>>Now welcome back to the Cube as we continue our coverage here. AWS Reinvent 2022, going out here at the Venetian in Las Vegas. Tens of thousands of attendees. That exhibit Hall is full. Let me tell you, it's been something else. Well, here in the executive summit, sponsored by Accenture. Accenture rather. We're gonna talk about Baptist Health, what's going on with that organization down in South Florida with me. To do that, I have Tony Abro, who's the SVP and Chief Digital and Information Officer. I have Ashley Lane, the managing director of the Accenture Healthcare Practice, and on the far end Poop Kumar, who is the VP and cto Baptist Health Florida won and all. Welcome. Thank you. First off, let's just talk about Baptist Health, the size of your footprint. One and a half million patient visits a year, not a small number. >>That was probably last year's number, but okay. >>Right. But not a small number about your footprint and, and what, I guess the client base basically that you guys are serving in it. >>Absolutely. So we are the largest organization in South Florida system provider and the 11 hospitals soon to be 12, as you said, it's probably about 1.8 million by now. People were, were, were supporting a lot of other units and you know, we're focusing on the four southern counties of South Florida. Okay. >>So got day Broward. Broward, yep. Down that way. Got it. So now let's get to your migration or your cloud transformation. As we're talking about a lot this week, what's been your, I guess, overarching goal, you know, as you worked with Accenture and, and developed a game plan going forward, you know, what was on the front end of that? What was the motivation to say this is the direction we're going to go and this is how we're gonna get there? >>Perfect. So Baptist started a digital transformation initiative before I came about three years ago. The board, the executive steering committee, decided that this is gonna be very important for us to support us, to help our patients and, and consumers. So I was brought in for that digital transformation. And by the way, digital transformation is kind of an umbrella. It's really business transformation with technology, digital technologies. So that's, that's basically where we started in terms of consumer focused and, and, and patient focus. And digital is a big word that really encompasses a lot of things. Cloud is one of, of course. And, you know, AI and ML and all the things that we are here for this, this event, you know, and, and we've started that journey about two years ago. And obviously cloud is very important. AWS is our main cloud provider and clearly in AWS or any club providers is not just the infrastructure they're providing, it's the whole ecosystem that provides us back value into, into our transformation. And then somebody, I think Adam this morning at the keynote said, this is a team sport. So with this big transformation, we need all the help and that we can get to mines and, and, and hands. And that's where Accenture has been invaluable over the last two years. >>Yeah, so as a team sport then depu, you, you've got external stakeholders, otherwise we talked about patience, right? Internal, right. You've, you've got a whole different set of constituents there, basically, but it takes that team, right? You all have to work together. What kind of conversations or what kind of actions, I guess have you had with different departments and what different of sectors of, of the healthcare business as Baptist Health sees it in order to bring them along too, because this is, you know, kind of a shocking turn for them too, right? And how they're gonna be doing business >>Mostly from an end user perspective. This is something that they don't care much about where the infrastructure is hosted or how the services are provided from that perspective. As long as the capabilities function in a better way, they are seemingly not worried about where the hosting is. So what we focus on is in terms of how it's going to be a better experience for, from them, from, from their perspective, right? How is it going to be better responsiveness, availability, or stability overall? So that's been the mode of communication from that perspective. Other than that, from a, from a hosting and service perspective, the clientele doesn't care as much as the infrastructure or the security or the, the technology and digital teams themselves. >>But you know, some of us are resistant to change, right? We're, we're just, we are old dogs. We don't like new tricks and, and change can be a little daunting sometimes. So even though it is about my ease of use and my efficiency and why I can then save my time on so and so forth, if I'm used to doing something a certain way, and that's worked fine for me and here comes Tony and Depo and here comes a, >>They're troublemaker >>And they're stir my pot. Yeah. So, so how do you, the work, you were giving advice maybe to somebody watching this and say, okay, you've got internal, I wouldn't say battles, but discussions to be held. How did you navigate through that? >>Yeah, no, absolutely. And Baptist has been a very well run system, very successful for 60 something odd years. Clearly that conversation did come, why should we change? But you always start with, this is what we think is gonna happen in the future. These are the changes that very likely will happen in the future. One is the consumer expectations are the consumer expectations in terms of their ability to have access to information, get access to care, being control of the process and their, their health and well-being. Everything else that happens in the market. And so you start with the, with that, and that's where clearly there are, there are a lot of signs that point to quite a lot of change in the ecosystem. And therefore, from there, the conversation is how do we now meet that challenge, so to speak, that we all face in, in, in healthcare. >>And then from there, you kind of designed the, a vision of where we want to be in terms of that digital transformation and how do we get there. And then once that is well explained and evangelized, and that's part of our jobs with the help of our colleagues who have, have been doing this with others, then is the, what I call a tell end show. We're gonna say, okay, in this, in this road, we're gonna start with this. It's a small thing and we're gonna show you how it works in terms of, in terms of the process, right? And then as, as you go along and you deliver some things, people understand more, they're on board more and they're ready for for more. So it's iterative from small to larger. >>The proof is always in the place, right? If you can show somebody, so actually I, I obviously we know about Accenture's role, but in terms of almost, almost what Tony was just saying, that you have to show people that it works. How, how do you interface with a client? And when you're talking about these new approaches and you're suggesting changes and, and making these maybe rather dramatic proposals, you know, to how they do things internally, from Accenture's perspective, how do you make it happen? How, how do you bring the client along in this case, batches >>Down? Well, in this case, with Tony and Depu, I mean, they have been on this journey already at another client, right? So they came to Baptist where they had done a similar journey previously. And so it wasn't really about convincing >>Also with Accenture's >>Health, also with Accenture's Health, correct. But it wasn't about telling Tony Dupe, how do we do this? Or anything like that. Cuz they were by far the experts and have, you know, the experience behind it. Well, it's really like, how do we make sure that we're providing the right, right team, the right skills to match, you know, what they wanted to do and their aspirations. So we had brought the, the healthcare knowledge along with the AWS knowledge and the architects and you know, we said that we gotta, you know, let's look at the roadmap and let's make sure that we have the right team and moving at the right pace and, you know, testing everything out and working with all the different vendors in the provider world specifically, there's a lot of different vendors and applications that are, you know, that are provided to them. It's not a lot of custom activity, you know, applications or anything like that. So it was a lot of, you know, working with other third party that we really had to align with them and with Baptist to make sure that, you know, we were moving together at speed. >>Yeah, we've heard about transformation quite a bit. Tony, you brought it up a little bit ago, depu, just, if you had to define transformation in this case, I mean, how big of a, of a, of a change is that? I mean, how, how would you describe it when you say we're gonna transform our, you know, our healthcare business? I mean, I think there are a lot of things that come to my mind, but, but how do you define it and, and when you're, when you're talking to the folks with whom you've got to bring along on this journey? >>So there's the transformation umbrella and compos two or three things. As Tony said, there is this big digital transformation that everybody's talking about. Then there is this technology transformation that powers the digital transformation and business transformation. That's the outcome of the digital transformation. So I think we, we started focusing on all three areas to get the right digital experience for the consumers. We have to transform the way we operate healthcare in its current state or, or in the existing state. It's a lot of manual processes, a lot of antiquated processes, so to speak. So we had to go and reassess some of that and work with the respective business stakeholders to streamline those because in, it's not about putting a digital solution out there with the anti cured processes because the outcome is not what you expect when you do that. So from that perspective, it has been a heavy lifting in terms of how we transform the operations or the processes that facilitates some of the outcomes. >>How do you know it's working >>Well? So I I, to add to what Deep was saying is I think we are fortunate and that, you know, there are a lot of folks inside Baptist who have been wanting this and they're instrumental to this. So this is not a two man plus, you know, show is really a, you know, a, a team sport. Again, that same. So in, in that, that in terms of how do we know it works well when, when we define what we want to do, there is some level of precision along the way. In those iterations, what is it that we want to do next, right? So whatever we introduce, let's say a, a proper fluid check in for a patient into a, for an appointment, we measure that and then we measure the next one, and then we kind of zoom out and we look at the, the journey and say, is this better? >>Is this better for the consumer? Do they like it better? We measure that and it's better for the operations in terms of, but this is the interesting thing is it's always a balance of how much you can change. We want to improve the consumer experience, but as deeply said, there's lot to be changed in, in the operations, how much you do at the same time. And that's where we have to do the prioritization. But you know, the, the interesting thing is that a lot of times, especially on the self servicing for consumers, there are a lot of benefits for the operations as well. And that's, that's where we're in, we're in it together and we measure. Yeah, >>Don't gimme too much control though. I don't, I'm gonna leave the hard lifting for you. >>Absolutely, absolutely right. Thank you. >>So, and, and just real quick, Ashley, maybe you can shine some light on this, about the relationship, about, about next steps, about, you know, you, you're on this, this path and things are going well and, and you've got expansion plans, you want, you know, bring in other services, other systems. Where do you want to take 'em in the big picture in terms of capabilities? >>Well, I, I mean, they've been doing a fantastic job just being one of the first to actually say, Hey, we're gonna go and make an investment in the cloud and digital transformation. And so it's really looking at like, what are the next problems that we need to solve, whether it's patient care diagnosis or how we're doing research or, you know, the next kind of realm of, of how we're gonna use data and to improve patient care. So I think it's, you know, we're getting the foundation, the basics and everything kind of laid out right now. And then it's really, it's like what's the next thing and how can we really improve the patient care and the access that they have. >>Well, it sure sounds like you have a winning accommodation, so I I keep the team together. >>Absolutely. >>Teamwork makes the dream >>Work. Absolutely. It is, as you know. So there's a certain amount of, if you look at the healthcare industry as a whole, and not, not just Baptist, Baptist is, you know, fourth for thinking, but entire industry, there's a lot of catching up to do compared to whatever else is doing, whatever else the consumers are expecting of, of an entity, right? But then once we catch up, there's a lot of other things that we were gonna have to move on, innovate for, for problems that we maybe we don't know we have will have right now. So plenty of work to do. Right. >>Which is job security for everybody, right? >>Yes. >>Listen, thanks for sharing the story. Yeah, yeah. Continued success. I wish you that and I appreciate the time and expertise here today. Thank you. Thanks for being with us. Thank you. Thank you. We'll be back with more. You're watching the Cube here. It's the Executive Summit sponsored by Accenture. And the cube, as I love to remind you, is the leader in tech coverage.

>>Hey everyone, and welcome back to The Cube's live coverage of AWS Reinvented 2022 Live from the Venetian Expo in Las Vegas. We're happy to be back. This is first full day of coverage over here last night. We've got three full days of coverage in addition to last night, and there's about 50,000 people here. This event is ready, people are ready to be back, which is so exciting. Lisa Martin here with Paul Gill and Paul, it's great to be back in person. Great to be hosting with you >>And likewise with you, Lisa. I think the first time we hosted again, >>It is our first time exactly. >>And we come here to the biggest event that the cube ever does during the year. >>It's the Super Bowl of the >>Cube. It's it's elbow to elbow out there. It's, it's, it's full tackle football, totally on the, on the floor of reinvent. And very exciting. This, you know, I've been to a lot of conferences going back 40 years, long as I can remember. Been going to tech conferences. This one, the, the intensity, the excitement around this is really unusual. People are jazzed, they're excited to be here, and that's great to see, particularly coming back from two years of isolation. >>Absolutely. The energy is so palpable. Even yesterday, evening, afternoon when I was walking in, you just feel it with all the people here. You know, we talk to so many different companies on the Q Paul. Every company these days has to be a data company. The most important thing about data is making sure that it's backed up and it's protected, that it's secure, that it can be recovered if anything happens. So we're gonna be having a great conversation next about data resiliency with one of our alumni. >>And that would be Rick Scott, Rick, excuse me, Rick Scott, >>Rick Clark. Rick Clark, say Rick Scott, cloud sales Veritas. Rick, welcome back >>To the program. Thank you. Thank you so much. It's a pleasure being here, you know, thank you so much. You're definitely very excited to myself and 40,000 of my closest cousins and friends all in one place. Yep. Or I could possibly go wrong, right? So >>Yeah, absolutely nothing. So, Rick, so Veritas has made some exciting announcements. Talk to us about some of the new things that you've >>Unveiled. Yeah, we've been, we've been incredibly busy and, you know, the journey that we've been on, one of the big announcement that we made about three or four weeks ago is the introduction, really, of a brand new cloud native data management platform that we call Veritas Alta. And this is a journey that we've been on for the better part of seven years. We actually started it with our, our flex appliances. We continued, that was a containerization of our traditional net backup business in, into a highly secured appliance that was loved by our customers. And we continued that theme and that investment into what we call a scale out and scale up form factor appliance as well, what we called flex scale. And then we continued on that investment theme, basically spending over a billion dollars over that seven year journey in our cloud native. And we call that basically the Veritas altar platform with our cloud native platform. And I think if you really look at what that is, it truly is a data management platform. And I emphasize the term cloud native. And so our traditional technologies around data protection, obviously application resiliency and digital compliance or data compliance and governance. We are the only, the first and only company in the world to provide really a cloud optimized, cloud native platform, really, that addresses that. So it's been fun, it's been a fun journey. >>Talk a little bit about the customer experience. I see over 85% of the Fortune 100 trust Veritas with their data management. That's >>A big number. Yeah. Yeah. It's, it is incredible actually. And it really comes back to the Veritas older platform. We sort of built that with, with four tenants in mind, all driving back to this very similar to AWS's customer obsession. Everything we do each and every day of our waiting moments is a Veritas employee is really surrounds the customer. So it starts with the customer experience on how do they find us to, how do they procure our solutions through things like AWS marketplace and how do they deploy it? And the second thing is around really cost optimization, as we know, you know, to, to say that companies are going through a digital transformation and moving workloads to the cloud. I mean, I've got customers that literally were 20% in cloud a year ago and 80% a year later, we've never seen that kind of velocity. >>And so we've doubled down on this notion of cost optimization. You can only do that with these huge investments that I talked about. And so we're a very profitable company. We've been around, got a great heritage of over 30 years, and we've really taken those investments in r and d to provide that sort of cloud native technology to ultimately make it elastic. And so everything from will spin up and spin down services to optimize the cloud bill for our customers, but we'll also provide the greatest workload support. You know, obviously on-prem workloads are very different from cloud workloads and it's almost like turning the clock back 20 years to see all of those new systems. There's no standard API like s and MP on the network. And so we have to talk to every single PAs service, every single DB PAs, and we capture that information and protect it. So it's really has been a phenomenal journey. It's been great. >>You said this, that that al represents a shift from clouds from flex scale to cloud native. What is the difference there? >>The, the main difference really is we took, you know, obviously our traditional product that you've known for many media years, net backup. It's got, you know, tens of millions of lines of code in that. And we knew if we lifted and shifted it up into the cloud, into an I AEs infrastructure, it's just not, it obviously would perform extremely well, but it wasn't cost optimized for our customer. It was too expensive to to run. And so what we did is we rewrote with microservices and containerization, Kubernetes huge parts of that particular product to really optimize it for the cloud. And not only have we done it for that technology, what we now call alter data protection, but we've done it across our entire port portfolio. That was really the main change that we made as part of this particular transition. And >>What have you done to prepare customers for that shift? Is this gonna be a, a drop in simple upgrade for them? >>Absolutely. Yeah. In fact, one of the things that we introduced is we, we invest still very heavily with regards to our OnPrem solutions. We're certainly not abandoning, we're still innovating. There's a lot of data still OnPrem that needs to move to the cloud. And so we have a unique advantage of all of the different workload supports that we provide OnPrem. We continue that expansion into the cloud. So we, we create it as part of the Veritas AL Vision, a technology, we call it AL view. So it's a single painter glass across both OnPrem and cloud for our customers. And so now they can actually see all of their data protection, all our application availability, single collect, all through that single unified interface, which is really game changing in the industry for us. >>It's game changing for customers too, because customers have what generally six to seven different backup technologies in their environment that they're having to individually manage and provision. So the, the workforce productivity improvements I can imagine are, are huge with Veritas. >>Yeah. You you nailed it, right? You must have seen my script, but Absolutely. I mean, I look at the analogy of, you think about the airlines, what's one of the first things airlines do with efficiency? South Southwest Airlines was the best example, a standardized on the 7 37, right? And so all of their pilots, all of their mechanics, all know how to operate the 7 37. So we are doing the same thing with enterprise data protection. So whether you're OnPrem at the edge or in the cloud or even multi-cloud, we can provide that single painter glass. We've done it for our customers for 30 plus years. We'll continue to do it for another 30 something years. And so it's really the first time with Veritas altar that, that we're, we're coming out with something that we've invested for so long and put, put such a huge investment on that can create those changes and that compelling solution for our customers. So as you can see, we're pretty pumped and excited about it. >>Yes, I can >>Use the term data management to describe Alta, and I want to ask about that term because I hear it a lot these days. Data management used to be database, now data management is being applied to all kinds of different functions across the spectrum. How do you define data management in Veritas >>Perspective? Yeah, there's a, we, we see it as really three main pillars across the environment. So one is protection, and we'll talk a little bit about this notion of ransomware is probably the number one use case. So the ability to take the most complex and the biggest, most vast applications. SAP is an example with hundreds of different moving parts to it and being able to protect that. The second is application resiliency. If, if you look at the cloud, there's this notion of, of responsibility, shared responsibility in the cloud. You've heard it, right? Yep. Every single one of the cloud service providers, certainly AWS has up on their website, this is what we protect, here's the demarcation line, the line in the sand, and you, the customer are responsible for that other level. And so we've had a technology, you previously knew it as InfoScale, we now call it alter application resiliency. >>And it can provide availability zone to availability zone, real time replication, high availability of your mission critical applications, right? So not only do we do the traditional backups, but we can also provide application resiliency for mission critical. And then the third thing really from a data management standpoint is all around governance and compliance. You know, ac a lot of our customers need to keep data for five, 10 years or forever. They're audited. There's regulations and different geographies around the world. And, and those regulations require them to be able to really take control of their cloud, take control of their data. And so we have a whole portfolio of solutions under that data compliance, data government. So back to your, your question Paul, it's really the integration and the intersection of those three main pillars. We're not a one trick pony. We've been at this for a long time, and they're not just new products that we invented a couple of months ago and brought to market. They're tried and tested with eight 80,000 customers and the most complex early solutions on the planet that we've been supporting. >>I gotta ask you, you know, we talked about those three pillars and you talked about the shared responsibility model. And think of that where you mentioned aws, Salesforce, Microsoft 365, Google workspace, whatnot. Are you finding that most customers aren't aware of that and haven't been protecting those workloads and then come to you and saying, Hey guys, guess what, this is what this is what they're responsible for. The data is >>You Yeah, I, it's, it's our probably biggest challenge is, is one of awareness, you know, with the cloud, I mean, how many times have you spoken to someone? You just put it in the cloud. Your applications, like the cloud providers like aws, they'll protect everything. Nothing will ever go down. And it's kind like if you, unless your house was ever broken into, you're probably not gonna install that burglar alarm or that fire alarm, right? Hopefully that won't be an event that you guys have to suffer through. So yeah, it's definitely, it wasn't till the last year or so the cloud service providers really published jointly as to where is their responsibility, right? So a great example is an attack vector for a lot of corporations is their SAS applications. So, you know, whether it it's your traditional SA applications that is available that's available on the web to their customers as a sas. >>And so it's certainly available to the bad actors. They're gonna, where there's, there's gonna be a point they're gonna try to get in. And so no matter what your resiliency plan is, at the end of the day, you really need to protect it. And protection isn't just, for example, with M 365 having a snapshot or a recycle bin, that's just not good enough. And so we actually have some pretty compelling technology, what we call ALTA SAS protection, which covers the, pretty much the, the gamut of the major SAS technologies to protect those and make it available for our customers. So yeah, certainly it's a big part of it is awareness. Yeah. >>Well, I understand that the shared responsibility model, I, I realize there's a lot of confusion about that still, but in the SaaS world that's somewhat different. The responsibility of the SaaS provider for protecting data is somewhat different. How, how should, what should customers know about that? >>I think, you know, the, the related to that, if, if you look at OnPrem, you know, approximately 35 to 40% of OnPrem enterprise data is protected. It's kind of in a long traditional problem. Everyone's aware of it. You know, I remember going to a presentation from IBM 20 something years ago, and someone held their push hand up in the room about the dis drives and says, you need to back it up. And the IBM sales guy said, no, IBM dis drives never crash. Right? And so fast forward to here we are today, things have changed. So we're going through almost a similar sort of changes and culture in the cloud. 8% of the data in the cloud is protected today, 8%. That's incredible. Meaning >>That there is independent backup devoted >>To that data in some cases, not at all. And something many cases, the customer just assumes that it's in the cloud, therefore it's always available. I never have to worry about protecting it, right? And so that's a big problem that we're obviously trying to, trying to solve. And we do that all under the umbrella of ransomware. That's a huge theme, huge investment that, that Veritas does with regards to providing that resiliency for our >>Customers. Ransomware is scary. It is becoming so prolific. The bad actors have access to technologies. Obviously companies are fighting them, but now ransomware has evolved into, no longer are we gonna get hit, it's when, yeah, it's how often it's what's the damage going to be. So the ability to help customers recover from ransomware, that resiliency is table stakes for businesses in any industry these days. Does that, that one of the primary pain points that your customers are coming to you with? >>It's the number one pain point. Yeah, it's, it's incredible. I mean, there's not a single briefing that our teams are doing customer meetings where that term ransomware doesn't come up as, as their number one use case. Just to give you something, a couple of statistics. There's a ransomware attack attack that happens 11 times a second right around the globe. And this isn't just, you know, minor stuff, right? I've got friends that are, you know, executives of large company that have been hit that have that some, you know, multimillion dollar ransom attack. So our, our play on this is, when you think about it, is data protection is the last line of defense. Yes. And so if they break through, it's not a case, Lisa, as you mentioned, if it's a case of when Yeah. And so it's gonna happen. So one of the most important things is knowing how do you know you have a gold copy, a clean copy, and you can recover at speed in some cases. >>We're talking about tens of thousands of systems to do that at speed. That's in our dna. We've been doing it for many, many years. And we spoke through a lot of the cyber insurance companies on this particular topic as well. And what really came back from that is that they're actually now demanding things like immutable storage, malware detection, air gaping, right? Anomaly detection is sort of core technologies tick the box that they literally won't ensure you unless you have those core components. And so what we've done is we've doubled down on that investment. We use AI in ML technologies, particularly around the anomaly detection. One of the, the, the unique and ne differentiators that Verto provides is a ransomware resiliency scorecard. Imagine the ability to save uran a corporation. We can come in and run our analytics on your environment and kind of give you a grade, right? Wouldn't you prefer that than waiting for the event to take place to see where your vulnerability really is? And so these are some of the advantages that we can actually provide for our customers, really, really >>To help. Just a final quick question. There is a, a common perception, I believe that ransomware is an on premise problem. In fact, it is also a cloud problem. Is that not right? >>Oh, absolutely. I I think that probably the biggest attack vector is in the cloud. If it's, if it's OnPrem, you've certainly got a certain line of defense that's trying to break through. But, you know, you're in the open world there. Obviously with SAS applications in the cloud, it's not a case of if, but when, and it's, and it's gonna continue to get, you know, more and more prevalent within corporations. There's always gonna be those attack factors that they find the, the flash wounds that they can attack to break through. What we are concentrating on is that resiliency, that ability for customers to recover at speed. We've done that with our traditional appliances from our heritage OnPrem. We continue to do that with regard to resiliency at speed with our customers in the cloud, with partners like aws >>For sure. Almost done. Give me your 30 seconds on AWS and Veritas. >>We've had a partnership for the better part of 10 years. It's incredible when you think about aws, where they released the elastic compute back in 2006, right? We've been delivering data protection, a data management solutions for, for the better part of 30 years, right? So, so we're, we're Junos in our space. We're the leader in, in data protection and enterprise data protection. We were on-prem. We, we continue to be in the cloud as AWS was with the cloud service provided. So the synergies are incredible. About 80 to 85% of our, our joint customers are the same. We take core unique superpowers of aws, like AWS outposts and AWS Glacier Instant retrieval, for example, those core technologies and incorporate them into our products as we go to Mark. And so we released a core technology a few months ago, we call it ultra recovery vault. And it's an air gap, a mutable storage, worm storage, right Once, right? You can't change it even when the bad actors try to get in. They're independent from the customer's tenant and aws. So we manage it as a managed backup service for our customers. Got it. And so our customers are using that to really help them with their ransomware. So it's been a tremendous partnership with AWS >>Standing 10 years of accounting. Last question for you, Rick. You got a billboard on the 1 0 1 in Santa Clara, right? By the fancy Verto >>1 0 1? >>Yeah. Right. Well, there's no traffic. What does that billboard say? What's that bumper sticker about? Vertus, >>I think, I think the billboard would say, welcome to the new Veritas. This is not your grandfather's old mobile. We've done a phenomenal job in, in the last, particularly the last three or four years, to really reinvent ourselves in the cloud and the investments that we made are really paying off for our customers today. So I'm excited to be part of this journey and excited to talk to you guys today. >>Love it. Not your grandfather's Veritas. Rick, thank you so much for joining Paula, me on the forgot talking about what you guys are doing, how you're helping customers, really established that cyber of resiliency, which is absolutely critical these days. We appreciate your >>Time. My pleasure. Thank you so much. >>All right, for our guest and Paul Gilland, I'm Lisa Martin, you're watching the Queue, which as you know is the leader in live enterprise and emerging check coverage.

