(corporate electronic xylophone jingle intro) >> Good afternoon and welcome back to our very last segment of Tuesday's live broadcast here on theCUBE from AWS re:Invent in fabulous Las Vegas, Nevada. My name is Savannah Peterson and I am joined here by the brilliant Paul Gillin. Paul, end of our first day. You holding up, are you still feeling overwhelmed with fire hose... >> Savannah, yet my feet are killing me. (savannah laughs) >> Yeah, we've done so much walking in these chairs. >> 14,000 steps already today. It's not even dinner time. >> Hey, well, at least you've earned your dinner, Paul. I love that. I love that. I'm very excited about our next guests. We have Krishna and Sowmya joining us from Tata Consultancy Services. Now, I was impressed when I was doing my background research on you all. The Tata Group has locations in 150 different spots, 46 different countries. You have over 600,000 employees on the team. We are talking about absolutely massive scale here but, today we're going to be focused specifically on the Tata Consultancy Services. Sowmya, can you tell me what you all do? What is that team specifically in charge of? >> Yeah, TCS, first of all, thank you very much for inviting us. >> Savannah: Our pleasure. >> Maybe the last session but, we'll make it very lively. >> Savannah: It's going to be the best session. That's the best part of the day. >> Yes, that's the attitude. From a company standpoint, we are a 50 plus year old company. Part of the Tata group. We focus on IT services. We are categorized as industry verticals and we have horizontal services where AWS is one of the horizontal services that we have. And, when I talk about TCS, we focus a lot more on growth and transformation of our customers. That is one of the key objectives of the current company's growth, I would say. So, that is TCS in a nutshell. >> Extraordinarily important topic to be focused on right now. Growth, transformation, pretty much the core topics of the show. I know you're on the hospitality and transportation side of the business, which is very exciting. And, we're going to dig into that a little bit more. Krishna, you're overseeing the world. Tell us a little bit more about your role within the whole ecosystem. >> Yeah, thank you for the opportunity. Great meeting all of you. It's been awesome experience here. re:Invent is coming back, catching up, right? 50,000 people compared to 25,000 last year. So, great to see and meet all of you. Coming to my role, I am responsible for AWS Business Unit within TCS. That means I am responsible for anything that happens on cloud, on AWS. It's a Full Stack unit. I have the global responsibility. That's whether it's a applications, data, infrastructure, transformation that happens, as well as OT at the edge. So, that's my responsibility. >> Savannah: Well, I love talking about the edge. One of my favorite. >> Transformation is a theme of what you do. We heard that the pandemic accelerated digital transformation initiatives at many companies. How did you see the pandemic affecting your business, affecting the customers you were working with? >> Pandemic definitely kind of accelerated a lot of cloud adoption, right? A lot of companies initially focused on resiliency, coming back to handling the pandemic, the situation. But, it also drove a lot of innovation in the business models. They had to think on their feet, re-look at their business models, change the channels and that continued. Pandemic is thankfully gone by but, the transformation actually continued. The way that we actually see on cloud, especially transformation, it has evolved. What we call as Cloud 2.0. Now, cloud is actually more focused on future-proofing the businesses. And, the initial days it was more about future-proofing the technology and technology architecture. But, it has evolved to future-proofing businesses. That means implementing new business models, bringing in agility, measuring the business value. And, that's where we see a significant traction. >> So, it's not about technology then. It's not about infrastructure. >> It is about technology but, really delivering business value. It's about, how can I improve the customer experience? >> Well, can you give us a couple of examples of companies you work with that embody this idea? >> I can imagine in the travel and hospitality zone. Probably few communities more sensitive than when someone's having a disruption or frustration within that process. And, perhaps few time periods less chaotic than the last few years. Tell us about your experience and what you've seen. >> Absolutely. To answer your question, first of all, coming out of pandemic, right? Many customers in the travel and hospitality industry where legacy, did not modernize for the last decade or so because, there have been many ups and downs in the industry. So, during pandemic, post-pandemic, one of the the way they wanted to rebound was, can we do the transformation? First of all, cloud as a technology adoption, but, beyond that, how do customers derive value, business value? That is one of the key aspects of the old transformation. And, if you take, I can give a couple of examples. Avis Car Rental, they had monolith mainframe applications and, that was there for almost couple of decades, right? But, over a period of time, they were not able to have the availability of those applications. There were many outages. As a result, businesses could not do the bookings. Like OTAs, customers could not do the bookings, the application was not available most of the time. And, it's all legacy, right? So, that is where we all came in, TCS. How do we first of all, simplify the complexity of the landscape? That is one. Then, second is, modernize the legacy application. That's the second thing. Third is, how do you scale it? Because, everyone wants to go faster, right? How do you scale it? That is where we partnered with AWS as well, to bring in some specific solutions. One example for Avis', their Rent Shop. Because, of the lack of availability, because, it's monolith application and legacy application. It was not available. So, as a result, we partnered and we brought in our contextual knowledge of the car rental industry to kind of transform, move it to cloud. And, today, as a result of it, Avis was able to save millions of dollars from a MIB standpoint. Second, in terms of availability, that was 99.9% availability. As a result, they had a pick in their business revenue as well. So, this is one of the ways that its helped. The second example I want to quote is, United Airlines. Here again, we've been present for a long time. We have a deep industry knowledge of the airline industry. So, we brought in our airline contextual knowledge and the United landscape to bring in a TCS's solution that we developed. It's called the Aviana. It's an intelligent operations solution for the airline industry, which we have developed. It's on AWS as well, that is being implemented in United. As a result, the ground staff, they have to take decisions on the moment when there is a irregular operation. That could be flight delays, as a result, customers connections will be lost. >> Savannah: Baggage. >> Baggage, right? Baggage delays. >> So many variables. The complexity... >> exactly >> in this matrix is wild. >> So, leveraging the Aviana solution, the ground staff were able to take decisions based on exceptions. They were able to take decisions quickly so that, they improved the customer experience. I think that was one of the key successes for United in the recent times. So, those two are the examples that I would call where customers have the right business value. So, cloud was not just for technology. They all are deriving a lot of business value as well. I would say. >> How important do you think it is for companies facing these unique challenges and scaling to work with partners like TCS? And, I'm sure you would say very important, but, tell me a little bit more why it's so important and those core benefits that they're going to get. Krishna, let's start off with you. Yeah, let me take again the AWS cloud transformation, right? TCS has formed AWS Business Unit two years back. So, we are a covid baby in a way. We have been working with the AWS for more than a decade but, we formed a dedicated Full-Stack Unit to drive cloud transformation on AWS. In these last two years, we've grown three X and customers we have added 400 new customers we have added. >> Nicely done. Just want to see you there. That's huge. Especially during these times. Congratulations. >> So, it's basically about the scale that we bring in. What we have done as a differentiation is, if you look at the entire cloud journey, right from taking a decision which cloud is, right, all the way to the cloud migration modernization and running operations. So, we have built complete platform. AML based platforms, where we have taken our delivery wisdom and codified it onto these platforms. So, we support around thousand plus customers on AWS in varying capacity. All of that knowledge is codified and, that is what we bring to the table, to the customers. And, so, customers obviously appreciate that value that best practices that are coming. And, coupled with that, the industry knowledge that we have on banking, life sciences, healthcare, automotive. So, it's partly the IT, it is the industry transformation as well. Because, we are working on connected cars, for example, in automotive. We are working on accelerated drug development platforms. We're working on complete banks as a platform that we have. TCS has built on AWS. So, 400 customers are there. It's the complete banking and insurance platform. So, this is the combination of the technical expertize that is digitized using platforms, as well as the industry knowledge, is the reason why customers work with us on the cloud transformation. >> So, we're seeing you talk about the vertical industry knowledge. AWS also has its own vertical industry plays. How do you, I guess, coordinate with them or, do you compete with them or, do you stay out of each other's way? >> No, we actually collaborate aggressively. >> Savannah: I like that (laughs) >> Right, so, it's not.. >> Savannah: With vigor. >> With vigor. TCS supports approximately 14 verticals. With AWS, we went with the focused industry play. We said we look at financial services, travel, transportation, hospitality, healthcare, life sciences and automotive, to start with. And, we have Go Big plans with AWS. very focused. The collaboration is actually at the industry solutions because, AWS is a great platform, ever evolving, keeps you on on your toes to really adapt it. But, that is always going on, the collaboration. But, the industry, I'm actually glad AWS last year took a pivot on focusing on industries. Now, we talk the same language when we go in front of a board or a CEO or COO. Present it. We are talking about the future of the industry not just the future of the technology. So, it's a win-win. >> You are also developing products on top of AWS that are not industry verticals, that build on the platform. What kinds of products are those? >> For cloud transformation, for example, consulting. We have a product called Cloud Counsell. We have a decision engine on the data side. We have something called Cloud Foundation, Mason. CloudMason. It's just the foundation, right? And, entire migration and modernization factory. And, the last one on cloud operations is actually Cloud Exponence. So, these are time tested. You have Fortune 500 customers using this regularly actively leveraging that. And, these are all AWS in a well architecture framework certified. So, they work well and they're designed to work on cloud, not only in the native environment, but, also legacy environment. Because, enterprises is not just only native, cloud-native. There is a lot of legacy. Sowmya spoke about the mainframe model... >> So much legacy, we were talking about it. >> So, you have to have a combination of solutions. So, the platforms that we're building, the products we're building, work in both the environments. >> Yeah, and that agility and ability to help customers navigate that prioritization. I mean, there's so many options. We talk about how many new companies there are every year. New solutions. Our adoption of technology is accelerating. As, McKinsey said, we went through 10 years of technological evolution and workplace evolution over the first six months of the pandemic. So, really everything's moving at unprecedented velocity unlike ever before. We have a new game here on theCUBE specifically for this show. And, we are challenging our guests, prompting our guests, to give us a 30 second sizzly sound bite with your hot take on the most important themes of this year's show. Think of it as a thought leadership moment. Opportunity to plug if you really want it. Krishna, you've just given me the nod. I'm going to start with you first and then we'll then we'll pass it along, yeah >> Sure. I think on thought leadership, the way that on cloud, business value is the focus, not the technology. Technology is important, but business value is the focus. And, the way that I see it evolving is with quantum computing coming out more and more, becoming relevant, and Edge is actually becoming quite active as well. All this while on cloud, we focused on business value at the centralized place at the corporate. But, I think the real value of cloud is when you deliver the results, business results, where the customers consume it, that is at the edge. I think that's basically the combination of centralized and the edge is where the real value of cloud is, right. And, I also loud, I know you said 30 seconds but, give me 30 more seconds. >> I like your answer right now. So, I'm going to give you a little more time. Yeah, thank you. >> You've earned more time. (laughs) >> So, I like the way Adam said in the keynote, if you look at it broadly, I categorizes two things. There are a lot of offerings that are becoming comprehensive, like AWS Connect, bringing in workforce management into it, making it a complete end to end product. Similarly, Security Lake, all bringing in the entire security and compliance under one, similarly data. So, there are lot of things that he announced where it is an end to end comprehensiveness of the thing. But, what I love about is, what Amazon is known for, supply chain. So, they rolled out AWS Supply Chain offering. Walk Out technology. So, the Amazon proposition is actually being brought to AWS as a core proposition. I think that's very futuristic and I think we can see more and more customers, enterprise customers, adopting AWS more to drive transformation >> Badly needed right now. Supply chain resiliency. >> Supply chain really having its moment the last two years. File under two words. No one knew, many of us did who worked in it before this. And, here we are, soon as we lost our toilet paper, everyone's freaked out. I love that you talked about business value and also that the end customer is on the edge and, everyone kind of forgets we are essentially the edge device. This is the edge device, it's all around us. And, all the technology that we're all using that you're even talking about is built right inside here from my airlines app to my car rentals to all of it. All right Sowmya, give us your 30 second hot take, roughly. >> Taking the cue from Krishna, right? Today, things are available on AWS Marketplace. So, tomorrow, somebody wants to start an airline, they just have to come and plug and play the apps that are available in the marketplace. Especially your supply chain. The Amazon is known for that. And, a small and medium business they want to start something, right, a .com. It's very easy. So, that's something that we are all looking for. The future is going to be very, very bright and great for the businesses, is what I would say because, most of it could be plug and play with all the solutions. >> Paul: It's already been built. >> On the cloud, so, we are looking forward to it. The second thing I would talk about is, we have to take it to scale. How more and more people can leverage AWS, right? The talent is very important and, that is where partners like us focus on re-scaling our talent. We have 600,000 people, right? We are not just... >> 600,000 people! That's basically as many people live in the San Francisco Bay area for contexts for our listeners. It's how many people work for Walmart? >> It's 1.2 million in Walmart? >> Is it really? >> It is, yes, yes. That's work for Walmart, sidebar. >> So from that standpoint, as the company, we are focusing on re-skilling, up-skilling our talent in order to work AWS cloud and so on, so, that they can go and support our customers. That is something that is very important and that's going to be the future as well. Bring it to scale, go faster. >> I love that you just touched on the fact that you essentially have to practice what you preach because, you've got to think about those 600,000 people in a 100 locations across 40 plus different countries. I love it. Sowmya, I'm going to close on that note. The future is bright, just like your fabulous blazer. >> Thank you so much. Krishna, Sowmya, thank you so much for being here with us. We can't wait to see what happens next, who you help next, and how Tata continues to transform. Thank all of you for tuning in today. A full jam packed day of coverage live here from Las Vegas, Nevada. We are at AWS re:Invent with Paul Gillin. I'm Savannah Peterson. We're theCUBE, the leader in High-Tech Coverage. (corporate electronic xylophone jingle outro)

>>Que presents HP Discover 2022. Brought to You by HP >>Good morning, everyone. It's the Cube live in Las Vegas. Day two of our coverage of HP Discover 2022 from the Venetian Expo Centre. Lisa Martin and David want a what a day we had yesterday and today. Unbelievable >>for today. Big Big day today, >>Big day Today we've got a lot. We got some big heavy hitters on talking with HP customers. Partners, leadership. We've a couple of guests up with us next. Going to be talking more about the ecosystem. He's welcome. Corey Dire, the chief revenue officer, Digital Realty and Cliff Evans, senior director. H P E Green like partner ecosystem Guys. Great to have you on the >>programme. Thank you. Great to be here. >>Thank you for having us excited to be here >>with. So that's so that's harness that excitement. Cory, talk to us about the partnership. The announcement? What's going on there with Digital Realty and Green like? >>Yeah, we're crazy excited about it. You know, we've got customers dealing with data, gravity and the opportunity around that and how they could make use of it. And then they're thinking through digital transformation. How how you doing? Multi cloud and they need a partnership. To do that in this partnership with Green Leg and digital is perfect solution for them. So I'm crazy excited to be here with Cliff absolute with all of you to talk about it and hopefully build out a great partnership in relationship with HP. >>Talk to us. Sure, you're crazy Excitement >>club? Absolutely no. I think it is absolutely fantastic Partnership. I think the term is coming together as organisations. Bringing the two platforms together isn't it is an amazing thing that we have for customers, customers we know they want. They want a cloud experience. But really, they want to do that without really the DC footprint that had previously. So how did they do that in a way that really works for them in a secure client secure, sustainable way. But with the cloud experience. Really, the combination of the two pieces coming together really makes that happen, and that is what that's exciting. So we >>dig in to the two things that you mentioned Cory digital transformation and multiply. When I go back to the early days of cloud, it was that girl, you know, nobody's going to do anything you know ever again in the data centre. You know Charles Phillips, the the CEO of in four, famously said, Friends don't let friends, Bill Data centres, right? Everything's going in the cloud. So a lot of people predicted, You know, guys like you were going to be in trouble. The exact opposite happened. The market took off. So you mentioned digital transformation of multi cloud. Can we peel the onion on that? What? What is it about those two items? Are there other trends? They're driving your business, >>you know, You tied right on to to where it started. All enterprises started going to the club and then they got to the cloud and there was more that they needed to make that rial. I talk about multi cloud. You're going to use different cloud providers for different opportunities and different applications. And so you have to start thinking about how does this work in a world where you're gonna go to multiple clouds, multiple locations and what it really drove? It is the need for Cole location to make this because you've got a distributed architecture in order to enable all of this and then having to have us help you out with it. And partners like HP. That's part of where it comes from. But if you think through going to the cloud, can you stay there? Is that the full solution? You need to secure sustainable solution for that. One of the opportunities for us around that is that if you're building data centres for yourself on Prem, you don't have all the cloud access we do. We've got more cloud access points than anybody. So that helps in this digital transformation. >>How How much home? I'm sorry, Didn't mean to you how much homogeneity is there are our clients or customers saying, Hey, I kind of want the same experience in the same infrastructure. Same same. Or they saying, Hey, I want to do stuff in Digital Realty that I can't get from, you know, a cloud provider, Oracle Rack. You know, something like that, >>I would tell you that they come to us from all the partners. So we are partner community. We are not going up the stack anywhere on that. We do are we do our part. We're really good at doing the data centres really good at building data. They descended sustainable. Our position in the market is sustainability around it. We were the first to sign up on the science based initiatives for zero kind of carbon neutrality and in the future in 2030. And so yeah, so I think there's the partner aspect that they need help with on it to drive that Yeah. >>And I think from that from the HP Green Lake perspective, I think customers they very much want that that cloud experience. But I want to do on their own terms. The partnership allows that to happen on Gapen simply the cloud experiencing with the green light cloud platform to really go and deliver that genuine cloud experience and then building cloud services. On top of that, they get all the benefits that they would have from a public cloud experience, but done in the way that they would prefer to do it. So it's bringing those pieces together on >>I think the other side of you asked if it was it was the same across the board and ubiquitous. It's very bespoke. Solutions weaken D'oh! Every customer we have has a different footprint. Most from the multinationals. So we think through where their data is, where it needs to be accessed where their customers are, where their employees are, what makes the most sense. And then the partnership we have with HP into a whole lot for making very bespoke solution for that customer and help them be successful. Journey >>s O on. That s o. So what we've done with destroy lt is we have a specific offer around how we go to market with this really going how customers So we call it Green Light with co location. It's all about really positioning on offer to customers that says, Look, we can go and do this with you and do it simply and really make it happen very quickly and efficiently. So the customer ends up with a single contract in a single invoice for Green Lake Cloud Services on the co location piece, all in one single contracts. That just makes it a lot easier in terms of organising on a really big part of that as well is that our involvement is also spans right from the design to the implementation to support. So we do the whole thing to really help organisations golf and do this. So that's the big for me. The big differentiator. So rather than just having Green Lake in Cloud Services, were saying, Look, we can now do the Coehlo piece and they can really take the whole thing to a whole new level in terms of that public cloud experience >>in the sari and that that that invoice comes from HPD or Digital Realty is bundled into that >>correct? Yes, directly through the channel. We can sell that in a number of different ways. Customers get that that single invoice on a big part of that as well, just going a little bit deeper on that. So what we do is we We use a part of the company called Data Centre Technology Services, which are a great kind of consulting organisation with tremendous experience and something like 3000 projects across 40 countries from the very smallest of the very largest of data centre implementation. So all of that really makes the whole thing a lot easier from a customer's perspective in terms of designing, implementing and then supporting. So you pull all of that together. It's fantastic >>and I think it's really changed to add on to that partner in prison. So customers, now we're thinking about it differently and data centres differently, and they see us as a strategic partner along with HP. To go after this used to be space, power and calling. Now it's How much connectivity do you have? What your sustainability profile? What's your security profile? How do you secure this data? Date is the lifeblood of all these companies and you have to have a really secure, sustainable solution for them, >>right? That's absolutely critical for every industry. Talk about the specific value prop at a bespoke co location solution delivers to customers. Maybe you got a favourite customer example that you think really articulates the value of this partnership. >>So I think a combination. So so I think we touched on a lot of it, actually. So there's obviously the data centre aspect itself in terms of with the footprint that realty have across the world, you can pick and choose the data centre in the class of data centre that you want in terms of your Leighton see and connectivity that you want. Then really, it's the green make peace in terms of the flexibility that you get with that really is that value. And as I touched on the Green Lake with Cole Oh, I think for me is from our perspective, I think the biggest piece of value that we provide there to really go make it happen. Yeah, >>there's about 70 applications right now that are part of Green Lake Polo that you can bespoke for what you need to. You can think around your specific solutions that you need, and we've got it all right there with HP Green like and follow for us. And because we have a 290 data centre footprint across 50 markets, it gives us the opportunity really be the data centre provider in the Partner for H P, pretty much anywhere but with connective ity everywhere. >>When you say 70 applications, these the 70 services are you talking about talking >>about? Okay, Category 70 services. There's a lot of stuff. >>Cory, when you talked about sustainability a couple of times, is a really important ingredient of the customer decision. Why is it because they're indirectly paying the power bill or is because that's the right thing to do? And they care. There's increased. People care about it more because you go back a while ago. People way always talked about green it, but it was all lip service. Is that changing or is that there? Is there an economics >>changing in a really big way? Almost every conversation I have with customers is how are you doing Sustainability. So if they're doing an on Prem, that's not their core capabilities. They don't know how to do that. On our end, I mentioned our SP R science based initiatives that we signed up for. But how do we enable that? Enable it for how do we build in designer data centres? How do we actually work them and operate them? And then how do we go after all the green sources of sustainable energy including, I think since 2015, we've issued six billion in green bonds around that same support of it. So yeah, >>and your customer can then I presume, report that on their sustainability report a >>good way to think about it. You no longer have your data centre at its sometimes less efficient way than way are we're really good at building sustainable data centres, and then you can actually get some credits back and forth, >>just from agreement. Perspective. So Green Lake. So there's a specific Forrester Impact report that looks a green lake on how it how it performs from sustainability. Perspective on Greenlee really is giving you their 30% reduction in your energy consumption. So there's a big kind of win there as well, I think. Which is then, >>why? Where does that come from? >>So it Zim part that kind of the avoidance of over provisioning such that you going right size things, Then you have you have you have a certain amount of reserve capacity that you're using them just using the extra consumption piece when you need it. So rather than having everything running at full speed, it really is kind of struggling as to how that work. So you get a combination of effects >>with consulting and the thoughtfulness around this bespoke solution that you have. You end up needing fewer servers, pure technology that drives less power consumption and therefore you get a lot of this same really base it down. You >>talked about the savings you talked about the simplification delivery perspective. Talk about the implementation. What's the time to value that Organisations can glean from this partnership >>superfast So So yeah this This does accelerate the whole process from from initial kind of opportunity if you like and customer inquiry through to actual implementation So previously this would take considerable amount of time in terms of to ing and froing between multiple organisations on Now what we do is coordinate that do it efficiently and effectively So D. C. T s Data Sentinel services team very closely. Just have those connections often do those things incredibly quickly and it does accelerate the whole time >>and they're tied in with our team is well around. Where's the leighton? See where the solutions Because we're really thinking about what is your stack looked like from an HP perspective, but then where you need to deploy it so that you have access to the clouds You have the right proper Leighton see across your environment and you really haven't distributed architecture that works the best for you and your company. >>So this is probably answer those questions Probably both, but I'm asking anyway, I've always been a repatriation sceptic, but I'm happy to be proven wrong. You guys have other data. And maybe this is part of what one of my blind spots question is, is what's driving your business in terms of the EU's case? Is it organisations saying Hey, we want to get out of the data centre business way Don't want to put everything into the cloud but we're going to go on a digital realty and being green leg and we're gonna move into that cola Or is it? People say, You know, while we over rotated into the cloud, you were going to come back. So it's >>both. It's both, >>Yeah, in the empire. The credit. >>I think there are a lot of customers with good intentions on going to the cloud, and then there's some cost with it that maybe they didn't fully factor in it at that time. And now you've got the ability around these bespoke solutions to really right size every bit of this. And when they originally did it, they didn't think through a distributor architecture. They thought my own prim, and then I'm just gonna burst everything that a cloud that's no longer the case, and it's not really the most efficient way to your point about repatriation. They start pulling their storage back in. Well, where do you want your data? Where do you want your storage? You wanted as close as you can to the clouds for that capability and in a solution that's wrapped around it makes it very simple for you. >>I think the repatriation is very real and is increasing, eh? So we're seeing a lot of it in terms of activity and customers really trying to understand the cost that they're incurring now from a public cloud perspective. And how can they do that differently? In fact, with combined offer that we have it, it makes it a lot easier to compare. So, yeah, that really is accelerating because you don't >>see it in the macro numbers. I mean, just to be honest, you see the cloud guys combined growing 35%. And is that because your business is in transition from traditional on prime model, too, and as a service model, and so you've got that imbalance and it gets hidden in >>all that, and I think it's I think it's a new wave of things that are happening. Yeah. I mean, there's a there's a lot of things, obviously, that makes complete sense to me in Public Cloud, but I do think there's been an over rotation towards it, so I think now that realisation and it's going to take time to kind of pick that. But it's absolutely happening. There are a lot of opportunities that we've gotten some very big ones I'd love to talk about. Can't quite talk about them just get but really, where there's big, big savings in terms of what they're paying from a public cloud perspective, Really, what they want is that full management cloud service to go make it happen. So the combination of the data centre piece to Green Lake piece and then some management services, whether they're from ourselves or from party community, from manage service providers that we also work with, that gives them the complete package. >>So I have another premise. A lot of it, of course, is traditionally been focused on internal, and I feel like there's a new era coming. It's talks of the ecosystem. Are you seeing customers not only running there it in digital realty and connecting to the cloud in a hybrid fashion, but also actually building new value and building businesses that are customer facing on that that air monetize herbal. Are you seeing that? Is that happening and having examples, even generic? >>Well, basic from our perspective, our partner community, that's what they do. We have a tonne of enterprise customers, but I'll need to connect and integrate the data that you have doesn't do anything for you, Fitz on its own. And it's not interacting with other data points. And it's not around interacting with other customers, other solutions in one night. So it does help build out a partner community, a solution community for our customers in our data centres and across the >>are their industry patterns emerging. In other words, is that data ecosystems emerging by industry or is a sort of or horizontal? >>There's a mix. So I think there's a lot of lot of financial sector stuff. Yes, certainly. And then certainly manufacturing s O. I think it's interesting that you're getting a bit of a combination, but not a lot of financial sector. >>Of course, the big bags early on that they could build their own cloud. Yeah, now they're probably rethinking that. Yeah, well, maybe >>they're also service providers. When you're that large a za bank on their end. They're doing a lot of work. E. I would also say the other part that a lot of people see as an opportunity is around all the HPC and AI applications as well, in addition to manufacturing distribution. So there's a lot of use cases, a lot of reasons, like us from sort of doing this >>wrap us up with value, perhaps that you're talking Torto Financial Services Organisation or a manufacturing company. What is that 32nd elevator pitch value problem? Why they should go HP Making Digital Realty together. >>So I would say green, like Rico location gives you a single contract. Singling voice, easy to go and design, implement support and go make happen. Sorry, that's very simple way say, very just make it easy >>on. And I would just say thank you on that. It's been great to speak with you guys. And yeah, when you think through that part of it also is a bespoke opportunity to put your data where it needs to be closer to your customers. Closer to the action you were thinking through the rape reiteration of it. A lot of it's being built out there on phones and whatnot. So you've got to think through where your data is and how you managed to >>write and enable every every company in every industry to be a data company. Because that's what, of course, the demanding consumers demanding that demand isn't it is not going to turn down right now. Absolutely. Just thanks so much for David. Very much. Thank you. Together in the ecosystem, there are guests. And Dave l want a I'm Lisa Martin. You're watching the key of live from the Venetian Expo Centre in Vegas, Baby. David, I will be back there next guest in a minute.