teams or different approaches what's the focus you know we we look at a couple things internally we have really focused on not just the hardware design that we're putting together and the speeds and feeds and we can do that great you take our you know our gaming business we have a we were showing off in the alien you can go over to a alien where a kind of gaming section we have here we have things that have more than 300 watts of power for CPUs and graphics in it feels to us if you went back in time it's super compact about what you used to have it's not anything like the latest XPS products I see you guys using there but we can design that kind of power into the systems and then we're focused on the experience we bring alive for people so you think about working with partners I'm working with services teams working with Microsoft working with VMware around how we bring alive the things people want to do on the consumer side like one thing we see people more people now watch TV and pcs then watch TV on TV oh it's like a great experience it's pretty headphones and nobody's bothering ya it's it's pretty good the other the other thing that's interesting I've switched all my viewing that way because we figured out the younger generations that that is even more true for them so in my millennial or gen Z fashion I've started a hundred percent of my TV viewing it's on a PC but it's a great way to do it we've done experience around that with audio video streaming that we go how do we bring that alive same thing on gaming gaming space I want to show you guys hopefully in a couple minutes we can talk about some of the latitudes we announced here but we've done that in the workspace of people want to be productive immediately they want a tool that lets them do that and we said how do we put technology and software and capability together to allow them to have that kind of experience they want that what if some of the things you announced today and you know what's uh what are the exciting parts of them so we brought a are we announced our new latitude lineup so you see from top to bottom some really amazing looking pcs and one of the things if you guys get that look you little high or we go to guys can you guys see that so awesome looking PC the other thing is if you take a look at this we built in different kind of capabilities that allow allow really fast log into the system so there's an Express Express login Express sign-in capability that under no under kind of infrared lights sensors you can basically recognize it recognizes when you walk up to that system it will log you into the system automatically so you don't have to touch the screen the keyboard it all saves you that kind of instant productivity you turn around walk away it'll sense when you're there and when you're not there will log you out of the system we also have something we call Express sign Express charge on this system so people are on the go some of the stats we were sharing when you think about audience here people are working in different offices people are working on the road John you were saying people are working in Starbucks how do we allow you to quickly you plug that in you can get 80% charge in an hour you can get 35% charge in 20 minutes so allow you to get up and going really quickly but basically designing some pretty awesome systems that if you go look at what some of the press is saying about this stuff of finally putting a business system in people's hands that users are gonna covet so we did cool stuff with Alienware we've done that with our XPS product we said we need to bring that into the commercial space so people have really cool tools to get these great reviews just to give a little shout out to props to you guys getting some good reviews also it's it's it's good tailwind for you that Apple is kind of struggling with their MacBooks when the prices are high people are now coming back and look into the PC in fact my son is a big-time gamer you depreciate it the acronym is called PCM R which stands for PC master-race because you know the gamers like to be hardcore on the PC gaming huge growth area alien and where is doing great but people people look at whether it's gamer or work you seeing the gamers are guys I think of canary in the coalmine they're I think a leading indicator of a trend around I want a relationship with my device and I want I want to be able to have things available whether it's mobile or or PC or gaming so it's a little bit more intimacy and then there's also a pressure we're seeing on the trend line around augmented reality built into the machine so you start to see again better monitors for K connections you know better immersive yep either whether it's single sign-on authentication to just overall experience that's a big trend yeah and I think you said it on gaming we've built a community around our Alienware brand we've built entry level gaming systems we've turned gaming that we've been in for 23 years with alien we're now at 3 billion dollar business inside our Dell PC business and there's a lot of affinity for people who going hey turn out awesome powered systems and deliver me a kind of experience and speed that I want to win in the game you know it's the same thing though on the commercial side of going people want tools when they're coming to work don't let them do a great job in in their business I know dad wants this question but I want to get one more thing out PC if people talk about other people don't want to hear about speeds and fees when it comes to machines people on a gear speeds and feeds how many cores is there a graphics accelerator in there is there a GPU I need to get AI what's going on with the inside the specs give us the latest state of the art oh we have like so you can look at core explosion in PCs is great the thing that I really like is all these systems now you see USB connectivity so you can put your just people before we're going hey the display is going away so you walk around see we have 49 inch curved displays we have huge 43 inch displays you can get four display side-by-side you can get to 27 inch displays side-by-side I go to trading floors around the world they're stacking two and three of these displays next to each other you can power that out coming out of the USB port on your system you can power that with the graphics on the system and then we have everything up to go to Alienware which is huge core counts but though the power the watts we literally have two huge power supplies - 300 watt power supplies that you're plugging into the back of our gaming desktops it will almost consume the 15 amps that you have in your house circuit to power that system and we fit that in a you know it's about an eight pound system today that's maybe an inch and inch and a bit thick that if you go back to legacy pcs we're talking about we're almost at 2020 in a new decade if you go back to the start of this decade that was like run in the middle average PC that we're now fitting incredible power into so I think all that and GPUs are up and what's the status on because graphics processors has become a big latest great racing graphics processors that we're now waiting the thing that's exciting to me is on the games think we'll see games now catch up to 2000 series GPUs from laying the race race and I think it's an important innovation because that's going to really come and help the gaming but also it's starting to bleed into some other creative areas we're way to get you stocked up with some alien we're here walking out of it I'm waiting for a display the curtains excited I want the curb display no we we see it in games we also see it in advertising so it's amazing the stuff you can go and do it say render a vehicle in a photo shoot that you used to have to go to a remote location and basically ray-tracing allows you to render that scene by putting individual beams of light into that into the interact with all the geometry that you have and it shows what it'll basically draw that picture for you so you get all kinds of nuances of shadows other images flickers and reflections that are just amazing and lifelike realism so we're gonna see that in games you see graphics designer is doing that in TV commercials and in print ads and you do it without ever having to touch the physical product which it's hugely time and processor compute graphics intensive to go and do that but you're now seeing us able to do that on a I brought in a precision workstation it's a little bit bigger than this and it's a horse-collar on the machines can handle that ray tracing that's the whole point yes guys are connecting the edge with your your laptops your your your your your PC's what are you doing a stress test them on the edge torture test you're doing any fun stuff like dropping them from the building and throwing flames at them and yeah what we do we have some fun labs so in Austin Texas we have a lot of fun whether it's dropping systems which is not unrealistic of what happens in the environment we actually find our hardest users are students in education environments so we've commercial really important because like the XPS I see you guys are using people will take a little bit better care of the stuff when it's their own dollars that went to that but you know the the work system gets thrown in a bag it gets thrown in in the back of the car so you look at temperature testing cold hot drops waters coffee in the office environment water in the office environment that gets thrown against it so we do all that kinds of stuff but we've learned a lot from students and we do things like little micro drop tests because you had literally we had systems that got not banged against the floor but the slammd in the bag by a student you know thousands of times across the lifecycle that we had to go and change how we engineer some of the connectors and how the systems are set up just to make them really durable so whatever you talk about your business a little bit John knows I'd love to get into the business that I want to explore the importance of the the client business to Dell it's about half of your revenue just a little under half of the revenue obviously lower margin than some of the enterprise businesses but it's critical and this is what the company was founded on it absorbs a lot of the corporate overhead it's growing what's going on in the business units dollars what can you share with us yes so forty-three billion dollar business grew double digits last year we had for the last five quarters we've led the industry in growth which is a reflection of our real focus on what customers are looking for and delivering great products to them we have 25 quarters of gaining share 25 consecutive quarters so we have a really good run going in the business we look at this year I see the industry continues to consolidate top three players in our industry are around less than 65% share kind of 63 and change and in most industries you see them as they've become more mature you see them more consolidated than than where we are today it's been consolidating last six years we've gained six hundred basis points a share we think is Michael and our team have invested in great designs and great experiences to customers there's lots of runway to continue growth here and you know that's what we're the thing that gets me excited in our engineers is turning out products that our customers go and love and as we went private you really began to transform this company we said we want to be the best bar no one in this industry and we've really you see that in the Alienware you see that in XPS you see that what we're doing in the latitude space we continue to set a very high bar for ourselves in the growth so people tend to keep their laptops longer you got to sell these cloud apps and it's great as a user you have to replace your your laptop every you know 15 months yeah I'm sure you'd love us to do that but so where's the growth coming from is that new applications is it obviously share gains and and how will it continue yeah well we see it more the premium space is growing a lot where people have said hey I want to trade up whether that's the the gamer like your son a user on XPS who wants a really mobile system that they can throw in their backpack or throw in their purse and take take with them it's interesting in the commercial space we actually see some of the highest end systems that we sell in our work station business have the fastest turnover and change rate because when you can add more cores more horsepower to that and go my expensive engineer designing airplanes or my graphics design or doing advertisements or videos for the company can now be more productive people go I want to spend the $3,000 because in comparison to the salary and the time I'm saving I'll get the best talent they're happier because it gets done faster and my business gets more done that's where they're actually switching the system's over so it's to us to make that easier and then the other thing that we're doing that's really interesting and that we announced this week is we're working across our businesses so we've gotten out of just the you know look at the hardware but we're going how do I partner with the services business how do I partner with VMware and start to make the whole process that get in technology and users hands easier because if you look at if you look at companies today 75% of their spend in our space is on all the stuff other than the hardware and the