>>We're back at Supercomputing 22 in Dallas, winding down day four of this conference. I'm Paul Gillan, my co-host Dave Nicholson. We are talking, we've been talking super computing all week and you hear a lot about what's going on in the United States, what's going on in China, Japan. What we haven't talked a lot about is what's going on in Europe and did you know that two of the top five supercomputers in the world are actually from European countries? Well, our guest has a lot to do with that. Florian, bearish, I hope I pronounce that correctly. My German is, German is not. My strength is the operations director for price, ais, S B L. And let's start with that. What is price? >>So, hello and thank you for the invitation. I'm Flon and Price is a partnership for Advanced Computing in Europe. It's a non-profit association with the seat in Brussels in Belgium. And we have 24 members. These are representatives from different European countries dealing with high performance computing in at their place. And we, so far, we provided the resources for our European research communities. But this changed in the last year, this oral HPC joint undertaking who put a lot of funding in high performance computing and co-funded five PET scale and three preis scale systems. And two of the preis scale systems. You mentioned already, this is Lumi and Finland and Leonardo in Bologna in Italy were in the place for and three and four at the top 500 at least. >>So why is it important that Europe be in the top list of supercomputer makers? >>I think Europe needs to keep pace with the rest of the world. And simulation science is a key technology for the society. And we saw this very recently with a pandemic, with a covid. We were able to help the research communities to find very quickly vaccines and to understand how the virus spread around the world. And all this knowledge is important to serve the society. Or another example is climate change. Yeah. With these new systems, we will be able to predict more precise the changes in the future. So the more compute power you have, the better the smaller the grid and there is resolution you can choose and the lower the error will be for the future. So these are, I think with these systems, the big or challenges we face can be addressed. This is the climate change, energy, food supply, security. >>Who are your members? Do they come from businesses? Do they come from research, from government? All of the >>Above. Yeah. Our, our members are public organization, universities, research centers, compute sites as a data centers, but But public institutions. Yeah. And we provide this services for free via peer review process with excellence as the most important criteria to the research community for free. >>So 40 years ago when, when the idea of an eu, and maybe I'm getting the dates a little bit wrong, when it was just an idea and the idea of a common currency. Yes. Reducing friction between, between borders to create a trading zone. Yes. There was a lot of focus there. Fast forward to today, would you say that these efforts in supercomputing, would they be possible if there were not an EU super structure? >>No, I would say this would not be possible in this extent. I think when though, but though European initiatives are, are needed and the European Commission is supporting these initiatives very well. And before praise, for instance 2008, there were research centers and data centers operating high performance computing systems, but they were not talking to each other. So it was isolated praise created community of operation sites and it facilitated the exchange between them and also enabled to align investments and to, to get the most out of the available funding. And also at this time, and still today for one single country in Europe, it's very hard to provide all the different architectures needed for all the different kind of research communities and applications. If you want to, to offer always the latest technologies, though this is really hardly possible. So with this joint action and opening the resources for other research groups from other countries, you, we, we were able to, yeah, get access to the latest technology for different communities at any given time though. And >>So, so the fact that the two systems that you mentioned are physically located in Finland and in Italy, if you were to walk into one of those facilities and meet the people that are there, they're not just fins in Finland and Italians in Italy. Yeah. This is, this is very much a European effort. So this, this is true. So, so in this, in that sense, the geography is sort of abstracted. Yeah. And the issues of sovereignty that make might take place in in the private sector don't exist or are there, are there issues with, can any, what are the requirements for a researcher to have access to a system in Finland versus a system in Italy? If you've got a EU passport, Hmm. Are you good to go? >>I think you are good to go though. But EU passport, it's now it becomes complicated and political. It's, it's very much, if we talk about the recent systems, well first, let me start a praise. Praise was inclusive and there was no any constraints as even we had users from US, Australia, we wanted just to support excellence in science. And we did not look at the nationality of the organization, of the PI and and so on. There were quotas, but these quotas were very generously interpreted. So, and if so, now with our HPC joint undertaking, it's a question from what European funds, these systems were procured and if a country or being country are associated to this funding, the researchers also have access to these systems. And this addresses basically UK and and Switzerland, which are not in the European Union, but they were as created to the Horizon 2020 research framework. And though they could can access the systems now available, Lumi and Leono and the Petascale system as well. How this will develop in the future, I don't know. It depends to which research framework they will be associated or not. >>What are the outputs of your work at price? Are they reference designs? Is it actual semiconductor hardware? Is it the research? What do you produce? >>So the, the application we run or the simulation we run cover all different scientific domains. So it's, it's science, it's, but also we have industrial let projects with more application oriented targets. Aerodynamics for instance, for cars or planes or something like this. But also fundamental science like the physical elementary physics particles for instance or climate change, biology, drug design, protein costa, all these >>Things. Can businesses be involved in what you do? Can they purchase your, your research? Do they contribute to their, I'm sure, I'm sure there are many technology firms in Europe that would like to be involved. >>So this involving industry though our calls are open and is, if they want to do open r and d, they are invited to submit also proposals. They will be evaluated and if this is qualifying, they will get the access and they can do their jobs and simulations. It's a little bit more tricky if it's in production, if they use these resources for their business and do not publish the results. They are some, well, probably more sites who, who are able to deal with these requests. Some are more dominant than others, but this is on a smaller scale, definitely. Yeah. >>What does the future hold? Are you planning to, are there other countries who will be joining the effort, other institutions? Do you plan to expand your, your scope >>Well, or I think or HPC joint undertaking with 36 member states is quite, covers already even more than Europe. And yeah, clearly if, if there are other states interest interested to join that there is no limitation. Although the focus lies on European area and on union. >>When, when you interact with colleagues from North America, do you, do you feel that there is a sort of European flavor to supercomputing that is different or are we so globally entwined? No. >>So research is not national, it's not European, it's international. This is also clearly very clear and I can, so we have a longstanding collaboration with our US colleagues and also with Chap and South Africa and Canada. And when Covid hit the world, we were able within two weeks to establish regular seminars inviting US and European colleagues to talk to to other, to each other and exchange the results and find new collaboration and to boost the research activities. So, and I have other examples as well. So when we, we already did the joint calls US exceed and in Europe praise and it was a very interesting experience. So we received applications from different communities and we decided that we will review this on our side, on European, with European experts and US did it in US with their experts. And you can guess what the result was at the meeting when we compared our results, it was matching one by one. It was exactly the same. Recite >>That it, it's, it's refreshing to hear a story of global collaboration. Yeah. Where people are getting along and making meaningful progress. >>I have to mention you, I have to to point out, you did not mention China as a country you were collaborating with. Is that by, is that intentional? >>Well, with China, definitely we have less links and collaborations also. It's also existing. There, there was initiative to look at the development of the technologies and the group meet on a regular basis. And there, there also Chinese colleagues involved. It's on a lower level, >>Yes, but is is the con conversations are occurring. We're out of time. Florian be operations director of price, European Super Computing collaborative. Thank you so much for being with us. I'm always impressed when people come on the cube and submit to an interview in a language that is not their first language. Yeah, >>Absolutely. >>Brave to do that. Yeah. Thank you. You're welcome. Thank you. We'll be right back after this break from Supercomputing 22 in Dallas.

>>The Cube presents UI Path Forward five. Brought to you by UI Path. >>Welcome back to The Cube's, continuous coverage with day two of UI Path forward. Five. My name is Dave Ante. I'm here with my co-host Dave Nicholson. And you are watching The Cube. It's all about the robots, the automations, the transformations and beyond. Audi Gana is here. She's group executive at Vodacom and Niva is back. She's senior director of telecommunications industry for UiPath. Ladies, welcome to the Cube. >>I thank you very much. >>So Vodacom a leading telco in in Africa across the continent. Tell us more about the company. >>The company is a traditionally telecommunications company, but our vision 2025 is first to transition from being a telco to a technology company. So you'll find that a lot of the use cases that we've actually started embarking on, combined the combination of telco and FinTech. And we've got a lot of RPA bot also supporting the FinTech platform, which is quite a major step in our strategy. >>So, you know, it's interesting Mark Andreessen's famous comment, Every company's a software company. I like to think every company's a technology company, technology driven. So what does that actually mean for you? Is it like a split brain between FinTech? Cuz it's pretty clear that FinTech is always a highly, you know, technology oriented and telecom. Are they sort of together driving a, a technology business? How does that >>Work? It's, it's a, it's a converge use of the technology to add value to the customer. So what we wanna do is to get to the point where we have converged services where the Telecommunicate, cuz at the end of the day in the African market, you'll find that there's a lot of markets that are unbanked. So you find that a cell phone is a means of communication and a a mobile platform for the users. So it's a natural progression for our company to actually play in both spaces. And I think one of the things I find quite interesting is the levels of trust that a lot of citizens have in our financial platform. In that even some of the governments are paying social grants using the platform. And so it almost becomes, without the phones a lot of people cannot function type of scenario. >>Nevas is your role a global role? >>Yes, it is a global role. >>Okay. So it's interesting cause you're I think based down under, right? I am. Is that true? Okay. Obviously spent some time in, in, in the African continent. How are you, what are you seeing in terms of the, the trends in, in telecommunications that, and are you noticing there's gotta be differences across different regions? You know, a lot of times you hear, oh no, there's really kind of a global world out and I know it is, but telco seems to be one of the industries that has some uniqueness within the different breaches. What are you seeing? >>Look, we are privileged to work with more than 200 telecoms around the world. But clearly from a technology perspective, there are some regions that have embraced technology sooner than the others, particularly when it comes to automation. Now we do have use cases with all of them that we are, you know, the 200 we are working with. But the extent to which they become strategic partners, Varie is, you know, what I find is in, in the US we are doing a lot in the customer experience space with the telecoms in aj it's more back of house. And with telecoms like Vodacom, it's really strategic. You know, automation is being applied practically in every facet of work. And you know, sometimes that could be because the demand is just so great for connectivity, you know, at times there's a skills gap, but it does vary. But what's reassuring is that there is a journey and you know, at this event what I have seen is telecoms wanting to learn from other telecoms. And I must say Artie has been in huge demand. We did about 22 meetings yesterday with others wanting to know, which again is that strategic trend. >>Artie, my understanding is you've been at this for a while, this automation journey for quite some time and p i pass. Interesting. I mean it's a company that's founded in 2005 and kind of did sort of its own thing for a long time and then realized it had lightning in a bottle Yeah. For a mid last decade. But my understanding is you've seen it all. You've seen the, the legacy platforms. And so tell me about your personal journey with automation and then the companies. >>Okay, so there's the automation pre rpa, which was strangely enough, I come from banking, got a finance degree, did automated ations in one of the bigger banks. And somehow I transitioned. And I mean from a history perspective, the one of the previous platforms, which was the biggest one at the time, that's where I got to learn about rpa. And then there's another vendor that we then use in another company. So this is almost my third vendor that I'm experiencing in the RPA space. Having joined RPA space in 2015, apparently I'm kind of a veteran, >>So, So what are you seeing is what's the difference between, I mean let's call UI path, that was sort of a modern focus on simple to deploy. That's really how they get started when I first found them. How do you compare what UiPath has? And there are others, there are other modern platforms to sort of the legacy platforms. What's the >>Difference? I think it's the diversity and the applicability of the technology across multiple industries is something that still amazes me up until today. Because the kind of customers I've been meeting today, I, I would not, I met a guy who owns an ice cream company and I'm like, where would automation come in here? But he's actually quite a big customer of, of UiPath, you know. So I think that's one thing I appreciate. I think the ease of use, it has actually allowed for a lot of people to be part of the digital transformation. I think in the his, in the past technology has been seen as something that was a bit elite and that you needed to have X amount of skills and level of education. Whereas the RPA industry has almost bridged that gap in actually bringing along as many people in the journey in terms of digital transformation. And the fourth industrial revolution is now starting to become more inclusive >>Horizontal across industries. >>Yeah. >>So Vodacom headquartered in South Africa. Okay. But presence throughout the continent. Yes. I imagine that various geographies have various twists and quirks to them and different needs. But as a general premise, the African continent has led the rest of the world in terms of embracing these little mobile devices for the most mission. Critical from a personal perspective things, right? Yeah. So if you, if you're already trusting all of your finances and even interaction with your government from a financial perspective. Yeah. When you say technology platform technology is moving forward, what's more critical from that? Or how do you, how do you, how do you branch off from that? What are some of the other things that you can share with us that you're looking towards in the future that may, that that may trickle over here eventually? >>So I think what one of the things we started playing around with quite well is actually the convergence of machine learning, AI and rpa. You would find that a lot of research will tell you that this is the future of the automation and for us, we are actually living the future in that we have civil use cases that are actually extracting a lot of business value. Where we've realized that RPA in of itself, and this is obviously oversimplifying the technology is almost the unlimited hands on keyboards that you could ever have, right? And then machine learning and AI almost the becomes the unlimited brains. So when you then combine the tool, you almost have this strong technology that can revolutionize how we operate and service our customers. >>Well how do, how does that translate? Can you translate that into a user experience at this point? So I mean, we're talking about people who they, they have a motor license, they don't have a desktop computer at home. Yeah. This is their portal into the world. >>So you find that if you're speaking pure telco, and I'm obviously over simplifying there some nowhere an engineer, right? But I think at, at a very simplified level, there's a lot of legacy technology that is used in the telco space and you'll find that because of that, there's a lot of lack of integration. And you'll find that the reasons why a lot of customers call corners is because there's poor integration in a lot of instances. And it's, it's, it's, it's ad hoc. So it's not as if the system is failed completely. So what we've now done is to try and see how do we use machine learning to pick up on those anomalies on the network, right? And because each time something breaks, right, it's almost a fixed way to fix it and therefore the machine learning picking up there normally almost the hands over to the RPA bot to fix the problem within the network element. But that means is that from a customer experience perspective, instead of you actually realizing there's a problem, we've fixed it before you even know that there's a problem. And therefore, and as you can imagine, it means that you then call the course into less because now you don't have the reason to complain because we've proactively identified the problem and we proactively use RPA then to fix it. So we almost have the almost like a self-healing element in within the, the, the RPA AI space. >>You know, I think of, we don't talk about the data, we haven't talked about the data much this week. I think in many respects this industry is, is data industry. Our automation is all about what you can do with the data. You said unlimited hands, unlimited brains. Cuz to me you have unlimited data and a lot of times you just can't handle it. Yeah. So what's the data angle on all this? >>So firstly, I know a lot of people will say data is the new oil. No, >>Right? So I would never >>Say that. I always though, I think I always ask people if I give you a bucket of brain crude oil, right? What are you gonna do with it? Right? Right. And similar to data, right? So I want to almost equate data to that crude oil element, but if you don't know how to refine it, process it, get it to be reliable, it's very useless in of its natural sense. So I think one of the things we've realized is that leveraging of the analogy of the, the machine learning in the brain, if you are in the sales space, you forever trying to push new sales, right? And then chances are when a customer leaves you, you are almost in a reactor state. So, and I imagine a world where you could proactively identify a customer with the propensity to leave your company because a lot of customers don't just, they are situations where they'll be walking down the street competitor calls them, they leave, not because they were unhappy, but a lot of customers actually had several engagements with us that were not pleasant, whatever the definition is. >>So we then saw there was almost five types of attributes that resulted in customers leaving us. So what then that said was imagine if you are an account manager, right? And you got told UiPath P two I limited has experienced 1, 2, 3, 4. Right? Actually, please go engage with them because something is happening. It means that as an account manager, you are then equipped to have a meaningful engagement with the customer because you're saying, hi UiPath, I see you've had X amount of job calls and you've had x amount of complaints in our call center. What is happening is it could be, could be your network, maybe the tower where you are, do you, And then the conversation becomes so meaningful. And I think even during covid what we found is lot of customers started using less of our data, not because they were unhappy, but it became an affordability thing, right? >>Because this is a thousands and thousands of, of data elements and pieces around Yeah. About customer transactions. There's no way one human would be able to go through all of the data and make me meaningful decisions out of it. So we then found that some customers were complaining about affordability. So we then built another model that says if an account manager is talking to a customer and they're struggling from an affordability perspective, what's the next best offer you can make to your customer while you're engaging? And then if in, if, if now your UiPath takes up that offer, then you'd find that the bot does the post engagement provisioning on the system. Because now if you then said, I've only, I can only afford 10 lines, but only pay 10 gigs, but not 10 lines and 20 gigs, that is at least better than us losing the customer. >>Yeah. Right? And we offering them almost a downward migration type of situation. Then the bot does that on the system. So you would find that we almost playing in the space of a human, human centered, intelligent automation where machine learning becomes the brain, the person is amplified in how they operate at the customer. And then the RPA bot becomes the hands that executes on that. And as the account manager you focusing on engagement and convincing, which is really what people are great and selling as opposed to going through all of the pro cause VOCA is a lot of products. So as opposed to having a person going through the products and trying to find the best product for you, you know, so we, we are using machine learning to assist the >>Humans. I I mean in every, every interaction is consistent in that case. I know I sometimes have to call three or four times to find a professional that knows enough that can help me. Yes. Such a frustrating thing as a consumer. So you are, are you, you're attacking churn with automation. So we haven't even talked about how you guys are working together, your journey and all that stuff, but, but how are you guys working here? What are you, what are you doing? You know, in addition to what you just described with with ui. iPad? >>So I think my portfolio's quite wide. So I am, my team is in every single vertical in the organization from customer care to the consumer enterprise business units to finance technology, network compliance. And we do all of this in about six countries, right? So one of the things we've actually realized is that if we are looking at customer service, we wanted to understand why do customers call us? And I think I came from a point of ignorance because I'm not from telco, so I actually realized that if we're talking billing and finance revenue assurance, customers call us because we build them arly. But technically speaking it's our systems that there's something that resulted in the customer calling us. So why do we not know about our own systems? Why are we waiting for the customers to call us? And literally those are the questions I was asking cuz I felt like why are we, why are we waiting for the customers to call us? >>So we then then found a way to try and see within the billing systems where do the breakages happen, right? So that we fix them before the customer has to call us again. So then again from a billing perspective, it means that cuz it the billing element can come in two ways where we are giving you a service and not charging you for it. We then have revenue leakage or we, you are consuming something and we are overcharging you. Then you call us and say, Whatcom is stealing my data. Yeah, you're right out there. I promise you nobody wakes up in the morning and wants to take one gig of your data. So it almost becomes a day integrity initiative that results in good customer service but then result in eradication of course. As opposed to us waiting for customers to tell us what the problem is and trying to help them fast. Cuz that's generally always been what I've picked up the energy around customer service. How do we help you fast? I'm saying why must you call us when our systems had fail that? So we almost trying to see how do we use the technology internally to give customers a better experience and then also have the financial benefits that we are now starting to see happening in the, >>What's the scope of, of your like how many automations, how many bots? Can you give us a sense >>Of this? So right now I think we over on with all of the four, five countries that we are in, we over 400 bots. Wow. Okay. So we started in 2004 years ago, this is my fourth year in Voca. We, and we are not using just one product with UiPath. It became a platform because as we became across more kinds of problems, I think what I've appreciated about part is how we've actually created a partnership. Instead of them trying to sell me products for the sake of consuming products, it became a, this is my problem, right? And then somehow they would whip out the product that solves my problem type of thing. So it became a ecosystem of solutions that >>You must love hanging out with Artie. >>I absolutely do and love, you know, I've spent a career in telecommunications myself and you know, the best days were when you could deliver an outstanding customer experience. And as you can see from what Artie has achieved when you were more proactive and predictive, you can serve your customers so much more effectively and that just lift the morale of the team because we all, you know, have this purpose in doing our jobs. But this is automation and AI built into every part of that customer journey. So end to end, you know, the customer's much happier. You know there's a problem before the customer knows you can solve the problem in most cases before they even know. And that's just what we are all in business to do to make things better. >>Great story. Thank you so much for sharing. Appreciate coming back >>In the queue. Thank you very much. Thank >>You. Thank you for watching. Keep it right there. Don't forget, go to silicon angle.com, all the news, go to the cube.net. You'll see me all these videos are available on demand as well as the other events that we do. Dave VTE for Dave Nicholson. Keep it right there. Right back at forward five UI.