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome back to the Cube's coverage of HPE. Discover 22 live from the Sans expo center in Las Vegas. Lisa Martin, here with Dave Velante. We've an alumni back joining us to talk about high performance computing and AI, Justin ARD, EVP, and general manager of HPC and AI at HPE. That's a mouthful. Welcome back. >>It is no, it's great to be back and wow, it's great to be back in person as well. >>It's it's life changing to be back in person. The keynote this morning was great. The Dave was saying the energy that he's seen is probably the most out of, of any discover that you've been at and we've been feeling that and it's only day one. >>Yeah, I, I, I agree. And I think it's a Testament to the places in the market that we're leading the innovation we're driving. I mean, obviously the leadership in HPE GreenLake and, and enabling as a service for, for every customer, not just those in the public cloud, providing that, that capability. And then obviously what we're doing at HPC and AI breaking, uh, you know, breaking records and, uh, advancing the industry. So >>I just saw the Q2 numbers, nice revenue growth there for HPC and AI. Talk to us about the lay of the land what's going on, what are customers excited about? >>Yeah. You know, it's, it's a, it's a really fascinating time in this, in this business because we're, you know, we just, we just delivered the first, the world's first exo scale system. Right. And that's, uh, you know, that's a huge milestone for our industry, a breakthrough, you know, 13 years ago, we did the first Petta scale system. Now we're doing the first exo scale system, huge advance forward. But what's exciting too, is these systems are enabling new applications, new workloads, breakthroughs in AI, the beginning of being able to do proper quantum simulations, which will lead us to a much, you know, brighter future with quantum and then actually better and more granular models, which have the ability to really change the world. >>I was telling Lisa that during the pandemic we did, uh, exo scale day, it was like this co yep. You know, produce event. And we weren't quite at exo scale yet, but we could see it coming. And so it was great to see in frontier and, and the keynote you guys broke through that, is that a natural evolution of HPC or is this we entering a new era? >>Yeah, I, I think it's a new era and I think it's a new era for a few reasons because that, that breakthrough really, it starts to enable a different class of use cases. And it's combined with the fact that I think, you know, you look at where the rest of the enterprises data set has gone, right? We've got a lot more data, a lot more visibility to data. Um, but we don't know how to use it. And now with this computing power, we can start to create new insights and new applications. And so I think this is gonna be a path to making HPC more broadly available. And of course it introduces AI models at scale. And that's, that's really critical cause AI is a buzzword. I mean, lots of people say they're doing AI, but when you know, to, to build true intelligence, not, not effectively, you know, a machine that learns data and then can only handle that data, but to build true intelligence where you've got something that can continue to learn and understand and grow and evolve, you need this class of system. And so I think we're at, we're at the forefront of a lot of exciting innovation. H how, >>In terms of innovation, how important is it that you're able to combine as a service and HPC? Uh, what does that mean for, for customers for experimentation and innovation? >>You know, a couple things I've been, I've actually been talking to customers about that over the last day and a half. And, you know, one is, um, you think about these, these systems are, they're very large and, and they're, they're pretty, you know, pretty big bets if you're a customer. So getting early access to them right, is, is really key, making sure that they're, they can migrate their software, their applications, again, in our space, most of our applications are custom built, whether you're a, you know, a government or a private sector company, that's using these systems, you're, you're doing these are pretty specialized. So getting that early access is important. And then actually what we're seeing is, uh, with the growth and explosion of insight that we can enable. And some of the diversity of, you know, new, um, accelerator partners and new processors that are on the market is actually the attraction of diversity. And so making things available where customers can use multimodal systems. And we've seen that in this era, like our customer Lumi and Finland number, the number three fastest system in the world actually has two sides to their system. So there's a compute side, dense compute side and a dense accelerator side. >>So Oak Ridge national labs was on stage with Antonio this morning, the, the talking about frontier, the frontier system, I thought what a great name, very apropo, but it was also just named the number one to the super computing, top 500. That's a pretty big accomplishment. Talk about the impact of what that really means. >>Yeah. I, I think a couple things, first of all, uh, anytime you have this breakthrough of number one, you see a massive acceleration of applications. And if you really, if you look at the applications that were built, because when the us department of energy funded these Exoscale products or platforms, they also funded app a set of applications. And so it's the ability to get more accurate earth models for long term climate science. It's the ability to model the electrical grid and understand better how to build resiliency into that grid. His ability is, um, Dr. Te Rossi talked about a progressing, you know, cancer research and cancer breakthroughs. I mean, there's so many benefits to the world that we can bring with these systems. That's one element. The other big part of this breakthrough is actually a list, a lesser known list from the top 500 called the green 500. >>And that's where we measure performance over power consumption. And what's a huge breakthrough in this system. Is that not only to frontier debut at number one on the top 500, it's actually got the top two spots, uh, because it's got a small test system that also is up there, but it's got the top two spots on the green 500 and that's actually a real huge breakthrough because now we're doing a ton more computation at far lesser power. And that's really important cuz you think about these systems, ultimately you can, you can't, you know, continue to consume power linearly with scaling up performance. There's I mean, there's a huge issue on our impact on our environment, but it's the impact to the power grid. It's the impact to heat dissipation. There's a lot of complexities. So this breakthrough with frontier also enables us no pun intended to really accelerate, you know, the, the capacity and scale of these systems and what we can deliver. >>It feels like we're entering a new Renaissance of HPC. I mean, I'm old enough to remember. I, it was, it wasn't until recently my wife, not recently, maybe five, six years ago, my wife threw out my, my green thinking machines. T-shirt that Danny Hillis gave you guys probably both too young to remember, but you had thinking machines, Ken to square research convex tried to mini build a mini computer HPC. Okay. And there was a lot of innovation going on around that time and then it just became too expensive and, and, and other things X 86 happened. And, and, but it feels like now we're entering a, a new era of, of HPC. Is that valid or is it true? What's that mean for HPC as an industry and for industry? >>Yeah, I think, I think it's a BR I think it's a breadth. Um, it's a market that's opening and getting much more broader the number of applications you can run, you know, and we've traditionally had, you know, scientific applications, obviously there's a ton in energy and, and you know, physics and some of the traditional areas that obviously the department of energy sponsor, but, you know, we saw this with, with even the COVID pandemic, right? Our, our supercomputers were used to identify the spike protein to, to help and validate and test these vaccines and bring them to market and record time. We saw some of the benefits of these breakthroughs. And I think it's this combination of that, that we actually have the data, you know, it's, it's digital, it's captured, um, we're capturing it at, you know, at the edge, we're capturing it and, and storing it obviously more broadly. So we have the access to the data and now we have the compute power to run it. And the other big thing is the techniques around artificial intelligence. I mean, what we're able to do with neural networks, computer vision, large language models, natural language processing. These are breakthroughs that, um, one require these large systems, but two, as you give them a large systems, you can actually really enable acceleration of how sophisticated these, these applications can get. >>Let's talk about the impact of the convergence of HPC and AI. What are some of the things that you're seeing now and what are some of the things that we're gonna see? >>Yeah. So, so I, one thing I like to talk about is it's, it's really, it's not a convergence. I think it's it. Sometimes it gets a little bit oversimplified. It's actually, it's traditional modeling and simulation leveraging machine learning to, to refine the simulation. And this is a, is one of the things we talk about a lot in AI, right? It's using machine learning to actually create code in real time, rather than humans doing it, that ability to refine the model as you're running. So we have an example. We did a, uh, we, we actually launched an open source solution called smart SIM. And the first application of that was climate science. And it's what it's doing is it's actually learning the data from the model as the simulation is running to provide more accurate climate prediction. But you think about that, that could be run for, you know, anything that has a complex model. >>You could run that for financial modeling, you can use AI. And so we're seeing things like that. And I think we'll continue to see that the other side of that is using modeling and simulation to actually represent what you see in AI. So we were talking about the grid. This is one of the Exoscale compute projects you could actually use once you actually get, get the data and you can start modeling the behavior of every electrical endpoint in a city. You know, the, the meter in your house, the substation, the, the transformers, you can start measuring the FX of that. You can then build equations. Well, once you build those equations, you can then take a model, cuz you've learned what actually happens in the real world, build the equation. And then you can provide that to someone who doesn't need a extra scale supercomputer to run it, but that, you know, your local energy company can better understand what's happening and they'll know, oh, there's a problem here. We need to shift the grid or respond more, more dynamically. And hopefully that avoids brownouts or, you know, some of the catastrophic outages we've >>Seen so they can deploy that model, which, which inherently has that intelligence on sort of more cost effective systems and then apply it to a much broader range. Do any of those, um, smart simulations on, on climate suggest that it's, it's all a hoax. You don't have to answer that question. <laugh> um, what, uh, >>The temperature outside Dave might, might give you a little bit of an argument to that. >>Tell us about quantum, what's your point of view there? Is it becoming more stable? What's H HPE doing there? >>Yeah. So, so look, I think there's, there's two things to understand with quantum there's quantum hardware, right? Fundamentally, um, how, um, how that runs very differently than, than how we run traditional computers. And then there's the applications. And ultimately a quantum application on quantum hardware will be far more efficient in the future than, than anything else. We, we see the opportunity for, uh, much like we see with, you know, with HPC and AI, we just talked about for quantum to be complimentary. It runs really well with certain applications that fabricate themselves as quantum problems and some great examples are, you know, the, the life sciences, obviously quantum chemistry, uh, you see some, actually some opportunities in, in, uh, in AI and in other areas where, uh, quantum has a very, very, it, it just lends itself more naturally to the behavior of the problem. And what we believe is that in the short term, we can actually model quantum effectively on these, on these super computers, because there's not a perfect quantum hardware replacement over time. You know, we would anticipate that will evolve and we'll see quantum accelerators much. Like we see, you know, AI accelerators today in this space. So we think it's gonna be a natural evolution in progression, but there's certain applications that are just gonna be solved better by quantum. And that's the, that's the future we'll we'll run into. And >>You're suggesting if I understood it correctly, you can start building those applications and, and at least modeling what those applications look like today with today's technology. That's interesting because I mean, I, I think it's something rudimentary compared to quantum as flash storage, right? When you got rid of the spinning disc, it changed the way in which people thought about writing applications. So if I understand it, new applications that can take advantage of quantum are gonna change the way in which developers write, not one or a zero it's one and virtually infinite <laugh> combinations. >>Yeah. And I actually, I think that's, what's compelling about the opportunity is that you can, if you think about a lot of traditional the traditional computing industry, you always had to kind of wait for the hardware to be there, to really write, write, and test the application. And we, you know, we even see that with our customers and HPC and, and AI, right? They, they build a model and then they, they actually have to optimize it across the hardware once they deploy it at scale. And with quantum what's interesting is you can actually, uh, you can actually model and, and, and make progress on the software. And then, and then as the hardware becomes available, optimize it. And that's, you know, that's why we see this. We talk about this concept of quantum accelerators as, as really interesting, >>What are the customer conversations these days as there's been so much evolution in HPC and AI and the technology so much change in the world in the last couple of years, is it elevating up the CS stack in terms of your conversations with customers wanting to become familiar with Exoscale computing? For example? >>Yeah. I, I think two things, uh, one, one is we see a real rise in digital sovereignty and Exoscale and HPC as a core fund, you know, fundamental foundation. So you see what, um, you know, what Europe is doing with the, the, the Euro HPC initiative, as one example, you know, we see the same kind of leadership coming out of the UK with the system. We deployed with them in Archer two, you know, we've got many customers across the globe deploying next generation weather forecasting systems, but everybody feels, they, they understand the foundation of having a strong supercomputing and HPC capability and competence and not just the hardware, the software development, the scientific research, the, the computational scientists to enable them to remain competitive economically. It's important for defense purposes. It's important for, you know, for helping their citizens, right. And providing, you know, providing services and, and betterment. >>So that's one, I'd say that's one big theme. The other one is something Dave touched on before around, you know, as a service and why we think HP GreenLake will be, uh, a beautiful marriage with our, with our HPC and AI systems over time, which is customers also, um, are going to scale up and build really complex models. And then they'll simplify them and deploy them in other places. And so there's a number of examples. We see them, you know, we see them in places like oil and gas. We see them in manufacturing where I've gotta build a really complex model, figure out what it looks like. Then I can reduce it to a, you know, to a, uh, certain equation or application that I can then deploy. So I understand what's happening and running because you, of course, as much as I would love it, you're not gonna have, uh, every enterprise around the world or every endpoint have an exit scale system. Right. So, so that ability to, to, to really provide an as a service element with HP GreenLake, we think is really compelling. >>HP's move into HPC, the acquisitions you've made it really have become a differentiator for the company. Hasn't it? >>Yeah. And I, and I think what's unique about us today. If you look at the landscape is we're, we're really the only system provider globally. Yeah. You know, there are, there are local players that we compete with. Um, but we are the one true global system provider. And we're also the only, I would say the only holistic innovator at the system level to, to, you know, to credit my team on the work they're doing. But, you know, we're, we're also very committed to open standards. We're investing in, um, you know, in a number of places where we contribute the dev the software assets to open source, we're doing work with standards bodies to progress and accelerate the industry and enable the ecosystem. And, uh, and I think that, you know, ultimately the, the, the last thing I'd say is we, we are so connected in, um, with, through our, through the legacy or the, the legend of H Hewlett Packard labs, which now also reports into me that we have these really tight ties into advanced research and that some of that advanced research, which isn't just, um, around kind of core processing Silicon is really critical to enabling better applications, better use cases and accelerating the outcomes we see in these systems going forward. >>Can >>You double click on that? I, I, I wasn't aware that kind of reported into your group. Yeah. So, you know, the roots of HP are invent, right? Yeah. HP labs are, are renowned. It kinda lost that formula for a while. And now it's sounds like it's coming back. What, what, what are some of the cool things that you guys are working on? Well, >>You know, let me, let me start with a little bit of recent history. So we just talked about the exo scale program. I mean, that was a, that's a great example of where we had a public private partnership with the department of energy and it, and it wasn't just that we, um, you know, we built a system and delivered it, but if you go back a decade ago, or five years ago, there were, there were innovations that were built, you know, to accelerate that system. One is our Slingshot fabric as an example, which is a core enable of, of acceler, you know, of, of this accelerated computing environment, but others in software applications and services that allowed us to, you know, to really deliver a, a complete solution into the market. Um, today we're looking at things around trustworthy and ethical AI, so trustworthy AI in the sense that, you know, the models are accurate, you know, and that's, that's a challenge on two dimensions, cuz one is the, model's only as good as the data it's studying. >>So you need to validate that the data's accurate and then you need to really study how, you know, how do I make sure that even if the data is accurate, I've got a model that then, you know, is gonna predict the right things and not call a, a dog, a cat, or a, you know, a, a cat, a mouse or whatever that is. But so that's important. And, uh, so that's one area. The other is future system architectures because, um, as we've talked about before, Dave, you have this constant tension between the fabric, uh, you know, the interconnect, the compute and the, and the storage and, you know, constant, constantly balancing it. And so we're really looking at that, how do we do more, you know, shared memory access? How do we, you know, how do we do more direct rights? Like, you know, looking at some future system architectures and thinking about that. And we, you know, we think that's really, really critical in this part of the business because these heterogeneous systems, and not saying I'm gonna have one monolithic application, but I'm gonna have applications that need to take advantage of different code, different technologies at different times. And being able to move that seamlessly across the architecture, uh, we think is gonna be the, you know, a part of the, the hallmark of the Exoscale era, including >>Edge, which is a completely different animal. I think that's where some disruption is gonna gonna bubble up here in the next decade. >>So, yeah know, and, and that's, you know, that's the last thing I'd say is, is we look at AI at scale, which is another core part of the business that can run on these large clusters. That means getting all the way down to the edge and doing inference at scale, right. And, and inference at scale is, you know, I, I was, um, about a month ago, I was at the world economic forum. We were talking about the space economy and it's a great, you know, to me, it's the perfect example of inference, because if you get a set of data that you know, is, is out at Mars, it doesn't matter whether, you know, whether you wanna push all that data back to, uh, to earth for processing or not. You don't really have a choice, cuz it's just gonna take too long. >>Don't have that time. Justin, thank you so much for spending some of your time with Dave and me talking about what's going on with HBC and AI. The frontier just seems endless and very exciting. We appreciate your time on your insights. >>Great. Thanks so much. Thanks. >>Yes. And don't call a dog, a cat that I thought I learned from you. A dog at no, Nope. <laugh> Nope. <laugh> for Justin and Dave ante. I'm Lisa Martin. You're watching the Cube's coverage of day one from HPE. Discover 22. The cube is, guess what? The leader, the leader in live tech coverage will be right back with our next guest.

(upbeat music) >> Okay, welcome back everyone. The cube coverage of AWS re:Mars, 2022. I'm John Furrier, host of theCUBE. We got Eric Foellmer, vice president of marketing at Boston Dynamics. Famous for Spot. We all know, we've seen the videos, zillion views. Mega views all over the internet. The dog robotics, it's famous. Rolls over, bounces up and down. I mean, how many TikTok videos are out there? Probably a ton. >> Oh, Spot is- Spot is world famous (John laughs) at this point, right? So it's the dance videos, and all the application videos that we have out there. Spot is become has become world famous. >> Eric, thanks for joining us on theCUBE here at re:Mars. This show really is back. There was still a pandemic hiatus there. But it's not a part of the re's. It's re Mars, reinforcement of security, and then reinvent the flagship show for AWS. But this show is different. It brings together a lot of disciplines. But it's converging in on what we see as the next general- Industrial space is a big poster child for that. Obviously in space, it's highly industrial, highly secure. Machine learning's powering all the devices. You guys have been in this, I mean a leader, in a robotics area. What's this show about? I mean, what's really happening here. What if you had to boil the essence of the top story of what's happening here? What would it be? >> So the way that I look at this show is it really is a convergence of innovation. Like this is really just the cutting edge of the innovation that's really happening throughout robotics, but throughout technology in general. And you know, part of this cultural shift will be to adopt these types of technologies in our everyday life. And I think if you ask any technology specialist here or any innovator here or entrepreneur. They'll tell you that they want their technologies to become ubiquitous in society, right? I mean, that's really what everyone is sort of driving towards from the perspective of- >> And we, and we got some company behind it. Look at this. >> Oh, there we go. >> All right. >> There's a (Eric laughs) There's one of our Spots. >> It's got one of those back there. All right so sorry to interrupt, got a little distracted by the beautiful thing there. >> So they're literally walking around and literally engulfing the show. So when I look at the show, that's what I see. >> Let's see the picture of- >> I see the future of technology. >> Get a camera on our photo bomb here going on. Get a photo bomb action. (Eric chuckles) It's just super exciting because it really, it humanizes, it makes you- Everyone loves dogs. And, you know, I mean, people have more empathy if you kicked Spot than, you know, a human. Because there's so much empathy for just the innovation. But let's get into the innovation because let's- The IOT tech scene has been slow. Cloud computing Amazon web services, the leader hyper scaler. They dominated the back office you know, data centers, all the servers, digital transformation. Now that's coming to the edge. Where robotics is now in play. Space, material handling, devices for helping people who are sick or in healthcare. >> Eric: Mhm. >> So a whole surge of revolutionary or transitionary technologies coming. What's your take on that? >> So I think, you know, data has become the driving force behind technology innovation. And so robotics are an enabler for the tech, for the data collection that is going to drive IOT and manufacturing 4.0 and other important edge related and, you know, futuristic technology innovations, right? So the driver of all of that is data. And so robots like Spot are collectors of data. And so instead of trying to retrofit a manufacturing plant, you know, with 30, 40, 50 year old equipment in some cases. With IOT sensors and, you know, fixed sensors throughout the network. We're bringing the sensors to the equipment in the form of an agile mobile robot that brings that technology forward and is able to assess. >> So explain that a little slower for me. So the one method would be retrofitting all the devices. Or the hardware currently installed. >> Eric: Sure. >> Versus almost like having a mobile unit next to it, kind of thing. Or- >> Right. So, I mean, if you're looking at antiquated equipment which is what most, you know, manufacturing plants are running off of. It's not really practical or feasible to update them with fixed sensors. So sensors that specifically take measurements from that machine. So, we enable Spot with a variety of sensors from audio sensors to listen for audio anomalies. Thermal detectors, to look for thermal hotspots in equipment. Or visual detectors, where it's reading analog gauges, that sort of thing. So by doing that, we are bringing the sensors to the machines. >> Yeah. >> And to be able to walk anywhere where a human can walk throughout a manufacturing plant. To inspect the equipment, take that reading. And then most importantly upload that to the cloud, to the users >> It's a service dog. >> you can apply some- >> It's a service dog. >> It really is. And it serves data for the understanding of how that equipment is operated. >> This is big agility for the customer. Get that data, agile. Talk about the cost impact of that, just alone. What the alternative would be versus say, deploying that scenario. Because I'd imagine the time and cost would be huge. >> Well, if you think, you know, about how much manufacturing facilities put into the predictive maintenance and being able to forecast when their equipment needs maintenance. But also when pieces of equipment are going to fail. Unexpected downtime is one of the biggest money drains of any manufacturing facility. So the ability to be able to forecast and get some insight into when that equipment is starting to perform less than optimally and start to degrade. The ability to forecast that in advance is massive. >> Well I think you just win on just in retrofit cost alone, nevermind the downside scenarios of manufacturing problems. All right, let's zoom out. You guys have been pioneers for a long time. What's changed in your mind now versus just a few years ago. I mean, look at even 5, 10 years ago. The evolution, cost and capability. What's changed the most? >> Yeah, I think the accessibility of robots has really changed. And we're just on the beginning stages of that evolution. We really are. We're at the precipice right now of robots becoming much more ubiquitous in people's lives. And that's really our foundation as a company. Is we really want to bring robots to mankind for the good of humanity, right? So if you think about, you know, taking humans out of harm's way. Or, you know, putting robots in situations where, you know, where it's assessing damage for a building, for example, right. You're taking people out of the, out of that harm's way and really standardizing what you're able to do with technology. So we see it as really being on the very entry point of having not only robotics, but technology in general to become much more prevalent in people's lives. >> Yeah. >> I mean, what, you know. 30 years ago, did you ever think that you would have the power of a supercomputer in your pocket to, you know. Which also happens to allow you to talk to people but it is so much more, right? So the power of a cell phone has changed our lives forever. >> A computer that happens to be a phone. You know, it's like, come on. >> Right. >> What's going on with that. >> That's almost secondary at this point. (John laughing) It really is. So, I mean, when you think about that transition from you know, I think we're at the cusp of that right now. We're at the beginning stages of it. And it's really, it's an exciting time to be part of this. An entire industry. >> Before I get your views on integration and scale. Because that's the next level. We're seeing a lot of action and growth. Talk about the use case. You've mentioned a few of them, take people out of harms way. What have you guys seen as use cases within Boston Dynamics customer base and or your partner network around use cases. That either you knew would happen, or ones that might have surprised you? >> Yeah. One of the biggest use cases for us right now is what we're demonstrating here at re:MARS. Which is the ability to walk through a manufacturing plant and collect data off various pieces of equipment. Whether that's pump or a gauge or seeing whether a valve is open or closed. These are all simple mundane tasks that people are, that manufacturers are having difficulty finding people to be able to perform. So the ability for a robot to go over and do that and standardize that process is really valuable. As companies are trying to collect that data in a consistent way. So that's one of the most prevalent use cases that we're seeing right now. And certainly also in cases where, you know, Spot is going into buildings that have been structurally damaged. Or, you know, assessing situations where we don't want people to be in harm's way. >> John: Yeah. >> You know- >> Bomb scares, or any kind of situation with police or, you know, threatening or danger situations. >> Sure. And fire departments as well. I mean, fire departments are becoming a huge, you know, a huge user of the robots themselves. Fire department in New York recently just adopted some of our robots as well. For that purpose, for search and rescue applications. >> Yeah. Go in, go see what's in there. See what's around the corner. It gives a very tactical edge capability for say the firefighter or law enforcement. I see that- I see the military applications must be really insane. >> Sure. From a search and rescue perspective. Absolutely. I mean, Spot helps you put eyes on situations that will allow a human to be operating at a safe distance. So it's really a great value for protecting human life and making sure that people stay out of harm's way. >> Well Eric, I really appreciate you coming on theCUBE and sharing your insight. One other question I'd like to ask if you don't mind is, you know. The one of the things I see next to your booth is the university piece. And then you see the Amazon, you know, material management. I don't know what to call it, but it's pretty impressive. And then I saw some of the demos on the keynotes. Looking at the scale of synthetic data. Just it's mind blowing what's going on in manufacturing. Amazon is pretty state of the art. I'm sure there are a customer of yours already. But they look complex these manufacturing sites. I mean, it looks like a maze. So how do you... I mean, I could see the consequences of something breaking, to be catastrophic. Because it's almost like, it's so integrated. Is this where you guys see success and how do these manufacturers deal with this? What's the... Is it like one big OS? >> Yeah, so the robots, because the robots are able to act independently. They can traverse difficult terrain and collect data on their own. And then, you know, what happens to that data afterwards is really up to the manufacturing. It can be delivered from the cloud and you can, it can be delivered via the edge. You know, edge devices and really that's where some of the exciting work is being done right now. Because that's where data can scale. And that's where robot deployments can scale as well, right? So you've got instead of a single robot. Now you have an operator deploying multiple robots. Monitoring, controlling, and assessing the data from multiple robots throughout a facility. And it really helps to scale that investment. >> All right, final question for you. This is personal question. Okay, I know- Saw your booth over there. And you have a lot of fan base. Spot's got a huge fan base. What are some of the crazy things that these nerd fans do? I mean, everyone get selfies with the Spot. They want to- I jump over the fence. I see, "Don't touch the dog." signs everywhere. The fan base is off the charts. What are the crazy things that people do to get either access to it. There's probably, been probably some theft, probably. Attempts, or selfies. Share some funny stories. >> I'll say this. My team is responsible for fielding a lot of the inbound inquiries that we get. Much of which comes from the entertainment industry. And as you've seen Spot has been featured in some really prominent, you know, entertainment pieces. You know, we were in that Super Bowl ad with Sam Adams. We were on Jimmy Kimmel, you know, during the Super Bowl time period. So the amount of entertainment... >> Value >> Pitches. Or the amount of entertainment value is immeasurable. But the number of pitches that we turn down is staggering. And when you can think about how most companies would probably pull out all the stops to take, you know. To be able to execute half the things that we're just, from a time perspective, from a resource perspective >> Okay, so Spots an A- not always able to do. >> So Spots an A-lister, I get that. Is there a B-lister now? I mean, that sounds like there's a market developing for Spot two. Is there a Spot two? The B player coming in? Understudy? >> So, I mean, Spot is always evolving. I think, you know, the physical- the physical statue that you see of Spot right now, Is where we're going to be in terms of the hardware, but we continue to move the robot forward. It becomes more and more advanced and more and more capable to do more and more things for people. So. >> All right. Well, we'll roll some B roll on this, on theCUBE. Thanks for coming on theCUBE. Really appreciate it. Boston Dynamics here in theCUBE, famous for Spot. And then here, the show packed here in re:MARS featuring, you know, robotics. It's a big feature hall. It's a set piece here in the show floor. And of course theCUBE's covering it. Thanks for watching. More coverage. I'm John Furrier, your host. After the short break. (upbeat music)

>>Time series data is any data that's stamped in time in some way that could be every second, every minute, every five minutes, every hour, every nanosecond, whatever it might be. And typically that data comes from sources in the physical world like devices or sensors, temperature, gauges, batteries, any device really, or things in the virtual world could be software, maybe it's software in the cloud or data and containers or microservices or virtual machines. So all of these items, whether in the physical or virtual world, they're generating a lot of time series data. Now time series data has been around for a long time, and there are many examples in our everyday lives. All you gotta do is punch up any stock, ticker and look at its price over time and graphical form. And that's a simple use case that anyone can relate to and you can build timestamps into a traditional relational database. >>You just add a column to capture time and as well, there are examples of log data being dumped into a data store that can be searched and captured and ingested and visualized. Now, the problem with the latter example that I just gave you is that you gotta hunt and Peck and search and extract what you're looking for. And the problem with the former is that traditional general purpose databases they're designed as sort of a Swiss army knife for any workload. And there are a lot of functions that get in the way and make them inefficient for time series analysis, especially at scale. Like when you think about O T and edge scale, where things are happening super fast, ingestion is coming from many different sources and analysis often needs to be done in real time or near real time. And that's where time series databases come in. >>They're purpose built and can much more efficiently support ingesting metrics at scale, and then comparing data points over time, time series databases can write and read at significantly higher speeds and deal with far more data than traditional database methods. And they're more cost effective instead of throwing processing power at the problem. For example, the underlying architecture and algorithms of time series databases can optimize queries and they can reclaim wasted storage space and reuse it. At scale time, series databases are simply a better fit for the job. Welcome to moving the world with influx DB made possible by influx data. My name is Dave Valante and I'll be your host today. Influx data is the company behind InfluxDB. The open source time series database InfluxDB is designed specifically to handle time series data. As I just explained, we have an exciting program for you today, and we're gonna showcase some really interesting use cases. >>First, we'll kick it off in our Palo Alto studios where my colleague, John furrier will interview Evan Kaplan. Who's the CEO of influx data after John and Evan set the table. John's gonna sit down with Brian Gilmore. He's the director of IOT and emerging tech at influx data. And they're gonna dig into where influx data is gaining traction and why adoption is occurring and, and why it's so robust. And they're gonna have tons of examples and double click into the technology. And then we bring it back here to our east coast studios, where I get to talk to two practitioners, doing amazing things in space with satellites and modern telescopes. These use cases will blow your mind. You don't want to miss it. So thanks for being here today. And with that, let's get started. Take it away. Palo Alto. >>Okay. Today we welcome Evan Kaplan, CEO of influx data, the company behind influx DB. Welcome Evan. Thanks for coming on. >>Hey John, thanks for having me >>Great segment here on the influx DB story. What is the story? Take us through the history. Why time series? What's the story >><laugh> so the history history is actually actually pretty interesting. Um, Paul dicks, my partner in this and our founder, um, super passionate about developers and developer experience. And, um, he had worked on wall street building a number of time series kind of platform trading platforms for trading stocks. And from his point of view, it was always what he would call a yak shave, which means you had to do a ton of work just to start doing work, which means you had to write a bunch of extrinsic routines. You had to write a bunch of application handling on existing relational databases in order to come up with something that was optimized for a trading platform or a time series platform. And he sort of, he just developed this real clear point of view is this is not how developers should work. And so in 2013, he went through why Combinator and he built something for, he made his first commit to open source in flu DB at the end of 2013. And, and he basically, you know, from my point of view, he invented modern time series, which is you start with a purpose-built time series platform to do these kind of workloads. And you get all the benefits of having something right outta the box. So a developer can be totally productive right away. >>And how many people in the company what's the history of employees and stuff? >>Yeah, I think we're, I, you know, I always forget the number, but it's something like 230 or 240 people now. Um, the company, I joined the company in 2016 and I love Paul's vision. And I just had a strong conviction about the relationship between time series and IOT. Cuz if you think about it, what sensors do is they speak time, series, pressure, temperature, volume, humidity, light, they're measuring they're instrumenting something over time. And so I thought that would be super relevant over long term and I've not regretted it. >>Oh no. And it's interesting at that time, go back in the history, you know, the role of databases, well, relational database is the one database to rule the world. And then as clouds started coming in, you starting to see more databases, proliferate types of databases and time series in particular is interesting. Cuz real time has become super valuable from an application standpoint, O T which speaks time series means something it's like time matters >>Time. >>Yeah. And sometimes data's not worth it after the time, sometimes it worth it. And then you get the data lake. So you have this whole new evolution. Is this the momentum? What's the momentum, I guess the question is what's the momentum behind >>You mean what's causing us to grow. So >>Yeah, the time series, why is time series >>And the >>Category momentum? What's the bottom line? >>Well, think about it. You think about it from a broad, broad sort of frame, which is where, what everybody's trying to do is build increasingly intelligent systems, whether it's a self-driving car or a robotic system that does what you want to do or a self-healing software system, everybody wants to build increasing intelligent systems. And so in order to build these increasing intelligent systems, you have to instrument the system well, and you have to instrument it over time, better and better. And so you need a tool, a fundamental tool to drive that instrumentation. And that's become clear to everybody that that instrumentation is all based on time. And so what happened, what happened, what happened what's gonna happen? And