devices so it's like planning going and doing deployment where I have technical people literally with box cutters opening boxes putting new images on systems they struggle to keep systems up-to-date how do I manage support them take all the calls that are coming in you start looking at that and you go there's a way we've we've always tried to redo it but it was like shuffle around where the people are and hey I can take your people and do the thing for you cheaper or maybe not because then you start getting charged for all these crazy change things now we're going pay with software and services I can start doing this in an automated intelligent way that makes it a lot easier so I can go when I want you me any of us to have an awesome system go start taking that other cost out make it easy and fast and then you go the system can be updated someone can go I get better technology in my users hands and hey I save money doing it because I'm not spending on this other crazy stuff hopefully invest a little more here but also invest in the infrastructure transformation they have going on 5% is seventy five fifty five percent the buckets what a hundred billion is that fair enough in commercial space if we throw phones printers everything in there's about two hundred billion dollars in companies spent on hardware four hundred billion on other stuff if you look at pcs that ratio it's a bunch of the two hundred billion and it's in a billion you can attack with just better services and automation and things like that's and that's what we're doing like with VMware and with our services team with going like how can i integrate take VMware software integrate with our Factory and go when your new system shows up it has your apps and your image on it you plug in you're literally logged in doing final last mile customization so think new employee rather than having to download a bunch of stuff or an IT person comes and sets up your system you get that system with what you need your profile which we figured out we've been figured out hey here's the kind of users aren't you are you're a really mobile person we're going to want to get you this system you're plugged in with that new system going in minutes and it eliminates that sneakernet of a bunch of people doing it and turns it into intelligence and sauce so that's tens of billions in Tam expansion yeah absolutely yes I think it's we look at is hey it's it's a good opportunity for us to expand and then it saves customers it saves them time and money it makes it easier you're innovating on two fronts making a great device more horsepower to get that step-up function on new kinds of productivity that warrant the price increase for the user and then all that integration back-end yes to innovation tracks big time yeah and then we have to keep pushing on the physical hardware and that's where I go if you went back in time ten years ago you know it's like the systems were big and thick we never imagined they would be this slim this powerful I look at the future and go when you think about AR VR you think about more natural interaction with systems with voice and with breaking pen really a first user class with the keyboard I think there's a lot of opportunity going forward we want to do stuff that will cause people to want to buy new systems so it's a good challenge to have well we'll do a deal for you with the cube special sponsorship consideration for the curve monitors and all the crates thanks for coming on and we got ray tracing into the cube conversation here Sam thanks for come on share and congratulations new success PCs getting stronger faster new productivity gains with ray tracing all this other stuff happening this is what cloud and data does it's the cue bringing you all the content here's the content cannon two sets be right back with more coverage here at Dell technology world after the short break [Music]

(upbeat jazz music) >> Woman: From our studio's, in the heart of Silicon Valley Palo Alto California this is a CUBE conversation. >> John: Hello and welcome to this CUBE conversation here, exclusive coverage of Google Next 2019. I'm John Furrier, host of theCUBE. Big Google Cisco news, we're here with KD who's the vice president of the data center for compute for Cisco and Kip Compton, senior vice president of Cloud Platform and Solutions Group. Guys, welcome to this exclusive CUBE conversation. Thanks for spending the time. >> KD: Great to be here. >> So Google Next, obviously, showing the way that enterprises are now quickly moving to the cloud. Not just moving to the cloud, the cloud is part of the plan for the enterprise. Google Cloud clearly coming out with a whole new set of systems, set of software, set of relationships. Google Anthos is the big story, the platform. You guys have had a relationship previously announced with Google, your role in joint an engineering integrations. Talk about the relationship with Cisco and Google. What's the news? What's the big deal here? >> Kip: Yeah, no we're really excited. I mean as you mentioned, we've been working with Google Cloud since 2017 on hybrid and Multicloud Kubernetes technologies. We're really excited about what we're able to announce today, with Google Cloud, around Google Cloud's new Anthos system. And we're gonna be doing a lot of different integrations that really bring a lot of what we've learned through our joint work with them over the last few years, and we think that the degree of integration across our Data Center Portfolio and also our Networking and Security Portfolios, ultimately give customers one of the most secure and flexible Multicloud and hybrid architectures. >> One of the things we're seeing in the market place, I want to get your reactions to this Kip because I think this speaks to what's going on here at Google Next and the industry, is that the company's that actually get on the Cloud wave truly, not just say they're doing Cloud, but ride the wave of the enterprise Cloud, which is here. Multicloud is big conversation. Hybrids and implementation of that. Cloud is big part of it, the data center certainly isn't going away. Seeing a whole new huge wave. You guys have been big behind this at Cisco. You saw what the results are with Microsoft. Their stock has gone from where it was really low to really high because they were committed to the Cloud. How committed is Cisco to this Cloud Wave, what specifically are you guys bringing to the table for Enterprises? >> Oh we're very committed. We see it as the seminal IT transformation of our time, and clearly on of the most important topics in our discussions with CIO's across our customer base. And what we're seeing is, really not as much enterprises moving to the Cloud as much as enterprises extending or expanding into the Cloud. And their on-prem infrastructures, including our data centers as you mentioned, certainly aren't going away, and their really looking to incorporate Cloud into a complete system that enables them to run their business and their looking for agility and speed to deliver new experiences to their employees and to their customers. So we're really excited about that and we think sorta this Multicloud approaches is absolutely critical and its one of the things that Google Cloud and Cisco are aligned on. >> I'd like to get this couple talk tracks. One is the application area of Multicloud and Hybrid but first lets unpack the news of what's going on with Cisco and Google. Obviously Anthos is the new system, essentially its just the Cloud platform but that's what they're calling it, Googles anthem. How is Cisco integrating into this? Cause you guys had great integration points before Containers was a big bet that you guys had made. >> Kip: That's right. >> You certainly have, under the covers we learned at Cisco Live in Barcelona around what's going on with HyperFlex and ACI program ability, DevNet developer program going on. So good stuff going on at Cisco. What does this connect in with Google because ya got containers, you guys have been very full throttle on Kubernetes. Containers, Kubernetes, where does this all fit? How should your customers understand the relationship of how Cisco fits with Google Cloud? What's the integration? >> So let me start with, and backing it with the higher level, right? Philosophically we've been talking about Multicloud for a long time. And Google has a very different and unique view of how Cloud should be architected. They've gone 'round the open source Kubernetes Path. They've embraced Multicloud much more so then we would've expected. That's the underpinning of the relationship. Now you bring to that our deep expertise with serving Enterprise IT and our knowledge of what Enterprise IT really needs to productize some of these innovations that are born elsewhere. You get those two ingredients together and you have a powerful solution that democratizes some of the innovations that's born in the Cloud or born elsewhere. So what we've done here with Anthos, with Google HyperFlex, oh with Cisco's HyperFlex, with our Security Portfolio, our Networking Portfolio is created a mechanism for Enterprise ID to serve their constituent developers who are wanting to embrace Containers, readily packaged and easily consumable solution that they can deploy really easily. >> One of the things we're hearing is that this, the difference between moving to the Cloud versus expanding to and with the Cloud, and two kind of areas pop up. Operational's, operations, and developers. >> Kip: Yep. >> People that operate IT mention IT Democratizing IT, certainly with automation scale Cloud's a great win there. But you gotta operate it at that level at the same time serve developers, so it seems that we're hearing from customers its complicated, you got open source, you got developers who are pushing code everyday, and then you gotta run it over and over networks which have security challenges that you need to be managing everyday. Its a hardcore op's problem meets frictionalist development. >> Yeah so lets talk about both of these pieces. What do developers want? They want the latest framework. They want to embrace some of the new, the latest and greatest libraries out there. They want to get on the cutting edge of the stuff. Its great to experiment with open source, its really really hard to productize it. That's what we're bringing to the table here. With Anthos delivering a manage service with Cisco's deep expertise and taking complex technologies, packaging it, creating validated architectures that can work in an enterprise, it takes that complexity out of it. Secondly when you have a enterprise ID operator, lets talk about the complexities there, right? You've gotta tame this wild wild west of open source. You can't have drops every day. You can't have things changing every, you need a certain level of predictability. You need the infrastructure to slot in to a management framework that exists in the dollar center. It needs to slot into a sparing mechanism, to a workflow that exists. On top of that, you've got security and networking on multiple levels right? You've got physical networking, you've got container networking, you've got software define networking, you've got application level networking. Each layer has complexity around policy and intent that needs to marry across those layers. Well, you could try to stitch it together with products from different vendors but its gonna be a hot stinking mess pretty soon. Driving consistency dry across those layers from a vendor who can work in the data center, who can work across the layers of networking, who can work with security, we've got that product set. Between ACI Stealthwatch Cloud providing the security and networking pieces, our container networking expertise, HyperFlex as a hyper converge infrastructure appliance that can be delivered to IT, stood up, its scale out, its easy to deploy. Provides the underpinning for running Anthos and then, now you've got a smooth simple solution that IT can take to its developer and say Hey you know what? You wanna do containers? I've got a solution for you. >> And I think one of the things that's great about that is, you know just as enterprise's are extending into the Cloud so is Cisco. So a lot of the capabilities that KD was just talking about are things that we can deliver for our customers in our data centers but then also in the Cloud. With things like ACI Anywhere. Bringing that ACI Policy framework that they have on-prem into the Cloud, and across multiple Clouds that they get that consistency. The same with Stealthwatch Cloud. We can give them a common security model across their on-prem workloads and multiple public Cloud workload areas. So, we think its a great compliment to what Google's doing with Anthos and that's one of the reasons that we're partners. >> Kip I want to get your thoughts on this, because one of the things we've seen over the past years is that Public Cloud was a great green field, people, you know born in the Cloud no problem. (Kip laughs) And Enterprise would want to put workloads in the Cloud and kind of eliminate some of the compute pieces and some benefits that they could put in the cloud have been great. But the data center never went away, and they're a large enterprise. It's never going away. >> Kip: Yep. >> As we're seeing. But its changing. How should your customers be thinking about the evolution of the data center? Because certainly computes become commodity, okay need some Cloud from compute. Google's