(gentle music) >> Hello, everyone welcome to "theCUBE's" live coverage here in San Francisco, California for VMware Explore not VMworld, it's VMware Explore. I'm John Furrier, your host of "theCUBE" with Dave Vellante. We're here with two sets. 12th year, Dave, covering VMworld, now VMware Explore, what a journey? I had a little reminiscing from Paul Maritz in 2010, who predicted the future but the timing was off. Raghu predicting the future, but is his timing right with multi-cloud or super-cloud? We're going to get into it. We got three days of wall to wall CUBE coverage, two sets. All the top execs from VMware coming on, including the CEO Raghu himself, Vittorio, Kit Colbert, the whole kit and caboodle of the executive group to talk about the future of VMware, where it's going, and of course the appearance of Hock Tan here from Broadcom, Dave, made an appearance. Michael Dell was also in presence. I get the vibe that there's something going on with Broadcom and VMware beyond just the acquisition. So a lot of people are curious. This event again is notable and historic from the sense of it's VMware Explore not VMworld, so they changed the name, and Broadcom's intent, and they're going to be buying VMworld. Dave, the keynote was anticipated by all, how it was going to go down, what was going to be said. Raghu set the table, I got a ton of notes, I know you do. What's your take? >> Well, you have to start with the Broadcom acquisition. You're right, Hock Tan was in the audience, he stood up, he got a little clap. >> Golf clap. >> He's paying $60 billion for VMware, he better be able to be recognized. And he was here yesterday with Michael Dell at the executive sessions. And their purpose I'm sure, they didn't let us in, but I'm sure the purpose was to make sure that customers were calm, they were comfortable with the direction. Of course, the narrative coming out of VMware is that, hey, they're investigating, they're going deep into our portfolio, and they like what they see, it's going to be all good, it's not going to be like the CA acquisition and de-levering and all that stuff. I still stand by what I wrote in my breaking analysis back in May. The fact is, Broadcom has promised $8.5 billion in EBITDA within three years. That's the only way they get there, is to cut, so that's going to happen. But the interesting dynamic in the market, I don't know if you've noticed this, VMware stock is trading at a 20% discount to what Broadcom is paying for it. So there's a big amount of fluff, if you want to do some arbitration. And I think it's due to the fact that it's a stock and a cash deal, it's a combination deal, and it's not going to close for a year. So there's maybe some skepticism around that. But that was an interesting dynamic. The keynote we'll get into it, but it's all around multi-cloud and what we call super-cloud. >> I have my conspiracy theories on Broadcom, actually they make chips. Looking at all the waves right now in the technology industry, silicon is hot, anyone who's doing custom silicon and putting software on the chip, making purpose built vertical applications is seeing performance gains in cloud and in these applications. So one, I'm really excited by the dots connecting there. But also the VMware story, Dave, is pretty interesting in the sense that timing's everything, the Broadcom acquisition, EBITDA focus might drive behavior. But notable for VMware, is Raghu has been on this vision for years. I remember in 2016 when I interviewed him with Andy Jassy, who was then the CEO of AWS, they had moved everything to Amazon Web Services. And that was the beginning of the vision of multi-cloud and cloud-native. VMware invested a ton, and so we're seeing some fruit come off the tree. If you will, bearing some fruit from that VMware investment in cloud-native across the board which was their bet prior to Broadcom buying them out. So the question is, does Broadcom harvest that, continue that nurturing of that "plantation of goodness" that could come out of that VMware? And again, it's probability, it's not guaranteed. Commentary on Twitter is pretty heavy on, can they win the Devs? Can the new Ops bringing around the front? So, VMware's and Broadcom in a tough position, they bought more than they thought in my opinion. And I think a lot of people are saying, does Broadcom recognize the strategic value of what's coming out of the oven, so to speak, or what's blowing off the tree from VMware? And is it real? That is the number one question. I talk to people in the hallway, that's what they're saying. They want to know what's going to happen with what's around the corner, that's on top of mind of everybody. >> It's a really important question because VMware's future is multi-cloud management, what we call super-cloud. And without Tanzu, and I speculated that Tanzu was probably going to be under the microscope and potentially on the chopping block because they spend a lot of money marketing it, but they're probably not today getting a lot of returns. But without Tanzu, without a cross-cloud PaaS we sometimes call a super PaaS. their strategy doesn't work, it basically fails. And I think what a lot of people are missing, and I saw you chime in on Twitter, is can they win the Devs? Can they win the Devs? This is table stakes. If you don't have a cross-cloud PaaS, and it's really about not necessarily just the Devs, it's about the ops, right? Because now it's about security. Yes, shift left, but shield right. But the DevOps team, the Ops team needs consistency. It's like Adrian Cockcroft says, the Devs, they love to get married, the Ops, they got to clean up after the divorce. And so they need standard- >> You're implying that they'll use any tool for the job and not really worry about lock in. And I think today on the keynote, Deshaun was up there who submitted a comment, "You kids have it easy these days." Implying us old guys, when we coded, you had to do everything yourself. Kelsey Hightower mentioned her support pack desktop edition. The old days when had to build everything by hand, now it's all automated, all goodness. But in all seriousness, the focus there was DevOps has won, DevOps is what the developers are doing. The developers are in the clear right now, as far as I'm concerned. They're sitting on the beach right now, sunglasses on, sun shining, everything's shift left, CI/CD pipeline, cloud-native goodness. If you're a dev, things are much rosier than an Ops person. So DevOps is developer, security and DataOps, is where the action is. So it's not so much IT operations as it is security and data leveling up to the velocity demand of developers and also ease of use. So self-service in the motion of coding, in the pipelining, that's what the developers have to have. And if people don't build that experience from the upside, the new ops is not going to enable the develop, it won't be adopted in my opinion. >> You mentioned Paul Maritz before, his whole thing was any workload, any cloud, the software mainframe, they're talking about any Kubernetes, any cloud. And we got to go through some of the announcements real quick here. VMware Aria is the new multi-cloud management platform. That is the fundamental strategy for going cross-cloud or what we call super-cloud. The vSphere and vSAN 8 are big deals. And as relates to compute with vSphere, they're really pushing that whole DPU. You might remember Project Monterey. Well, Project Monterey is essentially like AWS Nitro, it's the future of computing architecture seven years after AWS introduced it. So AWS has a huge lead here. But it's critical that a company like VMware is able to offer that capability with XPU optionality, GPU, CPU, Arm based, Pensando capabilities, eventually NPUs, other capabilities to bring in and support new workloads, new data driven workloads. So the lot of talk about the whole DPU thing. As I mentioned, Tanzu new version of Tanzu, they talked about edge. They're basically bringing VMware to the edge with an eventual consistency model. >> Hold on, the vSphere thing, just to jump in there real quick. I always thought that that'd be higher up in the keynote. Clearly in the keynote, they flexed their cloud-native positioning, they had to address the Broadcom thing, talk about modern applications. So it felt like they were selling the dream on the front end. And they buried the lead in my opinion, which is vSphere 8. They don't do a lot of vSphere 8 announcements. If you look at the history of VMworld, every few years they got a new release. This was packed with a lot of goodness. And I thought they'd buried that in the keynote. >> I don't know, Raghu mentioned it. Yeah, they had a lot to cover. And then the other thing was they announced support for Red Hat OpenShift. So everybody's like, "Ooh, wow." And then Tanzu for all the Kubernetes versions from the cloud guys. So a lot of announcements, you got to always give VMware props. It's not like they stopped engineering, they have a great engineering culture. And so it's nice to see Project Monterey in particular, go from R&D to actual product. And so we like to see that. >> Even towards the end, now that we're doing the keynote review, Raghu said, "As proud as we are," this is when they started talking about the sustainability, implying they're real proud engineering, and that's a good call out there. I think that's what were trying to get across to Hock Tan, who was sitting in the front row. But Dave, in terms of keynote, my analysis is clear. Raghu was nervous, you can tell. But he's a product guy, he even said that on stage. He set the table at the beginning, I thought really well with modern applications. He had to address the name change, and I thought that was interesting. He actually said, "We built a community with VMworld, but now with multi-cloud, we're going to recall it Explore." Not sure I agree with that. I think VMworld community is still vibrant, and that's why they're here. So I thought that was nice, the way he balance that out, the messaging is good, the graphics and the branding of Explore is world class, I think it's phenomenal. I'm not a big fan of the name change, but I never go well with change there. Hock Tan didn't speak, he did stand up and wave. >> There's no way he's going to get up to speak. >> He didn't speak. So I thought that was interesting front end, so they got that right out of the way. And absolutely you saying last night. And then they got into this digitally smart concept, which I thought was on point. Did not like the great replatforming message. I'm not a big fan of that because it reminded me of the great resignation. And I think there's going to be a lot of memes on that. So not a big fan of the great replatforming. I did like the Cloud Universal pitch. But this whole multi-cloud pitch seems to me, and I want to get your thoughts on this, is that that's what it reminded me of, Paul Maritz. So when Raghu is clearly betting the ranch on multi-cloud, the question is timing. Paul Maritz in 2010 here at VMworld Moscone, he laid out the vision, he was right. But timing was off, the top of the stack didn't materialize. But at the end of the day, ended up being the right architecture. Is VMware too early with multi-cloud, Dave? And that's the question, that's the question on the table. >> Well, so a couple things. So Maritz, the one mistake Maritz made was he really tried to go into apps, remember? So now at least I think Raghu, the current VMware thinking is, we're going to enable apps to be developed. And that is the right thinking. Are they too early or too late with multi-cloud? I think technically it just wasn't feasible, the customers weren't ready for it. VMware moves at the speed of the CIO we like to say. So I think the timing is actually really good because the technical capabilities are now there. You've got to have across-cloud paths, which Tanzu is about. And I think Tanzu was too immature before. They've got the pieces on the DPU side. And the other thing about the timing is now with Broadcom acquiring VMware, the whole non Dell ecosystem has got to be a lot happier. NetApp, guys like that, Cisco. >> Why is that? >> Because Dell, their thumb on the scale, they had the thing rigged, Dell was first in line for everything. When EMC owned VMware, that was the case. But they were required about it, Dell made no concessions. And they just came out and said, "We are going to be VMware first, we are the preferred partner, we do more business with anybody." They really drove a truck through that. And I think it caused a lot of the ecosystem to pull back, like HPE and others to say, "Okay, we're going to find some alternatives here." Now they can really lean in. It's like when HP broken two, that really changed the ecosystem posture with HPE. This is like that, but times 10. >> What did you think about the ecosystem floor last night? When I did a walk of the floor, I thought it was very vibrant, it was not a ghost town at all. >> No, not at all, we saw Alibaba Cloud was there, we saw a lot of- >> AWS. >> Smaller companies >> Microsoft. >> And so I thought it was better than I thought it would be. There's probably what, 7,000 people here I would say? So well off from the 15,000 pre-COVID highs, but still very robust, it's a good crowd. People are excited to be back in person obviously. And I think the messaging was right, John. I think cross-cloud, multi-cloud, super-cloud, that is the future. Well, David Floid took a stab at it and said, "I think it's going to be $100 billion market by the end of the decade." >> Super-cloud is a thing for sure. And I think that came out in Aria announcement, which was basically a rebranding. It's not a new product, essentially it's a cobble together management platform. I thought the Cloud Universal notes here were interesting. The Cloud Universal is the commercial cloud smart component. Meaning they're trying to make that the frame, Dave, for the hyperscalers to come in to a de facto consortium movement. I feel like that's next here. If this Cloud Universal could become the super-cloud consortium, that might give them a better shot. The ecosystem is buzzing, attendance is strong. It's interesting a lot of people were speculating, will this be an event? I thought they did a great job and I thought they came through well with this. >> You were saying about consortium, because have to have the cloud guys in any consortium. But is any one cloud going to drive it? VMware could be- >> AWS >> Could be the driver. >> I'm thinking if I had to make a prediction, looking at what I just saw in the keynote, we'll see what the VMware execs say, If I had to make a guess, I think you're going to have customers, "Let's still double down on VMware stuff." They're going to settle into vSphere and networking compute and storage, the normal stuff that they've got, the software to find data center core as a cloud operational platform. And then you're going to see a lot more AWS migration. You might see that if Broadcom doesn't nurture the fruit coming off the tree, as we mentioned earlier, I think you might see people go more cloud-native. But I think VMware's prepared for that with the hybrid. So it's going to be very interesting to see. I think the winners coming out of this will be AWS, maybe a little bit of trickle into Azure, Alibaba mostly for the European, I mean the China side. But I don't see them playing. Google is a wild card, we'll see it from them. >> I think the other big thing about the timing, to your earlier point is, VMware used to go to market with very bespoke, We got vSAN, we got NSX, we got vSphere, and now they're trying to bring that together. And essentially remember, they used to go to market and say, "Okay, hey, your ELA is up, time to renew." And they're talking to the wrong people. So now they're going forth with the Azure service model, they're going to move to a subscription model. And I think the timing is right for that. I would've liked to see it a little bit before hand, maybe pre COVID would have been better timing. But I think technically, the time is right now for that. >> And I think looking at the acquisition, speculating on that, I think let's discuss how we see things, how they might move forward. Again, we'll ask the guests as much as best as we can and the best they could answer. But let's take this forward. Okay, based upon what I'm seeing here, if I'm Hock Tan in the audience, I'm saying to myself, "Okay, I got more here than I thought I was buying." Maybe I thought I was getting some great EBITDA. I wonder if his outlook changed on how he goes to market with the new VMware post acquisition. So that means in the around February timeframe, I would probably, if I was advising him to say, "Okay, let's keep it as is, let's not do the cut, cut, cut. Maybe trim a little bit here and there." But for the most part, he's got the solid customer base and he's going to have to keep the event. >> Here's the problem with that. They have a very high do-say ratio. They do what they say they're going to do. And as a result, they've promised 8.5 billion in EBITDA within three years out of VMware. And they return 50% of their free cash flow to investors. If they break that promise, their stock will get crushed. I don't think they're going to break that promise. So I think they're going to run. That's something I believe in their playbook that they're not going to change. Now, could they get there without massive cuts? I think it's going to be hard. Can they get there with price increases? Yes. And better efficiency, yes. But they don't have a lot of go to market synergies, John. Broadcom doesn't have a big sales force that they can say, "Okay, we're going to fire all the VMware sales force and you're going to go to market through our channel." Like Oracle would do with their big sales force or a Dell would do with an acquisition, they can't. And so I just don't see how they're going to around it. The only other thing I would say is, to me, I thought the application development piece, the Tanzu piece was very appropriate. And I think they got it. Whether or not they're going to succeed there, we can debate that. But I thought what was missing was there wasn't enough, in my opinion, on their security posture, their security strategy. I thought they gave it lip service with, "Oh yeah, we're going to shift left and dev security, et cetera." They did not go in depth. I think when you talk to someone like Tom Gillis, who really can go deep, I think talking about Barry and the lead, that was not, security is the number one issue of CIOs, CSO. >> Data and security >> At boards, it's number one. And data is the second thing. And those two stories in the keynote where quasi non-existent or/and weak. >> Again, the reason why I believe, and you're discussing it publicly at a high level, is super-cloud is real because it's not just SaaS on cloud, it's hybrid, it's DevOps, it's developer. And security and data operations are just absolutely now leveling up, and the edge is a complete wild card. We met a company last night, they're doing the edge cloud. The edge is going to open up all kinds of new use cases and challenges. And that's on the DataOps, data security side. DevOps, IT operations is already in the dev cycle. If companies aren't doing that, in my opinion, they're not really doing it right. So I think it'll shift to security and Ops and DataOps, that's going to be the action. In the cloud operational framework, that's super-cloud. To me, if I'm Hock Tan, I'm saying, "VMworld, VMware Explore, VMware has to be a core component of super-cloud of the future. Not multi-cloud just a state." I think multi-cloud will be a description of a state, of an architecture, and an outcome, but that's not super-cloud, that's not a functioning operating system, that's not a functioning business driven technology. So I think VMware has the opportunity. So I look at that and say, I got cheap options all the way up to the top of the stack. And super-cloud paths layer, as you describe, that I think is the way to go. >> When you think about how VMware got here, VMware was a $13 billion trailing 12 month revenue company. There aren't a lot of $13 billion software companies. And the way VMware got here, is through great software engineering. They identified problems that the customers had and they went and solved them. They did it with virtualization, they did it with private cloud, they figured out their public cloud strategy. So I think the question for Broadcom is going to be okay, how fast can we monetize that engineering? Can we turn that engineering R&D into dollars? And how fast can we do that? They have two choices in my opinion, keep innovating, which of course we hope that's the case, or act like a private equity firm and just squeeze as much cash out of VMware as possible. Which I don't think would be the right strategy because eventually that says, okay, what's going to happen to Broadcom? How are they going to continue to grow? Are they're going to have to just keep growing through acquisitions? So I think R&D is a really good spend when it's VMware. >> And I think as we wrap up our keynote analysis, one of the things that's going to come out of this as the conversation, no doubt in my mind will be, VMware isn't CA. And the question is, does Broadcom go off their playbook with VMware because of the fact that you look at the sponsorships for the show, we got a robust set of sponsorships for "theCUBE." With two sets, we're booked, fully loaded. Conversation's high, the floor is all about next level cloud operations. This is not a dying market, this is a growth wave coming. So the question, as super-cloud becomes that growth, and everyone's talking about super-cloud there. Some people who don't like the name, which is good, keep grace debate. But there's no doubt that that next wave is the super-cloud philosophy, the super-cloud mindset and architecture, and development environment. And we've documented that on supercloud.world if anyone's interested. But that wave is coming, and you can see it on the floor. Look at the sponsors, look at what people are talking about, Dave. This is not like Broadcom buying VMware and tucking it under and saying, "Okay, hope we can service the customer." There's a real market growth here story. So the question is, what do you do with that? >> Well, so you start with the base. VMware is a very good platform. The reason why they don't have a ton of competition and the reason why, okay, Nutanix can maybe trickle some away, but VMware is really good, it works, it's stable, it recovers from failures, it's got a super strong ecosystem. So you start by building there and then you identify the places where you can spend a dollar and make it 10. >> Well, I was very excited that when we had our super-cloud event, which was a virtual event as a test, we had great VMware support. And a lot of the catalog sessions up here, on Moscone West, where we're sitting, upstairs is all the sessions, they're crowded. And they overlay, Dave, with our narrative and the industry narrative. On the influencer side, you're starting to see the influencers meeting our editorial and pursuing a super-cloud with VMware and their ecosystem. Kind of agreeing super-cloud is real. And I think that is an important note because just last December, when we coined the term at Reinvent, I think it was Reinvent look what's happened. I want to get your thoughts and your reaction to why super-cloud has got so much traction, it's a great buzz with the name. But why is it that our super-cloud, the VMware, and the ecosystem are all aligning with this? Why do you think that's happening? Why do you think that the momentum is accelerating? >> The reason is that, as everybody knows, organizations have multiple clouds, it's a function of shadow Devs, M&A. And so they end up with all these different clouds, all these different projects, different primitives, different APIs, different tool sets. And they called it cloud chaos today. It's accurate, it is cloud chaos. So what's the problem with that? Well, that makes it harder to secure, it makes it harder to govern, it makes it harder to share data, it creates data silos. What's the answer? Well, if you can create a layer that's an abstraction layer that simplifies all that cross cloud data sharing and development and have a consistent set of APIs through a PaaS layer, we call it super PaaS and you are going to have a metadata intelligence that says, "Okay, I'm going to put this here or put that there. And I'm going to deal with latency, I'm going to optimize for whatever purpose, data sharing, or performance or whatever it is." You're going to solve a lot of problems. And you're going to make the CIO's life easier so that they can invest in their own business and their digital transformation and their digital strategy. So that's why people agree. They might not agree with the name, but they certainly agree with the concept of that abstraction layer. >> The name is certainly a better name than multi-cloud, multi-cloud sounds broken. But I think CIOs and CXOs, CISO, CSOs have to get buy-in from their teams. The organic dev relationship with Ops and SecOps and DataOps has to be symbiotic, not conflicting. And I love the chaos story because as Andy Grove, the legend at Intel once said, "Let chaos reign and then reign in the chaos." >> Chaos is cash. >> So in any innovation inflection point, chaos becomes the complexity, abstraction layers, and or innovation takes that complexity away. This is the formula for success. And I think VMware is right in the middle of it. And I think if I'm looking at VMware right now, I'm saying, hey, reign in that chaos right now and you win. So chaos is not a bad thing if you can reign it in, Dave. >> And that's what they've done. You think about what they did with virtualization, it was chaotic, it was wasteful. I think of what they did with private cloud. They said, "Hey IT guys, we're going to help you not get cloudified. We're going to cloudify your presence on-prem and not just throw everything into the cloud." They did a great job there. And now it's all about multi-cloud. >> Well, we're going to reign in the chaos, extract the signal from the noise. Super CUBE here at super-cloud event VMware Explore. Dave, great to kick it off again. Again, 12th year of CUBE coverage. It seems like a lifetime, Dave. Just yesterday we were 2010 >> Amazing, right. We've been in Moscone South, we've been in North, we've been in Las Vegas. Now we're here West, first time in west. >> Some of these developers were in elementary school when we started "theCUBE" here, I was just feeling old relics. Anyway, we're going to bring more action, three days of coverage, thecube.net, check it out. Join our community, join the conversation. As the influences are coming more onto the market, you're seeing a lot more conversations on Twitter, on LinkedIn, on the internet, check it out. Join the conversation. I'm John Furrier and Dave Vellante. We'll be back with more coverage here in San Francisco after this break. (gentle music)