so you get to these applications like predictive maintenance or smarter systems. And increasingly you want to do that stuff, not just intelligently, but fast in real time. So millisecond response so that when you're driving a self-driving car and the system realizes that you're about to do something, essentially you wanna be able to act in something that looks like real time, all systems want to do that, want to be more intelligent and they want to be more real time. And so we just happen to, you know, we happen to show up at the right time in the evolution of a >>Market. It's interesting near real time. Isn't good enough when you need real time. >><laugh> yeah, it's not, it's not. And it's like, and it's like, everybody wants, even when you don't need it, ironically, you want it. It's like having the feature for, you know, you buy a new television, you want that one feature, even though you're not gonna use it, you decide that your buying criteria real time is a buying criteria >>For, so you, I mean, what you're saying then is near real time is getting closer to real time as possible, as fast as possible. Right. Okay. So talk about the aspect of data, cuz we're hearing a lot of conversations on the cube in particular around how people are implementing and actually getting better. So iterating on data, but you have to know when it happened to get, know how to fix it. So this is a big part of how we're seeing with people saying, Hey, you know, I wanna make my machine learning algorithms better after the fact I wanna learn from the data. Um, how does that, how do you see that evolving? Is that one of the use cases of sensors as people bring data in off the network, getting better with the data knowing when it happened? >>Well, for sure. So, so for sure, what you're saying is, is, is none of this is non-linear, it's all incremental. And so if you take something, you know, just as an easy example, if you take a self-driving car, what you're doing is you're instrumenting that car to understand where it can perform in the real world in real time. And if you do that, if you run the loop, which is I instrumented, I watch what happens, oh, that's wrong? Oh, I have to correct for that. I correct for that in the software. If you do that for a billion times, you get a self-driving car, but every system moves along that evolution. And so you get the dynamic of, you know, of constantly instrumenting watching the system behave and do it. And this and sets up driving car is one thing. But even in the human genome, if you look at some of our customers, you know, people like, you know, people doing solar arrays, people doing power walls, like all of these systems are getting smarter. >>Well, let's get into that. What are the top applications? What are you seeing for your, with in, with influx DB, the time series, what's the sweet spot for the application use case and some customers give some >>Examples. Yeah. So it's, it's pretty easy to understand on one side of the equation that's the physical side is sensors are sensors are getting cheap. Obviously we know that and they're getting the whole physical world is getting instrumented, your home, your car, the factory floor, your wrist, watch your healthcare, you name it. It's getting instrumented in the physical world. We're watching the physical world in real time. And so there are three or four sweet spots for us, but, but they're all on that side. They're all about IOT. So they're think about consumer IOT projects like Google's nest todo, um, particle sensors, um, even delivery engines like rapid who deliver the Instacart of south America, like anywhere there's a physical location do and that's on the consumer side. And then another exciting space is the industrial side factories are changing dramatically over time. Increasingly moving away from proprietary equipment to develop or driven systems that run operational because what, what has to get smarter when you're building, when you're building a factory is systems all have to get smarter. And then, um, lastly, a lot in the renewables sustainability. So a lot, you know, Tesla, lucid, motors, Cola, motors, um, you know, lots to do with electric cars, solar arrays, windmills, arrays, just anything that's gonna get instrumented that where that instrumentation becomes part of what the purpose >>Is. It's interesting. The convergence of physical and digital is happening with the data IOT. You mentioned, you know, you think of IOT, look at the use cases there, it was proprietary OT systems. Now becoming more IP enabled internet protocol and now edge compute, getting smaller, faster, cheaper AI going to the edge. Now you have all kinds of new capabilities that bring that real time and time series opportunity. Are you seeing IOT going to a new level? What was the, what's the IOT where's the IOT dots connecting to because you know, as these two cultures merge yeah. Operations, basically industrial factory car, they gotta get smarter, intelligent edge is a buzzword, but I mean, it has to be more intelligent. Where's the, where's the action in all this. So the >>Action, really, it really at the core, it's at the developer, right? Because you're looking at these things, it's very hard to get an off the shelf system to do the kinds of physical and software interaction. So the actions really happen at the developer. And so what you're seeing is a movement in the world that, that maybe you and I grew up in with it or OT moving increasingly that developer driven capability. And so all of these IOT systems they're bespoke, they don't come out of the box. And so the developer, the architect, the CTO, they define what's my business. What am I trying to do? Am I trying to sequence a human genome and figure out when these genes express theself or am I trying to figure out when the next heart rate monitor's gonna show up on my apple watch, right? What am I trying to do? What's the system I need to build. And so starting with the developers where all of the good stuff happens here, which is different than it used to be, right. Used to be you'd buy an application or a service or a SA thing for, but with this dynamic, with this integration of systems, it's all about bespoke. It's all about building >>Something. So let's get to the developer real quick, real highlight point here is the data. I mean, I could see a developer saying, okay, I need to have an application for the edge IOT edge or car. I mean, we're gonna have, I mean, Tesla's got applications of the car it's right there. I mean, yes, there's the modern application life cycle now. So take us through how this impacts the developer. Does it impact their C I C D pipeline? Is it cloud native? I mean, where does this all, where does this go to? >>Well, so first of all, you're talking about, there was an internal journey that we had to go through as a company, which, which I think is fascinating for anybody who's interested is we went from primarily a monolithic software that was open sourced to building a cloud native platform, which means we had to move from an agile development environment to a C I C D environment. So to a degree that you are moving your service, whether it's, you know, Tesla monitoring your car and updating your power walls, right. Or whether it's a solar company updating the arrays, right. To degree that that service is cloud. Then increasingly remove from an agile development to a C I C D environment, which you're shipping code to production every day. And so it's not just the developers, all the infrastructure to support the developers to run that service and that sort of stuff. I think that's also gonna happen in a big way >>When your customer base that you have now, and as you see, evolving with infl DB, is it that they're gonna be writing more of the application or relying more on others? I mean, obviously there's an open source component here. So when you bring in kind of old way, new way old way was I got a proprietary, a platform running all this O T stuff and I gotta write, here's an application. That's general purpose. Yeah. I have some flexibility, somewhat brittle, maybe not a lot of robustness to it, but it does its job >>A good way to think about this is versus a new way >>Is >>What so yeah, good way to think about this is what, what's the role of the developer slash architect CTO that chain within a large, within an enterprise or a company. And so, um, the way to think about it is I started my career in the aerospace industry <laugh> and so when you look at what Boeing does to assemble a plane, they build very, very few of the parts. Instead, what they do is they assemble, they buy the wings, they buy the engines, they assemble, actually, they don't buy the wings. It's the one thing they buy the, the material for the w they build the wings, cuz there's a lot of tech in the wings and they end up being assemblers smart assemblers of what ends up being a flying airplane, which is pretty big deal even now. And so what, what happens with software people is they have the ability to pull from, you know, the best of the open source world. So they would pull a time series capability from us. Then they would assemble that with, with potentially some ETL logic from somebody else, or they'd assemble it with, um, a Kafka interface to be able to stream the data in. And so they become very good integrators and assemblers, but they become masters of that bespoke application. And I think that's where it goes, cuz you're not writing native code for everything. >>So they're more flexible. They have faster time to market cuz they're assembling way faster and they get to still maintain their core competency. Okay. Their wings in this case, >>They become increasingly not just coders, but designers and developers. They become broadly builders is what we like to think of it. People who start and build stuff by the way, this is not different than the people just up the road Google have been doing for years or the tier one, Amazon building all their own. >>Well, I think one of the things that's interesting is is that this idea of a systems developing a system architecture, I mean systems, uh, uh, systems have consequences when you make changes. So when you have now cloud data center on premise and edge working together, how does that work across the system? You can't have a wing that doesn't work with the other wing kind of thing. >>That's exactly. But that's where the that's where the, you know, that that Boeing or that airplane building analogy comes in for us. We've really been thoughtful about that because IOT it's critical. So our open source edge has the same API as our cloud native stuff that has enterprise on pre edge. So our multiple products have the same API and they have a relationship with each other. They can talk with each other. So the builder builds it once. And so this is where, when you start thinking about the components that people have to use to build these services is that you wanna make sure, at least that base layer, that database layer, that those components talk to each other. >>So I'll have to ask you if I'm the customer. I put my customer hat on. Okay. Hey, I'm dealing with a lot. >>That mean you have a PO for <laugh> >>A big check. I blank check. If you can answer this question only if the tech, if, if you get the question right, I got all this important operation stuff. I got my factory, I got my self-driving cars. This isn't like trivial stuff. This is my business. How should I be thinking about time series? Because now I have to make these architectural decisions, as you mentioned, and it's gonna impact my application development. So huge decision point for your customers. What should I care about the most? So what's in it for me. Why is time series >>Important? Yeah, that's a great question. So chances are, if you've got a business that was, you know, 20 years old or 25 years old, you were already thinking about time series. You probably didn't call it that you built something on a Oracle or you built something on IBM's DB two, right. And you made it work within your system. Right? And so that's what you started building. So it's already out there. There are, you know, there are probably hundreds of millions of time series applications out there today. But as you start to think about this increasing need for real time, and you start to think about increasing intelligence, you think about optimizing those systems over time. I hate the word, but digital transformation. Then you start with time series. It's a foundational base layer for any system that you're gonna build. There's no system I can think of where time series, shouldn't be the foundational base layer. If you just wanna store your data and just leave it there and then maybe look it up every five years. That's fine. That's not time. Series time series is when you're building a smarter, more intelligent, more real time system. And the developers now know that. And so the more they play a role in building these systems, the more obvious it becomes. >>And since I have a PO for you and a big check, yeah. What is, what's the value to me as I, when I implement this, what's the end state, what's it look like when it's up and running? What's the value proposition for me. What's an >>So, so when it's up and running, you're able to handle the queries, the writing of the data, the down sampling of the data, they're transforming it in near real time. So that the other dependencies that a system that gets for adjusting a solar array or trading energy off of a power wall or some sort of human genome, those systems work better. So time series is foundational. It's not like it's, you know, it's not like it's doing every action that's above, but it's foundational to build a really compelling, intelligent system. I think that's what developers and archs are seeing now. >>Bottom line, final word. What's in it for the customer. What's what, what's your, um, what's your statement to the customer? What would you say to someone looking to do something in time series on edge? >>Yeah. So, so it's pretty clear to clear to us that if you're building, if you view yourself as being in the build business of building systems that you want 'em to be increasingly intelligent, self-healing autonomous. You want 'em to operate in real time that you start from time series. But I also wanna say what's in it for us influx what's in it for us is people are doing some amazing stuff. You know, I highlighted some of the energy stuff, some of the human genome, some of the healthcare it's hard not to be proud or feel like, wow. Yeah. Somehow I've been lucky. I've arrived at the right time, in the right place with the right people to be able to deliver on that. That's that's also exciting on our side of the equation. >>Yeah. It's critical infrastructure, critical, critical operations. >>Yeah. >>Yeah. Great stuff, Evan. Thanks for coming on. Appreciate this segment. All right. In a moment, Brian Gilmore director of IOT and emerging technology that influx day will join me. You're watching the cube leader in tech coverage. Thanks for watching >>Time series data from sensors systems and applications is a key source in driving automation and prediction in technologies around the world. But managing the massive amount of timestamp data generated these days is overwhelming, especially at scale. That's why influx data developed influx DB, a time series data platform that collects stores and analyzes data influx DB empowers developers to extract valuable insights and turn them into action by building transformative IOT analytics and cloud native applications, purpose built and optimized to handle the scale and velocity of timestamped data. InfluxDB puts the power in your hands with developer tools that make it easy to get started quickly with less code InfluxDB is more than a database. It's a robust developer platform with integrated tooling. That's written in the languages you love. So you can innovate faster, run in flex DB anywhere you want by choosing the provider and region that best fits your needs across AWS, Microsoft Azure and Google cloud flex DB is fast and automatically scalable. So you can spend time delivering value to customers, not managing clusters, take control of your time series data. So you can focus on the features and functionalities that give your applications a competitive edge. Get started for free with influx DB, visit influx data.com/cloud to learn more. >>Okay. Now we're joined by Brian Gilmore director of IOT and emerging technologies at influx data. Welcome to the show. >>Thank you, John. Great to be here. >>We just spent some time with Evan going through the company and the value proposition, um, with influx DV, what's the momentum, where do you see this coming from? What's the value coming out of this? >>Well, I think it, we're sort of hitting a point where the technology is, is like the adoption of it is becoming mainstream. We're seeing it in all sorts of organizations, everybody from like the most well funded sort of advanced big technology companies to the smaller academics, the startups and the managing of that sort of data that emits from that technology is time series and us being able to give them a, a platform, a tool that's super easy to use, easy to start. And then of course will grow with them is, is been key to us. Sort of, you know, riding along with them is they're successful. >>Evan was mentioning that time series has been on everyone's radar and that's in the OT business for years. Now, you go back since 20 13, 14, even like five years ago that convergence of physical and digital coming together, IP enabled edge. Yeah. Edge has always been kind of hyped up, but why now? Why, why is the edge so hot right now from an adoption standpoint? Is it because it's just evolution, the tech getting better? >>I think it's, it's, it's twofold. I think that, you know, there was, I would think for some people, everybody was so focused on cloud over the last probably 10 years. Mm-hmm <affirmative> that they forgot about the compute that was available at the edge. And I think, you know, those, especially in the OT and on the factory floor who weren't able to take Avan full advantage of cloud through their applications, you know, still needed to be able to leverage that compute at the edge. I think the big thing that we're seeing now, which is interesting is, is that there's like a hybrid nature to all of these applications where there's definitely some data that's generated on the edge. There's definitely done some data that's generated in the cloud. And it's the ability for a developer to sort of like tie those two systems together and work with that data in a very unified uniform way. Um, that's giving them the opportunity to build solutions that, you know, really deliver value to whatever it is they're trying to do, whether it's, you know, the, the out reaches of outer space or whether it's optimizing the factory floor. >>Yeah. I think, I think one of the things you also mentions genome too, dig big data is coming to the real world. And I think I, OT has been kind of like this thing for OT and, and in some use case, but now with the, with the cloud, all companies have an edge strategy now. So yeah, what's the secret sauce because now this is hot, hot product for the whole world and not just industrial, but all businesses. What's the secret sauce. >>Well, I mean, I think part of it is just that the technology is becoming more capable and that's especially on the hardware side, right? I mean, like technology compute is getting smaller and smaller and smaller. And we find that by supporting all the way down to the edge, even to the micro controller layer with our, um, you know, our client libraries and then working hard to make our applications, especially the database as small as possible so that it can be located as close to sort of the point of origin of that data in the edge as possible is, is, is fantastic. Now you can take that. You can run that locally. You can do your local decision making. You can use influx DB as sort of an input to automation control the autonomy that people are trying to drive at the edge. But when you link it up with everything that's in the cloud, that's when you get all of the sort of cloud scale capabilities of parallelized, AI and machine learning and all of that. >>So what's interesting is the open source success has been something that we've talked about a lot in the cube about how people are leveraging that you guys have users in the enterprise users that IOT market mm-hmm <affirmative>, but you got developers now. Yeah. Kind of together brought that up. How do you see that emerging? How do developers engage? What are some of the things you're seeing that developers are really getting into with InfluxDB >>What's? Yeah. Well, I mean, I think there are the developers who are building companies, right? And these are the startups and the folks that we love to work with who are building new, you know, new services, new products, things like that. And, you know, especially on the consumer side of IOT, there's a lot of that, just those developers. But I think we, you gotta pay attention to those enterprise developers as well, right? There are tons of people with the, the title of engineer in, in your regular enterprise organizations. And they're there for systems integration. They're there for, you know, looking at what they would build versus what they would buy. And a lot of them come from, you know, a strong, open source background and they, they know the communities, they know the top platforms in those spaces and, and, you know, they're excited to be able to adopt and use, you know, to optimize inside the business as compared to just building a brand new one. >>You know, it's interesting too, when Evan and I were talking about open source versus closed OT systems, mm-hmm <affirmative> so how do you support the backwards compatibility of older systems while maintaining open dozens of data formats out there? Bunch of standards, protocols, new things are emerging. Everyone wants to have a control plane. Everyone wants to leverage the value of data. How do you guys keep track of it all? What do you guys support? >>Yeah, well, I mean, I think either through direct connection, like we have a product called Telegraph, it's unbelievable. It's open source, it's an edge agent. You can run it as close to the edge as you'd like, it speaks dozens of different protocols in its own, right? A couple of which MQTT B, C U a are very, very, um, applicable to these T use cases. But then we also, because we are sort of not only open source, but open in terms of our ability to collect data, we have a lot of partners who have built really great integrations from their own middleware, into influx DB. These are companies like ke wear and high bite who are really experts in those downstream industrial protocols. I mean, that's a business, not everybody wants to be in. It requires some very specialized, very hard work and a lot of support, um, you know, and so by making those connections and building those ecosystems, we get the best of both worlds. The customers can use the platforms they need up to the point where they would be putting into our database. >>What's some of customer testimonies that they, that share with you. Can you share some anecdotal kind of like, wow, that's the best thing I've ever used. This really changed my business, or this is a great tech that's helped me in these other areas. What are some of the, um, soundbites you hear from customers when they're successful? >>Yeah. I mean, I think it ranges. You've got customers who are, you know, just finally being able to do the monitoring of assets, you know, sort of at the edge in the field, we have a customer who's who's has these tunnel boring machines that go deep into the earth to like drill tunnels for, for, you know, cars and, and, you know, trains and things like that. You know, they are just excited to be able to stick a database onto those tunnel, boring machines, send them into the depths of the earth and know that when they come out, all of that telemetry at a very high frequency has been like safely stored. And then it can just very quickly and instantly connect up to their, you know, centralized database. So like just having that visibility is brand new to them. And that's super important. On the other hand, we have customers who are way far beyond the monitoring use case, where they're actually using the historical records in the time series database to, um, like I think Evan mentioned like forecast things. So for predictive maintenance, being able to pull in the telemetry from the machines, but then also all of that external enrichment data, the metadata, the temperatures, the pressure is who is operating the machine, those types of things, and being able to easily integrate with platforms like Jupyter notebooks or, you know, all of those scientific computing and machine learning libraries to be able to build the models, train the models, and then they can send that information back down to InfluxDB to apply it and detect those anomalies, which >>Are, I think that's gonna be an, an area. I personally think that's a hot area because I think if you look at AI right now, yeah. It's all about training the machine learning albums after the fact. So time series becomes hugely important. Yeah. Cause now you're thinking, okay, the data matters post time. Yeah. First time. And then it gets updated the new time. Yeah. So it's like constant data cleansing data iteration, data programming. We're starting to see this new use case emerge in the data field. >>Yep. Yeah. I mean, I think you agree. Yeah, of course. Yeah. The, the ability to sort of handle those pipelines of data smartly, um, intelligently, and then to be able to do all of the things you need to do with that data in stream, um, before it hits your sort of central repository. And, and we make that really easy for customers like Telegraph, not only does it have sort of the inputs to connect up to all of those protocols and the ability to capture and connect up to the, to the partner data. But also it has a whole bunch of capabilities around being able to process that data, enrich it, reform at it, route it, do whatever you need. So at that point you're basically able to, you're playing your data in exactly the way you would wanna do it. You're routing it to different, you know, destinations and, and it's, it's, it's not something that really has been in the realm of possibility until this point. Yeah. Yeah. >>And when Evan was on it's great. He was a CEO. So he sees the big picture with customers. He was, he kinda put the package together that said, Hey, we got a system. We got customers, people are wanting to leverage our product. What's your PO they're sell. He's selling too as well. So you have that whole CEO perspective, but he brought up this notion that there's multiple personas involved in kind of the influx DB system architect. You got developers and users. Can you talk about that? Reality as customers start to commercialize and operationalize this from a commercial standpoint, you got a relationship to the cloud. Yep. The edge is there. Yep. The edge is getting super important, but cloud brings a lot of scale to the table. So what is the relationship to the cloud? Can you share your thoughts on edge and its relationship to the cloud? >>Yeah. I mean, I think edge, you know, edges, you can think of it really as like the local information, right? So it's, it's generally like compartmentalized to a point of like, you know, a single asset or a single factory align, whatever. Um, but what people do who wanna pro they wanna be able to make the decisions there at the edge locally, um, quickly minus the latency of sort of taking that large volume of data, shipping it to the cloud and doing something with it there. So we allow them to do exactly that. Then what they can do is they can actually downsample that data or they can, you know, detect like the really important metrics or the anomalies. And then they can ship that to a central database in the cloud where they can do all sorts of really interesting things with it. Like you can get that centralized view of all of your global assets. You can start to compare asset to asset, and then you can do those things like we talked about, whereas you can do predictive types of analytics or, you know, larger scale anomaly detections. >>So in this model you have a lot of commercial operations, industrial equipment. Yep. The physical plant, physical business with virtual data cloud all coming together. What's the future for InfluxDB from a tech standpoint. Cause you got open. Yep. There's an ecosystem there. Yep. You have customers who want operational reliability for sure. I mean, so you got organic <laugh> >>Yeah. Yeah. I mean, I think, you know, again, we got iPhones when everybody's waiting for flying cars. Right. So I don't know. We can like absolutely perfectly predict what's coming, but I think there are some givens and I think those givens are gonna be that the world is only gonna become more hybrid. Right. And then, you know, so we are going to have much more widely distributed, you know, situations where you have data being generated in the cloud, you have data gen being generated at the edge and then there's gonna be data generated sort sort of at all points in between like physical locations as well as things that are, that are very virtual. And I think, you know, we are, we're building some technology right now. That's going to allow, um, the concept of a database to be much more fluid and flexible, sort of more aligned with what a file would be like. >>And so being able to move data to the compute for analysis or move the compute to the data for analysis, those are the types of, of solutions that we'll be bringing to the customers sort of over the next little bit. Um, but I also think we have to start thinking about like what happens when the edge is actually off the planet. Right. I mean, we've got customers, you're gonna talk to two of them, uh, in the panel who are actually working with data that comes from like outside the earth, like, you know, either in low earth orbit or you know, all the way sort of on the other side of the universe. Yeah. And, and to be able to process data like that and to do so in a way it's it's we gotta, we gotta build the fundamentals for that right now on the factory floor and in the mines and in the tunnels. Um, so that we'll be ready for that one. >>I think you bring up a good point there because one of the things that's common in the industry right now, people are talking about, this is kind of new thinking is hyper scale's always been built up full stack developers, even the old OT world, Evan was pointing out that they built everything right. And the world's going to more assembly with core competency and IP and also property being the core of their apple. So faster assembly and building, but also integration. You got all this new stuff happening. Yeah. And that's to separate out the data complexity from the app. Yes. So space genome. Yep. Driving cars throws off massive data. >>It >>Does. So is Tesla, uh, is the car the same as the data layer? >>I mean the, yeah, it's, it's certainly a point of origin. I think the thing that we wanna do is we wanna let the developers work on the world, changing problems, the things that they're trying to solve, whether it's, you know, energy or, you know, any of the other health or, you know, other challenges that these teams are, are building against. And we'll worry about that time series data and the underlying data platform so that they don't have to. Right. I mean, I think you talked about it, uh, you know, for them just to be able to adopt the platform quickly, integrate it with their data sources and the other pieces of their applications. It's going to allow them to bring much faster time to market on these products. It's gonna allow them to be more iterative. They're gonna be able to do more sort of testing and things like that. And ultimately it will, it'll accelerate the adoption and the creation of >>Technology. You mentioned earlier in, in our talk about unification of data. Yeah. How about APIs? Cuz developers love APIs in the cloud unifying APIs. How do you view view that? >>Yeah, I mean, we are APIs, that's the product itself. Like everything, people like to think of it as sort of having this nice front end, but the front end is B built on our public APIs. Um, you know, and it, it allows the developer to build all of those hooks for not only data creation, but then data processing, data analytics, and then, you know, sort of data extraction to bring it to other platforms or other applications, microservices, whatever it might be. So, I mean, it is a world of APIs right now and you know, we, we bring a very sort of useful set of them for managing the time series data. These guys are all challenged with. It's >>Interesting. You and I were talking before we came on camera about how, um, data is, feels gonna have this kind of SRE role that DevOps had site reliability engineers, which manages a bunch of servers. There's so much data out there now. Yeah. >>Yeah. It's like reigning data for sure. And I think like that ability to be like one of the best jobs on the planet is gonna be to be able to like, sort of be that data Wrangler to be able to understand like what the data sources are, what the data formats are, how to be able to efficiently move that data from point a to point B and you know, to process it correctly so that the end users of that data aren't doing any of that sort of hard upfront preparation collection storage's >>Work. Yeah. That's data as code. I mean, data engineering is it is becoming a new discipline for sure. And, and the democratization is the benefit. Yeah. To everyone, data science get easier. I mean data science, but they wanna make it easy. Right. <laugh> yeah. They wanna do the analysis, >>Right? Yeah. I mean, I think, you know, it, it's a really good point. I think like we try to give our users as many ways as there could be possible to get data in and get data out. We sort of think about it as meeting them where they are. Right. So like we build, we have the sort of client libraries that allow them to just port to us, you know, directly from the applications and the languages that they're writing, but then they can also pull it out. And at that point nobody's gonna know the users, the end consumers of that data, better than those people who are building those applications. And so they're building these user interfaces, which are making all of that data accessible for, you know, their end users inside their organization. >>Well, Brian, great segment, great insight. Thanks for sharing all, all the complexities and, and IOT that you guys helped take away with the APIs and, and assembly and, and all the system architectures that are changing edge is real cloud is real. Yeah, absolutely. Mainstream enterprises. And you got developer attraction too, so congratulations. >>Yeah. It's >>Great. Well, thank any, any last word you wanna share >>Deal with? No, just, I mean, please, you know, if you're, if you're gonna, if you're gonna check out influx TV, download it, try out the open source contribute if you can. That's a, that's a huge thing. It's part of being the open source community. Um, you know, but definitely just, just use it. I think when once people use it, they try it out. They'll understand very, >>Very quickly. So open source with developers, enterprise and edge coming together all together. You're gonna hear more about that in the next segment, too. Right. Thanks for coming on. Okay. Thanks. When we return, Dave LAN will lead a panel on edge and data influx DB. You're watching the cube, the leader in high tech enterprise coverage. >>Why the startup, we move really fast. We find that in flex DB can move as fast as us. It's just a great group, very collaborative, very interested in manufacturing. And we see a bright future in working with influence. My name is Aaron Seley. I'm the CTO at HBI. Highlight's one of the first companies to focus on manufacturing data and apply the concepts of data ops, treat that as an asset to deliver to the it system, to enable applications like overall equipment effectiveness that can help the factory produce better, smarter, faster time series data. And manufacturing's really important. If you take a piece of equipment, you have the temperature pressure at the moment that you can look at to kind of see the state of what's going on. So without that context and understanding you can't do what manufacturers ultimately want to do, which is predict the future. >>Influx DB represents kind of a new way to storm time series data with some more advanced technology and more importantly, more open technologies. The other thing that influx does really well is once the data's influx, it's very easy to get out, right? They have a modern rest API and other ways to access the data. That would be much more difficult to do integrations with classic historians highlight can serve to model data, aggregate data on the shop floor from a multitude of sources, whether that be P C U a servers, manufacturing execution systems, E R P et cetera, and then push that seamlessly into influx to then be able to run calculations. Manufacturing is changing this industrial 4.0, and what we're seeing is influx being part of that equation. Being used to store data off the unified name space, we recommend InfluxDB all the time to customers that are exploring a new way to share data manufacturing called the unified name space who have open questions around how do I share this new data that's coming through my UNS or my QTT broker? How do I store this and be able to query it over time? And we often point to influx as a solution for that is a great brand. It's a great group of people and it's a great technology. >>Okay. We're now going to go into the customer panel and we'd like to welcome Angelo Fasi. Who's a software engineer at the Vera C Ruben observatory in Caleb McLaughlin whose senior spacecraft operations software engineer at loft orbital guys. Thanks for joining us. You don't wanna miss folks this interview, Caleb, let's start with you. You work for an extremely cool company. You're launching satellites into space. I mean, there, of course doing that is, is highly complex and not a cheap endeavor. Tell us about loft Orbi and what you guys do to attack that problem. >>Yeah, absolutely. And, uh, thanks for having me here by the way. Uh, so loft orbital is a, uh, company. That's a series B startup now, uh, who and our mission basically is to provide, uh, rapid access to space for all kinds of customers. Uh, historically if you want to fly something in space, do something in space, it's extremely expensive. You need to book a launch, build a bus, hire a team to operate it, you know, have a big software teams, uh, and then eventually worry about, you know, a bunch like just a lot of very specialized engineering. And what we're trying to do is change that from a super specialized problem that has an extremely high barrier of access to a infrastructure problem. So that it's almost as simple as, you know, deploying a VM in, uh, AWS or GCP is getting your, uh, programs, your mission deployed on orbit, uh, with access to, you know, different sensors, uh, cameras, radios, stuff like that. >>So that's, that's kind of our mission. And just to give a really brief example of the kind of customer that we can serve. Uh, there's a really cool company called, uh, totem labs who is working on building, uh, IOT cons, an IOT constellation for in of things, basically being able to get telemetry from all over the world. They're the first company to demonstrate indoor T, which means you have this little modem inside a container container that you, that you track from anywhere in the world as it's going across the ocean. Um, so they're, it's really little and they've been able to stay a small startup that's focused on their product, which is the, uh, that super crazy complicated, cool