got some stuff there, but the network still needs to move packets around. You still got to store stuff, you still need security. They may not be a perimeter, but you still have the nuts and bolts of networking, software, these roles need to be taking place, how should these customers be thinking about Cloud, compute, integration on data primus? >> That is a great point and what we've seen is actually Cloud makes the network even more important, right? So when you have workloads and staff services in the Cloud that you rely on for your business suddenly the reliability and the performance and latency of your networks more important in many ways than it was before, and so that's something any of our customers have seen, its driving a lot of interest and offerings like SD-WAN from Cisco. But to your point on the data center side, we're seeing people modernize their data centers, and their looking to take a lot of the simplicity and agility that they see in a Public Cloud and bring it home, if you will, into the data center. Cause there are lots of reasons why data centers aren't going away. And I think that's one of the reasons we're seeing HyperFlex take off so much is it really simplifies multiple different layers and actually multiple different types of technology, storage, compute, and networking together into a sort of a very simple solution that gives them that agility, and that's why its the center piece of many of our partnerships with the Public Cloud players including Anthos. Because it really provides a Cloud like workload hosting capability on-prem. >> So the news here is that you guys are expanding your relationship with Google. What does it mean? Can you guys summarize the impact to your customers and the industry? >> Well I think that, I mean the impact for our customers is that you've two leaders working together, and in fact they're two leaders who believe in open technology and in a Multicloud approach. And we believe that both of those are fundamentally more aligned with our customers and the market than other approaches and so we're really excited about that and what it means for our customers in the future. You know and we are expanding the relationship, I mean there's not only what we're doing with Google Cloud's Anthos but also associated advances we've made about expanding our collaboration actually in the collaboration area with our Webex capabilities as well as Google Swed. So we're really excited about all of this and what we can enable together for our customers. >> You guys have a great opportunity, I always say latency is important and with low latency, moving stuff around and that's your wheelhouse. KD, talk about the relationship expanding with Google, what specifically is going on? Lets get down and dirty, is it tighter integration? Is it policy? Is it extending HyperFlex into Google? Google coming in? What's actually happening in the relationship that's expanding? >> So let me describe it in three ways. And we've talked a little bit about this already. The first is, how do we drive Cloud like simplicity on-prem? So what we've taken is HyperFlex, which is a scale out appliance, dead simple, easy to manage. We've integrated that with Anthos. Which means that now you've got not only a hyper conversion appliance that you can run workloads on, you can deliver to your developers Kubernetes eco system and tool set that is best in class, comes from Google, its managed from the Cloud and its not only the Kubernetes piece of it you can deliver the silver smash pieces of it, lot of the other pieces that come as part of that Anthos relationship. Then we've taken that and said well to be Enterprise grade, you've gotta makes sure the networking is Enterprise grade at every single layer, whether that is at the physical layer, container layers, fortune machine layer, at the software define networking layer, or in the service layer. We've been working with the teams on both sides, we've been working together to develop that solution and bring back the market for our customers. The third piece of this is to integrate security, right? So Stealthwatch Cloud was mentioned, we're working with the other pieces of our portfolio to integrate security across these offerings to make sure those flows are as secure as can be possible and if we detect anomalies, we flag them. The second big theme is driving this from the Cloud, right? So between Anthos, which is driving the Kubernetes and RAM from the Cloud our SD-WAN technology, Cisco's SD-WAN technology driven from the Cloud being able to terminate those VPN's at the end location. Whether that be a data center, whether that be an edge location and being able to do that seamlessly driven from the Cloud. Innerside, which takes the management of that infrastructure, drives it from the Cloud. Again a Cisco innovation, first in the industry. All of these marry together with driving this infrastructure from the Cloud, and what did it do for our eventual customers? Well it gave them, now a data center environment that has no boundaries. You've got an on-prem data center that's expanding into the Cloud. You can build an application in one place, deploy it in another, have it communicate with another application in the Cloud and suddenly you've kinda demolished those boundaries between data center and the Cloud, between the data center and the edge, and it all becomes a continuum and no other company other than Cisco can do something like that. >> So if I hear you saying, what you're saying is you're bringing the software and security capabilities of Cisco in the data center and around campus et cetera, and SD-WAN to Google Cloud. So the customer experience would be Cisco customer can deploy Google Cloud and Google Cloud runs best on Cisco. That's kinda, is that kind of the guiding principles here to this deal? Is that you're integrating in a deep meaningful way where its plug and play? Google Cloud meets Cisco infrastructure? >> Well we certainly think that with the work that we've done and the integrations that we're doing, that Cisco infrastructure including software capabilities like Stealthwatch Cloud will absolutely be the best way for any customer who wants to adopt Google Cloud's Anthos, to consume it, and to have really the best experience in terms of some of the integration simplicity that KD talked about but also frankly security's very important and being able to bring that consistent security model across Google Cloud, the workloads running there, as well as on-prem through things like Stealthwatch Cloud we think will be very compelling for our customers, and somewhat unique in the marketplace. >> You know one of the things that interesting, TK the new CEO of Google, and I had this question to Diane Green she had enterprise try ops of VM wear, Google's been hiring a lot of strong enterprise people lately and you can see the transformation and we've interviewed a lot of them, I have personally. They're good people, they're smart, and they know what they're doing. But Google still gets dinged for not having those enterprise chops because you just can't have a trajectory of those economy of scales over night, you can't just buy your way into the enterprise. You got to earn it, there's a certain track record, it seems like Google's getting a lot with you guys here. They're bringing Cloud to the table for sure for your customer base but you're bringing, Cisco complete customer footprint to Google Cloud. That seems to be a great opportunity for Google. >> Well I mean I think its a great opportunity for both of us. I mean because we're also bringing a fantastic open Multicloud hybrid solution to our customer base. So I think there's a great opportunity for our customers and we really focus on at the end of the day our customers and what do we do to make them more successful and we think that what we're doing with Google will contribute to that. >> KD talk about, real quickly summarize what's the benefits to the customers? Customers watching the announcements, seeing all the hype and all the buzz on this Google Next, this relationship with Cisco and Google, what's the bottom line for the customer? They're dealing with complexity. What are you guys solving, what the big take away for your customers? >> So its three things. First of all, we've taken the complexity out of the equation, right? We've taken all the complexity around networking, around security, around bridging to multiple Clouds, packaged it in a scale out appliance delivered in an enterprise consistent way. And for them, that's what they want. They want that simplicity of deployment of these next gen technologies, and the second thing is as IT serves their customers, the developers in house, they're able to serve those customers much better with these latest generation technologies and frameworks, whether its Containers, Kubernetes, HDL, some of these pieces that are part of the Anthos solution. They're able to develop that, deliver it back to their internal stakeholders and do it in a way that they control, they feel comfortable with, they feel their secure, and the networking works and they can stand behind it without having to choose or have doubts on whether they should embrace this or not. At the end of the day, customers want to do the right things to develop fast. To be nimble, to act, and to do the latest and greatest and we're taking all those hurtles out of the equations. >> Its about developers. >> It is. >> Running software on secure environments for the enterprise. Guys that's awesome news. Google Next obviously gonna be great conversations. While I have you here I wanna get to a couple talk tracks that are I important around the theme's recovering around Google Next and certainly challenges and opportunities for enterprises that is the application area, Multicloud, and Hybrid Cloud. So lets start with application. You guys are enabling this application revolution, that's the sound bites we hear at your events and certainly that's been something that you guys been publicly talking about. What does that mean for the marketplace? Because certain everyone's developing applications now, (Kip laughs) you got mobile apps, you got block chain apps, we got all kinds of new apps coming out all the time. Software's not going away its a renaissance, its happening. (Kip laughs) How is the application revolution taking shape? How is and what's Cisco's roll in it? >> Sure, I mean our role is to enable that. And that really comes from the fact that we understand that the only reason anyone builds any kind of infrastructure is ultimately to deliver applications and the experiences that applications enable. And so that's why, you know, we pioneered ACI is Application Centric Infrastructure. We pioneered that and start focusing on the implications of applications in the infrastructure any years ago. You know, we think about that and the experience that we can deliver at each layer in the infrastructure and KD talked a little bit about how important it is to integrate those layers but then we also bring tools like AppDynamics. Which really gives our customers the ability to measure the performance of their applications, understand the experience that they're delivering with customers and then actually understand how each piece of the infrastructure is contributing to and affecting that performance and that's a great example of something that customers really wanna be able to do across on-prem and multiple Clouds. They really need to understand that entire thing and so I think something like App D exemplifies our focus on the application. >> Its interesting storage and compute used to be the bottle necks in developers having to stand that up. Cloud solved that problem. >> Kip: That's right. >> Stu Miniman and I always talk about on theCUBE networking's the bottle neck. Now with ACI, you guys are solving that problem, you're making it much more robust and programmable. >> It is. >> This is a key part for application developers because all that policy work can be now automated away. Is that kinda part of that enablement? >> It sure is. I mean if you look at what's happening to applications, they're becoming more consumerized, they're becoming more connected. Whether its micro services, its not just one monolithic application anymore, its all of these applications talking to each other. And they need to become more secure. You need to know what happens, who can talk to whom. Which part of the application can be accessed from where. To deliver that, when my customer tell me listen you deliver the data center, you deliver security, you deliver networking, you deliver multicloud, you've got AppDynamics. Who else can bring this together? And that's what we do. Whether its ACI that specifies policy and does that programmable, delivers that programmable framework for networking, whether its our technologies like titration, like AppDynamics as Kip mentioned. All of these integrate together to deliver the end experience that customers want which is if my application's slow, tell me where, what's happening and help me deliver this application that is not a monolith anymore its all of these bits and pieces that talk to each other. Some of these bits and pieces will reside in the Cloud, a lot of them will be on-prem, some of them will be on the edge. But it all needs to work together-- >> And developers don't care about that they just care about do I get the resources do I need, And you guys kinda take care of all the heavy lifting