(upbeat music) >> Okay, welcome back everyone. It's the CUBE's live coverage from Monaco for the Monaco Crypto Summit. I'm John Furrier, host of the CUBE. We're getting all the action here as the world goes decentralization as assets from the physical world connect with virtual to hybrid steady state. But Mattia Baldassarre's here, founder and CEO of Epico Play. Welcome to the CUBE! >> Thank you, John >> So I love to have you on. I love the Italian accent. Get a little European going here. We're from Silicon valley, where you're in Italy. Great to have you on. So Epico Play, what is it? >> So Epico Play is an innovative startup with the aim to digitalize the sport industry, to support clubs, federation leagues, to move into the digital era. Right? So we build up a technology. It is, actually two heads. One is a kind of white label technology for, you know, small, bigger club and then a B2C platform api-play.com where you actually can open up your own engaging channel straight away and allow clubs to have a digital infrastructure, to engage directly with their community, to monetize it and to make together some let's say two way engagement experience. Because we are used today, to just, you know a communication usually by this brand that has one way. So I tell you something, here is something, you know we create something together between the brand that is a club and the community itself. So it's kind of our ability to lump these experiences. >> Yeah. So I saw something on YouTube a day and a half ago. Roma soccer team introduced a new player and the fans were going crazy. They had a little light show. He comes out with the Big Digital Bits logo on this jersey. I forgot who the player was. You know, it was a young player. >> Dybala. Paulo Dybala. >> Yes. And the fans packed the place. And I know he's got the sponsorship with Digital Bits. So Digital Bits is sponsoring that club, but then the underlying technology. Are you over the top? Are you building apps on top of digital bits? >> Yes. I mean, that's also one of the, you know touching point of our partnership. Digital Bits today we announce our partnership with them, with Digital Bits Foundation. They're going to become, you know, our blockchain partner. They will support us on offering the token service to clubs. And for sure, we are going to, we are aiming to create our own token for Epico Play Platform which will always be the substances of the Digital Bits blockchain. And a second step will be for sure optimizing the relationship of Digital Bits, you know, also around the world. >> Yeah. >> But on ourself already has, you know a big pipeline of clubs onboarding. And I was telling before in the in the Summit is not just, we don't want just the top clubs. Right? That's easy. They have money. We want to help, you know, smaller club to go into this new era. Otherwise they're going to lose a lot of audience. They're going to lose a lot of revenue. >> It's interesting Mattia. I was telling earlier guests we had on about the meta version, sports. Sports clubs have been savvy around data for a decade, over a decade, all the big clubs that have TV contracts, certainly. They know how to manage, use technology to manage the team. They have technology to manage the stadiums and they have technology to manage the fan experience which was normally ticketing and, you know, I got a beer, I go to my seat, get stuff delivered, get a shirt, you know spot pricing, being smart. >> Sure. >> So with data. So, okay. That's good. That's a nice foundation. Now with the digital side of things and NFTs you've got assets and you've got a whole other level of interaction on the assets, the player, the brand the fan who can be a player and a fan. And so like now the multiple dimensions of new use cases. >> Completely. It is I believe it is, is like the game A New Hero, you know? So the touching point are much more our, let's say the Gen-Z, you know, the teenager, like they need more, much more input during the week. You know, for our, for my generation going to the stadium was the most exciting thing. So we were waiting for Sunday to go to the stadium, right? Now, the kids, they have so much information that if you don't engage them through this kind of fun engagement during the week, they will play PlayStation, you know or play whatever gaming on Sunday instead of watching the live match. >> But so to get that example let's stay with that for a second. You use your personal experience. Because I felt the same way for sports. If they could reach you during the week you'd be engaging with them. >> Exactly. You collect more data. >> You were ready. >> Exactly, you collect more data and mostly you have a higher quality of the data itself because you see how they behave. You see what they like, not just on the offline pitch. Right? But you can track everything here. So it's a, I think the big step that we bringing also into, into sports >> You know, I did a talk over 15 years ago at MIT and I said, web one was about information. Web two is about connections. And web three is about relationships. Okay, not just who you, you know connected to with devices, relationships. And guess what? Community, NFTs, self-expression, engagement, and the engagement patterns are changing as well. You're talking about things that aren't around right now. >> Yeah, exactly. >> This is new, new benefits. >> It's a new benefit, completely >> New benefits of everybody >> Completely for everybody. And especially, you know, actions that clubs need to do if they want to evolve, you know, that's I think really crucial for them. >> Great. You're building on Digital Bits. Where are you with the company? Talk about the origination story. How did it get started? Did you wake up one day and the apple fell on your head and you said, well, what happened? What's going on? >> So the story is this one, I worked in media, into sport media industry with a big group in London for a long time. And then I was also the CEO of a sport, OTT broadcaster. It is international, but I was taking care of Italy. While I was getting along with clubs, federation leagues, I said, there is a missing here. Right? They still not consider this as a main aspect. They always scared of investment or investing money in this. Right? So that's why we say, okay, you know what when I quit my job, we say, okay, I want, I'm going to... >> You just quit your job. Say I'm going to quit. >> Okay, no, I finished the season. Then I say, okay, done. Now I'm, I'm already thinking about what's going on. And then I open Epico Play. We also, with these mission say, okay there is an opportunity. There is a need in the market. And again, John, I'm not talking about just the top three teams of each league. I'm talking about all the teams. >> All the teams. >> All the teams, professional clubs, being basketball and volleyball. You know, all the sports need these changes. >> Yeah, some are bigger than others, but it's the power law. They all have communities. >> But if you aggregate all the small and medium teams, you know, right, You reach 1.5 billion fans. Right. So huge amount of data. And again, with our technology, we are able to give this environment without an investment from the club. So they are more open. They feel more like comfortable. And we are going to make money together with that. >> And they contribute the assets. So they're partner. >> Yeah. We are completely partner. So we build ecosystem, we then, for them and we make money together. >> It's a joint venture kind of, not formally but it's a win-win. >> It's a win. >> Not a lot of money out of pocket. They put a little bit probably to integrate in, but not big numbers. >> Not a lot of impact on the cash flow because in their mind is still for sure. The pitch, not the field is the most important thing. >> Yes. >> So that's why, okay, then we will help them. Okay. Don't worry. >> It's all upside for them. Do they have a rev share on things too? >> Yes. Exactly. >> So they do a business deal on their side? >> Yes >> So they're happy. They have the option for the future and... >> We build up everything for the future. Then we keep starting and keep monetizing together. So into different ways. >> So can you get some good tickets when the CUBE is in town? >> Whenever you want John. (laughs) >> Of course. What's next for you? Take us through your fundraising. You're building your team. Take a minute to put a plug in for your company. >> We actually, at the end, like seen around 1.2 million. Between, you know, an investment group that we're working with. This other venue, you know, one big TECHO company and some angel, strategic angel investor. Now we are also closing another bridge round to go then in 2023 to make a big round, you know, and scale internationally. So already, now we are approaching five to seven countries new countries, especially, you know, also going to South America where there is a massive adoption of this kind of opportunity, especially in terms of data. Then straight after we're going to, you know, make this fundraising and expand our business. Be really aggressive. As I told you before on the fact that, okay you know what we do the investment. Just let's build us your ecosystem together. >> Yes. >> And then we see, you know can be a different element between eventually other competitors will come out after. >> Okay. Great venture. Congratulations. >> Thank you. >> Thank you for coming on the CUBE. We'll see you at the yacht club later today. >> Thank you so much. >> The big gala event. Stay right there. We're wrapping it up here. I'm John for you here live in Monaco with the CUBE, Monaco Crypto Summit. All the next generation, new wave of businesses being refactored with new technologies, bring in value. That's what decentralization is, web three all coming together. Of course the Cube's covering it like a blanket. I'm John Furrier. We'll be back in more coverage after this short break. (upbeat music)

(upbeat music) >> Okay, welcome back everyone to the Cube's live coverage in Monaco. I'm John Furrier, host of theCube. Monaco Crypto Summit is the event and there's a big conversation later at the yacht club with Prince Albert and everyone else will be there, and it'll be quite the scene. And Rachel Wolfson is here. She's with Cointelegraph. They're the media partner of the event, the official media partner of the Monaco Crypto Summit. She's also MCing the event on stage, presented by DigitalBits. Rachel, thanks for coming on. >> Thanks for having me, John. >> So I know you're busy, thanks for taking the time cause' you got to go jump back in and moderate, and keep things on track. This isn't an inaugural event. So DigitalBits has exploded on the scene. I just saw a thing on YouTube news around this soccer player in Rome, has DigitalBits logo on their jersey. They're a big to do cause everyone's popular and they got a couple teams. So real world, kind of, assets coming together, what's going on in the event that you're MCing? What's the focus? What's the agenda? What's some of the conversations like? >> Yeah, definitely. Well, it's a great event. It's my first time here in Monaco and I'm loving it. And I think that Monaco is really becoming the next crypto hotspot. Definitely in terms of Metaverse and Web3 innovation, I think that we're going to start seeing a lot of that here. That's what we're seeing today at the Summit. So a lot of the presentations that we're seeing are really focused on Web3 and NFT platforms, so for instance, obviously what DigitalBits is doing. We watched a video before the break on Ecosystem and the Metaverse that people can join and be a part of, in terms of real estate, but we're seeing a lot of innovation here today with that. I moderated a great panel with Britney Kaiser, Lauren Bissell, Taross, I'm blanking on his last name, but it was about blockchain and how governments are implementing blockchain. So that was also really interesting to hear about what the Ukrainian government is doing with blockchain. So there's kind of a mix, but I'd say that the overall theme is Web3 and NFTs. >> Yeah. Britney was mentioning some of that, how they're going to preserve buildings and artifacts, so that in case they're looted or destroyed, they can preserve them. >> Right. I think it's called the Heritage Fund. And I just think it's such an interesting use case in terms of how governments are using blockchain because the best use for blockchain in my opinion, is recording data, and having that data be permanent. And so when we can have artifacts in Ukraine recorded on the blockchain, you know by being scanned, it's really revolutionary. And I think that a lot of governments around the world are going to see that use case and say, "Oh wow, blockchain is a great technology for things like that." >> So DigitalBits had a press conference this morning and they talked about their exchange and some other things. Did you attend that press conference or did you get briefed on that? >> I did not attend the press conference. I was prepping for my MC role. >> So they got this exchange thing and then there's real interest from Prince Albert's foundations to bring this into Monaco. So Monaco's got this vibe, big time. >> Rachel: Right. There's a vibe (John chuckles) >> What does it all mean, when you're putting in your reporting? What do you see happening? >> So, I mean, I honestly haven't covered Monaco actually ever in my reporting. And John, you know I've been reporting since 2017, but the vibe that I'm getting just from this summit today is that Web3 and NFTs are going to be huge here. I'm speaking, I haven't... You know, there's a panel coming up about crypto regulations, and so we're going to talk a little bit about laws being passed here in Monaco in terms of Metaverse and digital identity. So I think that there are a few laws around that here that they're looking at, the government here is looking at to kind of add clarity for those topics. >> I had a couple guests on earlier. We were talking about the old days, a couple years ago. You mentioned 2017, so much has changed. >> Yes. >> You know, we had a up and down. 2018 was a good year, and then it kind of dived back and changed a little bit. Then NFTs brought it back up again, been a great hype cycle, but also movement. What's your take on the real progress that's been made? If you zoom out and look at the landscape, what's happened? >> Right. I mean, well, a lot has happened. When I first entered the space, I initially came in, I was interested in enterprise, blockchain and private networks being utilized by enterprises to record data. And then we saw public blockchains come in, like Ethereum and enterprises using them. And then we saw a mix. And now I feel like we're just seeing public blockchains and there's really... (John chuckles) But there's still our private blockchains. But today, I mean, we've gone from that in 2017 to right now, I think, you know, we're recently seeing a lot of these centralized exchanges kind of collapsing. What we've seen with Celsius, for instance, and people moving their crypto to hardware wallets. I think that the space is really undergoing a lot of transformation. It's really revolutionary, actually, to see the hardware wallet market is growing rapidly, and I think that that's going to continue to grow. I think centralized exchanges are still going to exist in custody crypto for enterprises and institutions, and you know, in individuals as well. But we are seeing a shift from centralized exchanges to hardware wallets. NFTs, although the space is, you know, not as big as it was a year ago, it's still quite relevant. But I think with the way the market is looking today, we're only seeing the top projects kind of lead the way now, versus all of the noise that we were seeing previously. So yeah, I think it's- >> So corrections, basically? >> Right. Exactly. Corrections. And I think it's necessary, right. It's very necessary. >> Yeah. It's interesting. You know, you mentioned the big players you got Bitcoin, Ethereum driving a lot. I remember interviewing the crypto kiddies when they first came out, it was kind of a first gen Ethereum, and then it just exploded from there. And I remember saying to myself, if the NFTs and the decentralized applications can have that scale, but then it felt like, okay, there was a lot of jocking for under the covers, under the hood, so to speak. And now you've got massive presence from all the VCs, and Jason Ho has like another crypto fund. I mean, >> Right. you can't go a day without another big crypto fund from you know, traditional venture capitalists. Meanwhile, you got investors who have made billions on crypto, they're investing. So you kind of got a diversity of investor base going on and different instruments. So the investor community's changing and evolving too. >> Right. >> How do you see that evolving? >> Well, it's a really good point you mentioned. So Cointelegraph research recently released a report showing that Web3 is the most sought after investment sector this year. So it was DeFi before, and Web3 is now leading the way over DeFi. And so we're seeing a lot of these venture capitalist funds as you mentioned, create funds allocated just to Web3 growth. And that's exactly what we're seeing, the vibe I'm getting from the Monaco Crypto Summit here today, this is all about Web3. It's all about NFT, it is all about the Metaverse. You know, this is really revolutionary. So I think we're definitely going to see that trend kind of, you know, conquer all of these other sectors that we're seeing in blockchain right now. >> Has Web3 become the coin term for Metaverse and NFTs? Or is that being globalized as all shifted, decentralized? What's the read on it? It seems to be like, kind of all inclusive but it tends to be more like NFT's the new thing and the young Gen Zs >> Yeah want something different than the Millennials and the Xs and the Boomers, who screwed everything up for everybody. >> Yeah. (John chuckles) No, I mean, it's a great question. So when I think of Web3, I categorize NFTs and the Metaverse in there. Obviously it's just, you know the new form of the internet. It's the way the internet is- >> Never fight fashion, as I always say, right? >> Right. Yeah. Right. (John chuckles) It's just decentralization. The fact that we can live in these virtual worlds and own our own assets through NFT, it's all decentralized. And in my opinion, that all falls under the category of Web3. >> Well, you're doing a great job MCing. Great to have you on theCube. >> Rachel: Thanks. I'd like to ask you a personal question if you don't mind. COVID's impacted us all with no events. When did you get back onto the events circuit? What's on your calendar? What have you been up to? >> Yeah, so gosh, with COVID, I think when COVID, you know, when it was actually really happening, (John chuckles) and it still is happening. But when it was, you know, >> John: Like, when it was >> impacting- shut down mode. >> Right. When we were shut down, there were virtual events. And then, I think it was late last year or early this year when the events started happening again. So most recently I was at NFT NYC. Before that, I was at Consensus, which was huge. >> Was that the one in Austin or Miami? >> In Austin. >> That's right, Austin. >> Right. Were you there? >> No, I missed it. >> Okay. It was a very high level, great event. >> Huge numbers, I heard. >> Yes. Massive turnout. (John chuckles) Tons of speakers. It was really informative. >> It feels like a festival. actually. >> It was. It was just like South by Southwest, except for crypto and blockchain. (John chuckles) And then coming up, gosh, there are a lot of events. I'll be at an event in Miami, it's an NFT event that's in a few months. I know that there's a summit happening, I think in Turkey that I may be at as well. >> You're on the road. You're traveling. You're doing a lot of hopping around. >> Yes I am. And there's a lot of events happening in Europe. I'm US-based, but I'm hoping to spend more time in Europe just so I can go to those events. But there's a lot happening. >> Yeah. Cool. What's the most important story people should be paying attention to in your mind? >> Wow. That's... (Rachel chuckles) That's a big question. It's a good question. I think most, you know, the transition that we're seeing now, so in terms of prices, I think people need to focus less on the price of Bitcoin and Ethereum and more on innovation that's happening. So for instance, Web3 innovation, what we're seeing here today, you know, innovation, isn't about prices, but it's more about like actually now is the time to build. >> Yeah. because the prices are a bit down. >> Yeah. I mean, as, you know, Lewis Hamilton's F1 driver had a quote, you know, "It takes a team. No matter who's in the driver's seat, it's a team." So community, Wayne Gretzky skates where the puck is going to be I think is much more what I'm hearing now, seeing what you're saying is that don't try to count the price trade of Bitcoin. This is an evolution. >> Right. >> And the dots are connecting. >> Exactly. And like I said, now is the time to build. What we're seeing with the project Britney mentioned, putting the heritage, you know, on the blockchain from Ukraine, like, that's a great use case for what we're seeing now. I want to see more of those real world use cases. >> Right. Well, Rachel, thanks for coming on theCube. I really appreciate it. Great to see you. >> Thanks, John. >> And thanks for coming out of your schedule. I know you're busy. >> Thanks. Now you get some lunchtime now and get some break. >> Yeah. Get back on stage. Thanks for coming on. >> Rachel: Thank you. >> All right. We're here at the Monaco Crypto Summit. Rachel's MCing the event as part of the official media partner, Cointelegraph. Rachel Wolfson here on theCube. I'm John Furrier. More coverage coming after this short break. >> Thank you. (upbeat music)

(gentle music) >> Hey, everyone. Welcome back to New York City. Lisa Martin and John Furrier here with theCUBE, covering AWS Summit NYC. This is a series of summits this year. There's about 15 of them globally. We are excited to be here with a couple of guests. We have an alumni back with us. Couple of guests from Caylent, Stephen Garden joins us, the Executive Chairman, and Valerie Henderson, Chief Revenue Officer. Guys, welcome to the program. >> Thank you. >> Thank you. Thank you for having us. >> Great to have you, welcome back. >> Appreciate it, from 2016. >> 2016, it's been a minute. >> Yep. >> But that was before Caylent. Talk to us about Caylent, what do you guys do? What do you deliver? How are you affiliated with AWS? >> Sure, so we were founded in 2015, initially as a container management product. So our roots are very deeply centered around Cloud native. We've since evolved and become a Cloud native consultancy. We're all in with AWS. We were actually just awarded AWS Premier Partner a couple of weeks ago, so we're pretty pumped about that, but we're about 250 people now, across North and South America. And our goal is really to work with customers that are looking to innovate and evolve and use AWS as a catalyst to build new products for their business. >> As a catalyst, I like that. Valerie, talk about the customer. Obviously so much tumbled in the last couple of years. Still going through it. >> Yeah, of course. >> How have customer conversations evolved and changed in the last couple of years, from your perspective? >> Yeah, I think from my perspective it is such a unique time and it's a time that is constantly changing. And I think change breeds opportunity, and I feel like customers see that, and they're leaning in. They want the opportunity to create new revenue streams, do more, more efficiently, and I think that's the key. And the questions are really asking, how can we take our data, and turn it into something that we can monetize? How can we be smarter with what we have? And I think it's an incredible time to be in the space that we're in. Every conversation I have is really forward thinking, and about the business. And I've been in this space for a while, and that was not always that case. And I think now people are shifting that IT shop to IP shop, and that's so key, from my perspective. >> Interesting, interesting shift there. Every company has to be a data company these days, to be competitive, the last couple of years it was, how did we survive? Pivot, pivot, pivot. But to be a data company, means you have to be able to extract the value and insights from that data and act on it, to your point, develop new products, new revenue streams, new opportunities. How do you enable companies, and maybe this is a question that you can both answer, to truly become data companies? >> The whole model from a service's perspective is not a do-for model, it is a do-with model. And any time we go into a customer, it's like, where are they on the curve? From monolith application, to microservices, where do they sit today? And I think when you dig in, you assess, you deeply understand where they are, you can get them to where they want to be, and build a plan. And the way our model works is, we're doing it with them, and what that means is we're enabling them, documentation, we're supporting them, that if we're not there, they're going to be able to carry it forward and continue to do more. So, that's so so important. I'd love Stephen's take on it. >> Yeah, I think the other trend that we're seeing in data more recently is that customers need to share their information with other partners, collaborate. And AWS is just the perfect platform to be able to do that, enable that sharing. And you're seeing even businesses like Snowflake build a data Cloud on top of AWS. So, I think that's a new angle that we're seeing which is really bringing together way more innovation- >> What about that data clean-room trend that's going on, Snowflake's doing a lot of that. But some of them have a little lock in spec there, versus being open, security, privacy, governance, what's the balance between open sharing and the requirements you need