radio while we handle the whole space segment for them, which just, you know, before loft was really impossible. So that's, our mission is, uh, providing space infrastructure as a service. We are kind of groundbreaking in this area and we're serving, you know, a huge variety of customers with all kinds of different missions, um, and obviously generating a ton of data in space, uh, that we've gotta handle. Yeah. >>So amazing Caleb, what you guys do, I, now I know you were lured to the skies very early in your career, but how did you kinda land on this business? >>Yeah, so, you know, I've, I guess just a little bit about me for some people, you know, they don't necessarily know what they wanna do like early in their life. For me, I was five years old and I knew, you know, I want to be in the space industry. So, you know, I started in the air force, but have, uh, stayed in the space industry, my whole career and been a part of, uh, this is the fifth space startup that I've been a part of actually. So, you know, I've, I've, uh, kind of started out in satellites, did spent some time in working in, uh, the launch industry on rockets. Then, uh, now I'm here back in satellites and you know, honestly, this is the most exciting of the difference based startups. That I've been a part of >>Super interesting. Okay. Angelo, let's, let's talk about the Ruben observatory, ver C Ruben, famous woman scientist, you know, galaxy guru. Now you guys the observatory, you're up way up high. You're gonna get a good look at the Southern sky. Now I know COVID slowed you guys down a bit, but no doubt. You continued to code away on the software. I know you're getting close. You gotta be super excited. Give us the update on, on the observatory and your role. >>All right. So yeah, Rubin is a state of the art observatory that, uh, is in construction on a remote mountain in Chile. And, um, with Rubin, we conduct the, uh, large survey of space and time we are going to observe the sky with, uh, eight meter optical telescope and take, uh, a thousand pictures every night with a 3.2 gig up peaks of camera. And we are going to do that for 10 years, which is the duration of the survey. >>Yeah. Amazing project. Now you, you were a doctor of philosophy, so you probably spent some time thinking about what's out there and then you went out to earn a PhD in astronomy, in astrophysics. So this is something that you've been working on for the better part of your career, isn't it? >>Yeah, that's that's right. Uh, about 15 years, um, I studied physics in college, then I, um, got a PhD in astronomy and, uh, I worked for about five years in another project. Um, the dark energy survey before joining rubing in 2015. >>Yeah. Impressive. So it seems like you both, you know, your organizations are looking at space from two different angles. One thing you guys both have in common of course is, is, is software. And you both use InfluxDB as part of your, your data infrastructure. How did you discover influx DB get into it? How do you use the platform? Maybe Caleb, you could start. >>Uh, yeah, absolutely. So the first company that I extensively used, uh, influx DBN was a launch startup called, uh, Astra. And we were in the process of, uh, designing our, you know, our first generation rocket there and testing the engines, pumps, everything that goes into a rocket. Uh, and when I joined the company, our data story was not, uh, very mature. We were collecting a bunch of data in LabVIEW and engineers were taking that over to MATLAB to process it. Um, and at first there, you know, that's the way that a lot of engineers and scientists are used to working. Um, and at first that was, uh, like people weren't entirely sure that that was a, um, that that needed to change, but it's something the nice thing about InfluxDB is that, you know, it's so easy to deploy. So as the, our software engineering team was able to get it deployed and, you know, up and running very quickly and then quickly also backport all of the data that we collected thus far into influx and what, uh, was amazing to see. >>And as kind of the, the super cool moment with influx is, um, when we hooked that up to Grafana Grafana as the visualization platform we used with influx, cuz it works really well with it. Uh, there was like this aha moment of our engineers who are used to this post process kind of method for dealing with their data where they could just almost instantly easily discover data that they hadn't been able to see before and take the manual processes that they would run after a test and just throw those all in influx and have live data as tests were coming. And, you know, I saw them implementing like crazy rocket equation type stuff in influx, and it just was totally game changing for how we tested. >>So Angelo, I was explaining in my open, you know, you could, you could add a column in a traditional RDBMS and do time series, but with the volume of data that you're talking about, and the example of the Caleb just gave you, I mean, you have to have a purpose built time series database, where did you first learn about influx DB? >>Yeah, correct. So I work with the data management team, uh, and my first project was the record metrics that measured the performance of our software, uh, the software that we used to process the data. So I started implementing that in a relational database. Um, but then I realized that in fact, I was dealing with time series data and I should really use a solution built for that. And then I started looking at time series databases and I found influx B. And that was, uh, back in 2018. The another use for influx DB that I'm also interested is the visits database. Um, if you think about the observations we are moving the telescope all the time in pointing to specific directions, uh, in the Skype and taking pictures every 30 seconds. So that itself is a time series. And every point in that time series, uh, we call a visit. So we want to record the metadata about those visits and flex to, uh, that time here is going to be 10 years long, um, with about, uh, 1000 points every night. It's actually not too much data compared to other, other problems. It's, uh, really just a different, uh, time scale. >>The telescope at the Ruben observatory is like pun intended, I guess the star of the show. And I, I believe I read that it's gonna be the first of the next gen telescopes to come online. It's got this massive field of view, like three orders of magnitude times the Hub's widest camera view, which is amazing, right? That's like 40 moons in, in an image amazingly fast as well. What else can you tell us about the telescope? >>Um, this telescope, it has to move really fast and it also has to carry, uh, the primary mirror, which is an eight meter piece of glass. It's very heavy and it has to carry a camera, which has about the size of a small car. And this whole structure weighs about 300 tons for that to work. Uh, the telescope needs to be, uh, very compact and stiff. Uh, and one thing that's amazing about it's design is that the telescope, um, is 300 tons structure. It sits on a tiny film of oil, which has the diameter of, uh, human hair. And that makes an almost zero friction interface. In fact, a few people can move these enormous structure with only their hands. Uh, as you said, uh, another aspect that makes this telescope unique is the optical design. It's a wide field telescope. So each image has, uh, in diameter the size of about seven full moons. And, uh, with that, we can map the entire sky in only, uh, three days. And of course doing operations everything's, uh, controlled by software and it is automatic. Um there's a very complex piece of software, uh, called the scheduler, which is responsible for moving the telescope, um, and the camera, which is, uh, recording 15 terabytes of data every night. >>Hmm. And, and, and Angela, all this data lands in influx DB. Correct. And what are you doing with, with all that data? >>Yeah, actually not. Um, so we are using flex DB to record engineering data and metadata about the observations like telemetry events and commands from the telescope. That's a much smaller data set compared to the images, but it is still challenging because, uh, you, you have some high frequency data, uh, that the system needs to keep up and we need to, to start this data and have it around for the lifetime of the price. Mm, >>Got it. Thank you. Okay, Caleb, let's bring you back in and can tell us more about the, you got these dishwasher size satellites. You're kind of using a multi-tenant model. I think it's genius, but, but tell us about the satellites themselves. >>Yeah, absolutely. So, uh, we have in space, some satellites already that as you said, are like dishwasher, mini fridge kind of size. Um, and we're working on a bunch more that are, you know, a variety of sizes from shoebox to, I guess, a few times larger than what we have today. Uh, and it is, we do shoot to have effectively something like a multi-tenant model where, uh, we will buy a bus off the shelf. The bus is, uh, what you can kind of think of as the core piece of the satellite, almost like a motherboard or something where it's providing the power. It has the solar panels, it has some radios attached to it. Uh, it handles the attitude control, basically steers the spacecraft in orbit. And then we build also in house, what we call our payload hub, which is, has all, any customer payloads attached and our own kind of edge processing sort of capabilities built into it. >>And, uh, so we integrate that. We launch it, uh, and those things, because they're in lower orbit, they're orbiting the earth every 90 minutes. That's, you know, seven kilometers per second, which is several times faster than a speeding bullet. So we've got, we have, uh, one of the unique challenges of operating spacecraft and lower orbit is that generally you can't talk to them all the time. So we're managing these things through very brief windows of time, uh, where we get to talk to them through our ground sites, either in Antarctica or, you know, in the north pole region. >>Talk more about how you use influx DB to make sense of this data through all this tech that you're launching into space. >>We basically previously we started off when I joined the company, storing all of that as Angelo did in a regular relational database. And we found that it was, uh, so slow in the size of our data would balloon over the course of a couple days to the point where we weren't able to even store all of the data that we were getting. Uh, so we migrated to influx DB to store our time series telemetry from the spacecraft. So, you know, that's things like, uh, power level voltage, um, currents counts, whatever, whatever metadata we need to monitor about the spacecraft. We now store that in, uh, in influx DB. Uh, and that has, you know, now we can actually easily store the entire volume of data for the mission life so far without having to worry about, you know, the size bloating to an unmanageable amount. >>And we can also seamlessly query, uh, large chunks of data. Like if I need to see, you know, for example, as an operator, I might wanna see how my, uh, battery state of charge is evolving over the course of the year. I can have a plot and an influx that loads that in a fraction of a second for a year's worth of data, because it does, you know, intelligent, um, I can intelligently group the data by, uh, sliding time interval. Uh, so, you know, it's been extremely powerful for us to access the data and, you know, as time has gone on, we've gradually migrated more and more of our operating data into influx. >>You know, let's, let's talk a little bit, uh, uh, but we throw this term around a lot of, you know, data driven, a lot of companies say, oh, yes, we're data driven, but you guys really are. I mean, you' got data at the core, Caleb, what does that, what does that mean to you? >>Yeah, so, you know, I think the, and the clearest example of when I saw this be like totally game changing is what I mentioned before at Astro where our engineer's feedback loop went from, you know, a lot of kind of slow researching, digging into the data to like an instant instantaneous, almost seeing the data, making decisions based on it immediately, rather than having to wait for some processing. And that's something that I've also seen echoed in my current role. Um, but to give another practical example, uh, as I said, we have a huge amount of data that comes down every orbit, and we need to be able to ingest all of that data almost instantaneously and provide it to the operator. And near real time, you know, about a second worth of latency is all that's acceptable for us to react to, to see what is coming down from the spacecraft and building that pipeline is challenging from a software engineering standpoint. >>Um, our primary language is Python, which isn't necessarily that fast. So what we've done is started, you know, in the, in the goal of being data driven is publish metrics on individual, uh, how individual pieces of our data processing pipeline are performing into influx as well. And we do that in production as well as in dev. Uh, so we have kind of a production monitoring, uh, flow. And what that has done is allow us to make intelligent decisions on our software development roadmap, where it makes the most sense for us to, uh, focus our development efforts in terms of improving our software efficiency. Uh, just because we have that visibility into where the real problems are. Um, it's sometimes we've found ourselves before we started doing this kind of chasing rabbits that weren't necessarily the real root cause of issues that we were seeing. Uh, but now, now that we're being a bit more data driven, there we are being much more effective in where we're spending our resources and our time, which is especially critical to us as we scale to, from supporting a couple satellites, to supporting many, many satellites at >>Once. Yeah. Coach. So you reduced those dead ends, maybe Angela, you could talk about what, what sort of data driven means to, to you and your teams? >>I would say that, um, having, uh, real time visibility, uh, to the telemetry data and, and metrics is, is, is crucial for us. We, we need, we need to make sure that the image that we collect with the telescope, uh, have good quality and, um, that they are within the specifications, uh, to meet our science goals. And so if they are not, uh, we want to know that as soon as possible and then, uh, start fixing problems. >>Caleb, what are your sort of event, you know, intervals like? >>So I would say that, you know, as of today on the spacecraft, the event, the, the level of timing that we deal with probably tops out at about, uh, 20 Hertz, 20 measurements per second on, uh, things like our, uh, gyroscopes, but the, you know, I think the, the core point here of the ability to have high precision data is extremely important for these kinds of scientific applications. And I'll give an example, uh, from when I worked at, on the rocket at Astra there, our baseline data rate that we would ingest data during a test is, uh, 500 Hertz. So 500 samples per second. And in some cases we would actually, uh, need to ingest much higher rate data, even up to like 1.5 kilohertz. So, uh, extremely, extremely high precision, uh, data there where timing really matters a lot. And, uh, you know, I can, one of the really powerful things about influx is the fact that it can handle this. >>That's one of the reasons we chose it, uh, because there's times when we're looking at the results of a firing where you're zooming in, you know, I talked earlier about how on my current job, we often zoom out to look, look at a year's worth of data. You're zooming in to where your screen is preoccupied by a tiny fraction of a second. And you need to see same thing as Angela just said, not just the actual telemetry, which is coming in at a high rate, but the events that are coming out of our controllers. So that can be something like, Hey, I opened this valve at exactly this time and that goes, we wanna have that at, you know, micro or even nanosecond precision so that we know, okay, we saw a spike in chamber pressure at, you know, at this exact moment, was that before or after this valve open, those kind of, uh, that kind of visibility is critical in these kind of scientific, uh, applications and absolutely game changing to be able to see that in, uh, near real time and, uh, with a really easy way for engineers to be able to visualize this data themselves without having to wait for, uh, software engineers to go build it for them. >>Can the scientists do self-serve or are you, do you have to design and build all the analytics and, and queries for your >>Scientists? Well, I think that's, that's absolutely from, from my perspective, that's absolutely one of the best things about influx and what I've seen be game changing is that, uh, generally I'd say anyone can learn to use influx. Um, and honestly, most of our users might not even know they're using influx, um, because what this, the interface that we expose to them is Grafana, which is, um, a generic graphing, uh, open source graphing library that is very similar to influx own chronograph. Sure. And what it does is, uh, let it provides this, uh, almost it's a very intuitive UI for building your queries. So you choose a measurement and it shows a dropdown of available measurements. And then you choose a particular, the particular field you wanna look at. And again, that's a dropdown, so it's really easy for our users to discover. And there's kind of point and click options for doing math aggregations. You can even do like perfect kind of predictions all within Grafana, the Grafana user interface, which is really just a wrapper around the APIs and functionality of the influx provides putting >>Data in the hands of those, you know, who have the context of domain experts is, is key. Angela, is it the same situation for you? Is it self serve? >>Yeah, correct. Uh, as I mentioned before, um, we have the astronomers making their own dashboards because they know what exactly what they, they need to, to visualize. Yeah. I mean, it's all about using the right tool for the job. I think, uh, for us, when I joined the company, we weren't using influx DB and we, we were dealing with serious issues of the database growing to an incredible size extremely quickly, and being unable to like even querying short periods of data was taking on the order of seconds, which is just not possible for operations >>Guys. This has been really formative it's, it's pretty exciting to see how the edge is mountaintops, lower orbits to be space is the ultimate edge. Isn't it. I wonder if you could answer two questions to, to wrap here, you know, what comes next for you guys? Uh, and is there something that you're really excited about that, that you're working on Caleb, maybe you could go first and an Angela, you can bring us home. >>Uh, basically what's next for loft. Orbital is more, more satellites, a greater push towards infrastructure and really making, you know, our mission is to make space simple for our customers and for everyone. And we're scaling the company like crazy now, uh, making that happen, it's extremely exciting and extremely exciting time to be in this company and to be in this industry as a whole, because there are so many interesting applications out there. So many cool ways of leveraging space that, uh, people are taking advantage of. And with, uh, companies like SpaceX and the now rapidly lowering cost, cost of launch, it's just a really exciting place to be. And we're launching more satellites. We are scaling up for some constellations and our ground system has to be improved to match. So there's a lot of, uh, improvements that we're working on to really scale up our control software, to be best in class and, uh, make it capable of handling such a large workload. So >>You guys hiring >><laugh>, we are absolutely hiring. So, uh, I would in we're we need, we have PE positions all over the company. So, uh, we need software engineers. We need people who do more aerospace, specific stuff. So, uh, absolutely. I'd encourage anyone to check out the loft orbital website, if there's, if this is at all interesting. >>All right. Angela, bring us home. >>Yeah. So what's next for us is really, uh, getting this, um, telescope working and collecting data. And when that's happen is going to be just, um, the Lu of data coming out of this camera and handling all, uh, that data is going to be really challenging. Uh, yeah. I wanna wanna be here for that. <laugh> I'm looking forward, uh, like for next year we have like an important milestone, which is our, um, commissioning camera, which is a simplified version of the, of the full camera it's going to be on sky. And so yeah, most of the system has to be working by them. >>Nice. All right, guys, you know, with that, we're gonna end it. Thank you so much, really fascinating, and thanks to influx DB for making this possible, really groundbreaking stuff, enabling value creation at the edge, you know, in the cloud and of course, beyond at the space. So really transformational work that you guys are doing. So congratulations and really appreciate the broader community. I can't wait to see what comes next from having this entire ecosystem. Now, in a moment, I'll be back to wrap up. This is Dave ante, and you're watching the cube, the leader in high tech enterprise coverage. >>Welcome Telegraph is a popular open source data collection. Agent Telegraph collects data from hundreds of systems like IOT sensors, cloud deployments, and enterprise applications. It's used by everyone from individual developers and hobbyists to large corporate teams. The Telegraph project has a very welcoming and active open source community. Learn how to get involved by visiting the Telegraph GitHub page, whether you want to contribute code, improve documentation, participate in testing, or just show what you're doing with Telegraph. We'd love to hear what you're building. >>Thanks for watching. Moving the world with influx DB made possible by influx data. I hope you learn some things and are inspired to look deeper into where time series databases might fit into your environment. If you're dealing with large and or fast data volumes, and you wanna scale cost effectively with the highest performance and you're analyzing metrics and data over time times, series databases just might be a great fit for you. Try InfluxDB out. You can start with a free cloud account by clicking on the link and the resources below. Remember all these recordings are gonna be available on demand of the cube.net and influx data.com. So check those out and poke around influx data. They are the folks behind InfluxDB and one of the leaders in the space, we hope you enjoyed the program. This is Dave Valante for the cube. We'll see you soon.

>>Okay. Today we welcome Evan Kaplan, CEO of Influx Data, the company behind Influx DB Welcome, Evan. Thanks for coming on. >>Hey, John. Thanks for having me. >>Great segment here on the influx. DB Story. What is the story? Take us through the history. Why Time series? What's the story? >>So the history of history is actually actually pretty interesting. Paul Dicks, my partner in this and our founder, um, super passionate about developers and developer experience. And, um, he had worked on Wall Street building a number of times series kind of platform trading platforms for trading stocks. And from his point of view, it was always what he would call a yak shave, which means you have to do a tonne of work just to start doing work. Which means you have to write a bunch of extrinsic routines. You had to write a bunch of application handling on existing relational databases in order to come up with something that was optimised for a trading platform or a time series platform. And he sort of he just developed This real clear point of view is this is not how developers should work. And so in 2013, he went through y Combinator and he built something for he made his first commit to open source influx TB at the end of 2013. And basically, you know, from my point of view, you invented modern time series, which is you start with a purpose built time series platform to do these kind of work clothes, and you get all the benefits of having something right out of the box or developer can be totally productive right away. >>And how many people in the company What's the history of employees and stuff? Yeah, >>I think we're you know, I always forget the number, but it's something like 230 or 240 people now. Um, the company I joined the company in 2016 and I love Paul's vision, and I just had a strong conviction about the relationship between Time series and Iot. Because if you think about it, what sensors do is they speak time, series, pressure, temperature, volume, humidity, light. They're measuring their instrumented something over time. And so I thought that would be super relevant over long term, and I've not regretted. Oh, >>no, and it's interesting at that time to go back in history. You know the role of databases are relational database, the one database to rule the world. And then, as clouds started coming in, you're starting to see more databases, proliferate types of databases. And Time series in particular, is interesting because real time has become super valuable. From an application standpoint, Iot, which speaks Time series, means something. It's like time matters >>times, >>and sometimes date is not worth it after the time. Sometimes it's worth it. And then you get the Data lake, so you have this whole new evolution. Is this the momentum? What's the momentum? I guess the question is, what's the momentum behind >>what's causing us to grow? So >>the time series. Why is time series in the category momentum? What's the bottom line? We'll >>think about it. You think about it from abroad, abroad, sort of frame, which is where what everybody's trying to do is build increasingly intelligent systems, whether it's a self driving car or a robotic system that does what you want to do or self healing software system. Everybody wants to build increasing intelligence systems, and so, in order to build these increasingly intelligence systems. You have to instrument the system well, and you have to instrument it over time, better and better. And so you need a tool, a fundamental tool to drive that instrumentation. And that's become clear to everybody that that instrumentation is all based on time. And so what happened? What happened? What happened? What's going to happen? And so you get to these applications, like predictive maintenance or smarter systems. And increasingly, you want to do that stuff not just intelligently, but fast in real time, so millisecond response, so that when you're driving a self driving car and the system realises that you're about to do something, essentially, you want to be able to act in something that looks like real time. All systems want to do that. I want to be more intelligent, and they want to be more real time. So we just happened to, you know, we happen to show up at the right time. In the evolution of the market. >>It's interesting. Near real time isn't good enough when you need real time. Yeah, >>it's not, it's not, and it's like it's like everybody wants even when you don't need it. Uh, ironically, you want it. It's like having the feature for, you know, you buy a new television, you want that one feature even though you're not going to use it, you decide that you're buying criteria. Real time is a buying criteria. >>So what you're saying, then is near real time is getting closer to real time as possible as possible. Okay, so talk about the aspect of data cause we're hearing a lot of conversations on the Cubans particular around how people are implementing and actually getting better. So iterating on data. >>But >>you have to know when it happened to get know how to fix it. So this is a big part of what we're seeing with people saying, Hey, you know, I want to make my machine learning albums better after the fact I want to learn from the data. Um, how does that How do you see that evolving? Is that one of the use cases of sensors as people bring data in off the network, getting better with the data knowing when it happened? >>Well, for sure, So for sure, what you're saying is is none of this is non linear. It's all incremental. And so if you take something, you know, just as an easy example. If you take a self driving car, what you're doing is your instrument in that car to understand where it can perform in the real world in real time. And if you do that, if you run the loop, which is I instrumented, I watch what happens. Oh, that's wrong. Oh, I have to correct for that. Correct for that in the software, if you do that four billion times, you get a self driving car. But every system moves along that evolution. And so you get the dynamic of you know of constantly instrumented, watching the system behave and do it and this and sets up driving cars. One thing. But even in the human genome, if you look at some of our customers, you know people like, you know, people doing solar arrays. People doing power walls like all of these systems, are getting smarter. >>What are the top application? What are you seeing your with Influx DB The Time series. What's the sweet spot for the application use case and some customers give some examples. >>Yeah, so it's pretty easy to understand. On one side of the equation. That's the physical side is sensors are the sensors are getting cheap. Obviously, we know that, and they're getting. The whole physical world is getting instrumented your home, your car, the factory floor, your wrist watch your healthcare, you name it. It's getting instrumented in the physical world. We're watching the physical world in real time, and so there are three or four sweet spots for us. But they're all on that side. They're all about Iot. So they're talking about consumer Iot projects like Google's Nest Tato Um, particle sensors, Um, even delivery engines like Happy who deliver the interesting part of South America. Like anywhere. There's a physical location doing that's on the consumer side. And then another exciting space is the industrial side. Factories are changing dramatically over time, increasingly moving away from proprietary equipment to develop or driven systems that run operational because what it has to get smarter when you're building, when you're building a factory, systems all have to get smarter. And then lastly, a lot in the renewables sustainability. So a lot, you know, Tesla, lucid motors, Nicola Motors, um you know, lots to do with electric cars, solar arrays, windmills are raised just anything that's going to get instrumented, that where that instrumentation becomes part of what the purpose is. >>It's interesting. The convergence of physical and digital is happening with the data Iot you mentioned. You know, you think of Iot. Look at the use cases there. It was proprietary OT systems now becoming more I p enabled Internet protocol and now edge compute getting smaller, faster, cheaper ai going to the edge. Now you have all kinds of new capabilities that bring that real time and time series opportunity. Are you seeing Iot going to a new level? What was that? What's the Iot? Where's the Iot dots connecting to? Because, you know, as these two cultures merge operations basically industrial factory car, they gotta get smarter. Intelligent edge is a buzzword, but it has to be more intelligent. Where's the where's the action in all this? So the >>action really, really at the core? >>It's >>at the developer, right, Because you're looking at these things. It's very hard to get off the shelf system to do the kinds of physical and software interaction. So the actions really happen at the developers. And so what you're seeing is a movement in the world that that maybe you and I grew up in with I t r o T moving increasingly that developer driven capability. And so all of these Iot systems, their bespoke, they don't come out of the box. And so the developer and the architect, the CTO they define what's my business? What am I trying to do trying to sequence the human genome and figure out when these genes express themselves? Or am I trying to figure out when the next heart rate monitor is going to show up in my apple watch, right? What am I trying to do? What's the system I need to build? And so starting with the developers where all of the good stuff happens here, which is different than it used to be, right, used to be used by an application or a service or a sad thing for But with this dynamic with this integration of systems, it's all about bespoke. It's all about building something. >>So let's get to the death of a real quick, real highlight point. Here is the data. I mean, I could see a developer saying, Okay, I need to have an application for the edge Iot, edge or car. I mean, we're gonna test look at applications of the cars right there. I mean, there's the modern application lifecycle now, so take us through how this impacts the developer doesn't impact their CI CD. Pipeline is a cloud native. I mean, where does this all Where does this go to? >>Well, so first of all you talking about, there was an internal journey that we had to go through as a company, which which I think is fascinating for anybody's interested as we went from primarily a monolithic software that was open source to building a cloud native platform, which means we have to move from an agile development environment to a C I C d. Environ. So two degree that you're moving your service whether it's, you know, Tesla, monitoring your car and updating your power walls right? Or whether it's a solar company updating your race right to the degree that services cloud then increasingly removed from an agile development to a CI CD environment which is shipping code to production every day. And so it's not just the developers, all the infrastructure to support the developers to run that service and that sort of stuff. I think that's also going to happen in a big way >>when your customer base that you have now and you see evolving with influx DB is it that they're gonna be writing more of the application or relying more on others? I mean, obviously the open source component here. So when you bring in kind of old way new Way Old Way was, I got a proprietary platform running all this Iot stuff and I got to write, Here's an application. That's general purpose. I have some flexibility, somewhat brittle. Maybe not a lot of robustness to it, but it does its job >>a good way to think about this. >>This is what >>So, yeah, a good way to think about this is what What's the role of the developer slashed architect C T o that chain within a large enterprise or a company. And so, um, the way to think about is I started my career in the aerospace industry, and so when you look at what Boeing does to assemble a plane, they build very, very few of the parts instead. What they do is they assemble, they buy the wings, they buy the engines they assemble. Actually, they don't buy the wings. It's the one thing they buy, the material of the way they build the wings because there's a lot of tech in the wings and they end up being assemblers, smart assemblers of what ends up being a flying aeroplane, which is pretty big deal even now. And so what happens with software people is they have the ability to pull from, you know, the best of the open source world, so they would pull a time series capability from us. Then they would assemble that with potentially some E t l logic from somebody else, or they assemble it with, um, a Kafka interface to be able to stream the data in. And so they become very good integrators and assemblers. But they become masters of that bespoke application, and I think that's where it goes because you're not writing native code for everything, >>so they're more flexible. They have faster time to market because they're assembling way faster and they get to still maintain their core competency. OK, the wings. In this case, >>they become increasingly not just coders, but designers and developers. They become broadly builders is what we like to think of it. People who started build stuff. By the way. This is not different than the people have just up the road Google have been doing for years or the tier one Amazon building all their own. >>Well, I think one of the things that's interesting is that this idea of a systems developing a system architecture, I mean systems, uh, systems have consequences when you make changes. So when you have now cloud data centre on premise and edge working together, how does that work across the system? You can't have a wing that doesn't work with the other wing. That's exactly >>that's where that's where the, you know that that Boeing or that aeroplane building analogy comes in for us. We've really been thoughtful about that because I o. T. It's critical. So are open Source Edge has the same API as our cloud native stuff that hasn't enterprise on premises or multiple products have the same API, and they have a relationship with each other. They can talk with each other, so the builder builds at once. And so this is where when you start thinking about the components that people have to use to build these services is that you want to make sure at least that base layer that database layer that those components talk to each other. >>We'll have to ask you. I'm the customer. I put my customer hat on. Okay. Hey, I'm dealing with a lot. >>I mean, you have appeal for >>a big check blank check. If you can answer this question only if you get the question right. I got all this important operation stuff. I got my factory. I got my self driving cars. This isn't like trivial stuff. This is my business. How should I be thinking about Time Series? Because now I have to make these architectural decisions as you mentioned and it's going to impact my application development. So huge decision point for your customers. What should I care about the most? What's in it for me? Why is time series important? Yeah, >>that's a great question. So chances are if you've got a business that was 20 years old or 25 years old, you're already thinking about Time series. You probably didn't call it that you built something on a work call or you build something that IBM db two. Right, and you made it work within your system, right? And so that's what you started building. So it's already out there. There are, you know, they're probably hundreds of millions of Time series applications out there today. But as you start to think about this increasing need for real time and you start to think about increasing intelligence, you think about optimising those systems over time. I hate the word but digital transformation, and you start with Time series. It's a foundational base layer for any system that you're going to build. There's no system I can think of where time series shouldn't be the foundational base layer. If you just want to store your data and just leave it there and then maybe look it up every five years, that's fine. That's not time. Serious time series when you're building a smarter, more intelligent, more real time system, and the developers now know that, and so the more they play a role in building these systems, the more obvious it becomes. >>And since I have a P o for you in a big check, what what's the value to me as like when I implement this What's the end state? What's it look like when it's up and running? What's the value proposition for me? What's in it? >>So when it's up and running, you're able to handle the queries, the writing of the data, the down sampling of the data transforming it in near real time. So the other dependencies that a system that gets for adjusting a solar array or trading energy off of a power wall or some sort of human genome those systems work better. So time series is foundational. It's not like it's, you know, it's not like it's doing every action that's above, but it's foundational to build a really compelling intelligence system. I think that's what developers and architects are seeing now. >>Bottom line. Final word. What's in it for the customer? What's what's your What's your statement of the customer? Would you say to someone looking to do something in time, series and edge? >>Yeah. So it's pretty clear to clear to us that if you're building, if you view yourself as being in the building business of building systems that you want them to be increasingly intelligent, self healing, autonomous, you want them to operate in real time that you start from Time series. I also want to say What's in it for us in flux? What's in it for us is people are doing some amazing stuff. I highlighted some of the energy stuff, some of the human genome, some of the health care. It's hard not to be proud or feel like. Wow. Somehow I've been lucky. I've arrived at the right time in the right place, with the right people to be able to deliver on that. That's That's also exciting on our side of the equation. >>It's critical infrastructure, critical critical operations. >>Yeah, great >>stuff. Evan. Thanks for coming on. Appreciate this segment. All right. In a moment. Brian Gilmore, director of Iot and emerging Technology that influx, they will join me. You're watching the Cube leader in tech coverage. Thanks for watching