underneath the covers. >> Yeah and we do that in a modern programmable way. Which is the big change. We do it in intent based way. Which means we let the developers describe the intent and we control that via policy. At multiple levels. >> And that's good for the enterprises, they want to invest more in developing, building applications. Okay track number two, talk track number two Multicloud. its interesting, during the hype cycle of Hybrid Cloud which was a while, I think now people realize Hybrid Cloud is an implementation thing and so its beyond hype now getting into reality. Multicloud never had a hype cycle because people generally woke up one day and said yeah I got multiple Clouds. I'm using this over here, so it wasn't like a, there was no real socialization around the concept of Multicloud they got it right away. They can see it, >> Yep. >> They know what they're paying for. So Multicloud has been a big part of your strategy at Cisco and certainly plays well into what's happening at Google Next. What's going on with Multicloud? Why's the relation with Google important? And where do you guys see Multicloud going from a Cisco perspective? >> Sure enough, I think you're right. The latest data we saw, or have, is 94 percent of enterprises are using or expect to use multiple Clouds and I think those surveys have probably more than six points of potential error so I think for all intensive purposes its 100 percent. (John and KD laughing) I've not met a customer who's unique Cloud, if that's a thing. And so you're right, its an incredibly authentic trend compared with some of these things that seem to be hype. I think what's happening though is the definition of what a Multicloud solution is is shifting. So I think we start out as you said, with a realization, oh wait a second we're all Multicloud this really is a thing and there's a set of problems to solve. I think you're seeing players get more and more sophisticated in how they solve those problems. And what we're seeing is its solving those problems is not about homogenizing all the Clouds and making them all the same because one of the reasons people are using multiple Clouds is to get to the unique capabilities that's in each Cloud. So I think early on there were some approaches where they said okay well we're gonna put down like a layer across all these Clouds and try to make them all look the same. That doesn't really achieve the point. The point is Google has unique capabilities in Google Cloud, certainly the tenser flow capabilities are one that people point to. AWS has unique capabilities as well and so does Dajour. And so customers wanna access all of that innovation. So that kind of answers your question of why is this relationship important to us, its for us to meet our customers needs, we need to have great relationships, partnerships, and integrations with the Clouds that are important to our customers. >> Which is all the Clouds. >> And we know that Google Cloud is important. >> Well not just Google Cloud, which I think in this relationship's got my attention because you're creating a deep relationship with them on a development side. Providing your expertise on the network and other area's you're experts at but you also have to work with other Clouds because, >> That's right we do. >> You're connecting Clouds, that's the-- >> And in fact we do. I mean we have, solutions for Hybrid with AWS and Dejour already launched in the marketplace. So we work with all of them, and what our roll, we see really is to make this simpler for our customers. So there are things like networking and security, application performance management with things like AppDynamics as well as some aspects of management that our customers consistently tell us can you just make this the same? Like these are not the area's of differentiation or unique capabilities. These are area's of friction and complexity and if you can give me a networking framework, whether its SD-WAN or ACI Anywhere that helps me connect those Clouds and manage policy in a consistent way or you can give me application performance the same over these things or security the same over these things, that's gonna make my life easier its gonna be lower friction and I'm expecting it, since your Cisco, you'll be able to integrate with my own Prime environment. >> Yeah, so then we went from hard to simple and easy, is a good business model. >> Kip: Absolutely. >> You guys have done that in the past and you certainly have the, from routing, everything up to switches and storage. KD, but talk about the complexity, because this is where it sounds complex on paper but when you actually unpack the technologies involved, you know in different Cloud suppliers, different technologies and tools. Throw in open sources into the mix is even more complex. So Multicloud, although sounds like a simple reality, the complexities pretty significant. Can you just share your thoughts on that? >> It is, and that's what we excel. We excel, I think complexity and distilling it down and making it simple. One other thing that we've done is, because each Cloud is unique and brings some unique capabilities, we've worked with those vendors along those dimension's that they're really really passionate about and strong end. So for example, with Google we've worked on the container front. They are, maybe one of the pioneers in that space, they've certainly delivered a lot of technologies into that domain. We've worked with them on the Kubeflow front on the AI front, in fact we are one of the biggest contributors to the open source projects on Kubeflow. And we've taken those technologies and then created a simple way for enterprise IT to consume them. So what we've done with Anthos, with Google, takes those technologies, takes our networking constructs, whether its ACI Anywhere, whether its other networking pieces on different parts of it, whether its SD-WAN and so forth. And it creates that environment which makes an enterprise IT feel comfortable with embracing these technologies. >> You said you're contributing to Kubeflow. A lot of people don't look at Cisco and would instantly come to the reaction that you guys are heavily contributing into open source. Can you just share, you know, the level of commitment you guys are making to open source? Just get that out there, and why? Why are you doing it? >> Yeah. For us, some of these technologies are really in need for incubation and nurturing, right? So Kubeflow is early, its really promising technology. People, in fact there's a lot of buzz about AI-- >> In your contributing to Kubeflow, significantly? >> Yes, yeah. >> Cisco? >> We're number three contributor actually. Behind Google. >> Okay so you're up there? You're up at the top of the list? >> Yeah one of the top three. >> Top of the list. >> And why? Is this getting more collaborative? More Multicloud fabric-- >> Well I mean, again it comes back to our customers. We think Kubeflow is a really interesting framework for AI and ML and we've seen our customers that workload type is becoming more and more important to them. So we're supporting that because its something we think will help our customers. In fact, Kubeflow figures into how we think about Hybrid and Multicloud with Google and the Anthos system in terms of giving customers the ability to run those workloads in Google Cloud with TPU's or on-prem with some of the incredible appliances that we've delivered in the data centers using GPU's to accelerate these workings. >> And it also certainly is compatible with the whole Multicloud mission as well-- >> Exactly, yeah. >> That's right. >> So you'll see us, we're committed to open source but that commitment comes through the lens of what we think our customers need and want. So it really again it comes back to the customer for us, and so you'll see us very active in open source areas. Sometimes, I think to your point, we should be louder about that. Talk more about that but we're really there to help our customers. DevNet, DevNet Create that Susie Wee's been working on has been a great success. I mean we've witnessed it first hand, seeing it at the Cisco Live packed house. >> In Barcelona. >> You've got developers developing on the network its a really big shift. >> Yeah absolutely. >> That's a positive shift. >> Well its a huge shift, I think its natural as you see Cisco shifting more and more towards software you see much much more developer engagement and we're thrilled with the way DevNet has grown. >> Yeah, and networking guys in your target audience gravitates easily to software it seems to be a nice fit. So good stuff there. Third talk track, Hybrid. You guys have deep bench of tech and people on network security, networking security, data center, and all the things involved in the years and years of enterprise evolution. Whether its infrastructure and all the way through the facilities, lot of expertise. Now Hybrid comes onto the scene. Went through the little hype cycle, people now get it, you gotta operate across Clouds on-prem to the Cloud and now multiple Clouds so what's the current state of Cisco-Google relationship with Hybrid? How is that fitting in, Google Next and beyond? >> So let me tease that in the context of some history, right? So if we go back, say 10 years, virtualization was the bad word of the day. Things were getting virtualized. We created the best data center infrastructure for virtualization in our UCS platforms. Completely programmable infrastructure's code, a very programmable environment that can back a lot of density of virtual machines, right? Roll forward three or four years, storage and compute were getting unwieldily. There was complexity there to be solved. We created the category of converge infrastructure, became the leader of that category whether we work with DMC and other players. Roll forward another four or five years we got into the hyper conversion infrastructure space with the most performant ACI appliance on the market anywhere. And most performant, most consistent, deeply engineered across all the stacks. Can took that complexity, took our learnings and DNA networking and married it together to create something unique for the industry. Now you think, do other domains come together? Now its the Cloud and on-prem. And if that comes together we see similar kinds of complexity. Complexity in security, complexity in networking, complexity in policy and enforcement across layers. Complexity, frankly in management, and how do you make that management much more simple and consumerized? We're taking that complexity and distilling it down into developing a very simple appliance. So what we're trying to deliver to the customer is a simple appliance that they can stand and procure and set up much in the way that they're used to but now the appliance is scale out. Its much more Cloud like. Its managed from the Cloud. So its got that consumer modern feel to it. Now you can deliver on this a container environment, a container development environment, for your developer stakeholders. You can deliver security that's plumed through and across multiple layers, networking that's plumed through and across multiple layers, at the end of the day we've taken those boundaries between Cloud and data center and blown them away. >> And you've merged operational constructs of the old data center operations to Cloud like operations, >> Yeah. >> Everything's just a service, you got Microservices coming, so you didn't really lose anything, you'd mentioned democratizing IT earlier, you guys are bringing the HyperFlex to ACI to the table so you now can let customers run, is that right? Am I getting it right? >> That's right. Its all about how do you take new interesting technologies that are developed somewhere, that may have complexity because its open source and exchanging all the time or it may have complexity because it was not been for a different environment, not for the on-prem environment. How do you take that innovation and democratize it so that everybody, all of the 100's of thousands and millions of enterprise customers can use it and feel comfortable using it and feel comfortable actually embracing it in a way that gives them the security, gives them the networking that's needed and gives them a way that they can serve their internal stakeholders very easily. >> Guys thanks for taking the time for this awesome conversation. One final question, gettin you both to weigh in on, here at Google Next 2019, we're in 2019. Cloud's going a whole other level here. What's the most important story that customers should pay attention to with respect to expanding into the Cloud, taking advantage of the growing developer ecosystem as open source continues to go to the next level. What's the most important thing happening around Google Next and the industry with respect to Cloud and for the enterprise? >> Well I think certainly here at Google Next the Google Cloud's Anthos announcement is going to be of tremendous interest to enterprises cause as you said they are extending into the Cloud and this is another great option for enterprises who are looking to do that. >> Yeah and as I look at it suddenly IT has a set of new options. They used to be able to pick networking and compute and storage, now they can pick Kubeflow for AI or they can pick Kubernetes for container development, Anthos for an on-prem version. They're shopping list has suddenly gone up. We're trying to keep that simple and organized for them so that they can pick the best ingredients they can and build the best infrastructure they can, they can do it. >> Guys thanks so much. Kip Compton senior vice president Cloud Platform and Solutions Group and KD vice president of the Data Center compute group for Cisco. Its been exclusive CUBE conversation around the Google-Cisco big news at Google Next 2019 and I'm John Furrier thanks for watching. (upbeat jazz music)