to be secure and compliant? >> Yeah, I think very simplistically, the information that you are using to deliver your product and service to customers generally safer, more public and available, the information that's confidential to your business behind the scenes, obviously, you use the right protocols to lock it out. But it is a very hot topic in today's world, especially with Web3 and people seeking to get their information back, so... >> So you mentioned you guys around since 2015, if you go back in time, it seems like yesterday, but Cloud time, it's like two generations ago. Why is data now more relevant? Is it because the technology's gotten better and easier, or more maturization of the client's understanding, or being full with data, having a data problem and hence an opportunity? Or is it open source has evolved? Or all three, what's your reaction to that? Why is it exploding now when it's been around for a while? >> It keeps exponentially growing, right? The more and more data. There was a stat four or five years ago about, hey, we're taking more photographs in a single year now than all of mankind, leading up to that date, but I think just the sheer quantities and the way people are managing it now, and being able to actually capture information points of everything across their entire business, just presents a much bigger opportunity to be able to take and form decisions of the back of that. >> So do you see the customers having more data full problems, that they're having more data? So that's... And in that one >> 100%. >> Of the consequences of not leveraging it? >> Yeah, it's what to do. Yeah, absolutely, and if you think about when you wake up in the morning if you ask Alexa what the weather is, and like, you're creating data, in every engagement with the world. So I think it's this explosion of it, but then it exists, and what do you do, and having a strategy. I still think one of the biggest gaps is people, and talent, and expertise to do the work, frankly. Which is, the hypothesis of Caylent existing. >> Yeah, I think a data concept and application, because what's the weather to Alexa, is an application of what's the weather, it's a request, but it's actually the data's built into the app. >> It's built in. >> So data as code is a new trend. >> Yes, yeah, yeah, and I think it's funny to answer the question. There's more data points surrounding how to leverage your data, and I'm like, it's crazy, I think you're really seeing that working- >> We have an old data warehouse, we can't get the weather data, although it's there somewhere. But that's the problem. Getting the data, in the applications, this is not... Wasn't around 10 years ago. No one was talking like that. Now it's more standard. That sounds like DevOps to me, a DevOps problem. >> Yeah, moving from the monolithic to the microservice is wild, and just the way that people are building applications today. The users, their customers are demanding more from the service, and AWS is able to deliver that. >> What are some of your customers doing with you guys, can you give some examples and scope the scale of your relationship with the customers, vis-a-vis AWS and the Cloud, how they're using you guys and the Cloud. >> Yeah, yeah, for sure, a customer of ours, Allergen, which is an incredible organization, really had a large effort to modernize. And they actually have a data lab within their company called Allergen Data Labs, and they leveraged us to truly just modernize this containerization effort. How they can do more with less, and that serverless experience. So, I think from my perspective what we're seeing is also a need to be thoughtful about DevOps retooling and tooling because talent wants to work with the best toolset, the hottest stuff on the street, and again, to keep talent is key, in any organization's success. >> Valerie, how does Caylent help with that from a talent perspective? Obviously there's talent shortage, we're also still in the great resignation. >> Oh my gosh. >> How do you help organizations bridge the gap so that they can glean insights from data and be competitive and win? >> Yeah, we actually just published a case study with Novus which was bought by SEI, which is a huge financial firm. Where they said, "Listen, it's human nature to say I have a gap, and I need to fill it, I'm going to hire somebody." That's human nature to say, okay, this is what we're going to do. But the reality is, I think companies are starting to see the advantage of using a partner and say, okay, I could hire one person or I could bring in a partner who's going to have a team of five, works incrementally for a period of time, does with, helps coach my team up, document all of that, and I think that they're seeing value from that. And ultimately, it's not that we don't want them to eventually hire. When they do hire, we want that person to come in and have the best experience. >> And sometimes the people aren't even available, right? >> Correct, yeah. >> So you have a combination of managed services, a plethora of managed services that are also involved with the customers. So, it's that integration, scale, and partnering and sharing. You mentioned sharing data earlier, how do you guys view that integration piece, 'cause if you have a modern architecture, you got to have that decomposed, decoupled but integrated approach. >> Yeah, we really believe that the whole world of project services and managed services is coming together as one. So we have a single delivery model which we're really passionate about. And we look at it as an embedded team within our customers, embedded DevOps to support them, basically on anything that could be from a modernizing a new application through to addressing a more traditional Cloud architecture framework that's in place. But yeah, the trick to it is, as Val said earlier is the do with approach, not just do for, right? I think customers need to learn about the Cloud. They need to understand the technology that they're using. They want to have that understanding. And we found a way of fitting in our services to help them accelerate that part. >> So Valerie, I got to ask you the question. So, in sports you talk about the modern era of baseball or whatever, we're in the modern era of Cloud, going next generation. We call it Super Cloud, a concept that Dave and I put out at re:Invent. If someone asks you, what does the modern era look like? As you look at your customer base and the data you guys have, how would you describe this modern era? What is it made up of? Is it outcomes versus solutions? Is it technology that's decentralized? How do you talk about it? What is the modern era, if you were- >> Not to oversimplify it, but I'm going to, the idea that somebody could come into work and all they have to think about is business outcomes and the data points that they need to achieve said business outcomes. I'm the biggest fan of measure what matters, I think it is an incredibly powerful methodology. And I think anybody who thinks about running business, they know that it's a scale. The amount of companies that are in that place is very small right now. So I think modern era is really that running an IT company to an IP company. >> So Stephen, if you unpack that, what's under the covers to make that happen? Automation, machines, what's your assessment of that outcome, which by the way was well said. Beautiful, beautiful comment. What makes that happen? >> I think it is around automation. It is around do once and then apply many times. That is key. Obviously it's a fundamental principle of the Cloud, is that consistency in that repeatability. So when you can simplify services down to a point, click, deploy, I think you're in a much better position to be able to move quickly and then not have to worry about anything under the hood and just focus, like Val said, on the business outcomes. >> That's more creative. They're focusing on the problems, to not do the rock fetches and the heavy lifting that's not differentiated. >> I find that what gives people energy generates opportunity. And I think when people hit those roadblocks of, these things don't work together. There's all these interdependencies. It's really challenging. So I love what's happening. I think there's never been a better time to be in this business. >> Not a dull moment, That's for darn sure. >> Not a dull moment. >> Valerie, talk about outcomes. You mentioned a couple of customers that you're working with, some case studies. It is all about outcomes these days. That's the conversations that we have with the entire ecosystem is all about business outcomes. What are some of those key transformative business outcomes that Caylent is helping customers to achieve? >> Yeah, to me one thing that is key is, anytime I'm meeting with a customer, I want to understand who their customers are. I'm like, who is your customer? And how can we create a better experience for that customer. Whether it's their end users or their external customers. And I think that is a huge element. What we're seeing is that sassification of, how do I make it easier for my customers to procure and engage with my platform? And a lot of what we're doing right now is helping clients with that. And it's not a flip of a switch, it's not a click of a button, it's complicated. But that is what we are here to help, help simplify, help create that understanding of what's possible. >> How do you guys talk to your customers, take a minute to give a plug for the company. What are you looking for? What's the stats? How many employees you guys hiring, and what's the pitch to customers? >> Yeah, so I think every organization is on their journey to the Cloud now. It's gotten to that point where if you're not working with a public Cloud provider, you're part of a very, very small group. We like to say that we'll meet customers where they are, and help evolve them as a business, help evolve their teams. And that's what we mean when we say do with, so it's a pretty broad spectrum. We're big in healthcare. We're big in FinTech. We've worked with a lot of startup customers. We have about 250 customers today, 250 employees. And we're scaling rapidly. We've grown that from about 50 employees a year ago. >> Oh, wow. >> Yes, when I started, we were just around 60 people and we're at 260 today. >> And why are people working with you? What are you guys, solving a problem? Are you enabling them? What's the pitch? >> Without a doubt, I love that. Being in sales my whole career, somebody asking me for a pitch is my favorite. >> Okay, let's go. >> Yeah, yeah, the true value prop of what we do is all of the above. We enable, we help customers do more faster, but again, we do not want customers to walk away from an engagement with us saying, oh no, we don't know what to do. We want them to feel empowered. I still think the biggest gap from everything being in that IP business outcome is people. And for us, we're so passionate about that, and building a company that really truly believes that. And that's part of who we are as a company and our value system. >> And the digital transformation, ultimately what they're going through, you get them there faster. They get the outcomes and they're operational. >> Absolutely, and also to be clear, when a customer has a great experience working with you, they want to tell other people about the experience. And for us, like the referrals that we get, the partnership with Amazon is so key. >> What are some reactions after you go through an engagement? We've been riffing on this concept of Super Cloud where you're starting to see people build on top of, not the AWSs, but their partners that work with them. And so the customers are getting their own Cloud experience at scale. What are some of the comments you hear from your successful customers? What are some anecdotal feedback? >> Yeah, yeah. >> I'm so glad we did this because now I'm selling more, I'm doing this, what are some of the things that they're thinking? >> Yeah, yeah, I think ultimately the consistent theme that we get is, "I'm so glad that I didn't let fear hold me back from engaging a partner," because a lack of control scares a lot of customers. It does. And I think customers that are willing to say, "Okay, I'm going to have a little faith, trust in the process." They thank us. They do, and we've seen that across the board. I think that crossing that chasm is not to be underestimated without a doubt. >> Great story, congratulations. >> Oh, thank you. >> Well, there's nothing more powerful and potent than the voice of the customer. >> Without a doubt. And really you have to listen. >> Yes, yes, definitely. Stephen, Valerie, thank you so much for joining Dave and me on the program today, talking about Caylent, what you guys are doing for customers with AWS, empowering, enabling, collaboration. I love it, thank you. >> Yeah, thank you both. >> All right, our pleasure. For John Furrier, I'm Lisa Martin. You're watching theCUBE live in New York City, we are at AWSO in NYC, John and I will be right back with our next guest. (gentle music)

(digital music) >> Welcome back to VeeamON 2022. We're in the home stretch, actually, Dave Nicholson and Dave Vellante here. Daniel Fried is the general manager and senior vice president for EMEA and Worldwide Channel. Daniel, welcome to theCUBE. You got a big job. >> No, I don't have a big job. I have a job that I love. (chuckles) >> Yeah, a job you love. But seriously Veeam, all channel. I mean it has been. >> Yeah, I mean, it's something which just, just a few seconds on, on that piece here, the channel piece, it's something that I love because the ecosystem of partners, an ecosystem of partners, is something which is spending its time moving and developing and changing. You've got a lot of partners changing their roles, their missions, the type of services, type of product that they offer. They all adapt to what the market needs and all the markets around the world are very different because of all these different cultures, languages, and everything. So it's very interesting. In the middle of all that, you know, these tens of thousands of partners and you try to create and try to understand how you can organize, how you can make them happy. So this is fantastic. >> So you're a native of the continent in Europe, obviously. We heard Anton, today, who couldn't be here or chose not to be here, cause he's supporting family and friends in Ukraine. What's the climate like now? Can you share with us what's it like Europe? Just the overall climate and obviously the business climate. >> So the overall climate, the way I see it or I feel it, and obviously there may be some different opinions, that I will always appreciate as also very good opinions. My view is that it seems in Europe that there are a distinction between what people do for businesses, Their thinking for the business, which may be impacted by the situations that we know in Europe between, because of obviously the issues between Ukraine, because of Russia, let's put it this way. And then there is the personal view, which is okay. That happens from time to time, but life continues and we just continue pushing things and enjoying life, and getting the families together and so on and so forth. So, this is in most of the countries in Europe. Obviously, there are a number of countries, which are a little bit more sensitive, a little bit more impacted. All the ones who are next to Russia, or Belarus, so on and so forth. From an emotional standpoint, which is totally understandable. But overall, I'm pretty impressed by how the economy, how people, how the businesses are, you know, continue to thrive in Europe. >> Has Brexit had any...? What impact, if any, has it had? >> So for us Veeam, the impact is... So first there is an impact which is on the currencies. So all the European currencies are no, have slowed down and, and the US dollar is becoming much stronger. >> Despite its debt. >> Right. >> Shouldn't be, but yeah. >> But that doesn't impact on the business. I just... >> Yeah. Right. >> So everything which is economical, macroeconomical is impacted. We have the inflation also, which has an impact, which also has increased because of the oil, because of the gas of everything that they have been stuck, to be stuck. But people get used to it. As Veeam from a business standpoint, one of the big things is we stopped sales, selling into Russia and into Belarus and we are giving our technology, our product, our solutions for free to Ukraine. And that was a piece of the business that we were doing, within EMEA, which was non-neglectable. So it's, I would say a business hole, now that we need to try to fill with accelerating the business service in the other countries of Europe. >> I mean, okay. So thank you for that but we really didn't see it in last quarter's numbers that you guys shared with I mean, IBM. Similarly IBM said, it's noticeable, but it's not really a big impact on our business, but given the cultural ties that you had to Russia and the affinity, I mean you knew how to do business in Russia. It's quite remarkable that you're able to sort of power through that. How about privacy in, around data, in Europe, particularly versus the US? it seems like Europe is setting the trend on things like privacy, certainly on things like acquisitions, we saw the arm acquisition fail. >> Yeah. So there is a big difference. Effectively, there is a big difference between, I would say North America and the rest of the world. And I would say that EMEA, and within EMEA would say the EU is leading very much on what we call server sovereign cloud. So data privacy, which in other words, data is to as much as possible is to remain within either the EU or better within each of the countries, which means that there is again... It's I would say for in EMEA it's good, I would say for the business, for the partners, because then they have to develop around the cloud a number of functions to ensure that because of this data privacy, because of this GDPR or rules and things, all the data remains and resides in a given geographical environment. So it's, which is good because it creates a number of opportunities for the partners. It makes obviously the life of customers and their self a bit more difficult. But again, I think it's good. It's good. It's part of all the way we structure and we organize. And I think that it's going to expand because data is becoming so key, a key limit, a key asset of companies that we absolutely need to take care of it. And it is where Veeam plays a big role in that because we help paying companies managing their data and secure the data in sort of way. >> Yeah. Ransomware has been a big topic of conversation this week. Do you sense that the perception of that as a threat is universal? Are there, are there differences between North America and the EU and other parts of the world? Universal? >> Yeah, it is universal. We see that everywhere. And I think this is a good point, a good question too, is that it's very interesting because we need to get acquainted to the fact that we are going to ever. And so we are going to be attacked. No way out, no. There... Anybody the morning, is waking up, is going on emails and click clicking on an email. Too late. Was a run somewhere. What can you do against that? You know, all humans make mistakes. You can't so it'll happen, but where, where it's absolutely very important and where Veeam plays a big role and where our partners are going to play an even bigger role with our technology is that they can educate the customers to understand that, to have run somewhere is not an issue. What has, what happened is not a problem. What they have to do is to organize so that if they have run somewhere, their letter is safe. And this is where our place a big place. A couple hours back, I was, I was doing a kind of bar with something else. It's totally crazy, but that's okay. I'm going to say it. It's about the COVID. What, no, what do we do? Do we have, do we have something against COVID? No. People were going to get COVID, certainly many people still doing it, but what is important is to be capable of not being too sick. So it is the prevention, which is important. It's the same thing here. So there is this mindset we have psychologically with the partners and they have, they have to provide that services to their customers on how to organize their data using the technology of Veeam in order to be safe, if anything happens. >> So another related question, if I may. When Snowden blew the whistle on the NSA and divulged that the NSA was listening to all the phone calls, there was seemed to be at the time, as I recall, a backlash sentiment in Europe, particularly toward big tech and cloud providers and skepticism toward the cloud. Has the pandemic and the reliance on cloud and the rise of ransomware changed that sentiment? Had the sentiment changed before then? Obviously plenty of Cloud going on in Europe. But can you describe that dynamic? >> Yeah, no, I think that's... Yeah. I think that people were too... You know, as usual. It absolutely reminds me when I was at VMware, when we went from the physical boxes to the virtual machines. I remember the IT people in the company said, "No, I want to be capable of touching." Something here. When you talk about cloud, you talk about something which is virtual, but virtual outside, even outside somewhere. So there is a resistance, psychological resistance to where is my data? How do I control my data? And that is, I think that is very human. Then you need to, you know, it takes time. And again, depending on the cultures, you need to get acquainted to it. So that's what happened be before the pandemic, but then the pandemic took place. And then there was a big problem. There was nobody anymore in the data centers because they couldn't work there and then people were starting to, to work remotely. So the IT needed to be organized to compensate for all these different changes. And cloud was one of them where the data could be stored, where the data could reside, where things could happen. And that's how actually it has accelerated at least in a number of countries where people are a bit leg out to accept the adoption of cloud, cloud-based data. >> So is there a difference in terms of the level of domination by a small group of hyperscale clouds versus smaller service providers? You know, in theory, you have EU behaving in a unified way in sort of the same way that the United States behaves in sort of a federated way. Do you have that same level of domination or is there more, is there more market share available for smaller players in cloud? Any regional differences? >> Yeah. There are big differences. There are big differences again, because of this sovereignty, which is absolutely approved very much in Europe. I'm tell you, I'm going... I'm giving you an example that it was in, I think in October last year, somewhere. The French, the French administration said, "We don't want anymore. Any administration investing in Microsoft 365, because the data is in Azure. The data is out in the cloud." That's what they said. So now these last days, this last week that has changed because Microsoft, you know, introduced a number of technologies, data centers in France, and so on and so forth. So things are going to get better. But the sovereignty, the fact that the data, the privacy of data, everything has to remain in the countries is doing something like the technology of the hyperscalers is used locally wrapped by local companies like systematic writers, local systematic writers, to ensure that the sovereign is set and that the privacy of the data is for real and according to GDPR. So again, it's a value add. It makes things more complex. It doesn't mean that the Google, the Google cloud, the Azure, or the AWS are not going to exist in Europe, but there are going to be a number of layers between them and the customers in order to make sure that everything is totally brought up and that it complies with the EU regulations. >> Help us understand the numbers, Daniel. So the number of customers is mind-boggling it's over 400,000 now, is that right? >> Yeah. Correct. >> Yes. Comparable to VMware, which is again, pretty astounding and the partner ecosystem. Can you help us understand the scope of that? Part one. part two is how do you service and provide that partnership love to all those companies? >> The partners. So yeah, we have about 35,000 around the world, 35,000 partners, but again, it's 10 times less than Microsoft, by the way. So, and this is very interesting. I often have the questions, how do we manage? So first of all, we do tiering, like anybody does. >> Sure. >> We have an organization for that. And we have a two chair sales motion. That means that we use the distributors to take care of the mass, the volume of the smaller, smaller partners. We help the distributors, we help. So it's a leverage system. And we take care obviously more directly, of the large partners or the more complex partners or the ones of interest. But we don't want to forget any of those because even the small one is very important to us because he has these customers maybe in the middle of nowhere, but he's got a few of them. And again, to have a few of these customers, when you adapt, you know, it makes.. At the end, it makes a big business. You know, one plus one plus 1 million times makes, you know, makes huge things. And plus we are in the recurring business now, now that we've introduced three, four years ago, our subscription licenses, which means that it's only incremental. So it's just like the know the telephony, know the telephony business, where the number, the cell phone plans, you know, it's always grabbing as many as possible consumers in this case. So it was the same thing or I have the same, the same kind of, I do a parallel with the French, the French bakery, the French Boulangerie where I say they do their business with the baguette. And then from time to time, they sell the patisserie or they sell the cake, cookie or something, but the same of small things makes a big things. So it is important to have all these small partners everywhere that, that have their small customers or big customers, and that can serve them. So that's that's way. We segment by geography and what we do now is, it is something which is new. We segment by competencies. So it's what I call the soft segmentation. Because if not, we will have a lot of these partners competing to each other, just to sell Veeam. Veeam being number one in many countries, that is what