(upbeat music) >> Okay, welcome back everyone, Cube coverage live on the floor in the Moscone center in San Francisco, California. I'm John Furrier host of the Cube. AWS summit 2022 is here in San Francisco, we're back in live events. Of course, Amazon summit in New York city is coming, Amazon summit this summer we'll be there as well. We've got a great guest Mike Miller, GN of AI devices at AWS always one of my favorite interviews. We've got a little prop here, we got the car, DeepRacer, very popular at the events. Mike, welcome to the Cube. Good to see you. >> Hey John, thank you for having me. It's really exciting to be back and chat with you a little bit about DeepRacer. >> Well I want to get into the prop in a second, not the prop, the product. >> Yeah. >> So DeepRacer program, you got the race track here. Just explain what it is real quick, we'll get that out of the way. >> Absolutely so, well, you know that AI, AWS is passionate about making AI and ML more accessible to developers of all skill levels. So DeepRacer is one of our tools to do that. So DeepRacer is a 3D cloud-based racing simulator, a 1/18th scale autonomously driven car and a league to add a little spicy competition into it. So developers can start with the cloud-based simulator where they're introduced to reinforcement learning which basically teaches the, our car to drive around a track through trial and error and of course you're in a virtual simulator so it's easy for it to make mistakes and restart. Then once that model is trained, it's downloaded to the car which then can drive around a track autonomously, kind of making its own way and of course we track lap time and your successful lap completions and all of that data feeds into our league to try to top the leaderboard and win prizes. >> This is the ultimate gamification tool. (chuckles) >> Absolutely >> Making it fun to learn about machine learning. All right, let's get into the car, let's get into the showcase of the car. show everyone what's going on. >> Absolutely. So this is our 1/18th scale autonomously driven car. It's built off of a monster truck chassis so you can see it's got four wheel drive, it's got steering in the front, we've got a camera on the front. So the camera is the, does the sensing to the compute board that's driven by an Intel atom a processor on the, on the vehicle, that allows it to make sense of the in front of it and then decide where it wants to drive. So you take the car, you download your trained model to it and then it races around the track. >> So the front is the camera. >> The front is the camera, that's correct. >> Okay, So... >> So it's a little bit awkward but we needed to give it plenty of room here so that I can actually see the track in front of it. >> John: It needs eyes. >> Yep. That's exactly right. >> Awesome. >> Yes. >> And so I got to buy that if I'm a developer. >> So, developers can start in two ways, they can use our virtual racing experience and so there's no hardware cost for that, but once you want the experience, the hands on racing, then the car is needed but if you come to one of our AWS summits, like here in San Francisco or anywhere else around the world we have one or more tracks set up and you can get hands on, you can bring the model that you trained at home download it to a car and see it race around the track. >> So use a car here. You guys are not renting cars, but you're letting people use the cars. >> Absolutely. >> Can I build my own car or does it have to be assembled by AWS? >> Yeah, we, we sell it as a, as a kit that's already assembled because we've got the specific compute board in there, that Intel processor and all of the software that's already built on there that knows how to drive around the track. >> That's awesome, so talk about the results. What's going on? What's the feedback from developers? Obviously it's a nerd dream, people like race cars, people love formula one now, all the racing there. IOT is always an IOT opportunity as well. >> Absolutely, and as you said, gamification, right? And so what we found and what we thought we would find was that adding in those sort of ease of learning so we make it the on-ramp to machine learning very easy. So developers of all skill levels can take advantage of this, but we also make it fun by kind of gamifying it. We have different challenges every month, we have a leader board so you can see how you rank against your peers and actually we have split our league into two, there's an open division which is more designed for novices so you'll get rewarded for just participating and then we have a pro league. So if you're one of the top performers in the open league each month, you graduate and you get to race against the big boys in the pro leagues. >> What's the purse? >> Oh, the, (John laughing) we definitely have cash and prizes that happen, both every month. We have prizes cause we do races every month and those winners of those races all get qualified to race at the championship, which of course happens in Las Vegas at re:Invent. So we bring all the winners to re:Invent and they all race against each other for the grand prize the big trophy and the, and the, and the cash prize. >> Well, you know, I'm a big fan of what you guys are doing so I'm kind of obviously biased on this whole program but you got to look at trend of what's going on in eSports and the online engagement is off the charts, are there plans to kind of make this more official and bigger? Is there traction there or is this just all part of the Amazon goodness, love that you guys give back? I mean, obviously it's got traction. >> Yeah. I mean, the thing that's interesting about eSports is the number of young people who are getting into it and what we saw over the last couple years is that, there were a lot of students who were adopting DeepRacer but there were some hurdles, you know, it wasn't really designed for them. So what we did was we made some changes and at the beginning of this year we launched a student focused DeepRacer program. So they get both free training every month, they get free educational materials and their own private league so they know students can race against other students, as part of that league. >> John: Yeah. >> So that was really our first step in kind of thinking about those users and what do we need to do to cater to their kind of unique needs? >> Tell about some of the power dynamics or the, or not power dynamics, the group dynamics around teams and individuals, can I play as an individual? Do I, do I have to be on a team? Can I do teams? How does that look? How do you think about those things? >> Yeah, absolutely. Great, great question. The primary way to compete is individually. Now we do have an offering that allows companies to use DeepRacer to excite and engage their own employees and this is where operating as a team and collaborating with your coworkers comes into play so, if, if I may there's, you know, Accenture and JPMC are a couple big customers of ours, really strong partners. >> John: Yeah. >> Who've been able to take advantage of DeepRacer to educate their workforce. So Accenture ran a 24 hour round the, round the globe race a couple years ago, encouraging their employees to collaborate and form teams to race and then this past year JPMC, had over 3000 of their builders participate over a three month period where they ran a private league and they went on to win the top two spots, first place and second place. >> John: Yeah. >> At reinvent last year. >> It reminds me the NASCAR and all these like competitions, the owners have multiple cars on the race. Do you guys at re:Invent have to start cutting people like, only two submissions or is it free for all? >> Well, you have to qualify to get to the races at re:invent so it's very, it's very cutthroat leading up to that point. We've got winners of our monthly virtual contests, the winners like of the summit races will also get invited. So it's interesting, this dynamic, you'll have some people who won virtual races, some people who won physical races, all competing together. >> And do you guys have a name for the final cup or is it like what's the, what's the final, how do you guys talk about the prizes and the... >> It's, it's the DeepRacer Championship Cup of course. >> John: Of course. (laughter) >> Big silver cup, you get to hoist it and... >> Are the names inscribed in it, is it like the Stanley cup or is it just one. >> It's a unique one, so you get to hold onto it each year. The champion gets their own version of the cup. >> It's a lot of fun. I think it's really kind of cool. What's the benefits for a student? Talk about the student ones. >> Yeah. Yeah. >> So I'm a student I'm learning machine learning, what's in it for me is a career path and the fund's obvious, I see that. >> Yeah absolutely. You know, the, for students, it's a hands on way that's a very easy on-ramp to machine learning and you know, one of the things, as I mentioned we're passionate about making it accessible to all. Well, when we mean all we were really do mean all. So, we've got a couple partners who are passionate about the same thing, right? Which is how do we, if, if AI and ML is going to transform our world and solve our most challenging problems, how can we get the right minds from all walks of life and all backgrounds to learn machine learning and get engaged? So with two of our partners, so with Udacity and with Intel we launched a $10 million AWS, AI and ML scholarship program and we built it around DeepRacer. So not only can students who are college and high school students, age 16 and over can use DeepRacer, can learn about machine learning and then get qualified to win one of several thousand scholarships. >> Any other promotions going on that people should know about? >> Yeah, one, one final one is, so we talked about enterprises like JPMC and Accenture, so we've got a promotion that we just started yesterday. So if you are an enterprise and you want to host a DeepRacer event at your company to excite your employees and get 'em collaborating more, if you have over 50 employees participating, we're going to give you up to a hundred thousand dollars in AWS credits, to offset the costs of running your DeepRacer event at your, at your company so >> That's real money. >> Yeah. Real, real, real exciting I think for companies now to pick up DeepRacer. >> So, I mean, honestly, I know Andy Jassy, I have many sports car conversations with him. He's a sports guy, he's now the CEO of Amazon, gets to go all the sporting events, NFL. I wish I could bring the Cube there but, we'll stick with with cloud for now. You got to look at the purse kind of thing. I'm interested in like the whole economic point of cause I mean, forget the learning for side for a second which is by the way awesome. This is great competition. You got leader boards, you got regional activities, you got a funneling system laddering up to the final output. >> And we've really done a decent job and, and of adding capabilities into that user experience to make it more engaging. You can see the countries that the different competitors are from, you can see how the lap times change over time, you know, we give awards as I mentioned, the two divisions now. So if you're not super competitive, we'll reward you for just participating in that open league but if you want to get competitive, we'll even better rewards monthly in the Pro League. >> Do you guys have any conversations internally like, this is getting too big, we might have to outsource it or you keep it in inside the fold? (laughter) >> We, we love DeepRacer and it's so much fun running this, >> You see where I'm going with this. You see where I'm going with this right? The Cube might want to take this over. >> Hey. >> And you know >> We're always looking for partners and sponsors who can help us make it bigger so, absolutely. >> It's a good business opportunity. I just love it. Congratulations, great stuff. What's the big learning in this, you know, as a as an executive, you look back you got GM, AI super important and, and I think it is great community, communal activity as well. What's the learning, what have you learned from this over the years besides that it's working but like what's the big takeaway? >> Yeah, I mean. We've got such a wide range of developers and builders who are customers that we need to provide a variety of opportunities for people to get hands on and there's no better way to learn a complex technology like AI and ML than getting hands on and seeing, you know, physically the result of the AI and I think that's been the biggest learning, is that just having the hands on and the sort of element of watching what it does, just light bulbs go off. When, when developers look at this and they start piecing the, the puzzle pieces together, how they can benefit. >> So I have to ask the question that might be on other peoples minds, maybe it's not, maybe I'm just thinking really dark here but gamers love to hack and they love cheat codes, they love to get, you know, get into the system, any attempts to do a little hacking to win the, the the game, have you guys, is there, you know? >> Well, well, you know, last year we, we we released an open source version of the vehicle so that people could start using it as a platform to explore and do that kind of hacking and give them an opportunity build on top of it. >> So using mods, mods modules, we can mod out on this thing. >> Yeah, absolutely. If you go to deepracer.com, we have sort of extensions page there, and you can see, somebody mounted a Nerf cannon onto the top of this, somebody built a computer vision model that could recognize you know, rodents and this thing would kind of drive to scare 'em, all kinds of fun topics. >> So it's a feature, not a bug. >> Absolutely. >> Open it up. >> Yeah. >> And also on transparency, if you have the source code out there you guys can have some review. >> Yeah. The whole idea is like, let's see what developers, >> It's really not hackable. It's not hackable. >> Yeah, I mean, for the, if you think about it when we do the races, we bring the cars ourselves, the only way a developer interacts is by giving us their trained models so... >> And you, do you guys review the models? Nothing to review, right? >> Yeah. There's nothing really to review. It's all about, you know, there, there was a model that we saw one time where the car went backwards and then went forwards across the finish line but we, we, we gently told them, well that's really not a valid way to race. >> That was kind of a hack, not really a hack. That was a hack hack. (laughter) That was just a growth hack. >> Exactly, but everybody just has a lot of fun with it across the board. >> Mike, great, thanks for coming on. Love the prop. Thanks for bringing the car on, looks great. Success every year. I want to see the purse, you know, big up to $1,000,000 you know, the masters, you know, tournament. >> Someday. (John chuckles) >> You guys.. >> Thank you for having me John. >> DeepRacer again, Fun Start has a great way to train people on machine learning, IOT device, turns into a league of its own. Great stuff for people to learn, especially students and people in companies, but the competitive juices flowing. That's what it's all about, having fun, learning. It's the Cube here in San Francisco. Stay with us for more coverage after this short break. (gentle music)

(upbeat music) >> Okay today, we welcome Evan Kaplan, CEO of InfluxData, the company behind InfluxDB. Welcome Evan, thanks for coming on. >> Hey John, thanks for having me. >> Great segment here on the InfluxDB story. What is the story? Take us through the history, why time series? What's the story? >> So the history history is actually pretty interesting. Paul Dix my partner in this and our founder, super passionate about developers and developer experience. And he had worked on wall street building a number of time series kind of platform, trading platforms for trading stocks. And from his point of view, it was always what he would call a yak shave. Which means you had to do a ton of work just to start doing work. Which means you had to write a bunch of extrinsic routines, you had to write a bunch of application handling on existing relational databases, in order to come up with something that was optimized for a trading platform or a time series platform. And he sort of, he just developed this real clear point of view. This is not how developers should work. And so in 2013, he went through Y Combinator, and he built something for, he made his first commit to open source InfluxDB in the end of 2013. And he basically, you know from my point of view, he invented modern time series, which is you start with a purpose built time series platform to do these kind of workloads, and you get all the benefits of having something right out of the box. So a developer can be totally productive right away. >> And how many people are in the company? What's the history of employees is there? >> Yeah, I think we're, you know, I always forget the number but something like 230 or 240 people now. I joined the company in 2016, and I love Paul's vision. And I just had a strong conviction about the relationship between time series and IOT. 'Cause if you think about it, what sensors do is they speak time series. Pressure, temperature, volume, humidity, light, they're measuring, they're instrumenting something over time. And so I thought that would be super relevant over the long term, and I've not regretted it. >> Oh no, and it's interesting at that time if you go back in history, you know, the role of database. It's all relational database, the one database to rule the world. And then as cloud started coming in, you started to see more databases proliferate, types of databases. And time series in particular is interesting 'cause real time has become super valuable from an application standpoint. IOT which speaks time series, means something. It's like time matters >> Times yeah. >> And sometimes data's not worth it after the time, sometimes it's worth it. And then you get the data lake, so you have this whole new evolution. Is this the momentum? What's the momentum? I guess the question is what's the momentum behind it? >> You mean what's causing us to grow so fast? >> Yeah the time series, why is time series- >> And the category- >> Momentum, what's the bottom line? >> Well think about it, you think about it from a broad sort of frame which is, what everybody's trying to do is build increasingly intelligent systems. whether it's a self-driving car or a robotic system that does what you want to do, or a self-healing software system. Everybody wants to build increasing intelligent systems. And so in order to build these increasing intelligent systems, you have to instrument the system well. And you have to instrument it over time, better and better. And so you need a tool, a fundamental tool to drive that instrumentation. And that's become clear to everybody that that instrumentation is all based on time. And so what happened, what happened, what happened, what's going to happen. And so you get to these applications like predictive maintenance, or smarter systems, and increasingly you want to do that stuff not just intelligently, but fast in real time. So millisecond response, so that when you're driving a self-driving car, and the system realizes that you're about to do something, essentially you want to be able to act in something that looks like real time. All systems want to do that, they want to be more intelligent, and they want to be more real time. And so we just happen to, you know, we happen to show up at the right time in the evolution of a market. >> It's interesting near real time isn't good enough when you need real time. >> Yeah, it's not, it's not. And it's like everybody wants real even when you don't need it, ironically you want it. It's like having the feature for, you know you buy a new television, you want that one feature, even though you're not going to use it. You decide that's your buying criteria. Real time is criteria for people. >> So I mean, what you're saying then is near realtime is getting closer to real time as fast as possible? >> Right. >> Okay, so talk about the aspect of data, 'cause we're hearing a lot of conversations on theCUBE in particular around how people are implementing and actually getting better. So iterating on data, but you have to know when it happened to get know how to fix it. So this is a big part of what we're seeing with people saying, "Hey, you know I want to "make my machine learning algorithms better "after the fact, I want to learn from the data." How do you see that evolving? Is that one of the use cases of sensors as people bring data in off the network, getting better with the data, knowing when it happened? >> Well, for sure what you're saying is, is none of this is non-linear, it's all incremental. And so if you take something, you know just as an easy example, if you take a self-driving car, what you're doing is you're instrumenting that car to understand where it can perform in the real world in real time. And if you do that, if you run the loop which is, I instrument it, I watch what happens, oh that's wrong, oh I have to correct for that. I correct for that in the software. If you do that for a billion times, you get a self-driving car. But every system moves along that evolution. And so you get the dynamic of constantly instrumenting, watching the system behave and do it. And so a self driving car is one thing, but even in the human genome, if you look at some of our customers, you know, people like, people doing solar arrays, people doing power walls like all of these systems are getting smarter and smarter. >> Well, let's get into that. What are the top applications? What are you seeing with InfluxDB, the time series, what's the sweet spot for the application use case and some customers? Give some examples. >> Yeah so it's pretty easy to understand on one side of the equation, that's the physical side is, sensors are getting cheap obviously we know that. The whole physical world is getting instrumented, your home, your car, the factory floor, your wrist watch, your healthcare, you name it, it's getting instrumented in the physical world. We're watching the physical world in real time. And so there are three or four sweet spots for us, but they're all on that side, they're all about IOT. So they're thinking about consumer IOT kind of projects like Google's Nest, Tudor, particle sensors, even delivery engines like Rappi, who deliver the instant car to South America. Like anywhere there's a physical location and that's on the consumer side. And then another exciting space is the industrial side. Factories are changing dramatically over time. Increasingly moving away from proprietary equipment to develop or driven systems that run operational. Because what has to get smarter when you're building a factory is systems all have to get smarter. And then lastly, a lot in the renewables, so sustainability. So a lot, you know, Tesla, Lucid motors, Nicola motors, you know, lots to do with electric cars, solar arrays, windmills arrays, just anything that's going to get instrumented that where that instrumentation becomes part of what the purpose is. >> It's interesting the convergence of physical and digital is happening with the data. IOT you mentioned, you know, you think of IOT, look at the use cases there. It was proprietary OT systems, now becoming more IP enabled, internet protocol. And now edge compute, getting smaller, faster, cheaper. AI going to the edge. Now you have all kinds of new capabilities that bring that real time and time series opportunity. Are you seeing IOT going to a new level? Where's the IOT OT dots connecting to? Because, you know as these two cultures merge, operations basically, industrial, factory, car, they got to get smarter. Intelligent edge is a buzzword but I mean, it has to be more intelligent. Where's the action in all this? >> So the action, really, it really at the core, it's at the developer, right? Because you're looking at these things, it's very hard to get an off the shelf system to do the kinds of physical and software interaction. So the action's really happen at the developer. And so what you're seeing is a movement in the world that maybe you and I grew up in with IT or OT moving increasingly that developer driven capability. And so all of these IOT systems, they're bespoke, they don't come out of the box. And so the developer, the architect, the CTO, they define what's my business? What am I trying to do? Am I trying to sequence a human genome and figure out when these genes express themselves? Or am I trying to figure out when the next heart rate monitor is going to show up in my apple watch? Right, what am I trying to do? What's the system I need to build? And so starting with the developer is where all of the good stuff happens here. Which is different than it used to be, right. It used to be you'd buy an application or a service or a SaaS thing for, but with this dynamic, with this integration of systems, it's all about bespoke, it's all about building something. >> So let's get to the developer real quick. Real highlight point here is the data, I mean, I could see a developer saying, "Okay, I need to have an application for the edge," IOT edge or car, I mean we're going to have, I mean Tesla got applications of the car, it's right there. I mean, there's the modern application life cycle now. So take us through how does this impacts the developer. Does it impact their CICD pipeline? Is it cloud native? I mean where does this go to? >> Well, so first of all you're talking about, there was an internal journey that we had to go through as a company which I think is fascinating for anybody that's interested, is we went from primarily a monolithic software that was open sourced to building a Cloud-native platform. Which means we had to move from an agile development environment to a CICD environment. So to degree that you are moving your service, whether it's you know, Tesla monitoring your car and updating your power walls, right. Or whether it's a solar company updating the arrays, right, to a degree that that service is cloud. Then increasingly we remove from an agile development to a CICD environment, which you're shipping code to production every day. And so it's not just the developers, it's all the infrastructure to support the developers to run that service and that sort of stuff. I think that's also going to happen in a big way. >> When your customer base that you have now, and as you see evolving with in InfluxDB, is it that they're going to be writing more of the application or relying more on others? I mean obviously it's an open source component here. So when you bring in kind of old way, new way, old way was, I got a proprietary platform running all this IOT stuff, and I got to write, here's an application that's general purpose. I have some flexibility, somewhat brittle, maybe not a lot of robustness to it, but it does this job. >> A good way to think about this is- >> Versus new way which is what? >> So yeah a good way to think about this is what's the role of the developer/architect, CTO, that chain within a large, with an enterprise or a company. And so the way to think about is I started my career in the aerospace industry. And so when you look at what Boeing does to assemble a plane, they build very very few of the parts. Instead what they do is they assemble. They buy the wings, they buy the engines, they assemble, actually they don't buy the wings. That's the one thing, they buy the material for the wing. They build the wings 'cause there's a lot of tech in the wings, and they end up being assemblers, smart assemblers of what ends up being a flying airplane. Which is a pretty big deals even now. And so what happens with software people is, they have the ability to pull from you know, the best of the open source world. So they would pull a time series capability from us, then they would assemble that with potentially some ETL logic from somebody else. Or they'd assemble it with a Kafka interface to be able to stream the data in. And so they become very good integrators and assemblers but they become masters of that bespoke application. And I think that's where it goes 'cause you're not writing native code for everything. >> So they're more flexible, they have faster time to market 'cause they're assembling. >> Way faster. >> And they get to still maintain their core competency, AKA their wings in this case. >> They become increasingly not just coders but designers and developers. They become broadly builders is what we like to think of it. People who start and build stuff. By the way, this is not different than the people just up the road. Google have been doing for years or the tier one Amazon building all their own. >> Well, I think one of the things that's interesting is that this idea of a systems developing, a system architecture. I mean systems have consequences when you make changes. So when you have now cloud data center on-premise and edge working together, how does that work across the system? You can't have a wing that doesn't work with the other wing kind of thing. >> That's exactly, but that's where that Boeing or that airplane building analogy comes in. For us, we've really been thoughtful about that because IOT it's critical. So our open source edge has the same API as our cloud native stuff that has enterprise on prem edge. So our multiple products have the same API and they have a relationship with each other. They can talk with each other. So the builder builds it once. And so this is where, when you start thinking about the components that people have to use to build these services is that, you want to make sure at least that base layer, that database layer that those components talk to each other. >> So I'll have to ask you if I'm the customer, I put my customer hat on. Okay, hey, I'm dealing with a lot. >> Does that mean you have a PO for- >> (laughs) A big check, a blank check, if you can answer this question. >> Only if in tech. >> If you get the question right. I got all this important operation stuff, I got my factory, I got my self-driving cars, this isn't like trivial stuff, this is my business. How should I be thinking about time series? Because now I have to make these architectural decisions as you mentioned and it's going to impact my application development. So huge decision point for your customers. What should I care about the most? What's in it for me? Why is time series important? >> Yeah, that's a great question. So chances are, if you've got a business that was 20 years old or 25 years old, you were already thinking about time series. You probably didn't call it that, you built something on Oracle, or you built something on IBM's Db2, right, and you made it work within your system. Right, and so that's what you started building. So it's already out there, there are probably hundreds of millions of time series applications out there today. But as you start to think about this increasing need for real time, and you start to think about increasing intelligence, you think about optimizing those systems over time, I hate the word, but digital transformation. Then you start with time series, it's a foundational base layer for any system that you're going to build. There's no system I can think of where time series shouldn't be the foundational base layer. If you just want to store your data and just leave it there and then maybe look it up every five years, that's fine. That's not time series. Time series is when you're building a smarter more intelligent, more real time system. And the developers now know that. And so the more they play a role in building these systems the more obvious it becomes. >> And since I have a PO for you and a big check. >> Yeah. >> What's the value to me when I implement this? What's the end state? What's it look like when it's up and running? What's the value proposition for me? What's in it for me? >> So when it's up and running, you're able to handle the queries, the writing of the data, the down sampling of the data, the transforming it in near real time. So that the other dependencies that a system it gets for adjusting a solar array or trading energy off of a power wall or some sort of human genome, those systems work better. So time series is foundational. It's not like it's doing every action that's above, but it's foundational to build a really compelling intelligence system. I think that's what developers and architects are seeing now. >> Bottom line, final word, what's in it for the customer? What's your statement to the customer? What would you say to someone looking to do something in time series and edge? >> Yeah so it's pretty clear to us that if you're building, if you view yourself as being in the business of building systems, that you want 'em to be increasingly intelligent, self-healing autonomous. You want 'em to operate in real time, that you start from time series. But I also want to say what's in it for us, Influx. What's in it for us is, people are doing some amazing stuff. You know, I highlighted some of the energy stuff, some of the human genome, some of the healthcare, it's hard not to be proud or feel like, "Wow." >> Yeah. >> "Somehow I've been lucky, I've arrived at the right time, "in the right place with the right people "to be able to deliver on that." That's also exciting on our side of the equation. >> Yeah, it's critical infrastructure, critical of operations. >> Yeah. >> Great stuff. Evan thanks for coming on, appreciate this segment. All right, in a moment, Brian Gilmore director of IOT and emerging technology at InfluxData will join me. You're watching theCUBE, leader in tech coverage. Thanks for watching. (upbeat music)