>> Hello, and welcome to the special. Keep conversation here in Palo Alto, California John Furrier, Co-Host of the Cube. We're here with Jonathan Rosenberg, CTO chief technology officer and head of AI for Five9. Jonathan. Great. Great to see you. Thanks for coming in. >> Thanks. My pleasure to be here. >> So you've had a stellar career? Certainly. Technical career going way back to Lucent Technologies. Now here at Five9, Cisco along the way. You've been a really technical guru. You've seen the movie before. This's happening. Every wave of innovation, multiple ways you've been on. Now you're on the next wave, which is cloud AI, CTO Five9. Rapidly growing company. Yes, it is. What attracted you to five? >> Yeah, Great question. There's actually a lot of things that brought me to Five9. I think probably the most important thing is that I've got this belief, and I'm very motivated for myself. A least to do technology and innovate and create new things. And this belief that were on the cusp of the next generation of technology in the collaboration industry. And that next generation is going to be powered by artificial intelligence, and one of the ways I sort of talked about this is that if you look at the entire history of collaboration, up til now meetings, telephony, messaging was to figure out, a way to get the bits of data from one person to another person fast enough to have a conversation. That's it. You know, once we got the audio connected, we just moved the audio packets in the video packets and messaging from one place to another. And we didn't actually analyze any of that because we couldn't. We didn't have the technology to do that. But now, with the arrival of artificial intelligence and particular speech recognition, natural language processing, we can apply those technologies to that content and take all this dark data that's been basically thrown away the instant it was received, to process it and do things. And that is going to completely transform every field of collaboration, from meetings to messaging, to telephony. And I believe that so strongly, that is, That's great. That's going to be my next job. I wanna work on that. And it's going to start in the Contact Center because a contact center is the ideal place to do that. It's the tip of the spear for AI in collaboration, >> and it's in a really great area. Disruptive innovation are absolutely so Take us through the impact was one of things I have observed in this industry is you have You know, I don't want to say mainframe clients served to go back to date myself, but there was that wave of client server computer >> mainframes. Cool again. We just called clout. Now, hey, is >> exactly. So you have these structural industry waves take us through the waves of how we got here and what's different now? And why can't the old guard or the older incumbents surviving if you're not out in front that next wave your driftwood. So what? What's What's his ways mean? Why is this important? What has to change to be successful? >> Exactly. So there's been this this whole like you said these waves. So the first wave of telecommunications was like hardware: circuit switching, big iron switches, sitting in telco data centers, you know, And then that era transitioned to software and that was with the arrival voiceover IP and technologies like SIP, and that made it more less expensive. And anyone could do it, and it transformed the industry. The next wave, the third wave were still like halfway through and in some areas, actually, just beginning contact, center was early here, the third wave is cloud, right is now we're moving that software to a totally new delivery vehicle that allows us to deliver innovation and speed. And that wave has now enabled us to start the next wave, which is on ly in its infancy, which is AI right, and the application of machine learning techniques to automate all kinds of aspects of how people communicate in collaborate. >> I think cloud is a great example of Seen a. I, which had been a concept around when I was in computer science. Back in the eighties, there was a guy you know theory, and it's the science of it is not so much change, but computing's available. The data to be analysed for the first time is available. Yeah, you mentioned analyzing the bits writings. There's now a key part. What does it actually mean? Teo. Someone who's has a contact center has a large enterprise. Says, you know what? I got to modernize. How does A I fit them? What is actually going on, >> right? Great question. So a I actually consult lots different problem at the end of the day again, Hey, eyes like this, Let's. It's the biggest buzz word right on. It's in my title. So, like I'm a little guilty, right? >> We'll get a pay raise for, But >> what? It comes down to this, really this Korean machine learning, which is really like a fancy new algorithmic technique for taking a bunch of data and sort of making a decision based on it. So And it turns out, as we've learned that if you have enough data and you can have enough computing and we optimize the algorithms, you could do some amazing things, right? And it's been applied to areas like speech recognition and image recognition and all these kind of things. Self driving cars that are all about decision process is, Do I go left? I go right? Is this Bob? Is this Alice? Did the users say and or did they say or write those air all decision process? Is that these tools economy? What does it mean? The Contact Center? It means everything in the context. And if you look at the conduct center. It's all about decision. Process is, you know, where should this call get routed? What's the right agent to handle the call right now? When the agent gets the call, what kind of things should they be saying? What I do with the call after the call is done, How should the agent use their time? All those things are decision processes and their key to the contact center. So so, aye, aye. And Emily going to transform every aspect of it and, most importantly, analyzing what the person is saying connecting with the customer, allowing the age to >> be more. You know, I think this is really one of the most cutting edge areas of the business. And the technology and throw in CEO was talking about an emotional cognitive recognition around. Yeah, connecting with customers and data certainly is going to be a part of that. But as machine learning continues to get it, Sea legs. Yeah, you seeing kind of two schools of thought? I call it the Berklee School. Hard core mathematics. Throw math at it. And then you've got this other side of a machine learning which is much more learning. Yeah, it's less math. More about adaptive and self learning. One's deterministic one's non deterministic is starting to see these use cases where Yeah, there's a deterministic outcome, right throw machine learning at a great exactly helped humans come curate, create knowledge, create value that you've got a new emerging use case of non deterministic, like machine learning environments where I could be driving my test Look down the road or my company's run the Contact Center. I gotto understand what's gonna happen before it happens. Right? Talkabout this. What's your thoughts on this is This isn't really new, pioneering area. What's your view on >> this? Yeah, so I think it actually straight sort of a key point. I wantto narrow enough from what she said, which is that a lot of these problems still, it's about the combination of man and machine, right? It's that there's things that you know are going to be hard for the machine to predict. So the human in their usage of the product, teaches the machine, and the machine, as it observes, helped the human achieved mastery. And that human part, by the way, is even more important in the conduct centre than anywhere else. At the end of the day, your customer and you call up, you're reaching for human connection. You're calling this. You want to talk, you've got a problem. You need someone to not just give you the answers, but empathize with youto understand you. Right? And if you go back to anything about the best experience you've ever had when you called up for support or get a question answered. He was like it was someone who understood you who's friendly, polite, empathetic, funny. And they knew exactly what they were doing, right? And they solve it for you. So the way I think about that, is that actually the future of the context. Dinner is a combination of human and machine, and the human delivers the heart, and the machine delivers the master. >> And I just noticed your I'm looking at Twitter, right? And you just tweeted this forty minutes to go the future of Contact Center. Nice. A combination of human and machine human delivers heart. The machines lose mastery. I think this is so important because unpacking that words like trust come out True relationship. So you asked about my experiences is when I've gotten what I needed, You know, all ledger, the outcome I wanted. Plus I felt good about right. I trusted it. I trusted the truth. It was. And he's seeing that in media today with fake news. You're seeing it with Digital has kind of almost created, anonymous, non trustworthy its data. There's been no real human. Yeah, packaging. So I think you're I'm hearing you You're on the side of humans and machines, not just machines being the silver bullet. >> Absolutely, absolutely. And again, it goes back to sort of the history of the contact centre has been this desire to, like, just make it cheaper, right? But as the world is changing, and as customer experience is more important than ever before and is now, technology is enabling us to allow agents and human beings to be more effective through this. The symbiotic relationship that we're going to form with each other, like we can actually deliver amazing customer experiences. And that's what really matters. And that idea of trust I want to come back to that word that's like super Central to this entire thing. You know, you have that as a user, you have to trust the brand you have to trust the information you're getting from the agent. You have to trust the product that you're calling them talking about, and that's central to everything that we need to do. In fact, it's a It's a fundamental aspect of our entire business. In fact, if you again think about it for a moment here, we're going to customers who are looking to buy a context, and we're saying, Trust us, we're going to put it in the cloud, We're going to run it, We're going to operate it for you and we're going to deliver a great, highly reliable experience that takes trust to sew one of things that back to your early early question. Why did come two, five, nine? One of the things it has done is build this amazing trust with its customers to its huge, amazing reliability. Up time, a great human process of how we go in work with our customers. It's about building trust in every single >> way. So I want to put in the spot because I know you've seen many ways of innovation. You've seen a lot of different times, but now it's more accelerated. Got cloud computing at a much more accelerated innovation cycle. So as users expect interact with certain kind of environment. Roman talked about this in his interview. CEO Control. So you just want to be served on the channels that they want to be served in. So having a system that they have to go to to get support, They wanted where they are. And so how is the future of the customer interaction? Whether it's support our engagement is going to take place in context to nonlinear discovery, progression, meaning or digging a service themselves in the organic digital space. I honestly want to go to a site per se. How do you see the future evolving around this notion of organic discovery? Talking to their friends, finding things out? Does that impact how Five9 sees the future? >> Yeah, absolutely. And I think it gets back to sort of an old idea of Omni channel. I mean, this is something that the context people been talking about for, like forever, like the last ten years, right? And and its original meeting was just this idea. Oh, you know, you can talk to us via chat, or you can send us an e mail or you can send us a text or you could call us right and we'll work with you on any of those, like you said. Actually, what's more interesting is as customers and users moved between those things, and it actually switches from reactive to proactive right where we actually treat those channels as well. Depending on what the situation is, we're going to gather information from all these different data sources, and then we're going toe, find the right way to reach out to you and allow you to reach out to us in the most official. >> So you see a real change in user expectation experience with relative rule contact? >> Yeah, I mean, I mean, the one thing that technology is delivered is a change in user expectations on how things work. And if you look at the way we as human beings communicate with each other, it's dramatically different today than it was really just just a few years ago. >> So, Johnny, let's look under the hood