is taking place. And we want them to be happy. We want, we don't want them to fight against each other. So what we do is we do soft segmentation and soft segmentation is this partner is competent in this field with that kind of use case doing this or this or this or this. It's just like you, when you go to the restaurant, you want the restaurant next to your place. So you click for the geography and then you want to, to go for Indian food. So you click restaurant Indian food, and then you want something. So we want to give that possibility to the customers to say, "Yeah, I think I know what I want." And then you can just click and get the partners or the list of partners, which are the most suited for, for his needs. So it's what I call the soft segmentation. The other thing which is important is the network. It's very interesting because when we look at a lot of companies, it's not the network. You've got VARs, you've got cloud and service providers. You've got SARs, you've got all the things. But if you take each of those individually, they don't have the competencies to answer all the request of the customer. So the networking is partnering with partner. That means to have the, the connection so that the partner A who has his customer, but these customer's are requests that this partner cannot fulfill because it's not its competency. That it's going to find the partners or the other partners that can feel this competency and work together. And then it's between them to have the model that they want so that together they can please the customer with their requests. >> Do you ever want to have VeeamON... I mean, I'm happy it's in the US and I like going to Europe, but you, have you ever want to have VeeamON in Europe? >> Yeah, we have VeeamON. We have many VeeamONs in Europe. >> Yeah. The mini ones. Okay. >> VeeamON tours. >> Globally. So where do you have them? >> Europe in APJ, that's what we do. Yes. >> Where do you do it in a APJ? In Japan, obviously in... >> Yeah. I don't know all the locations, tens and tens of them. >> A lot of them. Okay. >> The small ones. What we do, replicate what is done here on one day and then it goes. >> And you'll do that in UK. France, Germany. >> Yeah. Yeah. >> Local. >> And also small countries in Saudi, in South Africa, in Israel, in Bulgaria, in all these countries. Because, you know, we can be virtual. That's nice. >> Oh, right. >> But I love to be having a breakfast or a lunch or drink next to a partner or a customer because you learn so much more. The informal information is so important to understand how the business and how the market develops and what the needs are of customers and so on and so forth. >> How was the European attendance this year? It must have been down. It's hard to get into US. It's actually easier to go back to Europe. >> Virtually I, don't have the numbers, but I- >> No. Virtual. I'm sure it was huge. Yeah. But physical. >> Physical here, we've got about 300, 300 Europeans. >> Yeah. Okay. Out of, do we know? What are the numbers here? Do we know? Have we heard numbers? >> I know 45 was supposed to be around 45K combined. >> That's hybrid. >> So, yeah. >> It's hard to get into the US. We're still figuring that out. So I'm not surprised, but now you... >> But it's complimentary. Yeah. >> Do you go to 'em all? >> No >> You can't. >> No. That's not possible. I cannot. I actually, I would love... >> But some, yes. >> I would love to be capable of duplicate myself, but- >> You go to the one. >> I'm unique. >> You go to the one in France, obviously. Yeah? >> Yeah. Usually in France. Well... >> Depends if you're home. >> Yeah. You know, that is interesting is, the way we organize, the way we organize in Europe is I really want the local leaders to be the ones managing the countries. I'm there to support. I'm not there to be, you know? Yeah. The big boss is coming, he showing. No. It is not that. Again, if they request me to come, if they want me to pass a message to certain type of customer partners, I'll do that. But I don't want to run the show. It's not the way I manage that. >> Yeah. I get that. You want to respect that as if you show up in France and that's your home country, it's like rat man showing up here. It's like taking over the stage. You'll be like, you know, it's our turn. >> But it's just like, you know, I give you another example. So obviously we have... It's even the headquarters, the EMEA headquarters is in France. Right? But it is the French office. And I don't go there. I try not to be there because it is the place for the French people taking care of the French market. And for the French manager, if I go there, everybody's going to come and ask me questions and ask me to make decisions and things. No, they have to run their business. >> So where do you spend, where and how do you spend your time? >> In airports and in planes. (indistinct) What are you asking? >> Of course. >> Do you have another question? >> Actually, if we have time really quickly on just on that subject of sovereignty, we are here in Nevada just across the border, California. People in California have no problem at all, replicating things here for disaster recovery, because it's in the US. Now, is there sort of a cultural sense that tearing down those borders from a sovereignty perspective within Europe would fundamentally change the business climate and maybe tilt things in favor of the AWS and GCPs of the world instead of local regional business? The joke that I heard recently from someone, I thought it was funny. I don't know if it would offend either Germans or French, but it was that it was that AWS was confused and they were planning on putting a data center in Strasbourg, because they thought it was in Germany and it was- >> A joke. >> But the point is, the point is it's like, it's a gum bear. >> Is it true? >> No. But it was a dumb American joke. This was told by a French person basically saying... >> But this person was certainly not from- >> Yes. Right. >> Tell you, because I would've been a very bad way. >> But the point is this idea that you have these mega hyper clouds coming in and saying, "Okay, boom, we're putting one here and you're going to use us regardless of the country you're in." How does that, you know... Is there a push within the EU to tear those barriers down? Or are those sovereignty walls enjoyed by the majority because of the way that it changes the business climate? Any thoughts from that perspective? >> Oh yeah. Yeah. To me, it's very simple. It is a hybrid thing. That means that these big hyperscalers are there, not going to be used but what they do is they're going to partition themselves and work with these local people. So that their big thing appears as being independent, smaller data centers. That's the only thing, you know. You build a house and then you put walls between the different, between the different rooms. That's the only thing that happens. So it's not at all, no. At all to Azures or Google cloud. No, it's not that. It just means that there is a structure and organization that has to be put in place in order that the data resides in given geographical locations using their infrastructures, their technologies. That make, does it make sense? >> Yeah. Except that it puts them in the position of having to have a physical presence in each place, which is advantageous in one way and maybe less efficient in another. >> Yeah. But there are some big markets. >> Yeah. And they eventually got to get there. Right. I mean... >> Yeah. >> They started it. One patient in the world where they restarted was in ANZ. And that's what they did. You know, what, 5, 6, 7 years ago. They put their data centers over there because they wanted to gain the Australian market and the New Zealand market. >> So build it and they will come. Daniel, thanks so much for coming to the theCUBE. Very interesting conversation. >> Pleasure. >> Appreciate it. >> Thank you very much. >> All right, we're wrapping up. Day two at VeeamON 2022. Keep it right there. Dave and I will be back right after this break. (vibrant music)

>>Welcome back to the cubes coverage of Veeam on 2022 at the RS. Nice to be at the aria. My co-host Dave Nicholson here. We spend a lot of time at the Venetian convention center, formerly the sand. So it's nice to have a more intimate venue. I really like it here. George Burg is joining us. He's the vice president of data protection at vast data, a company that some of you may not know about. George. >>Welcome a pleasure. Thank you so much for having me. >>So VAs is smoking hot, raised a ton of dough. You've got great founders, hard charging, interesting tech. We've covered a little bit on the Wikibon research side, but give us the overview of the company. Yeah, >>If I could please. So we're here at the, you know, the Veeam show and, you know, the theme is modern data protection, and I don't think there's any company that epitomizes modern data protection more than vast data. The fact that we're able to do an all flash system at exabyte scale, but the economics of cloud object based deep, cheap, and deep archive type solutions and an extremely resilient platform is really game changing for the marketplace. So, and quite frankly, a marketplace from a data protection target space that I think is, is ripe for change and in need of change based on the things that are going on in the marketplace today. >>Yeah. So a lot of what you said is gonna be surprising to people, wait a minute, you're talking about data protection and all flash sure. I thought you'd use cheap and deep disc or, you know, even tape for that or, you know, spin it up in the cloud in a, in a deep archive or a glacier. Explain your approach in, in architecture. Yeah. At a >>High level. Yeah. So great question. We get that question every day and got it in the booth yesterday, probably about 40 or 50 times. How could it be all flash that at an economic point that is the fitting that of, you know, data protection. Yeah. >>What is this Ferrari minivan of which you speak? >>Yeah, yeah, yeah. The minivan that goes 180 miles an hour, right. That, you know, it's, it's really all about the architecture, right? The component tree is, is somewhat similar to what you'll see in other devices. However, it's how we're leveraging them in the architecture and design, you know, from our founders years ago and building a solution that just not, was not available in the marketplace. So yeah, sure. We're using, you know, all flash QLC drives, but the technology, you know, the advanced next generation algorithms or erasure coding or rage striping allows us to be extremely efficient. We also have some technologies around what we call similarity, some advanced data reduction. So you need less, less capacity if you will, with a vast system. So that obviously help obviously helps us out tremendously with their economics. But the other thing is I could sell a customer exactly what they need. If you think about the legacy data protection market purpose built back of appliances, for example, you know, ALA, Adele, Aita, and HP, you know, they're selling systems that are somewhat rigid. There's always a controller in a capacity. It's tied to a model number right. Soon as you need more performance, you buy another, as soon as you need more capacity, you buy another, it's really not modular in any way. It's great >>Model. If you want to just keep, keep billing the >>Customer. Yeah. If, if that, if yeah. And, and I, I think, I think at this point, the purpose, you know, Dave, the purpose built backup appliance market is, is hungry for a change. Right. You know, there's, there's not anyone that has one. It doesn't exist. I'm not just talking about having two because of replication. I'm it's because of organic growth. Ransomware needs to have a second unit, a second copy. And just, and just scalability. Well, you >>Guys saw that fatigue with that model of, oh, you need more buy more, >>Right? Oh, without a doubt, you said we're gonna attack that. Yeah. Yeah. Sorry. No, no, no. That's great. Without a doubt. So, so we can configure a solution exactly. To the need. Cause let's face it. Every single data center, every single vertical market, it's a work of art. You know, everyone's retention policies are different. Everyone's compliance needs are different. There might be some things that are self mandated or government mandated and they're all gonna be somewhat different. Right? The fact of the matter is the way that our, our architecture works, disaggregated shared everything. Architecture is different because when we go back to those model numbers and there's more rigid purpose built back of appliances, or, or maybe a raise designed specifically for data protection, they don't offer that flexibility. And, you know, I, I, I think our, our, our, our entry point is sized to exactly what the need is. Our ease of scalability. You need more performance. We just add another compute, another compute box, what we call our C box. If you need more capacity, we just add another data box, a D box, you know, where the data resides. And, you know, I, you know, especially here at Veeam, I think customers are really clamoring for that next generation solution. They love the idea that there's a low point of entry, but they also love the idea that, that it's easy to scale on demand, you know, as, as needed and as needed basis. >>So just, I wanna be just, I want to go down another layer on that architecturally. Cause I think it's important for people to understand. Sure, exactly what you're saying. When you're talking about scaling, there's this concept of the, of the sort of devil's triangle, the tyranny of this combination of memory, CPU and storage. Sure. And if you're too rigid, like in an appliance, you end up paying for things you don't need. Correct. When all I need is a little more capacity. Correct. All I need is a little more horsepower. Well, you wanna horsepower? No, you gotta buy a bunch of capacity. Exactly. Oh, need capacity. No, no. You need to buy expensive CPUs and suck a bunch of power. All I need is capacity. So what, so go through that, just a little more detail in terms of sure. How you cobble these systems together. Sure. My, the way my brain works, it's always about Legos. So feel free to use Legos. >>Yeah. We, so, so with our disaggregated solution, right. We've separated basically hardware from software. Right. So, so, so that's a good thing, right? From an economic standpoint, but also a design and architecture standpoint, but also an underlining underpinning of that solution is we've also separated the capacity from the performance. And as you just mentioned, those are typically relatively speaking for every other solution on the planet. Those are tied together. Right? Right. So we've disaggregated that as well within our architecture. So we, we again have basically three tier, tier's not the right word, three components that build out a vast cluster. And again, we don't sell like a solution designed by a model number. And that's typically our C boxes connected via NVMe over fabric to a D box C is all the performance D is all the capacity because they're modular. You can end up like our, our baseline product would start out as a one by one, one C box one D box, right? >>Connected again, via different, different size and Vme fabrics. And that could scale to hundreds. When we do have customers with dozens of C boxes, meeting high performance requirements, keep in mind when, when vast data came to market, our founders brought it to the market for high performance computing machine learning, AI data protection was an afterthought, but those found, you know, foundational things that we're able to build in that modularity with performance at scale, it behooves itself, it's perfect fit for data protection. So we see in clients today, just yesterday, two clients standing next to each other in the same market in the same vertical. I have a 30 day retention. I have a 90 day retention. I have to keep one year worth of full backups. I have to keep seven years worth of full backups. We can accommodate both and size it to exactly what the need is. >>Now, the moment that they need one more terabyte, we license into 100 terabyte increments so they can actually buy it in a sense, almost in arrears, we don't turn it off. We don't, there's not a hard cat. They have access to that capacity within the solution that they provide and they can have access immediate access. And without going through, let's face it. A lot of the other companies that we're both thinking of that have those traditional again, purpose-built solutions or arrays. They want you to buy everything up front in advance, signing license agreements. We're the exact opposite. We want you to buy for the need as, and as needed basis. And also because the fact that we're, multi-protocol multi-use case, you see people doing many things within even a single vast cluster. >>I, I wanna come back to the architecture if I, I can and just understand it better. And I said, David, Flo's written a lot about this on our site, but I've had three key meetings in my life with Mosia and I, and I you've obviously know the first week you showed up in my offices at IDC in the late 1980s said, tell me everything, you know about the IBM mainframe IO subsystem. I'm like, oh, this is gonna be a short meeting. And then they came back a year later and showed us symmetric. I was like, wow, that's pretty impressive. The second one was, I gave a speech at 43 south of 42 south. He came up and gave me a big hug. I'm like, wow. He knows me. And the third one, he was in my offices at, in Mabo several years ago. And we were arguing about the flash versus spinning disc. And he's like, I can outperform an all flash array because we've tuned our algorithms for spinning disc. Everybody else is missing that. You're basically saying the opposite. Correct. We've turned tuned our algorithms to, for QC David Flos says Dave, there's a lot of ways to skin a cat in this technology industry. So I wanted to make sure I got that right. Basically you're skinning the cat with different >>Approach. Yeah. We've also changed really the approach of backup. I mean, the, the term backup is really legacy. I mean, that's 10, 12 years of our recovery. The, the story today is really about, about restore resiliency and recovery. So when you think about those legacy solutions, right, they were built to ingest fast, right? We wanna move the data off our primary systems, our, our primary applications and we needed to fit within a backup window. Restore was an afterthought. Restore was, I might occasionally need to restore something. Something got lost, something got re corrupted. I have to restore something today with the, you know, let's face it, the digital pandemic of, of, of cyber threats and, and ransomware it's about sometimes restoring everything. So if you look at a legacy system, they ingest, I'm sorry. They, they, they write very fast. They, they, they can bring the data in very quickly, but their restore time is typically about 20 to 25%. >>So their reading at only 20, 25% of their right speed, you know, is their rate speed. We flip the script on that. We actually read eight times faster than we write. So I could size again to the performance that you need. If you need 40 terabytes, an hour 50 terabytes an hour, we can do that. But those systems that write at 40 terabytes an hour are restoring at only eight. We're writing at a similarly size system, which actually comes out about 51 terabytes an hour 54 terabytes. We're restoring at 432 terabytes an hour. So we've broken the mold of data protection targets. We're no longer the bottleneck. We're no longer part of your recovery plan going to be the issue right now, you gotta start thinking about network connectivity. Do I have, you know, you know, with the, with our Veeam partners, do we have the right data movers, whether virtual or physical, where am I gonna put the data? >>We've really helped customer aided customers to rethinking their whole Dr. Plan, cuz let's face it. When, when ransomware occurs, you might not be able to get in the building, your phones don't work. Who do you call right? By the time you get that all figured out and you get to the point where you're start, you want to start recovering data. If I could recover 50 times faster than a purpose built backup appliance. Right? Think about it. Is it one day or is it 50 days? Am I gonna be back online? Is it one hour? Is it 50 hours? How many millions of dollars, tens of thousands of dollars were like, will that cost us? And that's why our architecture though our thought process and how the system was designed lends itself. So well for the requirements of today, data protection, not backup it's about data protection. >>Can you give us a sense as to how much of your business momentum is from data protection? >>Yeah, sure. So I joined VAs as we were talking chatting before I come on about six months ago. And it's funny, we had a lot of vast customers on their own because they wanted to leverage the platform and they saw the power of VAs. They started doing that. And then as our founders, you know, decided to lean in heavily into this marketplace with investments, not just in people, but also in technology and research and development, and also partnering with the likes of, of Veeam. We, we don't have a data mover, right. We, we require a data mover to bring us the data we've leaned in tremendously. Last quarter was really our, probably our first quarter where we had a lot of marketing and momentum around data protection. We sold five X last quarter than we did all of last year. So right now the momentum's great pipeline looks phenomenal and you know, we're gonna continue to lean in here. >>Describe the relationship with Veeam, like kind of, sort of started recently. It sounds like as customer demand. Yeah. But what's that like, what are you guys doing in terms of engineering integration go to market? >>Yeah. So, so we've gone through all the traditional, you know, verifications and certifications and, and, and I'm proud to say that we kind of blew the, the, the roof off the requirements of a Veeam environ. Remember Veeam was very innovative. 10, 12 years ago, they were putting flash in servers because they, they, they want a high performing environment, a feature such as instant recovery. We've now enabled. When I talked about all those things about re about restore. We had customers yesterday come to us that have tens of thousands of VMs. Imagine that I can spin them up instantaneously and run Veeam's instant recovery solution. While then in the background, restoring those items that is powerful and you need a very fast high performance system to enable that instant. Recovery's not new. It's been in the market for very long, but you can ask nine outta 10 customers walk in the floor. >>They're not able to leverage that today in the systems that they have, or it's over architected and very expensive and somewhat cost prohibitive. So our relationship with Veeam is really skyrocketing actually, as part of that, that success and our, our last quarter, we did seven figure deals here in the United States. We've done deals in Australia. We were chatting. I, I, I happened to be in Dubai and we did a deal there with the government there. So, you know, there's no, there's no specific vertical market. They're all different. You know, it's, it's really driven by, you know, they have a great, you know, cyber resilient message. I mean, you get seen by the last couple of days today and they just want that power that vast. Now there are other systems in the marketplace today that leverage all flash, but they don't have the economic solution that we have. >>No, your, your design anticipated the era that we're we're in right now from it, it anticipated the ability to scale in, to scale, you know, in >>A variety. Well, listen, anticipation of course, co coincidental architecture. It's a fantastic fit either way, either way. I mean, it's a fantastic fit for today. And that's the conversations that we're having with, with all the customers here, it's really all about resiliency. And they know, I mean, one of the sessions, I think it was mentioned 82 or 84% of, of all clients interviewed don't believe that they can do a restore after a cyber attack or it'll cost them millions of dollars. So that there's a tremendous amount of risk there. So time is, is, is ultimately equals dollars. So we see a, a big uptick there, but we're, we're actually continuing our validation work and testing with Veeam. They've been very receptive, very receptive globally. Veeam's channel has also been very receptive globally because you know, their customers are, you know, hungry for innovation as well. And I really strongly believe ASBO brings that >>George, we gotta go, but thank you. Congratulations. Pleasure on the momentum. Say hi to Jeff for us. >>We'll we'll do so, you know, and we'll, can I leave you with one last thought? Yeah, >>Please do give us your final thought. >>If I could, in closing, I think it's pretty important when, when customers are, are evaluating vast, if I could give them three data points, 100% of customers that Triva test vast POC, vast BVAs 100% Gartner peer insights recently did a survey. You know, they, they do it with our, you know, blind survey, dozens of vast customers and never happened before where 100% of the respondents said, yes, I would recommend VA and I will buy VAs again. It was more >>Than two respondents. >>It was more, it was dozens. They won't do it. If it's not dozens, it's dozens. It's not dozen this >>Check >>In and last but not. And, and last but not least our customers are, are speaking with their wallet. And the fact of the matter is for every customer that spends a dollar with vast within a year, they spend three more. So, I mean, if there's no better endorsement, if you have a customer base, a client base that are coming back and looking for more use cases, not just data protection, but again, high performance computing machine learning AI for a company like VA data. >>Awesome. And a lot of investment in engineering, more investment in engineering than marketing. How do I know? Because your capacity nodes, aren't the C nodes. They're the D nodes somehow. So the engineers obviously won that naming. >>They'll always win that one and we, and we, and we let them, we need them. Thank you. So that awesome product >>Sales, it's the golden rule. All right. Thank you, George. Keep it right there. VEON 20, 22, you're watching the cube, Uber, Uber right back.