(upbeat music) >> Welcome back to theCUBE's continuing coverage of AWS re:Invent 2021 live from Las Vegas. I'm Lisa Martin. We are doing one of the most important industry events, hybrid events this year with Amazon and its massive ecosystem of partners, some of which are joining me next. We've got two live sets, two remote sets, over 100 guests on the program, I'm going to be talking about the next decade in Cloud innovation. I'm pleased to welcome back Anthony Lye to the program, the Executive Vice President and General Manager of Public Cloud at NetApp. Anthony good to see you. >> Nice to see you again thanks for... >> Nice to see you in person. >> I know... >> It's been a couple of years. And Amiram Shachar is here, the VP and GM of Spot by NetApp, Amiram it's great to have you on the program, welcome. >> Likewise, thank you. >> So the acquisition, the Spot acquisition was during the pandemic mid 2020, Amiram talk to me about that why NetApp, how's it going? Give us the lay of the land. >> I think that's the, it's one of the greatest things that NetApp has done, and I think it's one of the most amazing outcomes we could have as a company. And if you think about it in a first sight, when you look at storage company and compute company, what's the connection? But the thing is that NetApp is a company that is going through a huge transformation into Cloud. And by doing this acquisition, it's really like signaling where it's going. It's going way beyond, and honestly I just wanted to be part of it. >> And what's the customer sentiment been the 18 months or so, post acquisition? >> I think NetApp has done specifically with Anthony leading that acquisition, NetApp has done a phenomenal job of keeping Spot as a business unit, independent business unit. So our customers didn't really feel that something had happened, like the only thing we told them is we're going to have more funding, so. >> I'm sure they like that. Anthony talk to us about NetApp's transformation, transition, Spot as part of that. And then of course, CloudCheckr which acquisition was just announced I believe yesterday? >> We closed on actually November 7th. >> Lisa: Okay. >> So it's almost been a month now since we closed, but I've been at NetApp my gosh, it'll be five years in February. And you know, I think that the company had a real desire to sort of, to re-imagine itself and to sort of to embrace the public Clouds and to give its customers you know, what I think it's done incredibly well is this idea of symmetry. That we wanted to build something on Amazon that was as good or maybe a little bit better than on-premise. And customers really I think appreciated, they appreciate that sort of, that desire for us to do those kinds of things. Now of course, CloudCheckr was my ninth acquisition in four years. Just to sort of, to build on what Amiram said I mean, CloudCheckr we acquired four Spot and we acquired what? Four companies in the last 12 months for Spot. So we really believe that as a company now we can address all of their potential opportunities, whether it's in a legacy application, whether it's a virtual desktop, whether it's a Cloud native application, or we just went and announced Ocean for Apache Spark. So Spot now has an optimization and automation solution for Spark on AWS which we announced, I think just yesterday. >> Correct. >> But I'd like to get both of your perspectives on keeping Spot as a brand, Anthony we'll start with you and then Amiram we'll go to you. >> Amiram is the founder, and he was the CEO of the company and built a fantastic company. And we, NetApp I think has a phenomenal brand, but a brand that's that's associated with the sort of the traditional IT organization. And as you note in the Cloud the buyers are slightly different. They're sort of the application owners, or they operate in a sort of a construct that most people call CloudOps or DevOps. And we felt that Spot represented that new buyer in ways that NetApp didn't and probably couldn't. And so we really liked the idea of having the structure of the big N supported by a little pink and a little blue and a more sort of Cloud native brand. >> And that's key, especially the dynamics in the market that we've seen the last 22 months with the rapid changes, the pivot to Cloud customers that weren't that digital needing to go in that direction to survive in the very beginning, I imagine this was really kind of core to NetApp's strategy, but also helping both of your customers to survive initially and then to be able to thrive and identify some of those key areas where they can cut costs would be a far more efficient. >> Okay I think you are in here, if you were born physical you're now digital, and if you weren't born physical you were born digital. And you know, digital is a very effective medium accelerated by the pandemic because as you said, we couldn't really get close to each other and you just look at the innovation around us here at Amazon, it's just amazing to watch. And we've just been really, really good partners with Amazon now for many, many years. And we continue to see just huge, huge opportunities. >> Well Adam Selipsky this morning in his keynote, one of the partners he called out was NetApp. >> Yeah I know I mean, I'll talk a little bit later on maybe with Yancey and I but you know, Amazon now sells our product. They haven't done that with anybody. So ONTAP is now a product that Amazon sells. >> Lisa: Okay. >> Amazon supports, Amazon bills, Amazon runs. So we've really, really demonstrated I think not just to our customers, that sort of a high rate of innovation and an opportunity to sort of accelerate their businesses, but we've demonstrated it to Amazon themselves, that we can operate like them. And we can develop with them at a speed that they are comfortable with. That maybe a few years ago many people would have doubted that a legacy company could operate this way. >> Right, one of the things we know about Amazon is the speed, but also their focus on the customer it's laser-focused, that whole flywheel of Amazon everything that was being announced this morning was exciting to your point Anthony, but it's also showing how involved the customers and the partners are in the ecosystem and that flywheel. Amiram talk to me from your perspective what are some of the, from a visionary standpoint what are some of the things that you're looking forward to going forward with CloudCheckr, but also knowing how deeply connected and integrated NetApp is with a big powerhouse like AWS? >> Yeah, so a few things about that. I think the first thing is also my take from today, like listening to the keynote and looking at all the new announcements. I think the trend is that deployment to the Cloud is becoming easier, but operations is becoming messier. And I think when we look at our category and where we aspire, where we want to be and where we're going. So I think with the CloudCheckr acquisition. So we're expanding into an area that we haven't been to because there are two categories in Cloud cost, there is optimization and there is cost management. What we've done, what we've built, what we've, the business we had is in the optimization space. It's actively reducing and optimizing resources for customers. And there are very few companies in that category as I can say. But right now we're expanding into that area of cost management, so we can meet our customers sooner and you can see us doing it in multiple areas, not only here, but also if we look at a customer journey in the Cloud, it starts with bring workloads in the Cloud, deploy them, and then secure them, and then automate them and then optimize them. Nobody moves to the Cloud and optimizes. So we're typically meeting customers at the end of their journey, we're meeting customers where they need an optimization and they have everything already set up. And right now with Ocean for Apache Spark, Ocean continuous delivery, Spot security, we're meeting customers sooner in their journey so we can provide a much more holistic solution and platform to customers wherever they are in their migration to the Cloud and scaling into Cloud. And with CloudCheckr also taking us to a whole new world of cost management. So, I think we're scaling and ramping and doing all these things, and it's so amazing to realize that we haven't unleashed even 1% of what we can do. >> Really, so there's much more under the covers that we're still waiting for? >> I think the good news is you know, to comment more on what you said, our roadmaps are now largely being driven by customers. And that's just so refreshing to know that you've not only solved a problem for a particular customer, but the customer wants you to solve more problems and that they trust us to be that sort of organization that can help them. So, we're full steam ahead. You know, we're going to continue to acquire in areas where we think we can get acceleration. But our acquisition of Spot was very much about as Amiram said, bringing not just a great company into the business, but to invest significantly in it. And that's really proven I think to me, as Amiram said, one of the most if not the most successful acquisition NetApp has ever done. >> Well congratulations, that's fantastic. But it also sounds like from that customer focus there's clear, strong alignment with how AWS operates, how it values its customers from NetApp's perspective and I imagine from Spots as well. >> You know, if there's one thing I was really proud of during the acquisition, is I got a phone call from a customer, it's the largest food delivery company in South America, and they were very worried about this acquisition and I asked them why? And they told me, "Because your customer service, Spot's customer service is the best customer service I've ever gotten, and if I'm not going to continue to get this customer service, I need to look how I'm finding another vendor." And they told me that, when they want to even tell AWS like which company they can learn from, they're always pointing at Spot. So, and that was a very refreshing moment for me to realize how much also at Spot we care about our customers, but not only as a gimmick, as something that customer obsession, as something that we really live. And that was interesting to see that, that was a concern by our customers when we got acquired. >> Well that's proof in the pudding, because you're right it's one thing to say, companies can always say, "We're customer obsessed, we're customer first, we're customer focused." It's one thing to say it as a marketing term it's a whole other thing to actually live it and demonstrate it, and actually have people coming to you saying that, "We want to model that." I'm curious Anthony, what did you pull over from that? What has NetApp learned from this? >> I always tell Amiram that the idea was that they would essentially take us over. That you know, we sort of loved their culture, we loved their people and their process. And we literally changed a lot of how NetApp operated to operate along the Spot model. So we really did, as Amiram said earlier on, we let them not just sort of exist, but we let them thrive. And we encourage them to point at other areas that NetApp, that they thought we should change to be more like them. And it's raised the bar across everything we do now. And so, we now have a lot of the Spot business processes, a lot of the Spot cultures sort of seeping into the whole of the company. >> That's a very empathetic approach, and that's one of the things that we've learned in the last year and a half that's been, it's key to leadership, it's key to anything is that empathy. But the ability to recognize where there are things within an organization that can be improved and looking at leaders like Spot to go, "Let's actually make this really symbiotic and bi-directional." And I imagine with CloudCheckr it's going to be the same type of influence? >> Well as I've always said, and I say this to the employees and to the acquisitions that we make, what we are acquiring is people. You know the logo, the software, even in many ways the customer base is really very much I think a function of the people. And we work incredibly hard to retain the people, but we do so by sort of empowering them and encouraging them to lead. We really don't want to have the historical perspective of acquisitions, where big company swamps the little company. And I think we've tried very hard to make that a part of our acquisition strategy. And so CloudCheckr is very early in the process but very much, we're following those things, even Amiram and his team are learning from them. If they're doing something a little better than Spot is, then that's something we'll pick up from them. >> And that's just from a very open cultural perspective, that's a big change for NetApp but it's also a smart way to go, 'cause you're right it's, you're acquiring people. And we often talk about people, process, technology. But it's, sometimes to be honest with you it's rare that we hear companies talking about the people focus as being that's critical. It's because of our people that we have successful support, happy successful customers. So that people focus is (inaudible). >> You know, it's the company and culture is not something you can manufacture. It's something that happens and it happens I think through people. And it's an important thing is, if you can establish an organization with the right kinds of people and again, all credit goes to Amiram as the founder and CEO of the company. I think you sort of demanded a kind of person and a kind of culture that set you apart from so many other companies. >> I think the focus on culture was, I was very obsessed with it from very early on in the process that even Spot investors were very, they were questioning like, how come that you are so much obsessed with culture so early on? And I think it paid off big time. There was a book I read while being a CEO that really helped me to scale from quarter to quarter, because I really believe that as a CEO of a startup, every quarter you're basically applying again to your job because you're getting a new company every quarter. And about people, processes, technology, so at Spot it was a little bit different through the book I read, which is "The Hard Thing About Hard Things" by Ben Horowitz, it's people, product, revenue, PPR. And you need to take care of the people, and if you don't take care of the people, so nothing else matter, like it's nothing else just... >> Right. >> And if the people and the product are not working well, so the revenue are not going to come. So revenue was always for us as something that is coming, it's trailing after a good product and good people. >> I love that, what a great, honest focus and vision you guys both have congratulations on the acquisition, CloudCheckr. But also just the cultural alignment that you've done that's really driven by your people and the customers, it's really refreshing to hear that and congrats on NetApp's continued partnership with AWS. We look forward to having you on again next time we can see you in person and talk more about customer successes. >> Thank you very much for hosting us. >> My pleasure guys. >> Thank you. >> For my guests, I'm Lisa Martin. You're watching theCUBE, the global leader in live tech coverage. (upbeat music)

>>Mhm Hello and welcome back to the cubes coverage of 80 of his public sector summit live for two days in D. C. In person. CuBA's here is an expo floor that people face to face down here. Adriana guest co founder and Ceo of Girls in tech cube alumni friend of the cube. We've known her for a long time. Watch their success really making an impact. Great to see you. Thanks for coming on. >>Wonderful to see you, john, thanks so much for having me. >>You know, one of the things that Sandy carter talks about matt max Peter talks about all of the Amazonian leadership that's about is skills training. Okay, this is a big deal. Okay, so getting talented to the industry is critical and also diversity and women attacking underrepresented minority groups are key. This has been a look at constant focus, you've been successful and and convincing folks about tech and working hard, what's the update, >>wow. So the reason why we're here, not only as Sandy carter are amazing chairman of the board of six plus years, but I heard we heard so many pain points from several of our partners as well as our good friends over at the White House and the Department of State and many other public sector agencies that there is a deficit. It's been very difficult to find diverse groups of talent and talent period to join their companies and populate those important I. T. Jobs stem jobs, whether it's very very technical or more data driven or more sort of design focus, product development focus across the board it's been very hard for them to find talent for those jobs. So girls in tech has partnered with AWS to create an initiative called the next generation public sector leaders and really focusing on creating awareness on career development opportunities for up and coming talent diverse talent that is curious and interested in job opportunities and educational opportunities within the public sector. So it has multi tiers, right? And it's something that we've devised based on the need and based on a lot of data and a lot of interviews from a lot of our partners and within the A. P. N. Network and we're doing a mentorship program which is a six month long program matching these amazing public sector executives, really accomplished leaders as well as our members from around the world um to connect and expose them and provide that nurturing, fostering mentality so that they can succeed in their careers. So >>eight of us getting behind this mission. Yes. And public sector is really fast growing changing. You start to see a lot of public private partnerships go on. So not just the old school public sector business, I mean the pandemic has shown the impact of society. So what does that do for the melting pot of talent out there? Have you seen anything out there? And how does that relate to this? Is that helped you at all or what's that does that mean for the mission? >>So there is a melting pot of talent. I just think we need to do a better job of creating awareness and really knowing where that talent lives. Like what are the blogs that they read? What are the videos that they watch and listen to? Where are they? Right. And we need to do the hard work and investigating and understanding like taking a more empathetic approach to really finding out what um how we can access them what their needs are. What are the things that interest piqued their interest within these jobs within the public sector um And customize it and market it so that they'll be eager and excited. Um And it would be more appealing to them. >>So I looked at the press release I just want to get your reaction to something you got evening with the experts. It's an in person event. >>Yes. When >>is that? Is that here is that going to be on your own event? What's that about? >>All the events that are going to be in person? Will be in D. C. Um There will be some virtual events as well. Our mentorship program is all virtual six month long program with curriculum and matchmaking on a platform that we use the evening with the experts which is a panel discussion with experts from a A. W. S. And beyond the A. P. N. Network. We'll talk about challenges and technology opportunities within a career development and also jobs. Um Well do recruitment like on the fly type of activities as well. Speed and speed interviewing, speed networking? Um We also have a few other programs, our webinar which is about the next gen public sector opportunities and this is more about the challenges that people face that companies face and the new technologies that will be launched very soon. And we're doing a widget on our jobs board to highlight the new career opportunity, new job opportunities from all of the public sector partners. We work with >>a very comprehensive, >>It's very comprehensive on the six >>month guided mentorship program. How does someone get involved in applications? How what's that going on there? >>It will be an application process and we will promote it to anyone who signs up to our newsletter. So go to Girls in tech dot org. Sign up for our newsletter and we will be posting and sharing more information on how people get involved. But we'll definitely send custom uh E. D. M essentially promoting to the people who are here at the conference and also through our Girls in tech D. C. Chapter as well. >>So I have to ask you, I know you've been really busy, been very successful. You've been out and about what's the trend line looked like? Well >>not for the last few years though, >>you've >>been in lockdown now. >>You've been working hard, you know have not not about now. You >>are not >>about what's the temperature like now in terms of the pulse of the industry relative to progress, what's what's what are you finding, what's the current situation >>progress for women in tech in the industry. So Since I started girls in tech in 2007, we've made A lot of progress, I would say it's a lot slower than I thought it would be, but you do see more and more women and people representing bipac actually apply for those jobs. We it is astronomically different than 2006, when I started in my first startup and there's a lot more mentorship, There are a lot more organizations out there that companies are more accountable with the R. G. Groups and they're changing their policies, are changing their training programs are having more off sites, there's now technologies that focus on tracking uh productivity and happiness of employees so that like all of that did not exist or I should say none of that existed, you know? And so we worked hard, we've worked hard, but it takes a village, it takes a lot of different people to create that change. And now one of girls in text mission is not just providing that education that community, that mentorship, we want to get the corporate involved, we want to teach the corporate about D and I training the importance of diversity, different tactics to recruit uh so on and so forth. And and it's been so amazing, so inspirational, I love, I started working more in partnerships and having our monthly calls with partners because I love it. I love collaborating to >>recruit good peer group around you to accelerate and create more territory of awareness and impact more people can get their hands involved. And I think to me that's what I think you're starting to see that with podcasts and media people are starting to go direct to tell their story, apps are out there now as you mentioned. So, but I feel like we're on a crossover point coming soon, totally thinks it's different. Um, but it's still a >>lot more work to do a lot more. We just got the service. I know, I know you've just scratched the surface, but we're so excited to be here. Aws is a huge supporter thanks to Sandy carter and her team. Um, it's been an amazing experience. >>Sandy's got great vision, she takes risks. So she's actually got the Amazonian concept of experiment, try something double down if it works and that's great to see that you guys have extended that relationship with, with her and the team. I like this idea of the fellowship cohort model of the or that program, you have the mentorship program. I think that's super cool. Um, that's something I think will be very successful. >>Uh, it's been successful so far. We typically over sell our mentorship are mentee spots. Uh, we only have 500 spots and last one we had over 2300 like a crazy amount, so we know that our members are really hungry for it around the world. And we know it will just be as just as popular for the public sector. So >>what's next for you? What's the vision? What's the next step was events are coming back in person? We're here in person. >>Yeah, there's just so much going on. I wish I could clone myself and we're busting at the seams. And I think the things that are really exciting to me are being able to produce our programs internationally, specifically in developing countries. So we're working um we haven't made an official announcement yet or anything, but we are working on expanding in african countries with Aws. They're doing some efforts and making some movements there. So places like Cameroon Ghana Nigeria Egypt. Uh we are looking to create chapters there for Girls in Tech and then expand our programming. Uh we're also, as mentioned earlier, we're working a lot with corporations to provide DNA training. So, training about policies, Inclusive leadership. Making sure they have the tools and policies to succeed and for their employees to feel comfortable, safe and productive in their work environment >>is great to see you. Congratulations Girls in tech dot org. Yes. Is the U. R. L. Check it out a great mission, very successful. Making progress any stats you can throw out there, you can share. >>Yeah, of course, you >>wrap it up. >>Yeah. So right now, girls in tech has 58 active chapters in 38 countries with over 70,000 active members. And by the end of the year we will have close to 100 active members. So hopefully we'll see you next year and that number will double or triple sign >>up. Tell him johN sent, you know, don't say that because you won't get no. Great to see you. >>Thank you. Nice to see you too. Thanks so >>much, john. Great to have you on cube coverage here at AWS public Sector summit in Washington, D. C. Is a live event. Were face to face. We had some remote guests. It's a hybrid event. Everything is being streamed. I'm john Kerry with the cube. Thanks for watching. Mhm. Mhm

from the cube studios in Palo Alto in Boston connecting with thought leaders all around the world this is a cube conversation [Music] hi buddy this is Dave Volante and welcome to this cute conversation you know the we've been following a company called Activia for quite some time now they they've really popularized the concept of copy data management really innovative Boston based Waltham based company and with me Brian Regan who's the chief marketing officer and all 40 who's the newly minted chief revenue officer of actifi Oh guys great to see you I wish we were face to face that you're you're you're June event but this will have to do yeah you bet yeah so you know Brian you've been on the cube a bunch I'm gonna start with Paul if that's okay Paul you know just let's talk a little bit about your your background you've you've done a number of stance at a variety of companies you know big companies like IBM and others as well what attracted you to Activia in all honesty I've been a software guy and candidly a data specific leader for many many years and so IT infrastructure particularly associated around data has always been sort of my forte for fun on words there and and so Activia was just smack dab in the middle of that right and so when I was looking for my next adventure you know I had an opportunity to to meet with a shower CEO and Founder and describe and discuss kind of what activity was all about and candidly the the number of connections that we had that were the same a lot of our OEM relationships with people that I actually worked with and for and some that worked for me historically so it was almost this perfect world right and I'm a Boston guy so it was in my in my old backyard and it was just a perfect yeah it was a perfect match for what I was looking for which was really a small growth company that was trying to you know get to the next level that had compelling technology in a space that I was super familiar with and understanding and articulate the value proposition well as we're saying in Boston Paulie we got to get you back here I know I pack my cock let's talk about the let's talk about the climate right now I mean nobody expected this of course I mean it's funny I was I saw ash and an event in in Boston last fall we were talking like hey what do you expected for next year yeah a little bit of softening but you know nobody expected this sort of Black Swan but you guys I just got your press release you put out you had a good you had a good quarter you had a record first quarter um what's going on in the marketplace how you guys doing yeah well I think that today more than than ever businesses are realizing that data is what is actually going to carry them through this crisis and that data whether it's changing the nature of how companies interact with their customers how they manage through their supply chain and in frankly how they take care of their employees is all very data-centric and so businesses that are protecting that data that are helping businesses get faster access to that data and ultimately give them choice as to where they manage that data on-premises in the cloud and hybrid configuration those are the businesses that are really going to be top of a CIOs mind I think our q1 is a demonstration that customers voted with their wallets in their confidence in ectopy Oh has an important part of their data supplied nopal I want to come back to you first of all your your other people know you're next you're next Army Ranger so thank you for your service that's awesome you know I was talking to Frank's lute man we interviewed me other day and he was sharing with me sort of how he manages and and he says the other managed by a playbook he's a situational manager and that's something that he learned in the military well this is weird this is a situation okay and that really is kind of how you're trained and and of course we've never seen anything like this but you're trained to deal with things that you've never seen before so how are you seeing organizations generally actifi Oh specifically going to manage through this process what are some of the moves that you're advising recommending give us some insight there yeah so I'm it's really interesting it's a it's funny that you mentioned my military background I was just having this discussion with one of my leaders the other day that you know one of the things that they trained for in the military is the eventualities of chaos right and so when you when you do an exercise they we will literally tap the leader on the shoulder and say okay you're now dead and without that person being allowed to speak they take a knee and the unit has to go on and so what happens is you you learn by muscle memory like how to react in time suffice it or and you know this is a classic example of leadership and crisis and so um so it's just it's just interesting like so to me you have a playbook I think everybody needs to start with a playbook and then start with a plan I can't remember if it was Mike Tyson but one of them one of my famous quotes was you know let you know plan is good until somebody punches you in the face that's the reality of what just happened the business across the globe is it just got punched in the face and so you got a playbook that you rely on and then you have to remain nimble and creative and candidly opportunistic and from a leadership perspective I think you can't lose your confidence right so I've watched some of my friends and of what some other businesses crippled in the midst of this and I'm because they're afraid instead of instead of looking at this in my first commentary that our first staff meeting Brian if I remember it was this okay so what makes active feel great in disembark like not why is it not great right and so we didn't get scared we jumped right into it we you know we adjusted our playbook a little bit and candidly we just had a record quarter and we just down here the honestly date we took down deals in every single geography around the globe to include Italy I mean so it was insane it was really fun okay so this wasn't just one monster deal that gave you that record Porter is really a broad-based the demand yeah so if you you know if you dug underneath the covers you would see that we had the largest number of transactions ever in the first quarter we had the largest average selling price in the first quarter ever we had the largest contribution from our panel partners and our OEM partners ever and we had the highest number ever and so it was a it was really a nice truly balanced performance across the globe and across the size of deal sets and candidly across industries interesting I mean you use the term opportunistic and and I think you're right on I mean you obviously you don't want to be chasing ambulances at the same time you know we've talked to a lot of CEOs and essentially what they're doing and I'd like to get your feedback on this Brian you you you're kind of reassessing the ideal profile of a customer you're reassessing your value proposition in the context of the current pandemic and and I noticed that you guys in your press release talked about cyber resiliency you talked about digital initiatives you know data center transformations etc so maybe you could talk a little bit about that Brian did you do those things how did you do those things what kind of pace were you guys at how did you do it remotely with everybody working from home give us some color on that sure and you know Ashley if you were here you would probably remind us that Activia was born in the midst of the 2008 financial crisis so we we have essentially been bookended by two black swans over the last decade the and the lessons we learned in 2008 are every bit as as relevant today everything starts with cost containment in hospital and in protection of the business and so cio is in the midst of this shock to the system I think we're very much looking at what are the absolutely vital critical initiatives and what is a nice to have and I'm going to pause on my step and invest entirely in the critical mission and the critical initiatives tended to be around getting people safely working for remotely getting people safe access to their systems and their applications in their data and then ultimately it also became about protecting the systems from malicious individuals and state actors up unfortunately as we've seen in other times of crisis this is when crime and cyber crime particularly tends to spike particularly against industries that don't have the strong safeguards in place to to really ensure the resiliency their applications so we very much went a little bit back to the 2008 playbook around helping people get control of their costs helping people continue to do the things they need to do at a much more infrastructure light manner but also really emphasize the fact that if you are under attack or if you are concerned that you're infected but you don't know when you know instant access to data and a time machine that can take you back and forth to those points in time is something that is incredibly valuable so so let's >> cyber resiliency so specifically what is aekta video doing for its customers from a product standpoint capabilities maybe it's part of the the 10 see announcement as well but but can you can you give us some specifics on where you fit in let's take that use case cyber resiliency yeah absolutely so I think there's there's a staff of capabilities when it comes to cyber resiliency at the lowest level you need a time machine because most people don't know when they're in fact and so the ability to go back in time test the recoverability of data test the validity of the data is step one step two is once you've found the clean point being able to resume operations being able to resume the applications operation instantly or very rapidly is the next phase and that's something that Activia was founded on this notion of instant access to data and then the third phase and this is really where our partnerships really shine is you probably want to go back and mitigate that risk you want to go back and clean that system you want to go back and find the infection and eliminate it and that's where our partnership with IBM freezing resiliency services and their cyber incident recovery solution which takes the activity of platform and then rappers and a complete managed services around it so they can help the customer not only get their their systems and applications back on their feet but clean the systems and allow them to resume operations normally on a much safer and more stable okay so so that's interesting so Paul Paul was it kind of new adoptions was it was it increases from existing customers kind of a combination and you talk to that yeah totally so like ironically to really come clean we are the metrics that we had in the first quarter were very similar through the metrics that we see historically so the mix need our existing customer base and then our new customer acquisition were very similar to our historical metrics which candidly we were a little surprised by we anticipated um that the majority of our business would come from that safe harbor of your existing customer base but candidly we had a really nice split which was great which meant that you know a value proposition was resonating not only with our existing customer base where you would expect it but also in in any of our new customers as well who had been evaluating us that either accelerated or or just continue down the path of adoption during the time frame of Koba 19 across industries I would say that again um there was there were there were some industries I would say that pushed pause and so the ones that you can imagine that accelerated during during this past period were the ones you would think of right so financial institutions primarily as well as some some of the medical so some of those transactions healthcare and medical they accelerated along with financial institutions and then I would say that that we did have some industries that push pause and you can probably guess what some of those are a majority of those were the ones that we're dealing with the small and mid-sized businesses or consumer facing businesses things like retail stuff like that where we typically do have a pretty nice residence in a really nice value proposition but there were there were definitely some transactions that we saw basically just pause like we're going to come back but overall the yeah the feedback was just in general it felt like any other quarter and it felt like just pretty normal as strange as that sounds because I know speaking to a lot of my friends and gear companies your software companies they didn't have that experience but we did pretty well that's interesting I mean you're right I mean certain industries Airlines I'm interviewing a cio of major resort next week you know really interested to hear how they're you know dealing with this but those those are obviously depressed and they've dialed everything down but but we've we were one of the first to report that work from home pivot it didn't it didn't you know buffer the decline in IT spending that were expecting to be down you know maybe as much as 5% this year but it definitely offset it what about cloud we're seeing elevated levels in cloud demand guys you know have offerings there what are you seeing in cloud guys you want that yeah I'll start and then fall please please weigh in I think that'd be the move to the cloud that we've been witnessing and the acceleration of the MOOC table that we've been whipped over the past several years probably ramped up in intensity over the last two months The Improv been on the you know 18 to 24 month road map have all of a sudden been accelerated into maybe this year but in terms of the wholesale you know everything moves to cloud and I abandoned my on-premises estate I I don't think we've seen that quite yet I think the the world is still hybrid when it comes to cloud although I do think that the beneficiaries of this are probably the the non number one or number two cloud providers but the rest of the hyper scalers who are fighting for market share because now they have an opportunity to perhaps google for example a strategic partner of ours has a you know a huge offering when it comes to enabling work home and remote work so leveraging that as a platform and then extending into their enterprise offerings I think gives them a wedge that the you know Amazon might not have so this it's an acceleration of interest but I think it's just a continuation of the trend of seeing four years yeah and I would add a little bit if the you know IBM held their think conference this past week I don't know if you had an opportunity to participate there one of our OEM partners and oh yeah because you know when our the CEO presented his kind of opening his opening remarks it was really about digital transformation and he really he really kind of put it down to two things and said you know any business that's trying to transform is either talking about hybrid cloud but they're talking about AI and machine learning and that's kind of it right and so every digital business is talking in one of those categories and so when I look 2q1 it's interesting that we really didn't see anything other than as brian talked about all the cloud business which is some version of an acceleration but outside of that the customers that are in those industries that are in position to accelerate and double down during this opportunity didn't so and those that did not you know kind of just peeled back a little bit but overall I still I would agree with with ibm's assessment of the market that you know those are kind of the two hot spots and have a cloud is hot and the good news is we've got a nice guy operating Molloy yeah Arvind Krista talked about the the in and it has it maybe not I think but he talked earlier in his remarks on the earnings call just in Publix Davis that IBM must win the battle the architectural battle the hybrid cloud and also that he wants to lead with a more technical sell essentially which is submitted to me those those two things are great news for you guys obviously you know Red Hat is the linchpin of that I want to ask you guys about your your conference data-driven so we were there last year it was a great really great intimate event of course you know you hand up the physical events anymore so you've pushed to September you're going all digital would give us the update on on that program we're um we're eager to have the cube participate in our September event so I'm sure we'll be talking more about that in the coming weeks but awesome we love it we exactly so you can tell Frank to put that so we we've been participating in some of the other conferences I think most notably last week learning a lot and and really trying to cherry pick the best ideas and the best tactics for putting on a digital event I think that as we look to September and as we look to put on a really rich digital event one of the things that is I think first and foremost in our minds is we want to actually produce more on-demand digital content particularly from a technology standpoint our technology sessions last year were oversubscribed the digital format allows people to stream whenever they can and frankly as many sessions as they as they might so I think we can be far more efficient in terms of delivering technical content or the users of our technology and then we're also eager to have as we've done with data driven in the years past our customers tell the story of how they're using data and this year certainly I think we're going to hear a lot of stories about in particular how they use data during this incredible you know crisis and and hopefully renewal from crisis well one of my favorite interviews last year your show is the the guys from draft King so hopefully they'll be back on it will have some football to talk about let's hope I mean I want it I want to end with just sort of this notion of you know we've been so tactical the last eight weeks right I'm you guys too I'm sure just making sure you're there for customers making sure your employees are ok but as we start to think about coming out of this you know into a post probe Adaro it looks like it's gonna be with us for a while but we're getting back the you know quasi opening so I'm hearing you know hybrid is here to stay we agree for sure cyber resiliency is very interesting I think you know one of the things we've said is that that companies may sub optimize near-term profitability to make sure that they've got the flexibility and resilience business resiliency in place you know that's obviously something that is I think good news for you guys but but I'll start with Paul and then maybe Brian you can bring us home how do you see this sort of emergence from this lockdown and into the post ghovat era yeah so this is a really interesting topic for me in fact I've had many discussions over the last couple weeks with some of our investors as well as our executive staff and so my personal belief is that the way buying and selling has occurred for IT specifically at the enterprise level is about to go through a transformation no different than we watched the transformation of SAS businesses when you basically replace the cold-calling salesperson with an inside and you know inbound marketing kind of effort followed up with SDR and vdr because what we're finding is that our clients now are able to meet more frequently because we don't have the friction of airplane ride or or physical building to go through and so like that that whole thing has been removed from the sales process and so it's interesting to me that one of the things that I'm starting to see is that the amount of activity that our sales organization is doing and the amount of physical calls that were going on they happen to be online however you couple that with the cost savings of not traveling around the globe and not being in offices and and I really think that those companies that embrace this new model are gonna find ways to penetrate more customers in a less expensive way and I do believe that the professional sales enterprise salesperson of tomorrow is gonna look at then it looks today and so I'm super excited to be in a company that is smack dab in the middle of selling to enterprise clients and and watching us learn together how we're gonna buy sell and market to each other in this post public way because I I'm the only thing I really do know it's just not gonna be the way it used to be what is it gonna look like I think all of us are placing bets and I don't think anybody has the answer yet but it's gonna look different for sure they're very very thoughtful comments and so Brian you know our thinking is the differentiation and the war yes it gets one in digital how is that affecting you know sort of your marketing and your thing around that we we fortunately decided coming into 2020 our fiscal 21 that we were actually going to overweight digital anyway we felt that it was far more effective we were seeing far better conversion rates we saw you know way better ROI in terms of very targeted tentative digital campaigns or general-purpose ABM type of efforts so our strategy had essentially been set and and what this provided us is the opportunity to essentially redirect all of the other funds individually so you know we have essentially a two-pronged marketing you know attack Frank now which is you know digital creating inbounds and B DRS that are calling on those in bounds that are created digital and so it's a you know it's going to be a really interesting transition back when physical events if and when they do actually come back into form you know how much we decide to actually go back into that that been I think that you know to someone to some extent we've talked about this in the past II you know the physical events and the the sheer spectacle and this year you know audacity of having to spend a million dollars just to break through that was an unsustainable model and so I think this is this is hastening perhaps the decline or demise of really silly marketing expense and getting back to telling telling customers what they need to know to help their an assist their buying journey in their investigation journey into a new technology I mean the IT world is hybrid and I think the events world is also going to be hybrid to me nice intimate events you know they're gonna live on but they're also gonna have a major digital component to them I'm very excited that you know we're a lot of learnings now in digital especially around events and by September the a lot of the the bugs are gonna be worked out you know we've been going to it so it feels like 24/7 but really excited to have you guys on thanks so much really looking forward to working with you in in September it's data-driven so guys thanks a lot for coming on the cube oh my gosh thank you Dave so nice it's so nice to be here thank you alright pleasure you did thank you everybody thank you and thanks for watching this is Dave Volante for the cube and we'll see you next time [Music]