now in terms of the customer environment, because certainly I've seen Legacy after Legacy sisters being deployed. It's almost like cyber security kind of matches the same kind of trend that in your world, which is throw money at something and build it out. So there's a lot of sprawl of solutions out there and trying to solve these problems. How does the customer deal with that? And they're going forward there on this new wave. They want to be modernized, but they got legacy. They had legacy process, legacy, culture. What's the key technical architecture, How you see them deploying this? What's the steps of the patient and her opinion? >> It will surprise you not one drop when I say it's go to the cloud, all right, and there are real reasons for it and by the way, this is going to be going to be talking about this at Enterprise Connect. So, So tune in Enterprise Connect. I'm going to be talking about this. Um, there's a ton of reasons, five huge ones, actually, about why people need to get to the cloud. And one of them is actually one of the ones we've been talking about here, which is a lot of this. Modernization is rooted in artificial intelligence. It turns out you just cannot do artificial intelligence on promise you cannot. So the traditional gear, which used to be installed and operated by legacy vendors like a VIA, you know, they go in, and Genesis, they go in the install a thing and it works just for one customer at a time. The oly way artificial intelligence works is when it gathers data across multiple customers. So multi tendency and artificial intelligence go hand in hand. And so if you want to take any benefit from the stuff that we've been talking about this conversation, the first step is you gotta take your context int the cloud just to begin building and adding your data on the set and then leverage the technologies and they come out >> So data is the central equation And in all this because good data feed's good machine learning good machine learning feeds Great a. I So data is the heart of this, yes. So data making data in the cloud addressable seems to be a key. Thought Your reaction and what are you guys doing with? >> Absolutely, absolutely. And this is, by the way, another reason why I joined five nine, that I've been speculating here. I said, All right, if Date if ya if the future is about a I miss, I said, That's what I want to do in collaboration. You need data to do that. You actually have to work for a company that has a lot of data. So market leadership matters. And if you go look at the contact center and you go look at all the industry and analyst reports like it made it pretty obvious, like who to go to there is like the leader in cloud Conduct. Sonar with with tons of agents and tons of data is Five9 and ah, and so that's That's why you're so building the data aggregating data. That's one of the first things I'm working on here is how do we increase and utilize the data that we've been gathering for years. >> And and a lot of that we've had this conscious with many customs before about Silas Silas. Kill innovation When it comes to data address ability, your thoughts on that and what customs Khun due to start thinking about breaking down those silent >> exactly so In fact, Silas have been a big part of the history of especially on premise systems. Once in fact, Afghan one silo for inbound contacts and are different for outbound. Different departments, by the way, also had their own different comic centers. And then you had other tools that on the other data, if you don't like a separate tool over there for serum and a different tool over there for WFOR debut Fam and something else for Q M. And all these things were like barely integrated together in the cloud that becomes much more natural. Spring these technologies together and the data can begin to flow from the systems in and out of each other. And that means that we have a much greater access to data and correlated data across these different things that allows us to automate all over the place. So it's this positive reinforcement sile cycle that you only get one year when you've gone to the club. >> The question I want to ask you, it's more customers on pretend I'm a customer for second. I won't ask you, Jonathan, what's the core innovation for me to think about and bring to my organization? If I want to go down the modern monitors you. How do you answer that question? What is the core innovation? Stretch it. I should have Marcy moving through the cloud is one beyond that is itjust cloud. Then what else? What, Juanito? Be preaching internally and organizing my culture >> around. Yeah, great questions. So, I mean, I think the cloud is sort of the enabler of many of these different pieces of innovation. Right? So velocity and speed is one of them. And then setting up and adjusting these things used to be super super hard. Ah, you wanted to add agents seats? Oh, my gosh, enough to go binding hardware and racket stack boxes and whatever. So even simple things like reactive nous, right? That's something that's important to talk about is that many of our customers and our businesses are highly seasonal. Right? We've seen like someone showed me a graph. This was like, Oh, my gosh, it was It was a company that was doing ah, telethon. And they said, Here's how many agents they have over this year. It was like two agents, and then it shut up. It's like five hundred agents of phones. Two days exactly. Drop back down. And I'm like, if you think about a business like that, you could never even do that. And so the so cloud is nice, but the way you talk about it, and as an I t buyer of these technologies, you talk your business owners about reacted nous speed, velocity, right? That's what matters to a business and then customer experience. >> You're one of the things that just to kind of end of second, I want to get your thoughts on. I'm gonna bring kind of industry trend. That's I think, might be a way to kind of talk about some of these core problems on data. Most mainstream people look at Facebook and saying, Well, what a debacle. They used my data. These men against me. I'm not in control of my data. You're seeing that weaponization people saying elections were rigged. So weaponizing data for bad is this content, and this context ends right? An infrastructure that's right, >> that's right. >> But there's also the other side, which is, you actually make it for good. So you started thinking about this people starting to realize Wow, I should be thinking about my data and the infrastructure that I have to create a better outcome. That's right, Your thoughts on that as people start to think about II in terms of the business context, right? How did they get to that moment where they can saying, I don't want anyone weaponizing did against me. I want to use it for good. How did the head of the company comes back to >> trust, by the way, right? Is that you know, on and to some degree that's an uphill battle due to some of these debacles that you just talked about. But Contact Center is a different beast of the whole thing. And interestingly, it's an area where there's already been an assumption by users that when they interact with the contact center, that data is sort of used to improve the experience. I mean, every contacts and the first thing I say, by the way, this call may be recorded for training. Um, honoring purses, Captain, that they are right. It's it's already opt in. There's an assumption that that's exactly how that is being used. So it's This is another reason. By the way, what's a contact center is? It was the tip of the spear because it was a place where there was already permission, where the data is exactly the kind of stuff that had already been subject to analysis and Attock customer expectation that that's actually what was happening. The expectation was there they building action, that data what was missing. So now we're filling in the ability to action on that All that data with artificial intelligence >> and final question. What's your vision going forward? A CTO and aye, aye. What's the vision of Five9? What do what do you see? The twenty miles stair for Five9 within consciousness. We just talked about >> it. So? So it's It's about revolution. I'll be honest. Right on. I tell people like, I'm not like an incremental, steady Eddie CTo like I do things because I want to make big changes. And I believe that the context and R is on the cusp of a massive change. And my boss, Rohan said this and this has been actually central to how I'm thinking about this. The Contact Center in the next five years will be totally different than the twenty five years before that. It's a technologist. I say. Wow, five years like that's not very long in terms of softer development. That's what we were going pretty much rewrite our entire stack over the next five years. And show. What should that start to look like? So for me, it's about how do we completely reimagine every single aspect of the context center to revolutionize the experience by merging together, human and machine and totally new >> and the innovation strategies cloud in a cloud and and and data great job and great to have you on pleasure. Great, great conversation. Quick plug for you guys. Going to be a enterprise, connect to Cuba. Lbi. They're covering the event as well. What you going to talk about that? What? Some of the interactions? What will be the hallway conversations? What's your objective? What's your focus >> exactly? So so I'm going to be having my own session. We're going to be talking about the five reasons that you may not think about to goto context on the cloud. I've hinted already. A James of them. I think we're too well. That's you can you know, A. I is clearly central and I'm going to start to talk about the other four. >> Great, great conversation. A lot of change. Massive change happening. Great innovation Stretch. Great mission here at Five9. Great, great mission around. Changing and reimagine. More change the next five years in the past twenty five years. Again cloud computing eyes doing it will be winners. Will be losers will be following it here on the Cube. Jonathan Rosenberg, CTO ahead of AI at Five9. I'm John Furrier with the Cube. Thanks for watching.

(bright symphony music) >> Hello, I'm John Furrier, the founder of SiliconANGLE Media and co-host of theCUBE. We're here in Paulo Alto at our studio here. I'm joining with Joseph Jacks, the founder and general partner of OSS Capital. Open Source Software Capital, is what OSS stands for. He's also the founder of KubeCon which now is part of the CNCF. It's a huge conference around Kubernetes. He's a cloud guy. He knows open source. Very well respected in the industry and also a great guest and friend of theCUBE, CUBE alumni. Joseph, great to see you. Also known as JJ. JJ, good to see you. >> Thank you for having me on again, John. >> Hey, great to have you come on. I know we've talked many times on theCUBE, but you've got some exciting news. You got a new firm, OSS Capital. Open Source Software, not operational support like a telco, but this is an investment opportunity where you're making investments. Congratulations. >> Thank you. >> So I know you can't talk about some of the specifics on the funds size, but you are actually going to go out, talk to entrepreneurs, make some equity investments. Around open source software. What's the thesis? How did you get here, why did you do it? What's motivating you, and what's the thesis? >> A lot of questions in there. Yeah, I mean this is a really profoundly huge year for open source software. On a bunch of different levels. I think the biggest kind of thing everyone anchors towards is GitHub being acquired by Microsoft. Just a couple of weeks ago, we had the two huge hadoop vendors join forces. That, I think, surprised a lot of people. MuleSoft, which is a big opensource middleware company, getting acquired by Salesforce just a year after going public. Just a huge outcome. I think one observation, just to sort of like summarize the year 2018, is actually, starting in January, almost on sort of like a monthly basis, we've observed a major sort of opensource software company outcome. And sort of kicking off the year, we had CoreOS getting acquired by Red Hat. Brandon and Alex, the founders over there, built a really interesting company in the Kubernetes ecosystem. And I think in February, Al Fresco, which is an open source content portal taking privatization outcome from a private equity firm, I believe in March we had Magento getting acquired by Adobe, which an open source based CMS. PHP CMS. So just a lot of activity for significant outcomes. Multibillion dollar outcomes of commercial open source companies. And open source software is something like 20 years old. 20 years in the making. And this year in particular, I've just seen just a huge amount of large scale outcomes that have been many years in the making from companies that have taken lots of venture funding. And in a lot of cases, sort of partially focused funding from different investors that have an affinity for open source software and sort of understand the uniqueness of the open source model when it's applied to business, when it's applied to company building. But more sort of opportunistic and sort of affinity oriented, as opposed to a pure focus. So that's kind of been part of the motivation. I'd say the more authentically compelling motivation for doing this is that it just needs to exist. This is sort of a model