(upbeat music) >> We're back at VeeamON 2022. We're here at the Aria in Las Vegas Dave Vellante with Dave Nicholson. Bill Andrews is here. He's the president and CEO of ExaGrid, mass boy. Bill, thanks for coming on theCUBE. >> Thanks for having me. >> So I hear a lot about obviously data protection, cyber resiliency, what's the big picture trends that you're seeing when you talk to customers? >> Well, I think clearly we were talking just a few minutes ago, data's growing like crazy, right This morning, I think they said it was 28% growth a year, right? So data's doubling almost just a little less than every three years. And then you get the attacks on the data which was the keynote speech this morning as well, right. All about the ransomware attacks. So we've got more and more data, and that data is more and more under attack. So I think those are the two big themes. >> So ExaGrid as a company been around for a long time. You've kind of been the steady kind of Eddy, if you will. Tell us about ExaGrid, maybe share with us some of the differentiators that you share with customers. >> Sure, so specifically, let's say in the Veeam world you're backing up your data, and you really only have two choices. You can back that up to disc. So some primary storage disc from a Dell, or a Hewlett Packard, or an NetApp or somebody, or you're going to back it up to what's called an inline deduplication appliance maybe a Dell Data Domain or an HPE StoreOnce, right? So what ExaGrid does is we've taken the best of both those but not the challenges of both those and put 'em together. So with disc, you're going to get fast backups and fast restores, but because in backup you keep weekly's, monthly's, yearly retention, the cost of this becomes exorbitant. If you go to a deduplication appliance, and let's say the Dell or the HPs, the data comes in, has to be deduplicated, compare one backup to the next to reduce that storage, which lowers the cost. So fixes that problem, but the fact that they do it inline slows the backups down dramatically. All the data is deduplicated so the restores are slow, and then the backup window keeps growing as the data grows 'cause they're all scale up technologies. >> And the restores are slow 'cause you got to rehydrate. >> You got to rehydrate every time. So what we did is we said, you got to have both. So our appliances have a front end disc cache landing zone. So you're right directed to the disc., Nothing else happens to it, whatever speed the backup app could write at that's the speed we take it in at. And then we keep the most recent backups in that landing zone ready to go. So you want to boot a VM, it's not an hour like a deduplication appliance it's a minute or two. Secondly, we then deduplicate the data into a second tier which is a repository tier, but we have all the deduplicated data for the long term retention, which gets the cost down. And on top of that, we're scale out. Every appliance has networking processor memory end disc. So if you double, triple, quadruple the data you double, triple, quadruple everything. And if the backup window is six hours at 100 terabyte it's six hours at 200 terabyte, 500 terabyte, a petabyte it doesn't matter. >> 'Cause you scale out. >> Right, and then lastly, our repository tier is non-network facing. We're the only ones in the industry with this. So that under a ransomware attack, if you get hold of a rogue server or you hack the media server, get to the backup storage whether it's disc or deduplication appliance, you can wipe out all the backup data. So you have nothing to recover from. In our case, you wipe it out, our landing zone will be wiped out. We're no different than anything else that's network facing. However, the only thing that talks to our repository tier is our object code. And we've set up security policies as to how long before you want us to delete data, let's say 10 days. So if you have an attack on Monday that data doesn't get deleted till like a week from Thursday, let's say. So you can freeze the system at any time and do restores. And then we have immutable data objects and all the other stuff. But the culmination of a non-network facing tier and the fact that we do the delayed deletes makes us the only one in the industry that can actually truly recover. And that's accelerating our growth, of course. >> Wow, great description. So that disc cache layer is a memory, it's a flash? >> It's disc, it's spinning disc. >> Spinning disc, okay. >> Yeah, no different than any other disc. >> And then the tiered is what, less expensive spinning disc? >> No, it's still the same. It's all SaaS disc 'cause you want the quality, right? So it's all SaaS, and so we use Western Digital or Seagate drives just like everybody else. The difference is that we're not doing any deduplication coming in or out of that landing zone to have fast backups and fast restores. So think of it like this, you've got disc and you say, boy it's too expensive. What I really want to do then is put maybe a deduplication appliance behind it to lower the cost or reverse it. I've got a deduplication appliance, ugh, it's too slow for backups and restores. I really want to throw this in front of it to have fast backups first. Basically, that's what we did. >> So where does the cost savings, Bill come in though, on the tier? >> The cost savings comes in the fact that we got deduplication in that repository. So only the most recent backup >> Ah okay, so I get it. >> are the duplicated data. But let's say you had 40 copies of retention. You know, 10 weekly's, 36 monthly's, a few yearly. All of that's deduplicated >> Okay, so you're deduping the stuff that's not as current. >> Right. >> Okay. >> And only a handful of us deduplicate at the layer we do. In other words, deduplication could be anywhere from two to one, up to 50 to one. I mean it's all over the place depending on the algorithm. Now it's what everybody's algorithms do. Some backup apps do two to one, some do five to one, we do 20 to one as well as much as 50 to one depending on the data types. >> Yeah, so the workload is going to largely determine the combination >> The content type, right. with the algos, right? >> Yeah, the content type. >> So the part of the environment that's behind the illogical air gap, if you will, is deduped data. >> Yes. >> So in this case, is it fair to say that you're trading a positive economic value for a little bit longer restore from that environment? >> No, because if you think about backup 95% of the customers restores are from the most recent data. >> From the disc cache. >> 95% of the time 'cause you think about why do you need fast restores? Somebody deleted a file, somebody overwrote a file. They can't go work, they can't open a file. It's encrypted, it's corrupted. That's what IT people are trying to keep users productive. When do you go for longer-term retention data? It's an SEC audit. It's a HIPAA audit. It's a legal discovery, you don't need that data right away. You have days and weeks to get that ready for that legal discovery or that audit. So we found that boundary where you keep users productive by keeping the most recent data in the disc cache landing zone, but anything that's long term. And by the way, everyone else is long term, at that point. >> Yeah, so the economics are comparable to the dedupe upfront. Are they better, obviously get the performance advance? >> So we would be a lot looped. The thing we replaced the most believe it or not is disc, we're a lot less expensive than the disc. I was meeting with some Veeam folks this morning and we were up against Cisco 3260 disc at a children's hospital. And on our quote was $500,000. The disc was 1.4 million. Just to give you an example of the savings. On a Data Domain we're typically about half the price of a Data Domain. >> Really now? >> The reason why is their front end control are so expensive. They need the fastest trip on the planet 'cause they're trying to do inline deduplication. >> Yeah, so they're chasing >> They need the fastest memory >> on the planet. >> this chips all the time. They need SSD on data to move in and out of the hash table. In order to keep up with inline, they've got to throw so much compute at it that it drives their cost up. >> But now in the case of ransomware attack, are you saying that the landing zone is still available for recovery in some circumstances? Or are you expecting that that disc landing zone would be encrypted by the attacker? >> Those are two different things. One is deletion, one is encryption. So let's do the first scenario. >> I'm talking about malicious encryption. >> Yeah, absolutely. So the first scenario is the threat actor encrypts all your primary data. What's does he go for next? The backup data. 'Cause he knows that's your belt and suspend is to not pay the ransom. If it's disc he's going to go in and put delete commands at the disc, wipe out the disc. If it's a data domain or HPE StoreOnce, it's all going to be gone 'cause it's one tier. He's going to go after our landing zone, it's going to be gone too. It's going to wipe out our landing zone. Except behind that we have the most recent backup deduplicate in the repository as well as all the other backups. So what'll happen is they'll freeze the system 'cause we weren't going to delete anything in the repository for X days 'cause you set up a policy, and then you restore the most recent backup into the landing zone or we can restore it directly to your primary storage area, right? >> Because that tier is not network facing. >> That's right. >> It's fenced off essentially. >> People call us every day of the week saying, you saved me, you saved me again. People are coming up to me here, you saved me, you saved me. >> Tell us a story about that, I mean don't give me the names but how so. >> I'll actually do a funnier story, 'cause these are the ones that our vendors like to tell. 'Cause I'm self-serving as the CEO that's good of course, a little humor. >> It's your 15 minutes of job. >> That is my 15 minutes of fame. So we had one international company who had one ExaGrid at one location, 19 Data Domains at the other locations. Ransomware attack guess what? 19 Data Domains wiped out. The one ExaGrid, the only place they could restore. So now all 20 locations of course are ExaGrids, China, Russia, Mexico, Germany, US, et cetera. They rolled us out worldwide. So it's very common for that to occur. And think about why that is, everyone who's network facing you can get to the storage. You can say all the media servers are buttoned up, but I can find a rogue server and snake my way over the storage, I can. Now, we also of course support the Veeam Data Mover. So let's talk about that since we're at a Veeam conference. We were the first company to ever integrate the Veeam Data Mover. So we were the first actually ever integration with Veeam. And so that Veeam Data Mover is a protocol that goes from Veeam to the ExaGrid, and we run it on both ends. So that's a more secure protocol 'cause it's not an open format protocol like SaaS. So with running the Veeam Data Mover we get about 30% more performance, but you do have a more secure protocol layer. So if you don't get through Veeam but you get through the protocol, boom, we've got a stronger protocol. If you make it through that somehow, or you get to it from a rogue server somewhere else we still have the repository. So we have all these layers so that you can't get at it. >> So you guys have been at this for a while, I mean decade and a half plus. And you've raised a fair amount of money but in today's terms, not really. So you've just had really strong growth, sequential growth. I understand it, and double digit growth year on year. >> Yeah, about 25% a year right now >> 25%, what's your global strategy? >> So we have sales offices in about 30 countries already. So we have three sales teams in Brazil, and three in Germany, and three in the UK, and two in France, and a lot of individual countries, Chile, Argentina, Columbia, Mexico, South Africa, Saudi, Czech Republic, Poland, Dubai, Hong Kong, Australia, Singapore, et cetera. We've just added two sales territories in Japan. We're adding two in India. And we're installed in over 50 countries. So we've been international all along the way. The goal of the company is we're growing nicely. We have not raised money in almost 10 years. >> So you're self-funding. You're cash positive. >> We are cash positive and self-funded and people say, how have you done that for 10 years? >> You know what's interesting is I remember, Dave Scott, Dave Scott was the CEO of 3PAR, and he told me when he came into that job, he told the VCs, they wanted to give him 30 million. He said, I need 80 million. I think he might have raised closer to a hundred which is right around what you guys have raised. But like you said, you haven't raised it in a long time. And in today's terms, that's nothing, right? >> 100 is 500 in today's terms. >> Yeah, right, exactly. And so the thing that really hurt 3PAR, they were public companies so you could see all this stuff is they couldn't expand internationally. It was just too damn expensive to set up the channels, and somehow you guys have figured that out. >> 40% of our business comes out of international. We're growing faster internationally than we are domestically. >> What was the formula there, Bill, was that just slow and steady or? >> It's a great question. >> No, so what we did, we said let's build ExaGrid like a McDonald's franchise, nobody's ever done that before in high tech. So what does that mean? That means you have to have the same product worldwide. You have to have the same spares model worldwide. You have to have the same support model worldwide. So we early on built the installation. So we do 100% of our installs remotely. 100% of our support remotely, yet we're in large enterprises. Customers racks and stacks the appliances we get on with them. We do the entire install on 30 minutes to about three hours. And we've been developing that into the product since day one. So we can remotely install anywhere in the world. We keep spares depots all over the world. We can bring 'em up really quick. Our support model is we have in theater support people. So they're in Europe, they're in APAC, they're in the US, et cetera. And we assign customers to the support people. So they deal with the same support person all the time. So everything is scalable. So right now we're going to open up India. It's the same way we've opened up every other country. Once you've got the McDonald's formula we just stamp it all over the world. >> That's amazing. >> Same pricing, same product same model, same everything. >> So what was the inspiration for that? I mean, you've done this since day one, which is what like 15, 16 years ago. Or just you do engineering or? >> No, so our whole thought was, first of all you can't survive anymore in this world without being an international company. 'Cause if you're going to go after large companies they have offices all over the world. We have companies now that have 17, 18, 20, 30 locations. And there were in every country in the world, you can't go into this business without being able to ship anywhere in the world and support it for a single customer. You're not going into Singapore because of that. You're going to Singapore because some company in Germany has offices in the U.S, Mexico Singapore and Australia. You have to be international. It's a must now. So that was the initial thing is that, our goal is to become a billion dollar company. And we're on path to do that, right. >> You can see a billion. >> Well, I can absolutely see a billion. And we're bigger than everybody thinks. Everybody guesses our revenue always guesses low. So we're bigger than you think. The reason why we don't talk about it is we don't need to. >> That's the headline for our writers, ExaGrid is a billion dollar company and nobody's know about it. >> Million dollar company. >> On its way to a billion. >> That's right. >> You're not disclosing. (Bill laughing) But that's awesome. I mean, that's a great story. I mean, you kind of are a well kept secret, aren't you? >> Well, I dunno if it's a well kept secret. You know, smaller companies never have their awareness of big companies, right? The Dells of the world are a hundred billion. IBM is 70 billion, Cisco is 60 billion. Easy to have awareness, right? If you're under a billion, I got to give a funny story then I think we got to close out here. >> Oh go ahead please. >> So there's one funny story. So I was talking to the CIO of a super large Fortune 500 company. And I said to him, "Just so who do you use?" "I use IBM Db2, and I use, Cisco routers, and I use EMC primary storage, et cetera. And I use all these big." And I said, "Would you ever switch from Db2?" "Oh no, the switching costs would kill me. I could never go to Oracle." So I said to him, "Look would you ever use like a Pure Storage, right. A couple billion dollar company." He says, "Who?" >> Huh, interesting. >> I said to him, all right so skip that. I said, "VMware, would you ever think about going with Nutanix?" "Who?" Those are billion dollar plus companies. And he was saying who? >> Public companies. >> And he was saying who? That's not uncommon when I talk to CIOs. They see the big 30 and that's it. >> Oh, that's interesting. What about your partnership with Veeam? Tell us more about that. >> Yeah, so I would actually, and I'm going to be bold when I say this 'cause I think you can ask anybody here at the conference. We're probably closer first of all, to the Veeam sales force than any company there is. You talk to any Veeam sales rep, they work closer with ExaGrid than any other. Yeah, we are very tight in the field and have been for a long time. We're integrated with the Veeam Data Boomer. We're integrated with SOBR. We're integrated with all the integrations or with the product as well. We have a lot of joint customers. We actually do a lot of selling together, where we go in as Veeam ExaGrid 'cause it's a great end to end story. Especially when we're replacing, let's say a Dell Avamar to Dell Data Domain or a Dell Network with a Dell Data Domain, very commonly Veeam ExaGrid go in together on those types of sales. So we do a lot of co-selling together. We constantly train their systems engineers around the world, every given week we're training either inside sales teams, and we've trained their customer support teams in Columbus and Prague. So we're very tight with 'em we've been tight for over a decade. >> Is your head count public? Can you share that with us? >> So we're just over 300 employees. >> Really, wow. >> We have 70 open positions, so. >> Yeah, what are you looking for? Yeah, everything, right? >> We are looking for engineers. We are looking for customer support people. We're looking for marketing people. We're looking for inside sales people, field people. And we've been hiring, as of late, major account reps that just focus on the Fortune 500. So we've separated that out now. >> When you hire engineers, I mean I think I saw you were long time ago, DG, right? Is that true? >> Yeah, way back in the '80s. >> But systems guy. >> That's how old I am. >> Right, systems guy. I mean, I remember them well Eddie Castro and company. >> Tom West. >> EMV series. >> Tom West was the hero of course. >> The EMV 4000, the EMV 20,000, right? >> When were kids, "The Soul of a New Machine" was the inspirational book but anyway, >> Yeah Tracy Kidder, it was great. >> Are you looking for systems people, what kind of talent are you looking for in engineering? >> So it's a lot of Linux programming type stuff in the product 'cause we run on a Linux space. So it's a lot of Linux programs so its people in those storage. >> Yeah, cool, Bill, hey, thanks for coming on to theCUBE. Well learned a lot, great story. >> It's a pleasure. >> That was fun. >> Congratulations. >> Thanks. >> And good luck. >> All right, thank you. >> All right, and thank you for watching theCUBE's coverage of VeeamON 2022, Dave Vellante for Dave Nicholson. We'll be right back right after this short break, stay with us. (soft beat music)