>> From the SiliconANGLE media office in Boston, Massachusetts, it's theCUBE. Now here's your host, Stu Miniman. (techy music) >> Hi, I'm Stu Miniman, and welcome to a special CUBE conversation here in our Boston area studio. Happy to welcome to the program first time guest, Patrick Morley, who's the CEO of Carbon Black. Of course, recently announced acquisition by VMware of $2.1 billion. Patrick, thanks so much for joining us. >> Stu, thanks for having me. >> All right. So, you know, we love digging into tech. There is no hotter space than security, you know? All the cybers are, you know, really exciting stuff, and even your company's Waltham-based. >> That's right. >> So actually a little closer to Boston than we are here in Marlborough, Massachusetts. When we had a green screen we used to kind of fake it with the skyline, but you know, the Boston area people know more than just Massachusetts Tech, but you know, a lot of, you know, great technology in Boston of course, you know? A lot of good technologies, a lot of good schools that have driven things. You have been CEO since 2007 and have seen quite a bit. You know, merger, Bit9 and Carbon Black many years ago, IPO, you know, not that long ago in the past, and now acquisition, as we said, for $2.1 billion. So, you know, give us a little bit of step back as to, you know, the journey, how we got here, and you know, what's it like to be kind of at the helm with your crew through, you know, all of those changes? >> Yep, well certainly very, very proud and very thankful to all of the customers that have been with us for many, many, many years. And as you said when you first started here, Boston is an awesome place for cybersecurity. I think I fits a bit of the personality on the East Coast, and if you just look at Boston in general there's a lot of great cybersecurity talent, a lot of great cybersecurity companies. And I'm extremely proud and grateful to all of my employees in Massachusetts who have built Carbon Black over the last number of years. And of course we have offices elsewhere across the globe, but Boston is, and Massachusetts is, where the companies roots really come from. And as you said, 2007 is when I joined the company. Obviously cyber was a very different world back then, and it's amazing if you just kind of roll back. In 2007, the idea of a CISO, of a chief information security officer, was still very new, and most companies we dealt with back then did not have a CISO, they had a network administrator or somebody, so that's all changed. If you look at security as a board-level issue, in 2007 there were certainly some areas of some sectors like the government where it had a lot of importance, but outside of that it did not have the same visibility as a strategic issue as it does now, it's been amazing. >> So much, you know, my background is networking and virtualization. I've spent a lot of time, you know, since 2007 looking at all the cloud world, and as I said, back in the early 2000s security was top of mind but often bottom of budget. You know, the network people, you know, back in the day it was like, "Can't you just lock the door," or you know, "Make sure the rack is secure," and you know, "Well we'll run things over Optical," and therefore we'll know if somebody splices into it from a networking standpoint. Today, as you stated, clearly it's a board-level discussion, CISOs, you know, rising power in the organization, and often dictating a lot of how the stack is built out there. >> Absolutely. >> So wow, bring us a little bit, you know, your portfolio. You know, security is not a thing. You know, any customer I talk to, they're like, you know, there is no such thing as a silver bullet in security. Most customers I talk to really think of security as a programmatic effort, so help us understand a little bit, you know, where Carbon Black fits today, and then we'll get into, you know, your, you know, broadened scope once you're going to be under VMware. >> Yeah, so the core founding idea behind Carbon Black was a simple one, which was that fundamentally the adversary was in a position where they eventually would figure out a way to get in, and if you fundamentally believe that then you do everything you can to stop the adversary, but you say, "I need telemetry. "I need data in order to understand what's happening across my environment in order to be able to see and stop the adversary." And so we began a journey to essentially be able to collect and analyze all the data that an adversary, that an attacker would touch in order to run their program, and you know, we always have equated it to essentially a movie camera that allows you to rewind the tape, and with all that data that we collect we can run tremendous analytics against that in order to be able to see and stop the adversary and understand what's happening across the environment. We essentially created a market that's now called EDR endpoint detection and response, and it's that simple idea of being able to understand and have situational analysis, situational visibility across the whole enterprise. We did that initially on-premise, so we did all that analytics, and each one of our customers' back-ends in their data center, and two years ago we began a journey to say, "Look, we want to do two things." One is we want to leverage that data to be able to provide more security capabilities across a platform, so let's revolutionize, continue to revolutionize cybersecurity by offering a cloud-based platform, we're going to move all of that analytics up into the cloud, all those capabilities up into the cloud, and offer a multi-tenant, cloud native SaaS platform, and over the last two years we've done that with multiple services now up on that cloud, with thousands of customers who are using it, and the benefits of the cloud are pretty straightforward, and they've revolutionized other industries, they're revolutionizing cyber right now. Certainly you can analyze data at a scale that's just not possible when that data's locked up in multiple customers, so that's one big change. Obviously-- >> Yeah, I just, to want to help unpack and tease out that data piece, because you know, we always hear out there it almost, you know, is a bit trite, you know, the importance of data. Data's the new oil, it's the rocket ship, but you know, the value of that data, how much of that is Carbon Black leveraging the data, how much can the customer themselves take advantage of that data, or you know, this isn't in a vacuum. There are other security products, other pieces of, you know, that vendor's stack that might be able to leverage that data. >> Yeah, well Carbon Black's cloud native platform, security platform, is built on a totally, it's totally open, so from an API basis, so you should, you should think about, our customers certainly think about it this way, as one, we're leveraging that data, we analyze a trillion security events a day, one trillion, just immense, and the benefit of that is if we see something across the globe that has a high risk score, that's known malware, that might be a new form of attack, that might be a living-off-the-land attack, all of our customers get the benefit of that analytic. So Carbon Black, we certainly leverage it, but in addition, the way we've built the platform, customers can get access to all the data from their enterprise, and they can correlate that data with other aspects of their security or their IT infrastructure in order to build a more holistic view across the entire enterprise, and we also have third party partners out there, managed security service providers and others, who also have access to that data for their customer set to be able to run analytics on it. So when we think about data, as you said, you know, as the oil of the new world, we need to leverage that data, but we also need, in this new world order, to give our partners and our customers the capabilities to do what they want with that data as well for their own data. >> Yeah, love that, especially if you're talking in that cloud native world it can't just be something that's locked up and only used in one environment. You know, we track the observability companies out there, you know, they have similar type of messaging. Of course data protection, you know, once there is that, you know, breach, you know, how do I recover from this information? So that ripple effect, and love, you know, openness, APIs, making sure that can be shared. You know, maybe not something that traditionally I'd heard from VMware when you talk about the openness and where they're doing maybe. I think there are a couple things you want to talk about Carbon Black, but why not get to the VMware piece, too? >> Yeah, I was just going to, on the cloud side, you know, the power of the cloud, obviously it's revolutionized other industries, and certainly one of it is the ability to provide analytics at scale. The other piece, which I already mentioned, is the network effect on my ability to see something somewhere across the globe and help millions of other customers across the globe when I see something, and the other piece is just my ability to deploy quickly and my ability to innovate quickly, because rather than having to deliver new software into each enterprise I can do that on my cloud native platform. So I think it positions the defender, the security teams around the globe where they can be more on the offensive than they've ever been before because suddenly I don't have to spend my time worrying about deployment mechanics or other pieces. I can focus on what I really want to do, which is I want to secure my environment, I want to be able to understand what the adversary might be doing. So we're real excited about what we've done over the last two years with our cloud platform. >> Okay, so the deal hasn't closed yet but it's announced that you will be leading up the cloud security group at VMware. Give us a little bit, you know, directionally, where's that heading, what will that mean? Of course we've tracked, you know, where VMware touches a lot of that environment, you know, with my background in networking I talked to the Nicira team before, and then through what's become a very successful NSX, Sanjay Poonen with the AirWatch acquisition and where they've gone. Of course I would expect that's the closest piece that you started out with the endpoint protection with that team, with the Workforce ONE. So explain kind of the security portfolio, and interesting, cloud security is the discussion because that's the newer piece of the Carbon Black portfolio. Help us understand how the whole, all the pieces fit together. >> Yeah, so first I'll just reiterate what you said, which is the transaction's not yet closed, so everything I'm talking about is pre-closed, and obviously post-close we'll have additional commentary about what everything will look like. But absolutely we are very, my team, my customers, we announced the transaction a little over a month ago. Everyone was really, really excited, and I think fundamentally they're excited because organizations understand what Carbon Black delivers today, and what we deliver are great security products, and increasingly the majority of those products are in the cloud. And VMware has a tremendous reputation in the industry for the technical capabilities, for the value that they provide to customers, and just for the breadth of the portfolio that they have. You mentioned a few of them, right? And many organizations and people think about VMware from a virtualization standpoint. But increasingly over the last few years they've dramatically expanded their portfolio, network virtualization, and the NSX, the Workspace ONE as well, which was based on the AirWatch acquisition they did. Those are big businesses today, and they're helping organizations transform their infrastructure, the way they manage devices, et cetera. And so Carbon Black, on the security side, we've been partnered with VMware for the last couple of years. We've had an opportunity to get to know each other quite well. We've had an opportunity to integrate in two key spots. One, we've integrated with their App D capabilities, which you can think about essentially as helping to protect and provide telemetry for what's happening inside of the virtualized environment. And then secondarily, we've also partnered with Workspace ONE as well, again more on the device side. Those are two natural points where security, building security intrinsically into that compute stack, we've seen with customer reaction, has a fundamental impact on being able to have security right there rather than having to bolt it on afterwards. >> Yeah, you walk into an interesting configuration. First of all, you know, as you said VMware not thought of as a security company per se, lots of products that absolutely fit in the security space and are there. When you look out, of course VMware, you know, primarily owned by Dell, there's Secureworks, there's RSA, those are well known security brands. You know, how, give us how you think of how all those pieces go together and kind of the trajectory of where things are headed. >> Yeah, well goal number one, once we close the transaction, goal number one is to do two things. One, we're going to continue to drive forward with the cloud roadmap that we have. It's an aggressive road map we've been innovating aggressively over the last couple of years and we're going to continue to do that within VMware. The second piece is obviously to maximize the opportunity to build security into the compute stack of VMware, so that when customers think about security they don't have to think about it as a separate piece, but it's already there at their fingertips. And then as you mentioned, so those are two big goals right there, and as you mentioned obviously Dell has a large portfolio. There's other security products within the Dell portfolio, and you know, when we think about that obviously over time we're already partnered with some of those. Secureworks, for example, has been a very close and valuable part of Carbon Black's for many years. You'll see us continue to partner. There's other parts of the Dell family where we have partnered in the past, not tightly, but I think we'll have the opportunity to do more as part of the Dell family. All of this means for customers more value, because rather than having to go and figure it out themselves we're going to be delivering it in conjunction with the solutions they're already using. >> All right, Patrick, I want to help you, have you address a schism I see in the marketplace when it comes to the messaging around security. When peers of mine went to the RSA conference this year they came back almost unanimously with two words, doom and gloom. >> (laughing) Right. >> In Boston this year Amazon held the inaugural re:Inforce, positioned itself as the, you know, cloud security conference for the industry. We covered that, you know, both of those shows with theCUBE, and Stephen Schmidt from AWS said the state of cloud security is strong. VMware, very much we hear from Pat, you know, we need to do over, security's broken. Friends of mine in the security industry, and Carbon Black's been around since 2002, is you know, come on, you know, it's not just another acquisition, it's going to be a point product. You know, yes we have work to do as a whole, but you know, saying we need a do over or it's broken is a between hyperbolic from my peers in the industry, so what is the state of the industry, is there traditional storage and cloud storage is all rainbows and unicorns, or you know, where do you see it today? Of course we know as an industry there's always work to do, but you know, how do you round that circle? >> Yeah, I would take it, and you're right, by the way, I hear all the same commentary, and I think we have to take a step back and just look at industry, the industry in general, look at security in general. We started the interview talking about well, what was the world like in security in 2007? Security has gone from, "Hey, it's a niche area over here "and we know it's important but don't talk to us," to super strategic, again, at a board level, at a company level, and so that rapid growth has driven a lot of funding into the environment, a lot of vendors, there's over 5,000 security vendors out there today, all competing. I don't know how CISOs and CIOs and practitioners really figure out who does what, it's very challenging, and at the same time you've got the adversary, this third party continuing to advance their attack types using new techniques. You've got ransomware, which is a huge industry now, driving billions of dollars, so you have all of that happening, and so in hyper growth environments like that you get a lot of vendors. The average enterprise security team has 75 different products, and so, and they have to stitch that together, so the fundamentals of what, the way you described it I think are accurate on both sides. One, security's broken, it is broken. We've got too many vendors and we're bolting it on, we got to fix that. VMware is in a position, partnered with Carbon Black, to do that I think really well. The second piece is that the cloud does allow us, I'm not sure about rainbows, but the cloud does allow us to change security fundamentally because of some of the characteristics that I described earlier, and if you take Carbon Black plus VMware, plus what VMware is doing to deliver across any cloud, any device, any application, I think we're in a really interesting spot to help customers get more value from their compute stack and from security. >> You know, one of the things that VMware has always done well is they play in multiple environments. Back in the early days of server ritualization, didn't matter what hardware, they would get that across. Their cloud strategy went through quite a few iterations, you know, Sanjay Poonen came on our program and said, you know, "vCloud Air, we failed. "We got it wrong, we did it," but today every cloud show I go to there's a VMware piece of that. They're partnering with AWS, with Azure, with Google, with Alibaba, with Oracle even-- (chuckling) And IBM recently. But still one of the critiques I have for VMware is VMware does good at managing their house, but security, customers, as you said, they've got 75 tools and they're going to have their VMware state, and they're going to have their native cloud pieces, and they're going to have their non-VMware environment. So how can, you know, once you're under VMware, you know, participate in that environment? Will you primarily be VMware environment and the VMware cloud environment, or will it be a broader cloud security strategy? >> Yeah, well I think certainly VMware has done an amazing job over the last few years of really pushing this any-cloud model, right? "Hey, no matter where your workloads "are going to be in a hybrid cloud environment," you know, "we're going to be there to help you," and more effectively, more efficiently, faster, better performance, strong ROI. And so if you look at Carbon Black's roots, and I mentioned this earlier, one of our core beliefs is that one vendor can't do it all. You have to build on an open, extensible API-based platform, and that's what we've done since the beginning of the company, and so you will not see Carbon Black change our philosophy. You know, we will continue to be very, very open, and I think, by the way, that reflects very much VMware's strategy as of late, which is an open strategy where they're playing with lots of providers in the marketplace. Again, the benefit of Carbon Black plus VMware on that platform is that for VMware infrastructure, their products, I think you're going to see out of the box security capabilities that are going to give advantage to customers, from ease of use, from the way that that security works, et cetera, and then we will continue to partner with other vendors out there across the market. >> All right, Patrick, we know, you mentioned how many different tools customers have to deal with. There are more new threats coming out, you know, every day. There's no way that a person or a team can keep up with all of this, so you know, is AI the answer? How are these technologies going to be able to allow our systems to be able to protect us better and update, you know, we haven't talked abut AI yet. I know it does fit in-- >> We have to talk about AI. (chuckling) >> So just to understand how you know, the systems and the software and the solutions are going to help enable teams to be able to keep up with, you know, the rapidly expanding and changing landscape in security. >> Yeah, AI is a tool, we use it, and just as I've mentioned cloud, right, along with the ability to analyze trillions of events on a daily basis, things like AI can play a very significant role in helping me to understand what's happening across very large corpuses of data, and so we use a lot of it, and that allows us to understand when there's an anomaly somewhere across the globe on some system, some endpoint or device, anywhere across the globe and then leverage that to help our other customers. So AI role is playing an important part. It will continue to play an important part. But AI leverages the data that we collect, so if you go back to where Carbon Black is today with all that data that we're analyzing, one of the really interesting things is VMware today has 70 million VMs. 60 million of those are on-prem, 10 million of them are on the cloud. Part of the benefit that Carbon Black gets from VMware is we're going to get all this additional telemetry that we're going to be able to, again, consume, leverage AI capabilities to help with the analysis of that, and again, provide more customer back to the value on seeing and stopping the adversary. That also extends to what VMware's doing on the device side with Workspace ONE, et cetera, so there's a lot of opportunity over the coming quarters and years to provide more value for customers in understanding what's happening across their environment because of all of the touchpoints we're going to have as part of the VMware compute stack. >> All right, Patrick, final thing, what does this mean for your customers? You know, I think back to, you know, not that long ago you did an IPO, you know? What would that mean for the growth, the investment into technology and growing the team. Now, you know, in industry parlance, you know, you had another exit and you will be part of VMware, so we might not get as much visibility into the specific revenues and the hiring that you're doing there, but what will this ultimately mean for Carbon Black's current and potential future customers? >> Yeah, so we have over 5,000 global customers out there today, and first and foremost it's going to mean more investment from a product roadmap standpoint. If you look at 2019, this year, the number one area of investment for Carbon Black was in R&D, and as we move forward, again post-close, our customers are going to see continued investment in the platform, in our cloud security platform, in order to ensure we continue to bring more capabilities to market. And then, as I said earlier, in conjunction with that do everything we can to integrate in with the VMware product portfolio, again, so that security's not bolted on but it's intrinsic to the compute stack, and so I think that's the biggest thing. I have had the opportunity to go out and speak to many customers over the last four weeks. Customer and partner reaction has been outstanding. They get it, they understand it, they understand that there's a better way and that's what we're going to be doing as part of VMware. >> Yeah, any surprising nuggets in the last month talking to the customers and partners more that you've learned? >> This is going to sound self-serving, but it's the truth. I will tell you that the VMware reputation out there is outstanding. I mean, and I had been surprised at how little I have to do to tell them why this makes so much sense. They get it, the majority of our customers get it. They understand the possibilities of what we can provide, and there's a level of excitement out there, again with our customers and partners. It's just, it's awesome. >> All right, Patrick Morley, CEO of Carbon Black. Thank you so much for joining us on theCUBE. >> Stu, thanks. >> All right, lots of coverage, of course, through 2019 and gearing up for 2020 where we'll all have perfect hindsight, I'm sure. Check out thecube.net for the events we've been at, search where we're going to be, and please reach out if you have any questions. I'm Stu Miniman, and as always, thank you for watching theCUBE. (techy music)

>> Live from Las Vegas, it's theCUBE, covering Dell Technologies World 2019. Brought to you by Dell Technologies and it's ecosystem partners. >> Welcome to Vegas! Lisa Martin with John Furrier. You're watching us on theCUBE live. The end of Day One of our three days of coverage of Dell Technologies World. Can you hear the music? The party's already getting started. We have more content to bring you. Please welcome a couple of guests from DXE Technology, Kevin Johnston, Chief Sales and Revenue Officer, Cloud and Platform Service. Kevin, it's great to have you. >> Thank you very much. Glad to be here. >> Our pleasure. We've got Graham Stringer, Managing Director of Workplace and Mobility for DXE Americas. >> Thank you. Good to be here as well. >> Yeah, you waited just in time for the concert, guys! >> We did. >> Just in time. Here we go. >> All right, so, Kevin, let's go ahead and start with you. Give our audience and understanding of DXE. What you guys do, who you are, all that good stuff. >> Yeah, okay. That's great. So DXE was formed two years ago as a result of the merger of legacy HP Enterprise Services Business and CSC. DXE was formed really for the purpose of helping our large enterprise clients accelerate their digital transformation. So we're about a $22 billion IT services company, really aligned with our partners helping our clients transform digitally. >> And you guys were on the cloud early, too. There's a lot of devops going on. >> Yep. >> You guys had your hands in all the clouds. >> We have. >> What's your take on, here at Dell Technologies World, Microsoft's partnering with VMware? >> Yeah, so we would share a lot of beliefs with Dell Technology and VMware in particular, in that multi-cloud is a real thing. And we see multi-cloud, especially for the large enterprise clients, really being an answer for quite some number of years to come. We also believe that a large percentage of application portfolios will migrate to cloud. Whether it's private clouds or public clouds, and that there's a lot of work to be done to transform those applications to really take advantage of cloud native features. >> So last year's theme of Dell Technologies World was Make It Real, 'It' being digital transformation, security transformation, IT transformation, and workforce workplace automation. Graham, I'd love to get your perspectives on workplace mobility and some of the things that were announced this morning with Unified Workspace, Workspace ONE, and recognizing, hey, for our customers to transform digitally successfully, we've got to make sure that their are people are successful, and their people are highly distributed. What are some of the things that you heard this morning that are exciting, aligning with some of the trends that you're seeing in the workplace? >> Well the big trend that we're seeing is the role that HR is now playing in digital transformation of the workplace. If you go back two, three, four years, it was very IT centric. Conversations were predominantly with the CIO. We're now seeing 30, 40% of organizations or more engaging at the HR level. We did a recent project with one of the big retailers in the industry and right out of the bat, this chief HR officer was engaged right from the get-go. They want to know that their employees are going to experience work very differently. So that's one of the big trends we're seeing emerging. >> When did this shift happen? When was this going on? Past year, two years? Because this is a shift. >> I would say the shift has definitely happened the last couple of years. Millennials are having a huge impact. You're getting quite the cross-pollination of a lot of different generations. Millennials are now having an enormous impact. If you look at outlets like Glassdoor, millennials want to know when they go to an organization can I bring my own device? Am I going to have a great workplace experience? And you can't stick with a very traditional, legacy way of delivering IT where everything was shift left and you got to a point where everybody hated each other. >> That's a problem for productivity. >> Yes, a very big problem for productivity, absolutely. >> Talk about some of the challenges that customers have overcome with digital transformation, as it starts to become less of a buzz word and actually more of a reality and strategic imperative that has some visibility at the unit economics and value. >> Yeah, I think every large enterprise client we talk to has a digital transformation agenda of some sort and at some varying place along the path to trying to adopt a new business model or adapt to a different business process, so the challenges that we see with these clients in general is how do we scale? So I have legacy IT that won't disappear overnight and I have all the possibilities of digitally enabling or bringing new digital technologies that enable these processes or models. So this is a challenge: how to enable digital at scale where traditional and digital have to live together for some period of time. >> And it's not just a tech challenge, it's culture, too. How far has tech come because you've mentioned containers with legacy? That has been a great message to IT is I can put a container around it and hold onto it for a little while longer, I don't have to kill it, and make the changes to cloud-native. >> For the tech guys, there's been a lot of fun things and containers probably is the bridge for legacy apps into cloud for sure. For the rest of the folks, for the normal people, the way work gets done and the way to rethink how to do work in the mix of IT or technology into business is just different. >> Graham's point is beautiful because the expectation of the employee or the worker whether they're in the firm or outside the firm, outside in or inside out, however they look at it, is the new experience they want. So the expectations are changing. What's the biggest thing, we saw some stats on stage about remote working, three places, two places, I mean, hell, I'm always on the road. What is some of the expectations that you're seeing? Obviously millennials and some of the older folks. >> They want to see IT delivered in the way they want to receive it. That's one of the biggest trends we're seeing. So for Millennials, my son's kind of in that age category, right, they love to text. To pick up a phone for a younger generation is a little bit foreign. You go and deal with baby boomers, they want to be dealt with in a much different manner. So you've got that whole change, and then you've got the whole notion now of work is changing; where do I work, the ability to basically work 24/7, wherever I want, however I want, using whatever device that I want. And that of course is now creating a whole new set of challenges for IT, particularly around security. >> But employee experience is absolutely fundamental to a business' success; their ability to delight costumers, their ability to deliver outcome, so it's really pretty core. Talk to us about those conversations that you're having with customers. Are they understanding how significant that employee experience is to bottom line business outcomes differentiation? >> Very much so. We're working right now with a large manufacturing firm and they're doing not just an inside out, but outside in, so they're actually coming to watch. It's part of a workplace strategy to look at it from the outside as well. In other words, how can our client take innovation to their suppliers, their customers, to demonstrate that they understand it? So that's extremely exciting when we see that they're not just focused on their own employees and the experience germane to them. >> One thing I might add is that maybe less so from a user experience per say, but the individuals as an employee. So the shift to digital and the skill shift that's required to go with that is really probably the most monumental change that all of us technology companies and the business part of our large enterprise clients is dealing with. Whether it's a skills gap or whether it's a culture gap, this idea of just simply waterfall to agile and the way to think about that or silo versus end-to-end as just simple ways to think differently about how to go faster. So the experience, how you recruit, whose going to make it, who can be trained, and then where you need to be able to source the new talent from as well. >> I totally agree with you. We do hundreds of shows a year, this is our tenth year doing theCUBE, that is the number one things that we hear over and over again from practitioners and customers and from people working. It's not the check, you can always get a check solution, it's the cultural and the skills gap. Both are huge problems. >> And this is part of the digital at scale point. So we'll hire something in the neighborhood of six to eight thousand digital skills people. We're just about to close on active position of Luxoft, an agile devops digital company. We'll bring another 13,000 in. But if you think about the normal large enterprise and what you need to do to be able to have the university networks and to be able to really source that scale in order to effect the transformations that business need to make to stay competitive. >> And the other point, the engagements have changed too. I'm sure you guys have seen your end but every IT or CIO we talk to says, "I outsourced everything decades ago and now I've got a couple guys running the show. Now I need to have a hundred x more people coding and building core competency." That's still going to need to engage people in the channel or our service providers but they need to build core talent in house. It's swinging back and they don't know what to do. (laughter) Is that why they call you guys? Is that how you guys get involved? >> We'll help train. We'll help clients think through what does an IT or business organization need to look like profile wise, skill wise, operating model wise, and in many cases it's I have my digital model but I still have my traditional model that needs to coexist with it and then here's where the opportunities are for people to develop career paths and progress. >> Kevin, talk about the sweet spot of your engagements that you're doing right now. Where's the heart of your business? Is it someone whose really hurting, needs an aspirin, they've got a headache, is it a problem? Is it an opportunity? Is it a growth issue? Where do you see the spectrum of your engagements? >> We kind of find clients in one of three spots normally. "Hey, I know I need to do something but I'm not sure what it is, can you help me figure out to get started?" So more design thinking, problem solving. We have other clients at the other end of the spectrum who are, "Hey, I've got this figured out. I need a partner to help me execute it's scale. And I know the model that I want to do, I know the business reason for doing it." And then we have a lot of folks that are in the middle, which is, "I've started, I've got a few hundred AWS accounts. I got private clouds sitting idle. Someone help me." Or, "I've got security issues, compliance issues." >> So they're in the middle of the journey and they just need a little reboot or a kickstart. >> They need help scaling. >> They ran out of gas. (laughter) >> And how are you working with Dell Technologies and their companies, Dell EMC, if they were to do that? >> The partnership with Dell Technologies, VMware, are really center to how we go to market. DXE is one of the top few partners largest in the ecosystem. The breadth of our portfolios are extremely complementary, whether it's things like device as a service or multi- and hybrid cloud, or pivotal and devops. So the breadth of the portfolios max up really well which makes it the impact potential for our clients even more important. Dell Technology broadly is really one of the few partners that we're shoulder-to-shoulder going with to the market as well. >> Awesome. Great stuff. What's the biggest learnings you guys can share with the audience that you gathered over your multiple engagements holistically across your client base? That's learnings, that could be a best practice, or just either some scar tissue or revelations or epiphanies. Share some experience here. >> I think one of the big learnings we're seeing is the shift now to very much business outcome driven decision making. If you go back to your point about the big ITO outsourcing days, that was all about just strictly driving cost out, and that's why you got to that point where everybody was left hating each other. Now it's about business outcomes. You've got the impact of Millennials, you've got organizations wanting to create a new and better experience for the employees and they're coming to us to say, "How do we accomplish that?" We've got an organization we're working with right now, they're trying to elevate themselves to be one of the top 50 best places to work for in the US. How do they arrive at that? For them, that's their barometer and so it's not about driving costs out, it's really achieving that overall experience and enhance a business outcome. >> So they're betting on productivity gains from morale and happy workers. >> Right. And also they're recognizing the downstream impact on their customers, productivity, the level of employee engagement, right? I mean those are the things that the organization knows that if they hit on those, I mean the sky's the limit. >> Right. Anything on your end? Learnings? >> Yeah, I would say the "don't understand the talent" challenge. The ability to pivot from here's the way we all know and are familiar with doing things to the new way. There will be a big talent challenge. The other thing is the operating model from an IT standpoint. Traditional IT operating model operates at a particular speed, cloud operates at a different speed. And the tools, the talents, the skills that go with that are just completely different. And then I think the last thing is just it seems maybe surprising, but compliance at scale and at speed. So security and regulatory compliance, we see that falling over all the time. >> Great practice you guys. I've been following you guys for many years, you've got a great organization, lots of smart people there we've interviewed many times. My final question is a tech question: what technologies do you guys like that you think is ready for prime time or almost ready for prime time worth having customer keep focusing on and which one's a little more over hyped and out of reach at the moment? >> I'll take a stab at that. If you look at today's Wall Street Journal, Deloitte talks to I believe the figure they quoted was roughly 25% of organizations are doing AI in some form already, PoC or at least are committing to it in terms of strategy. We're seeing that inside DXE as well. AI is now being incorporated into our workplace offerings. The potential for that is enormous, it's real. The technology in the last couple of years, particularly with cloud computing, has really enabled it. When you look at platforms like Watson, these are capabilities that just weren't there 10, 12, 15 years ago, and now the impact that it can have on the workplace, help lines, chats, chatbots, and so forth, is enormous and it's real. Five, 10 years ago it definitely was not in it's maturity. >> Okay, over hyped. >> What's over hyped? I don't know, what comes to mind for you? >> Or maybe I'll rephrase it differently: not yet ready for prime time, but looks good on the fairway but not yet known. . . >> I think for me through workplace, IoT has still got a ways to go. AI and analytics is definitely there. IoT I would say is a little bit behind. I'm sure that Kevin has cloud and platform thoughts. >> Yeah, I would say from an over hyped standpoint, we've seen a lot of companies, large enterprises, legacy application portfolios think they're going to refactor all their applications and cloud native everything. So it feels that people are now kind of getting past that point, but we still see that idea a lot. I think the opportunity that is really in front of us, and you kind of called out, containers. Legacy applications into cloud feel like a remaining frontier for the large enterprise. We think containers and the idea of autonomous, continue optimization, financial performance, is a way to make apps run in cloud financially and performance wise in a way that we don't see a lot of companies fully solving for that yet. >> Awesome. >> A lot of work to do, a lot of opportunity. Kevin, Graham, thank you so much for sharing some of your time and thoughts and insights with John and me on theCUBE this afternoon. >> Very good. >> Thank you. >> We appreciate it. For John Furrier, I'm Lisa Martin, and you've been watching theCUBE live from Vegas. Day One of our coverage of Dell Technologies World is now in the books. Thanks for watching. (upbeat techno music)