that is happening by necessity. We're seeing more and more software companies be open source software companies. So open source first. They're built in a distributed way. They're leveraging engineers and talent around the world. They're just part of this open source kind of philosophy. And they are fundamentally kind of commercial open source software companies. We felt that if you had a firm basically designed in a way to exclusively focus on those kind of companies, and where the firmware actually backed and supported by the founders of the largest commercial open source companies in the world before sort of the last decade. That could actually deliver a lot of value. So we've been sort of blogging a little bit about this. >> And you wrote a great post on it. I read about open source monetization. But I think one of the things I'm seeing as well that supports your thesis, and I like to get your reaction to it because I think this is something that's not really talked about, but open source is still young. I mean, you go back. I remember the days when we used to have to hide in the shadows to get licenses and pirate stuff and do all those crazy stuff. But now, it's only a couple decades away. The leaders that were investing were usually entrepreneurs that've been successful. The Rob Bearns, the Amar Wadhwa, the guy that did Spring. All these different open source. Linux, obviously, great success story. But there hasn't any been any institutional. Yeah, you got benchmark, other things, done some investments. A discipline around open source. Where open source is now table stakes in all software development. Cloud is scaling, scaling out globally. There's no real foc- There's never been a firm that's been focused on- Just open source from a commercial, while maintaining the purity and ethos of open source. I mean, is that. >> You agree? >> That's true. >> 100%, yeah. That's been the big part of creating the firm is aligning and solving for a pure focused structure. And I think what I'll say abstractly is this sort of venture capital, venture style approach to funding enterprise technology companies, software companies in general, has been to kind of find great entrepreneurs and in an abstract way that can build great technology companies. Can bring them to market, can sell them, and can scale them, and so on. And either create categories, or dominate existing categories, and disrupt incumbents, and so on. And I think while that has worked for quite a while, in the venture industry overall, in the 50, 60 years of the venture industry, lots of successful firms, I think what we're starting to see is a necessary shift toward accounting for the fundamental differences of opensource software as it relates to new technology getting created and going, and new software companies kind of coming into market. So we actually fundamentally believe that commercial open source software companies are fundamentally different. Functionally in almost every way, as compared to proprietary closed source software companies of the last 30 years. And the way we've sort of designed our firm and we'll about ten people pretty soon. We're just about a month in. We're growing the team quickly, but we're sort of a small, focused team. >> A ten's not focused small, I mean, I know venture firms that have two billion in management that don't have more than 20 people. >> Well, we have portfolio partners that are focused in different functional areas where commercial open source software companies have really fundamental differences. If you were to sort of stack rank, by function, where commercial open source software companies are really fundamentally different, sort of top to bottom. Legal would be, probably, the very top of the list. Right, in terms of license compliance management, structuring all the sort of protections and provisions around how intellectual property is actually shipped to and sold to customers. The legal licensing aspects. The commercial software licensing. This is quite a polarizing hot topic these days. The second big functional area where we have a portfolio partner focused on this is finance. Finance is another area where commercial open source software companies have to sort of behaviorally orient and apply that function very, very differently as compared to proprietary software companies. So we're crazy honored and excited to have world experts and very respected leaders in those different areas sort of helping to provide sort of different pillars of wisdom to our portfolio companies, our portfolio founders, in those different functional areas. And we provide a really focused kind of structure for them. >> Well I want to ask you the kind of question that kind of bridges the old way and new way, 'cause I definitely see you guys definitely being new and different, which is good. Or as Andy Jassy would say, you can be misunderstood for a while, but as you become successful, people will start understanding what you do. And that's a great example of Amazon. The pattern with success is traditionally the same. If we kind of encapsulate the difference between open source old and new, and that is you have something of value, and you're disrupting the market and collecting rents from it. Or revenue, or profit. So that's commercial, that's how businesses run. How are you guys going to disrupt with open source software the next generation value creation? We know how value's created, certainly in software that opensource has shown a path on how to create value in writing software if code is value and functionality's value. But to commercialize and create revenue, which is people paying something for something. That's a little bit different kind of value extraction from the value creation. So open source software can create value in functionality and value product. Now you bring it to the market, you get paid for it, you have to disrupt somebody, you have to create something. How are you looking at that? What's the vision of the creation, the extraction of value, who's disrupted, is it greenfield new opportunities? What's your vision? >> A lot of nuance and complexity in that question. What I would say is- >> Well, open source is creating products. >> Well, open source is the basis for creating products in a different kind of way. I'll go back to your question around let's just sort of maybe simplify it as the value creation and the value capture dynamics, right? We've sort of written a few posts about this, and it's subtle, but it's easy to understand if you look at it from a fundamental kind of perspective. We actually believe, and we'll be publishing research on this, and maybe even sort of more principled scientific, perhaps, even ways of looking at it. And then blog posts and research. We believe that open source software will always generate or create orders of magnitude more value than any constituent can capture. Right, and that's a fundamental way of looking at it. So if you see how cloud providers are capturing value that open source creates, whether it's Elasticsearch, or Postgres, or MySQL or Hadoop. And then commercial open source software companies that capture value that open source software creates, whether it's companies like Confluent around Kafka, or Cloudera around Hadoop, or Databricks around Apache Spark. Or whether it's the creators of those projects. The creators of Spark and Hadoop and Elasticsearch, sometimes many of them are the founders of those companies I mentioned, and sometimes they're not. We just believe regardless of how that sort of value is captured by the cloud providers, the commercial vendors, or the creators, the value created relative to the value captured will always be orders and orders of magnitude greater. And this is expressed in another way, which this may be easier to understand, it's a sort of reinforcing this kind of assertion that there's orders of magnitude value created far greater than what can be captured. If you were to do a survey, which we're currently in the process of doing, and I'm happy to sort of say that publicly for the first time here, of all the commercial open source software companies that have projects with large significant adoption, whether, say for example, it's Docker, with millions of users, or Apache Hadoop. How many Hadoop deployments there are. How many customers' companies are there running Hadoop deployments. Or it may be even MySQL. How many MySQL installations are there. And then you were to sort of survey those companies and see how many end users are there relative to how many customers are paying for the usage of the project. It would probably be something like if there were a million users of a given project, the company behind that project or the cloud provider, or say the end user, the developer behind the project, is unlikely to capture more than, say, 1% or a couple percent of those end users to companies, to paying companies, to paying customers. And many times, that's high. Many times, 1% to 2% is very high. Often, what we've seen actually anecdotally, and we're doing principled research around this, and we'll have data here across a large number of companies, many times it's a fraction of 1%. Which is just sort of maybe sometimes 10% of 1%, or even smaller. >> So the practitioners will be making more money than the actual vendors? >> Absolutely right. End users and practitioners always stand to benefit far greater because of the fundamental nature of open source. It's permissionless, it's disaggregated, the value creation dynamics are untethered, and it is fundamentally freely available to use, freely available to contribute to, with different constraints based on the license. However, all those things are sort of like disaggregating the creating of technology into sort of an unbounded network. And that's really, really incredible. >> Okay, so first of all, I agree with your premise 100%. We've seen it with CUBE, where videos are free. >> And that's a good thing. All those things are good. >> And Dave Vellante says this all the time on theCUBE. And we actually pointed this out and called this in the Hadoop ecosystem in 2012. In fact, we actually said that on theCUBE, and it turned out to be true, 'cause look at Hortonworks and Cloudera had to merge because, again, the market changed very quickly >> Value Creation. >> Because value >> Was created around them in the immediate cloud, etc. So the question is, that changes the valuation mechanisms. So if this true, which we believe it is. Just say it is. Then the traditional net present value cash flow metric of the value of the firm, not your firm, but, like, if I'm an open source firm, I'm only one portion of the extraction. I'm a supplier, and I'm an enabler, the valuation on cash flow might not be as great as the real impact. So the question I have for you, have you thought about the valuation? 'Cause now you're thinking about bigger construct community network effects. These are new dynamics. I don't think anyone's actually crunched a valuation model around this. So if someone knew that, say for example, an open source project created all this value, and they weren't necessarily harvesting it from a cash flow perspective, there might be other ways to monetize it. Have you though about that, and what's your reaction to that concept? 'Cause capitalism would kind of shake down the system. 'Cause why would someone be motivated to participate if they're not capturing any value? So if the value shifts, are they still going to be able to participate? You follow the logic I'm trying to- >> I definitely do. I think what I would say to that is we expect and we encourage and we will absolutely heavily invest in more business model innovation in the area of open source. So what I mean by that is, and it's important to sort of qualify a few things there. There's a huge amount of polarization and lack of consensus, lack of industry consensus on what it actually means to have or implement an open source based business model. In fact there's a lot of people who just sort of point blankedly assert that an opensource business model does not exist. We believe that many business models for monetizing and commercializing open source exist. We've blogged and written about a few of them. Their services and training and support. There's open core, which is very effective in sort of a spectrum of ways to implement open core. Around the core, you can have a thin crust or a thick crust. There's SAS. There are hardware based distribution models, things like Sourcefire, and Cumulus Networks. And there are also network based approaches. For example, project called Storj or Stor-J. Being developed and run now by Ben Golub, who's the former CEO of Docker. >> CUBE alumni. >> Ben's really great open source veteran. This is a network, kind of decentralized network based approach of sort of right sizing the production and consumption of the resource of a storage based open source project in a decentralized network. So those are sort of four or five ways to commercializing value, however, four or five ways of commercializing value, however what we believe is that there will be more business model innovation. There will be more developments around how you can better capture more, or in different ways, the value that open source creates. However, what I will say though, is it is unrealistic to expect two things. It is unrealistic and, in fact, unfair to expect that any of those constituents will contribute back to open source proportional to the value that they received from it, or the benefit, and I'm actually paraphrasing Doug Cutting there, who tweeted this a couple of years ago. Very profoundly deep, wise tweet, which I very strongly agree with. And it is also unrealistic to expect a second thing, which is that any of those constituents can capture a material portion of the value that open source creates, which I would assert is many trillions of dollars, perhaps tens of trillions of dollars. It's really hard to quantify that. And it's not just dollars in economic sense, it's dollars in productivity time saved, new markets, new areas, and so on. >> Yeah, I think this is interesting, and I think that we'll be an open book at that. But I will say that what I've observed in looking through all these CUBE interviews, I think that business model innovation absolutely is something that is an IP. >> We need it. Well, it's now intellectual property, the business model isn't, hey I went to business school, learned this at Babson or Harvard, I learned this business model. We're going to do SAS premium. Okay, I get that. There's going to be very interesting new innovations coming, and I think that's the new IP. 