(light music playing) >> Welcome back to VEEAMON 2022 in Las Vegas. We're at the Aria. This is theCUBE and we're covering two days of VEEAMON. We've done a number of VEEAMONs before, we did Miami, we did New Orleans, we did Chicago and we're, we're happy to be back live after two years of virtual VEEAMONs. I'm Dave Vellante. My co-host is David Nicholson. Eric Herzog is here. You think he's, Eric's been on theCUBE, I think more than any other guest, including Pat Gelsinger, who at one point was the number one guest. Eric Herzog, CMO of INFINIDAT great to see you again. >> Great, Dave, thank you. Love to be on theCUBE. And of course notice my Hawaiian shirt, except I now am supporting an INFINIDAT badge on it. (Dave laughs) Look at that. >> Is that part of the shirt or is that a clip-on? >> Ah, you know, one of those clip-ons but you know, it looks good. Looks good. >> Hey man, what are you doing at VEEAMON? I mean, you guys started this journey into data protection several years ago. I remember we were actually at one of their competitors' events when you first released it, but tell us what's going on with Veeam. >> So we do a ton of stuff with Veeam. We do custom integration. We got some integration on the snapshotting side, but we do everything and we have a purpose built backup appliance known as InfiniGuard. It works with Veeam. We also actually have some customers who use our regular primary storage device as a backup target. The InfiniGuard product will do the data reduction, the dedupe compression, et cetera. The standard product does not, it's just a standard high performance array. We will compress the data, but we have customers that do it either way. We have a couple customers that started with the InfiniBox and then transitioned to the InfiniGuard, realizing that why would you put it on regular storage? Why not go to something that's customized for it? So we do that. We do stuff in the field with them. We've been at all the VEEAMONs since the, since like, I think the second one was the first one we came to. We're doing the virtual one as well as the live one. So we've got a little booth inside, but we're also doing the virtual one today as well. So really strong work with Veeam, particularly at the field level with the sales guys and in the channel. >> So when INFINIDAT does something, you guys go hardcore, high end, fast recovery, you just, you know, reliable, that's kind of your brand. Do you see this movement into data protection as kind of an adjacency to your existing markets? Is it a land and expand strategy? Can you kind of explain the strategy there. >> Ah, so it's actually for us a little bit of a hybrid. So we have several accounts that started with InfiniBox and now have gone with the InfiniGuard. So they start with primary storage and go with secondary storage/modern data protection. But we also have, in fact, we just got a large PO from a Fortune 50, who was buying the InfiniGuard first and now is buying our InfiniBox. >> Both ways. Okay. >> All flash array. And, but they started with backup first and then moved to, so we've got them moving both directions. And of course, now that we have a full portfolio, our original product, the InfiniBox, which was a hybrid array, outperformed probably 80 to 85% of the all flash arrays, 'cause the way we use DRAM. And what's so known as our mural cash technology. So we could do very well, but there is about, you know, 15, 20% of the workloads we could not outperform the competition. So then we had an all flash array and purpose built backup. So we can do, you know, what I'll say is standard enterprise storage, high performance enterprise storage. And then of course, modern data protection with our partnerships such as what we do with Veeam and we've incorporated across the entire portfolio, intense cyber resilience technology. >> Why does the world, Eric, need another purpose built backup appliance? What do you guys bring that is filling a gap in the marketplace? >> Well, the first thing we brought was much higher performance. So when you look at the other purpose built backup appliances, it's been about our ability to have incredibly high performance. The second area has been CapEx and OpEx reduction. So for example, we have a cloud service provider who happens to be in South Africa. They had 14 purpose built backup appliances from someone else, seven in one data center and seven in another. Now they have two InfiniGuards, one in each data center handling all of their backup. You know, they're selling backup as a service. They happen to be using Veeam as well as one other backup company. So if you're the cloud provider from their perspective, they just dramatically reduce their CapEx and OpEx. And of course they've made it easier for them. So that's been a good story for us, that ability to consolidation, whether it be on primary storage or secondary storage. We have a very strong play with cloud providers, particularly those meeting them in small that have to compete with the hyperscalers right. They don't have the engineering of Amazon or Google, right? They can't compete with what the Azure guys have got, but because the way both the InfiniGuard and the InfiniBox work, they could dramatically consolidate workloads. We probably got 30 or 40 midsize and actually several members of the top 10 telcos use us. And when they do their clouds, both their internal cloud, but actually the clouds that are actually running the transmissions and the traffic, it actually runs on InfiniBox. One of them has close to 200 petabytes of InfiniBox and InfiniBox, all flash technology running one of the largest telcos on the planet in a cloud configuration. So all that's been very powerful for us in driving revenue. >> So phrases of the week have been air gap, logical air gap, immutable. Where does InfiniGuard fit into that universe? And what's the profile of the customer that's going to choose InfiniGuard as the target where they're immutable, Write Once Read Many, data is going to live. >> So we did, we announced our InfiniSafe technology first on the InfiniGuard, which actually earlier this year. So we have what I call the four legs of the stool of cyber resilience. One is immutable snapshots, but that's only part of it. Second is logical air gapping, and we can do both local and remote and we can provide and combine local with remote. So for example, what that air gap does is separate the management plane from the actual data plane. Okay. So in this case, the Veeam data backup sets. So the management cannot touch that immutable, can't change it, can't delete it. can't edit it. So management is separated once you start and say, I want to do an immutable snap of two petabytes of Veeam backup dataset. Then we just do that. And the air gap does it, but then you could take the local air gap because as you know, from inception to the end of an attack can be close to 300 days, which means there could be a fire. There could be a tornado, there could be a hurricane, there could be an earthquake. And in the primary data center, So you might as well have that air gap just as you would do- do a remote for disaster recovery and business continuity. Then we have the ability to create a fenced forensic environment to evaluate those backup data sets. And we can do that actually on the same device. That is the purpose built backup appliance. So when you look at the architectural, these are public from our competitors, including the guys that are in sort of Hopkinton/Austin, Texas. You can see that they show a minimum of two physical devices. And in many cases, a third, we can do that with one. So not only do we get the fence forensic environment, just like they do, but we do it with reduction, both CapEx and OpEx. Purpose built backup is very high performance. And then the last thing is our ability to recover. So some people talk about rapid recovery, I would say, they dunno what they're talking about. So when we launched the InfiniGuard with InfiniSafe, we did a live demo, 1.5 petabytes, a Veeam backup dataset. We recovered it in 12 minutes. So once you've identified and that's on the InfiniGuard. On the InfiniBox, once you've identified a good copy of data to do the recovery where you're free of malware ransomware, we can do the recovery in three to five seconds. >> Okay. >> So really, really quick. Actually want to double click on something because people talk about immutable copies, immutable snapshots in particular, what have the actual advances been? I mean, is this simply a setting that maybe we didn't set for retention at some time in the past, or if you had to engineer something net new into a system so to provide that logical air gap. >> So what's net new is the air gapping part. Immutable snapshots have been around, you know, before we were on screen, you talked about WORM, Write Once Read Many. Well, since I'm almost 70 years old, I actually know what that means. When you're 30 or 40 or 50, you probably don't even know what a WORM is. Okay. And the real use of immutable snapshots, it was to replace WORM which was an optical technology. And what was the primary usage? Regulatory and compliance, healthcare, finance and publicly traded companies that were worried about. The SEC or the EU or the Japanese finance ministry coming down on them because they're out of compliance and regulatory. That was the original use of immutable snap. Then people were, well, wait a second. Malware ransomware could attack me. And if I got something that's not changeable, that makes it tougher. So the real magic of immutability was now creating the air gap part. Immutability has been around, I'd say 25 years. I mean, WORMs sort of died back when I was at Mac store the first time. So that was 1990-ish is when WORMs sort of fell away. And there have been immutable snapshots from most of the major storage vendors, as well as a lot of the small vendors ever since they came out, it's kind of like a checkbox item because again, regulatory and compliance, you're going to sell to healthcare, finance, public trade. If you don't have the immutable snapshot, then they don't have their compliance and regulatory for SEC or tax purposes, right? With they ever end up in an audit, you got to produce data. And no one's using a WORM drive anymore to my knowledge. >> I remember the first storage conference I ever went to was in Monterey. It had me in the early 1980s, 84 maybe. And it was a optical disc drive conference. The Jim Porter of optical. >> Yep. (laughs) >> I forget what the guy's name was. And I remember somebody coming up to me, I think it was like Bob Payton rest his soul, super smart strategy guy said, this is never going to happen because of the cost and that's what it was. And now you've got that capability on flash, you know, hard disk, et cetera. >> Right. >> So the four pillars, immutability, the air gap, both local and remote, the fence forensics and the recovery speed. Right? >> Right. Pick up is one thing. Recovery is everything. Those are the four pillars, right? >> Those are the four things. >> And your contention is that those four things together differentiate you from the competition. You mentioned, you know, the big competition, but how unique is this in the marketplace, those capabilities and how difficult is it to replicate? >> So first of all, if someone really puts their engineering hat to it, it's not that hard to replicate. It takes a while. Particularly if you're doing an enterprise, for example, our solutions all have a hundred percent availability guarantee. That's hard to do. Most guys have seven nines. >> That's hard. >> We really will guarantee a hundred percent availability. We offer an SLA that's included when you buy. We don't charge extra for it. It's like if you want it, like you just get it. Second thing is really making sure on the recovery side is the hardest part, particularly on a purpose built backup appliance. So when you look at other people and you delve into their public material, press releases, white paper, support documentation. No one's talking about. Yeah, we can take a 1.5 petabyte Veeam backup data set and make it available in 12 minutes and 12 seconds, which was the exact time that we did on our live demo when we launched the product in February of 2022. No one's talking that. On primary storage, you're hearing some of the vendors such as my old employer that also who, also starts with an "I", talk about a recovery time of two to three hours once you have a known good copy. On primary storage, once we have a known good copy, we're talking three to five seconds for that copy to be available. So that's just sort of the power of the snapshot technology, how we manage our metadata and what we've done, which previous to cyber resiliency, we were known for our replication capability and our snapshot capability from an enterprise class data store. That's what people said. INFINIDAT really knows how to do the replication snapshot. I remember our founder was one of the technical founders of EMC for a product known as the Symmetric, which then became the DMAX, the VMAX and is now is the PowerMax. That was invented by the guy who founded INFINIDAT. So that team has the real chops at enterprise high-end storage to the global fortune 2000. And what are the key feature checkbox items they need that's in both the InfiniBox and also in the InfiniGuard. >> So the business case for cyber resiliency is changing. As Dave said, we've had a big dose last several months, you know, couple years actually, of the importance of cyber resiliency, given all the ransomware tax, et cetera. But it sounds like the business case is shifting really focused on avoiding that risk, avoiding that downtime time versus the cost. The cost is always important. I mean, you got a consolidation play here, right? >> Yeah, yeah. >> Dedupe, does dedupe come into play? >> So on the InfiniGuard we do both dedupe and compression. On the InfiniBox we only do compression. So we do have data reduction. It depends on which product you're using from a Veeam perspective. Most of that now is with the InfiniGuard. So you get the block level dedupe and you get compression. And if you can do both, depending on the data set, we do both. >> How does that affect recovery time? >> Yeah, good question. >> So it doesn't affect recovery times. >> Explain why. >> So first of all, when you're doing a backup data set, the final final recovery, you recovered the backup data set, whether it's Veeam or one of their competitors, you actually make it available to the backup administrator to do a full restore of a backup data set. Okay. So in that case, we get it ready and expose it to the Veeam admin or some other backup admin. And then they launch the Veeam software or the other software and do a restore. Okay. So it's really a two step process on the secondary storage model and actually three. First identifying a known good backup copy. Second then we recover, which is again 12, 13 minutes. And then the backup admin's got to do a, you know, a restore of the backup 'cause it's backup data set in the format of backup, which is different from every backup vendor. So we support that. We get it ready to go. And then whether it's a Veeam backup administrator and quite honestly, from our perspective, most of our customers in the global fortune 2000, 25% of the fortune 50 use INIFINIDAT products. 25% and we're a tiny company. So we must have some magic fairy dust that appeals to the biggest companies on the planet. But most of our customers in that area and actually say probably in the fortune 500 actually use two to three different backup packages. So we can support all those on a single InfiniGuard or multiples depending on how big their backup data sets. Our biggest InfiniGuard is 50 petabytes counting the data reduction technology. So we get that ready. On the InfiniBox, the recovery really is, you know, a couple of seconds and in that case, it's primary data in block format. So we just make that available. So on the InfiniBox, the recovery is once, well two. Identifying a known good copy, first step, then just doing recovery and it's available 'cause it's blocked data. >> And that recovery doesn't include movement of a whole bunch of data. It's essentially realignment of pointers to where the good data is. >> Right. >> Now in the InfiniBox as well as in InfiniGuard. >> No, it would be, So in the case of that, in the case of the InfiniGuard, it's a full recovery of a backup data set. >> Okay. >> So the backup software just launches and it sees, >> Okay. >> your backup one of Veeam and just starts doing a restore with the Veeam restoration technology. Okay? >> Okay. >> In the case of the block, as long as the physical InfiniBox, if that was the primary storage and then filter box is not damaged when you make it available, it's available right away to the apps. Now, if you had an issue with the app side or the physical server side, and now you're pointing new apps and you had to reload stuff on that side, you have to point it at that InfiniBox which has the data. And then you got to wait for the servers and the SAP or Oracle or Mongo, Cassandra to recognize, oh, this is my primary storage. So it depends on the physical configuration on the server side and the application perspective, how bad were the apps damaged? So let's take malware. Malware is even worse because you either destroying data or messing, playing with the app so that the app is now corrupted as well as the data is corrupted. So then it's going to take longer the block data's ready, the SAP workload. And if the SAP somehow was compromised, which is a malware thing, not a ransomware thing, they got to reload a good copy of SAP before it can see the data 'cause the malware attacked the application as well as the data. Ransomware doesn't do that. It just holds it for ransom and it encrypts. >> So this is exactly what we're talking about. When we talk about operational recovery and automation, Eric is addressing the reality that it doesn't just end at the line above some arbitrary storage box, you know, reaching up real recovery, reaches up into the application space and it's complicated. >> That's when you're actually recovered. >> Right. >> When the application- >> Well, think of it like a disaster. >> Okay. >> Yes, right. >> I'll knock on woods since I was born and still live in California. Dave too. Let's assume there's a massive earthquake in the bay area in LA. >> Let's not. >> Okay. Let's yes, but hypothetically and the data center's cat five. It doesn't matter what they're, they're all toast. Okay. Couple weeks later it's modern. You know, people figure out what to do and certain buildings don't fall down 'cause of the way earthquake standards are in California now. So there's data available. They move into temporary space. Okay. Data's sitting there in the Colorado data center and they could do a restore. Well, they can't do a restore. How many service did they need? Had they reloaded all of the application software to do a restoration. What happened to the people? If no one got injured, like in the 1989 earthquake in California, very few people got injured yet cost billions of dollars. But everyone was watching this San Francisco giants played in Oakland, >> I remember >> so no one was on the road. >> Al Michael's. >> Epic moment. >> Imagine it's in the middle of commute time in LA and San Francisco, hundreds of thousands of people. What if it's your data center team? Right? So there's a whole bunch around disaster recovery and business country that have nothing to do with the storage, the people, what your process. So I would argue that malware ransomware is a disaster and it's exactly the same thing. You know, you got the known good copy. You've got okay. You're sure that the SAP and Oracle, especially on the malware side, weren't compromised. On the ransomware side, you don't have to worry about that. And those things, you got to take a look at just as if it, I would argue malware and ransomware is a disaster and you need to have a process just like you would. If there was an earthquake, a fire or a flood in the data center, you need a similar process. That's slightly different, but the same thing, servers, people, software, the data itself. And when you have that all mapped out, that's how you do successful malware ransomeware recovery. It's a different type of disaster. >> It's absolutely a disaster. It comes down to business continuity and be able to transact business with as little disruption as possible. We heard today from the keynotes and then Jason Buffington came on about the preponderance of ransomware. Okay. We know that. But then the interesting stat was the percentage of customers that paid the ransom about a third weren't able to recover. And so 'cause you kind of had this feeling of all right, well, you know, see it on, you know, CNBC, should you pay the ransom or not? You know, pay the ransom. Okay. You'll get back. But no, it's not the case. You won't necessarily get back. So, you know, Veeam stated, Hey, our goal is to sort of eliminate that problem. Are you- You feel like you guys in a partnership can actually achieve that. >> Yes. >> So, and you have customers that have actually avoided, you know, been hit and were able to- >> We have people who won't publicly say they've been hit, but the way they talk about what they did, like in a meeting, they were hit and they were very thankful. >> (laughs) Yeah. >> And so that's been very good. I- >> So we got proof. >> Yes, we absolutely have proof. And quite honestly, with the recent legislation in the United States, malware and ransomware actually now is also regulatory and compliance. >> Yeah. >> Because the new law states mid-March that whether it's Herzog's bar and grill to bank of America or any large foreign company doing business in the US, you have to report to the United States federal government, any attack, same with the county school district with any local government, any agency, the federal government, as well as every company from the tiniest to the largest in the world that does, they're supposed to report it 'cause the government is trying to figure out how to fight it. Just the way if you don't report burglary, how they catch the burglars. >> Does your solution simplify testing in any way or reduce the risk of testing? >> Well, because the recovery is so rapid, we recommend that people do this on a regular basis. So for example, because the recovery is so quick, you can recover in 12 minutes while we do not practice, let's say once a month or once every couple weeks. And guess what? It also allows you to build a repository of known good copies. Remember when you get ransomeware, no one's going to come say, Hey, I'm Mr. Rans. I'm going to steal your stuff. It's all done surreptitiously. They're all James Bond on the sly who doesn't say "By the way, I'm James Bond". They are truly underneath the radar. And they're very slowly encrypting that data set. So guess what? Your primary data and your backup data that you don't want to be attacked can be attacked. So it's really about finding a known good copy. So if you're doing this on a regular basis, you can get an index of known good copies. >> Right. >> And then, you know, oh, I can go back to last Tuesday and you know that that's good. Otherwise you're literally testing Wednesday, Thursday, Friday, Saturday to try to find a known good copy, which delays the recovery process 'cause you really do have to test. They make sure it's good. >> If you increase that frequency, You're going to protect yourself. That's why I got to go. Thanks so much for coming on theCUBEs. Great to see you. >> Great. Thank you very much. I'll be wearing a different Hawaiian shirt next to. >> All right. That sounds good. >> All right, Eric Herzog, Eric Herzog on theCUBE, Dave Vallante for David Nicholson. We'll be right back at VEEAMON 2022. Right after this short break. (light music playing)

>>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