>> Live from Las Vegas. It's theCUBE. Covering VMworld 2018. Brought to you by VMware and its ecosystem partners. >> Welcome to theCUBE. We are live at VMworld 2018. Day one, VMware's 20th anniversary. I am Lisa Martin, very excited to be joined by Dave Vellante. Hey, Dave! >> Hey, Lisa, good to see you again. >> Good to see you, too. We are welcoming back to theCUBE, an alumni, Geoff Waters, the VP of Global Cloud Sales for Vmware, hi, Geoff. >> Hi, great to be here, guys. Last year, we talked about the buzz, VMware getting the buzz back. Boy, this is a sonic boom this year. >> Yeah, it's a lot of buzz. >> Superpower infused. And we've also got David Wigglesworth, the Chief Revenue Officer for OVH. David, welcome to theCUBE. >> Thank you very much, both of you, Dave and Lisa. >> So, I have to ask first, do you have the VMware tattoo that Pat Gelsinger sported this morning? >> I don't have VMware, but I do have OVHcloud. Okay, so, speaking of OVH, David give our viewers an overview of what you guys are doing and what momentum you have created with VMware. >> Yeah, you know, it's an exciting time for us, especially to be here, as a Global Diamond sponsor, right? This is our second year, as OVHcloud, to be here. Last year, when we came, it was right after the vCloud Air acquisition of the asset from Vmware. Which is where our partnership just continued to grow more and more. And, so, for the last year, what we've been doing is we've really been focusing on deploying our data centers here, as well as getting our products ready to go to market. I always joke that OVHcloud is, probably, the best-kept secret in the US because that, when we acquired vCloud Air's assets, is when we kind of launched in the US. But, as Geoff can tell you in a few minutes, we've been a partner with VMware for years, right? And it's been really exciting. >> Yeah, I wonder if you could talk about that, Geoff, a little bit, I mean, the signal on vCloud Air early on, you guys kept having to tune the radio station, so to speak. >> Yep. >> Yep. >> And then, boom, finally it hit the OVH acquisition and then AWS deal, of course, IBM and other cloud service providers. Talk about how that all came about, and the track that you're on now. >> Yes, so, I mean, we've been partnering with OVH for actually nine years, I went back and I researched it. >> Did you? >> Yeah, back in Europe. So, they've actually been a seven-time Service Provider of the Year award winner. So, our relationship with OVH is nothing new. And we've been working with them for years. The other thing is the breadth of the portfolio adoption, the full SDDC stack, so not just vSphere, NSX, vSAN, the entire stack. So, you know, OVH is right in the forefront of our overall cloud strategy, and it has been for years. >> Yeah, and as a global infrastructure provider, we have almost a million 500 thousand customers, in 138 different countries. We have 28 data centers, three here in North America. We've got the breadth to go to the market in a big way. So, it's exciting to be here. >> So, lay out the options that you have for OVH customers. What services can they get from you? What are the platforms? >> No, it's a great question. So, obviously, have a very purpose-felt solution built on VMware, right, with our Hybrid Private Cloud. It's all built on the SDDC stack. So vSphere, vSAN, NSX, everything that Geoff mentioned. We also offer a bare metal solution. And then we also have a public cloud offering that's built on our relationship that we have with OpenStack. So, we give our customers three different choices on what they want to go to the market with. >> So, what do you make of, what's the AWS-VMware partnership mean for OVH? How do you guys take advantage of that? >> Well, I mean, you know, look. I think Pat, in his keynote this morning, talked about that eight out of every 10 customers is using cloud today, multi-cloud strategy. The average large customer is using, what did he say, eight clouds? >> Yep. >> He said that they're forecasting that there would be 10 clouds by the end of 2019. I'd like to take one of those two spots, if you don't mind. So, no, we think there's huge opportunity. I mean, Amazon's built a business on, and has created kind of the standard. We think there's plenty of room to play in a very large market. >> Well, the services market has always been highly fragmented. >> Yep. >> And it's always been local in nature. Maybe not as to the degree and scale, but, so, you've got, what did you say, a million and a half customers? >> Globally. >> So what are they telling you about their cloud strategy? >> Well, what our customers are asking for is they're asking for agility. They're looking for low cost. You know, we announced a partner program earlier this morning, where we're launching that. And our partners are coming to us saying, David, give us choice, give us flexibility, and help us save a little bit of money. I mean, all of our partners are dealing with margin erosion, as well as everybody else in the industry. So, if we can come to market and actually help them go acquire a customer, and help them do that in a way that's cost-effective, they're very excited about that. >> So, what's the conversation that you're having with customers? You know, we were, a lot of press, a lot of news came out this morning. A lot of great announcements made by Pat and team on stage. Customers talking about migrating from on-prem to the cloud, from public back to on-premises, for security compliance reasons. What are some of the things that you guys are hearing from customers, when you're having those business-level discussions about being able to execute a successful cloud strategy? >> You want to hit that first, and I'll come over. >> Go ahead. Well, I can. So, what our customers are talking about is simplicity. One of the things that we're excited to work about, to work with VMware on, is that our customers, when they move their solution on-prem to our hybrid cloud, they use the exact same resources that they use on-prem today. They don't have to go hire new people. It's all of the exact same economics that they've built to an on-prem solution, is in their off-prem solution with OVHcloud. That's what makes this so unique, right? I mean, look, part of the vCloud Air acquisition, what are we doing? We're migrating VMware customers, right, that are using VMware technology, that we're setting on vCloud Air into OVH data centers, using VMware technology to do it. And, so, it's. >> Just to add to that, the beauty is reducing day two complexity onto the operations, day two operations. So, instead of customers having to build out all themselves and integrating it, OVH is doing that already. Right out of the gate, in a hosted managed environment. >> That's because it is a like to like homogeneous, and you guys have laid that vision out years ago. >> Yep, yep. >> We sure did. >> When Maritz was running the company. But how does that actually manifest itself? So, a customer says, look, I'm sick of the heavy lifting, I want to get to the cloud. Alright, so they come to you guys, what are the steps that they take to get there? >> Well, there's, you know, the first thing you'll do is you'll sit down with the client. And some clients know exactly what they want to do and how they want to do it. And some customers say, hey, I think I need to be in the cloud, please help me. So we'll have that conversation, right, first of all. Yeah, exactly, it's from A to Z, soup to nuts, whatever you want to say. So, you know, a lot times we'll sit down and we'll walk them through that journey to the cloud. And then, once we determine what applications or workloads we want to move, then we'll back into, okay, well here's the best way to move that, right, and whatever technologies we then decide to do. And if it's vSphere based, it makes it real simple, right? >> And you hit the nail on the head. It starts with the application. It's always about the application. What is the end goal? Right, once you identify that, you start looking at the use cases, a lot of it's app migration, a lot of data center evacuation. A lot of these data centers, as the different leases are coming up, they want to get out of there. Right, and that's the opportunity to then have the discussion. There's also tools that we got. HDX, which allows for bulk migration of workloads and it reduces, you know, the complexity of going to another cloud and another hypervisor from, like, years down to months and weeks. We've had some customers that have done that, migrated hundreds of VMs over a weekend. >> Oh sure. And we're in the process of that right now. >> So, go ahead, please. >> Oh, thank you, I was going to say, could you give us an example of a customer, whether they're in Europe, where you guys have really had a lot success, or here in the Americas, that have really demonstrated substantial business outcomes, revenue, et cetera, leveraging the joint service? >> Well, sure, I mean, you know, we've got customers both in the U.S. and in EMEA, but, you know, I'm thinking about a customer in particular that's based in the U.K.. That, they're a MNA company, right? And, at one time, they had 97 data centers that they were trying to manage. The complexity of that. And, so, they originally went to vCloud Air because they were like, help us with this complexity, we're built on VMware, but we've got to close these data centers, right, we need to go to more of an asset-like model, and we need to be able to manage it effectively with the staff that I have that's already overworked. So that's how we won them as a client with vCloud Air. What's exciting is, is when we come in and we start talking about what we're doing with OVH, and some of the new technology that we're building, on the VMware stack, right, plus the fact that we own our own network. I don't charge ingress and egress charges, right. A lot of the things that we do, We've got 33 points of presence, you know, globally. Then we start having a conversation and they're like, listen I already had a great solution in vCloud Air on VMware, now I've got that on steroids. I've got the benefit of both companies coming together for a solution for my client. >> So how do you get the data from point A to point B? Do you back up the Chevy truck and load it on? >> You can do it that way. >> You talked about your network. What's the kind of best practice? >> Yeah, so the best practice is to come in and understand the actual environment we're working with. What is the tolerance to take that workload up or down? But, if we use technology like HDX, I don't have to take that workload down at all. I'm able to basically, essentially, and don't let me get over my skis, VMware guy, but I am going to essentially do a Vmotion over my network, right, no cost to the customer, into my data center, and the customer can continue to use the app while that's happening. >> And the time that takes is a function of, obviously, the volume of the data, >> Sure, of course. The bandwidth. >> The number of VMs, the complexity of that. >> So you'll schedule that out over a period of, what, days, weeks, months? >> Exactly Years, even, I mean, maybe not years but, maybe I have a multi-year strategy, right? So that's how you're seeing people do it? It's sort of a planned approach. >> Weeks and months is sort of. >> I would say, typically. >> It's project based, yeah. >> So, within months, I can get an entire data center from my on-premises into your platform. Is that a fair statement? >> And if you ever wanted to bring it back, we can do that real easy too. >> You see that happening? >> We see customers moving workloads back and forth, it depends on seasonality. I mean, you take the retail industry, right? There's a lot of times where, during the retail industry, they'll send things to us, they'll flip it around, and, after the holidays are over, they'll bring there on-prem or what have you. >> And, more importantly, I think having network access back into the on-prem data center, with HDX, allows you to have a network connection. So it does need a talk back. The whole workload may not move back, but you need to have communications back into the network. And that's what HDX, their technology, allows. >> Right. >> So it allows me to leave whatever component of my workload I want to keep there. >> Yep, that's right. >> When I'm talking to each other. >> That's right. >> Okay, so for years at VMware, we heard this theme, any app, any workload, really anywhere in the world. >> Exactly. >> Now, you guys, right, you guys have an open source based public cloud. Vmware, obviously, like, hey, some of these cloud native apps, we'd like a piece of that action. You hear Pat talking about Kubernetes and containers. So what's that conversation like, between you guys, I mean you want some of that, right? Are you talking about Edge? Is that more integration? You guys got some work to do there to really compete in the that space? >> Well, I mean, it's your solution. But I'll start off of on the Edge. So, the announcement on Edge today, I don't know if you guys have heard it yet, but really exciting. We've actually announced a lot of different solutions around automation of the data center. I mean, this whole cloud operations is becoming sort of a major problem, as we have eight to 10 global service providers in most enterprises. So, reducing the complexity of that down is incredibly important. All the pieces that we're announcing, a VMware as a service, we're going to roll to our service providers in a managed service environment. So all these new technologies that we just announced, right, David and OVH are going to get access to that and have the same capability. >> That's right. >> I'll let you guys speak, specifically on your OpenStack. >> Well, I mean, listen, the beautiful thing about OpenStack is it's open, right, so, I mean, it doesn't really matter what cloud's out there, we can interface with it, right? So, that's the beauty of it, right? And it doesn't change at all the way that we go to market. It's just, really, we're giving the customers choice. What do you want? And it depends on the app, right? That's what's beautiful about it, is when we've sit down and meet with customers or partners, it's, like, what do you want to do, what workload would you want to move? And we've got choice for you. >> Yeah, I remember when we talked to Pat about this, years ago, when OpenStack was kind of the hot new toy, and he said, OpenStack, we like OpenStack, that's cool, we'll embrace it, no problem, and we're like, really? Yeah, I mean, that's kind of exactly what's happened. I mean, you're seeing the same thing with Kubernetes, and containers, and the like. But, again, you guys still got some work to do to really earn their business for those types of workloads, and I presume you're hard at work. >> We are. I don't know if you wanted to hit on some of the announcements that you. >> Yeah, I'd love to. >> Yeah, let's do that. >> So, the real thing I'm excited about is this morning we announced the announcement of our partner program at OVHcloud. It's an exciting day for us on that because, if you'll remember a few minutes ago, I was talking about all of the things we've been doing for the last year, right, getting our data centers ready, and, also, building out our product stack to be able to go to market, and migrating our customers. Well, the fourth thing we were doing, for the last nine to 12 months, is we've been meeting with partners. And I'm fortunate, from my years at EMC-Vmware, and my team, we have a lot of relationships out there. And so we were able to go meet with these partners and say, listen, here's what we're thinking, what do you guys think, what are you looking for, right? We've got all these big players out there, obviously we know all the names, but what differentiation could we bring to your business to help you go grow revenue? And, you know, they came back to us and they said, Wiggs, what we really want to be able to do is we want to be able to come in slowly, expand that as much as we can, make big commitments, make small commitments, we want the ability to be agile, we want to be able to, help us figure out a way that we can save money and worry about that. Help us resolve that issue of that margin erosion. That's a big thing that a lot of the channel's dealing with today. And, so, that's what we did. We came up with a program of four different levels, right? You can dip your toe in, and with a very minimum commitment, the higher commitment you make, not only do you get a better price, but you also get a ton of support on the backend. So, I actually come in and work with you on your messaging. I have sales teams that can actually go out and help them sell the solution, with us as the infrastructure layer in the underpinning, right, and, so far, it's been really good. >> So these are, don't hate me for saying this, these are sort of traditional box sellers, now trying to transform their business, right, and add more value, or their value added supply. Maybe they're SAP. >> Well, you've got manage service providers. You've got manage service providers. >> Okay, so hosting. >> You've got the SI's and the OS's, right? So, you know, some of these guys they either want a private label, right? Or white label your solution? Some guys just want to go to mark up their solution and they just need an asset like model, right? They're just exhausted with, you know, investing in infrastructure, right? So, they're like, "Listen >> And bodies. >> And body, you take that over and let us worry about that. >> You see, from VMware's perspective, that's exactly what we're seeing. We've got an ecosystem of 42 hundred global service providers. They build their own data centers, have a VMwares based hosted solution of some type. A lot of different flavors. They want to get out of the hardware space and out of the data center management space. This is why it's a great solution for OVH, they want to focus on, and, again, we call this asset light, they want to focus on high margin trusted value. Things that they're good at, where they can make a lot of money. >> Which is what? Like, I always see there's a consulting piece up front, security. >> It could be security specialist. >> Yep, security security services. >> Patching monitor, you know, automation, migration services, I mean, the exact discussion we just talked about, right? Customers need that journey. So OVH abstracts a way, the need to do hardware, and that allows them to go focus on the rich or higher margin services that they offer. >> And how are they making it sticky? Because, obviously, they want that, right? So what do you see there and how are you helping them? >> I think anytime you're adding a value added service, if you add that value it is sticky, right? >> Yeah. >> I mean, for an example, to help our relationship with Vmware, and just how strong it is, you know, FusionStormers was one of the partners that we had announced today, right? And they had a quote in there. And I was just sitting in Pat's keynote, next to our customer. You know, and I'm like, so, you know, I get this, it makes sense, you're looking for this, you know, infrastructure as a service play. He's like, David, what we're trying to do is help our customers that love the VMware stack, we're trying to help them to get to the Cloud, right? They don't care about the infrastructure, all they want is great service, right, and great support. And he said, that's my secret sauce, that I am able to offer that. And he goes, you guys handle the infrastructure. He said, it's perfect. >> Last question, David, for you. What are people going to be able to see and feel and touch at the OVH booth here at VMWorld? >> Oh, that's a great question. So, you're going to be able to go over, and you're going to be able to learn about some of our other announcements, with VMwares. Specifically, around what we're doing on the whole SCDC as a stack, right? In the VMware Cloud foundation, and the announcement we had on that this morning. Or, actually, I think that was Friday. You're actually going to be able to go over and they'll pull up and they'll show you some demos, and be able to see the technology live. I think they have a show every hour, and you go over there. And if you go over, you might win a Yeti mug. I think they're giving a Yeti mug to whoever pays the most attention. (Lisa and Dave ooh) So, go over there and learn about that. >> Can always use another Yeti, yeah, I love the Yeti. >> Yeah >> You can't have too many Yeti's. >> Does it come with caffeine? Because that, I'm all over it. >> No, well, we'll leave it clean, yes, maybe caffeine. >> Okay, awesome. David, Geoff, thanks so much for joining Dave and me this morning. >> Thank you so much, we really enjoyed it. >> You're watching theCUBE, live from VMWorld 2018. Day one, Lisa Martin for Dave Vellante, stick around, we'll be right back. (electronic music)

>> From Orlando, Florida, it's theCUBE. Covering SAP Sapphire Now 2018, brought to you by NetApp. >> Welcome back to theCUBE, I am Lisa Martin, with Keith Townsend. We have been here all day at SAP Sapphire 2018. Keith, this venue in Orlando is so huge. It's the equivalent of 16 American football fields. >> Yeah, probably should not have worn a pair of new shoes. >> No, but you did close your rings, so it's a trade-off, right? >> It's a trade-off, yeah. >> So, the keynote this morning started out with a bang. Bill McDermott, the CEO of SAP, is probably the most energetic, evangelical, C-level I've ever seen on stage. You really could feel the excitement, the momentum. They also followed that with some great announcements. You know, they've been saying for awhile, being pretty bullish about wanting to not just disrupt the Sierra market, but wanting to become one of the world's most valuable brands. They wanna be up there with the Apples, and the Googles, and Coca-Cola and Mercedes-Benz, who all have products that we all see, and touch, and feel, and buy. And they announced that the brands e-rankings just came out the other day, that they're number 17, up four spots from last year. So, their momentum is, they're really putting their money where their mouth is. >> Yeah, so SAP is the cash register of the world. 70% of the world's transactions go through SAP, but most of us don't see it. So, it's amazing to see that they're ranked number 17 on those brands that are very, you know, if you told somebody you worked for SAP, they'd be like, oh, okay, I think I might have heard of that. >> Right. >> Or, I've heard that that was the reason why manufacturing is down, because the SAP system was down. So, it is a bold statement to say that you're gonna go from that, to a household name. Interestingly enough, part of that is becoming an ecosystem. So, becoming a platform. What we've heard today was a lot of talk about how SAP is transforming from a product company. You know, a point-of-sale system is one thing, but to say that you've built a ecosystem, and a platform around that, is the goal that I think I heard today from the stage floor. >> And you're right, you talk about, you know, them becoming a household name, with a product that's basically invisible to most people who probably use it. They have amassed 390,000 customers in 46 years. They've been around for a long time. This event, though, is massive. The partner area alone is huge. There's probably more than 20,000 people not just that are here, in Orlando, but, he said, Bill McDermott, a million people engaging with SAP Sapphire via the online experience. That's enormous. But to your point, it's all really fundamentally due to the partnerships, the systems integrators, the technology partners and more who have helped them on their transformation. >> Yeah, we had KPIT on, they said the guest has been on 20 Sapphires for 20 years, the event has gone on for 25 years in some form. He remembered, initially, they might have had one or two sessions. They have 12, KPIT has 12 sessions this year at the Sapphire 2018. There's a huge ecosystem of partners, here on the show floor. Over 500, I think, sessions in general. We had the VP of Community for S/4. They have 1,000 how-to videos on how to just do basic things in S/4. Huge community, huge event. SAP is starting to make end rolls and becoming, again, not just a products company, but an ecosystem company, I think. Sapphire in Orlando is a great example of how they're expanding the brand. >> Yes, and in fact, on the brand part, you know, that's one of the things that their CMO, Alicia Tillman, who was on main stage this morning, that's something that I've heard her talk about before. She's been the CMO for about nine months now, and she said, you know, and marketers will know, campaigns and messaging will change every quarter, six months, and that is fine. It's the brand narrative that they really started to work on at SAP. So, you're seeing this "Best-run companies run on SAP", it's sharing the value of what SAP can deliver with their partner ecosystem, in terms of how it's helping customers transform their businesses, transform industries, save lives. They've done a very focused job on showing how this invisible technology is really revolutionizing the world. They're now going, you know, full-force, embedding A.I., and really being quite bold, they're saying. I loved what Bill McDermott had on the slide this morning, of augmented intelligence. And there's always a lot of concern with A.I, right? Jobs being replaced. And he talked about what he, and some of the other world leaders, were talking about. And I liked augmented intelligence, to augment humanity, this connection of humans and machines working together. They're really being quite bold, and focused, in that area. I'm just curious what your take was from an advanced analytics A.I. perspective. >> So, there's a lot of talk around advanced A.I. analytics. At the end of the day, it's about actual business results. We're here in the booth of NetApp, who has done a great job, frankly, of transforming their image from a storage company in the middle of a transformation to being known as a data-driven company. So, NetApp has gone through a similar change that SAP is looking to do, from a brand perspective. Reasonably enough, we had the CIO, Bill, from NetApp, that talked about that transformation, and how data is a key part of their own transformation, internally. And, how SAP could probably hold NetApp up as a great example of a company that's using the predecessor to C/4HANA, which was just announced, on the staged hypers of taking data, analyzing that data, applying A.I, machine learning, more like machine learning in reality. Machine learning to that data, and then getting insights, so that humans can make better decisions. >> Right. You know, on that front, one of the themes I heard today, Keith, from not just Bill Miller, the CIO of NetApp, who was on here with us earlier, but some of their other partners, NetApp and SAP's partners, all talk about their own transformations, internally, as essential for them to become intelligent enterprises, which is a lot of what SAP's talking about. But I also thought that was quite valuable, from an external perspective, to hear NetApp talk so candidly about their transformation, and share that with their customers who are in similar positions. I think, when vendors will, say, drink their own champagne, and there's real proof there in the pudding. I think that's tremendously valuable for these brands. And we've just heard that kind of consistently throughout the day today, of companies that are showing how they're transforming to then help their customers also transform. >> So, one of the things that we like to ask on theCUBE is not just about current customer base, but, what new customers are you attracting? So, one of the interesting conversations is one of the last ones we had with WorkSpan, and how they're a small company, and they started out the gate with SAP, and how the brand has gone beyond this, oh, this is a manufacturing, supply chain, you must be a Fortune 500 company to even consider rolling it out to. You know what? We're a brand new company, providing a data-driven product, and out of the gate, we're selecting a S/4HANA and the platform to create this new product that's consumed by not necessarily technologists, that powers an alliance platform to find and curate business alliances. I thought that was an extremely interesting interview that shows the power of expanding beyond just a focus on traditional enterprise, but the power of data. And once you've become a platform, how you can power your partner ecosystem. >> I thought that was a great example, as well, of a company that's only been in business for three years, less than four years. How they saw this gap in the market, where they said, you know, we're surrounded by alliance partners of SAP's in this 16 football fields location that we're in. And WorkSpan found that 60 to 75% of announced alliances fail. Huge opportunity for them to then get in from a systematic perspective and align, you know, two companies' marketing automation systems, for example, and sales automation systems. And they really saw this big opportunity to, like you were saying, create an entirely new product, and probably create a new market as a result. I thought that was a really modern example of an idea that saw a huge gap, and can be transformative. I asked Ahmed, after we stopped rolling the cameras, all right, so you found 60 to 75% of these announced alliances fail, typically. What does WorkSpan think you can do to bring that number down? And he said, within two years, we wanna get that down to about 30%. >> Wow. That is an amazing stat. So, let's look at the companies that are digitally transforming. So we had two guests that I want to highlight, one with Mike McGivney from SAP SuccessFactors, which is SAP's people-focused cloud, and then Wolfgang Hopfes, the head of SAP Business for EMEA. And they're on a unique challenge. SAP has been around for 46 years, and in IT years, that's like, you know, 1,000. So, there's a lot of technical debt, that companies are now paying for. You know, back in the nineties, early 2000s, customizing SAP was all the rage. Now, customers are faced with, they have to digitally transform their organizations, how do they do so? Well, it's not so easy to move from a customized SAP to S/4. Bill trumpeted the numbers of 1,800 SAP HANA customers, which is great, well over a billion dollars in sales for an in-memory database. However, SAP has over 300,000 customers. So there's a lot of opportunity, but a lot of challenge. So, the ecosystem of partners, Fujitsu, NetApp, other infrastructure companies looking to help simplify the infrastructure so that technologists within these customer organizations can focus on the higher stack of those larger business challenges of basically pulling apart what they've built. Bill from NetApp shared how difficult their transformation was from their CRM to >> Hypers? >> Hypers. He called it painful, a painful six months. And what we saw today, I think, was a reality check. A lot of enterprises have a lot of pain ahead of them. >> Well, it's pain in a number of areas, and one of them is cultural. And I really thought, you know, you say, SAP being 46 years old is like, 1,000 in IT, or dog years. They're like the Gandalf of IT, right? But one of the things that I found quite remarkable is 46 year-old history, 390,000 customers. But clearly, they have been able to evolve their culture to be able to support what their customers need, and go from just being a supply chain procurement-focused type of business. And I thought that was really quite compelling, to see how they must have had to transform their culture, so that they can help businesses transform. They make it look easy, with the messaging and the momentum, but that was something that for a company that's an incumbent like that, is a bit of, you might say, even a model for how to do that right. >> Yeah, we talked to Joe Lazar, he's the SAP VP of Global Technology Partners. He talked about how SAP likes to be pushed to be a little uncomfortable by their partners, and we asked him the tough questions. You know, there's been tweets and there's been announcements from all the ACI vendors. I've talked to customer after customer that says, you know what, S/4HANA on HCI is what we want. A very quotable comment that he made was, we're not doing S/4 on HANA because we want to, we're doing S/4 on HANA because customers demand it. So, SAP is definitely listening to customer demand, S/4 on HANA is one of those things. You know, he tried to stay away from the bad word of certified on 4HANA, and validated, and focused on solutions, but SAP has a little ways to go. And that's kind of a, you talk to any HCI customer, validated and certified 4HANA is a bad word today, but SAP understands it and they're moving to certify the platform for HCI, so I thought that was a great example of them listening to customers and continuing to transform over the years. >> You're absolutely right. In fact, you know, if you look up digital transformation, one of the first pillars that you're gonna see is you gotta become customer-centric. And we really heard that a lot today. Even NetApp, when you were talking with Bill Miller about ONTAP in the cloud, going it's okay guys, maybe we have to listen to our customers. If we don't we won't be in business. That's a hallmark of an enterprise that is digitally transforming. >> Yeah, I'd argue that Dave Hitts was the one who forced that, that kind of cultural change. You had to bring in the founder to talk to the engineers and that had very engineer-driven thinking And I think Dave was very direct, like you know, we have to make the change or we won't be in business. The pendulum has changed to cloud. The SAP, which is not by any stretch of the mind, was never designed to run in the cloud, but they're adopting the technology for what customers are demanding. There's an AWS booth here, Fujitsu was the first one to say that, you know what, if customers need fail-fast environments, that's exactly where they should go, and put S/4 implementations, and then steady states should be moved to RMPRAM or private dating center or hosted solutions. So, the ecosystem seems to be embracing this change. >> Definitely. Anything that you're particularly looking forward to tomorrow for Day 2? >> You know what? I love talking to customers, so I'm looking forward to more customer conversations, talking about how is this being used? We haven't really talked a lot about Leonardo much. So, you know, IoT, A.I., how are these things that get a lot of press being perceived by actual customers? How are they being implemented? What's their true adoption rate? >> Awesome. Well, I look forward to hosting with you tomorrow, Keith. Thanks so much. >> I appreciate it. >> Thanks for watching. Keith and I have been at SAP Sapphire, bringing you some hopefully great informative content. From the NetApp booth, Lisa Martin for Keith Townsend. Thanks for watching.