'Cause open source, if it's community based, there's going to be formulas. So that's going to be really inter- Okay, so now let's get back to actual funding itself. You guys are doing early stage. Can you take us through the approach? >> We're very focused on early stage, investing, and backing teams that are, just sort of welcoming the idea of a commercial entity around their open source project. Or building a business fundamentally dependent on an open source project or maybe even more than one. The reason for that is this is really where there's a lot of structural inefficiency in supporting and backing those types of founders. >> I think one of the things with ... is with that acquisition. They were pure on the open source side, doing a great job, didn't want to push the business model too hard because the open source, let's face it, you got people like, eh, I don't want to get caught on the business side, and get revenue, perverse incentives might come up, or fear of incentives that might be different or not aligned. Was a great a value. >> I think so. >> So Red Hat got a steal on that one. But as you go forward, there's going to be certainly a lot more stuff. We're seeing a lot of it now in CNCF, for instance. I want to get your thoughts on this because, being the co founder of KubeCon, and donating it to the CNCF, Kubernetes is the hottest thing on the planet, as we talked about many years ago. What's your take on that, now? I see exciting things happening. What is the impact of Kubernetes, in your opinion, to the world, and where do you see that evolving rapidly, and where is the focus here as the people should be paying attention to? >> I think that Kubernetes replaces EC2. Kubernetes is a disaggregated API for distributed computing anywhere. And it happens to be portable and able to run on any kind of computer infrastructure, which sort of makes it like a liquid disaggregated EC2-like API. Which a lot of people have been sort of chasing and trying to implement for many years with things like OpenStack or Eucalyptus. But interestingly, Kubernetes is sort of the right abstraction for distributed computing, because it meets people where they are architecturally. It's sort of aligned with this current movement around distributed systems first designs. Microservices, packaging things in small compartmentalized units. >> Good for integrating of existing stuff. >> Absolutely, and it's very composable, un-opinionated architecturally. So you can sort of take an application and structure it in any given way, and as long as it has this sort of isolation boundary of a container, you can run it on Kubernetes without needing to sort of retrofit the architecture, which is really awesome. I think Kubernetes is a foundational part of the next kind of computing paradigm in the same way that Linux was foundational to the computing paradigm that gave rise to the internet. We had commodity hardware meeting open source based sort of cost reduction and efficiency, which really Linux enabled, and the movement toward scale out data center infrastructure that supported the Internet's sort of maturity and infrastructure. I think we're starting to see the same type of repeat effect thanks to Kubernetes basically being really well received by engineers, by the cloud providers. It's now the universal sort of standard for running container based applications on the different cloud providers. >> And think having the non-technical opinion posture, as you said, architectural posture, allows it to be compatible with a new kind of heterogeneous. >> Heterogeneity is critical. >> Heterogeneity is key, 'cause it's not just within the environment, it's also within each vendor, or customer has more heterogeneity. So, okay, now that's key. So multi cloud, I want to get your thoughts on multi cloud, because now this goes into some of things that might build on top of if Kubernetes continues to go down the road that you say it does. Then the next question is, stateful applications, service meshes. >> A lot of buzz words. A lot of buzz words in there. Stateful application's real because at a certain point in time, you have a maturity curve with critical infrastructure that starts to become appealing for stateful mission critical storage systems, which is typically where you have all the crown jewels of a given company's infrastructure, whether it's a transactional system, or reading and writing core customer, or financial service information, or whatever it is. So Kubernetes' starting to hit this maturity curve where people are migrating really serious mission critical storage workloads onto that platform. And obviously we're going to start to see even more critical work loads. We're starting to see Edge workloads because Kubernetes is a pretty low footprint system, so you can run it on Edge devices, you can even run it on microcontrollers. We're sort of past the experimental, you know, fun and games was Raspberry Pi, sort of towers, and people actually legitimately doing real world Edge kind of deployments with Kubernetes. We're absolutely starting to see multi-geo, multi-replication, multi-cloud sort of style architectures becoming real, as well. Because Kubernetes is this API that the industry's agreeing upon sufficiently. We actually have agreement around this sort of surface area for distributed system style computing that if cloud providers can actually standardize on in a way that lets application specific vendors or new types of application deployment models innovate further, then we can really unlock this sort of tight coupling of proprietary services inside cloud providers and disaggregate it. Which is really exciting, and I forget the Netscape, Jim Barksdale. Bundling, un-bundling. We're starting to see the un-bundling of proprietary cloud computing service API's. Things like Kinesis, and ALB and ELB and proprietary storage services, and these other sticky services get un-bundled because of two big things. Open source, obviously, we have open source alternative data paths. And then we have Kubernetes which allows us to sort of disaggregate things out pretty easily. >> I want to hear your thoughts, one final concept, before we break, 'cause I was having a private conversation with three people besides myself. A big time CIO of a company that if I said the name everyone would go, oh my god, that guy is huge, he's seen it all going back many, many ways. Currently done a lot of innovation. A hardcore network chip guy who knows networking, old school infrastructure. And then a cloud native application founder who knows a lot about software development and is state-of-the-art cloud native. So cloud native, all experienced, old-school, kind of about my age, a cloud native app developer, a big time CIO, and a chip networking kind of infrastructure guy. And we're talking, and one thing that came out, I want to get you thoughts on this, he says, so what's going on with DevOps, how do you see this service mesh, is a stay for (mumbles) on top of the stack, no stacks, horizontally scalable. And the comment that came out was storage and networking have had this relationship with everything since day one. Network moves a packet from point A to point B, and nothing happens in between, maybe some inspection. And storage goes from here now to the then, because you store it. He goes, that premise moves up the stacks, so then the cloud native guy goes, well that's what's happening up at the top, there's a lot of moving things around, workloads and or services, provisioning services, and then from now to then state. In real time. And what dawned on the next conversation the CIO goes, well this is exactly our challenge. We have under the hood infrastructure being programmable, >> We're having some trouble with the connection. Please try again. >> My phone's calling me. >> Programmable connections. >> So you got the programmable on the top of the stack too, so the CIO said, that's exactly the problem we're trying to solve. We're trying to solve some of these network storage concepts now at an application level. Your thoughts to that. >> Well, I think if I could tease apart everything you just said, which is profound synthesis of a lot of different things, I think we've started to see application logic leak out of application code itself into dedicated layers that are really good at doing one specific thing. So traditionally we had some crud style kind of behavioral semantics implemented around business logic. And then, inside of that, you also had libraries for doing connectivity and lookups and service discovery and locking and key management and encryption and coordination with other types of applications. And all that stuff was sort of shoved into the single big application binary. And now, we're starting to see all those language runtime specific parts of application code sort of crack or leak out into these dedicated, highly scalable, Unix philosophy oriented sort of like layers. So things like Envoy are really just built for the sort of nervous system layer of application communication fabric up and down the layer two through layer seven sort of protocol transport stack, which is really profound. We're seeing things like Vault from Hashicorp handle secure key storage persistence of application dedication, authorization, metadata and information to sort of access different systems and end points. And that's a dedicated sort of stateful layer that you can sort of fragment out and delegate sort of application specific functionality to, which is really great for scalability reasons. And on, and on, and on. So we've started to see that, and I think one way of looking at that is it's a cycle. It's the sort of bundling and un-bundling aspect. >> One of the granny level services are getting a really low level- >> Yeah, it's a sort of like bundling and un-bundling and so we've got all this un-bundling happening out of application code to these dedicated layers. The bundling back may happen. I've actually seen a few Bay Area companies go like, we're going back to the monolith 'cause it actually gives us lots of efficiencies in things that we though were trade offs before. We're actually comfortable with a big monorepo, and one or two core languages, and we're going to build everything into these big binaries, and everyone's going to sort of live in the same source code repository and break things out through folders or whatever. There's a lot of really interesting things. I don't want to say we're sort of clear on where this bundling, un-bundling is happening, but I do think that there's a lot of un-bundling happening right now. And there's a lot of opportunity there. >> And the open source, obviously, driving it. So final question for you, how many deals have you done? Can you talk a little bit about the firm? And exciting things and plans that you have going forward. >> Yeah, we're going to be making a lot of announcements over the next few months, and we're, I guess, extremely thrilled. I don't want to say overwhelmed, 'cause we're able to handle all of the volume and inquiries and inbound interest. We're really honored and thrilled by the reception over the last couple weeks from announcing the firm on the first of October, sort of before the Hortonworks Cloudera merger. The JFrog funding announcement that week. The Elastic IPO. Just a lot of really awesome things happened that week. This is obviously before Microsoft open sourced all their patents. We'll be announcing more investments that we've made. We announced our first one on the first of October as well with the announcement of the firm. We've made a good number of investments. We're not able to talk to much about our first initiative, but you'll hear more about that in the near future. >> Well, we're excited. I think it's the timing's perfect. I know you've been working on this kind of vision for a while, and I think it's really great timing. Congratulations, JJ >> Thank you so much. Thanks for having me on. >> Joesph Jacks, also known as JJ, founder and general partner of OSS Capital, Open Source Software Capital, co founder of KubeCon, which is now part of the CNCF. A real great player in the community and the ecosystem, great to have him on theCUBE, thanks for coming in. I'm John Furrier, thanks for watching. >> Thanks, John. (bright symphony music)