>> Well, welcome back here to the Venetian. We're in Las Vegas. It is Wednesday, Day 2 of our coverage here of AWS re:Invent, 22. I'm your host, John Walls on theCUBE and it's a pleasure to welcome in two more guests as part of our AWS startup showcase, which is again part of the startup program globally at AWS. I've got Anant Verma, who is the Vice President of Engineering at Elation. Anant, good to see you, sir. >> Good to see you too. >> Good to be with us. And Haseeb Budhani, who is the CEO and co-founder of Rafay Systems. Good to see you, sir. >> Good to see you again. >> Thanks for having, yeah. A cuber, right? You've been on theCUBE? >> Once or twice. >> Many occasions. But a first timer here, as a matter of fact, glad to have you aboard. All right, tell us about Elation. First for those whom who might not be familiar with what you're up to these days, just give it a little 30,000 foot level. >> Sure, sure. So, yeah, Elation is a startup and a leader in the enterprise data intelligence space. That really includes a lot of different things including data search, data discovery, metadata management, data cataloging, data governance, data policy management, a lot of different things that companies want to do with the hoards of data that they have and Elation, our product is the answer to solve some of those problems. We've been doing pretty good. Elation is in running for about 10 years now. We are a series A startup now, we just raised around a few, a couple of months ago. We are already a hundred million plus in revenue. So. >> John: Not shabby. >> Yeah, it's a big benchmark for companies to, startup companies, to cross that milestone. So, yeah. >> And what's the relationship? I know Rafay and you have worked together, in fact, the two of you have, which I find interesting, you have a chance, you've been meeting on Zoom for a number of months, as many of us have it meeting here for the first time. But talk about that relationship with Rafay. >> Yeah, so I actually joined Elation in January and this is part of the move of Elation to a more cloud native solution. So, we have been running on AWS since last year and as part of making our solution more cloud native, we have been looking to containerize our services and run them on Kubernetes. So, that's the reason why I joined Elation in the first place to kind of make sure that this migration or move to a cloud native actually works out really well for us. This is a big move for the companies. A lot of companies that have done in the past, including, you know, Confluent or MongoDB, when they did that, they actually really reap great benefits out of that. So to do that, of course, you know, as we were looking at Kubernetes as a solution, I was personally more looking for a way to speed up things and get things out in production as fast as possible. And that's where I think, Janeb introduced us... >> That's right. >> Two of us. I think we share the same investor actually, so that's how we found each other. And yeah, it was a pretty simple decision in terms of, you know, getting the solution, figuring it out if it's useful for us and then of course, putting it out there. >> So you've hit the keyword, Kubernetes, right? And, so if you would to honestly jump in here, there are challenges, right? That you're trying to help them solve and you're working on the Kubernetes platform. So, you know, just talk about that and how that's influenced the work that the two of you are doing together. >> Absolutely. So, the business we're in is to help companies who adopt Kubernetes as an orchestration platform do it easier, faster. It's a simple story, right? Everybody is using Kubernetes, but it turns out that Kubernetes is actually not that easy to to operationalize, playing in a sandbox is one thing. Operationalizing this at a certain level of scale is not easy. Now, we have a lot of enterprise customers who are deploying their own applications on Kubernetes, and we've had many, many of them. But when it comes to a company like Elation, it's a more complicated problem set because they're taking a very complex application, their application, but then they're providing that as a service to their customers. So then we have a chain of customers we have to make happy. Anant's team, the platform organization, his internal customers who are the developers who are deploying applications, and then, the company has customers, we have to make sure that they get a good experience as they consume this application that happens to be running on Kubernetes. So that presented a really interesting challenge, right? How do we make this partnership successful? So I will say that, we've learned a lot from each other, right? And, end of the day, the goal is, my customer, Anant's specifically, right? He has to feel that, this investment, 'cause he has to pay us money, we would like to get paid. >> John: Sure. (John laughs) >> It reduces his internal expenditure because otherwise he'd have to do it himself. And most importantly, it's not the money part, it's that he can get to a certain goalpost significantly faster because the invention time for Kubernetes management, the platform that you have to build to run Kubernetes is a very complex exercise. It took us four and a half years to get here. You want to do that again, as a company, right? Why? Why do you want to do that? We, as Rafay, the way I think about what we deliver, yes, we sell a product, but to what end? The product is the what, the why, is that every enterprise, every ISV is building a Kubernetes platform in house. They shouldn't, they shouldn't need to. They should be able to consume that as a service. They consume the Kubernetes engine the EKS is Amazon's Kubernetes, they consume that as an engine. But the management layer was a gap in the market. How do I operationalize Kubernetes? And what we are doing is we're going to, you know, the Anant said. So the warden saying, "Hey you, your team is technical, you understand the problem set. Would you like to build it or would you rather consume this as a service so you can go faster?" And, resoundingly the answer is, I don't want to do this anymore. I wouldn't allow to buy. >> Well, you know, as Haseeb is saying, speed is again, when we started talking, it only took us like a couple of months to figure out if Rafay is the right solution for us. And so we ended up purchasing Rafay in April. We launched our product based on Rafay in Kubernetes, in EKS in August. >> August. >> So that's about four months. I've done some things like this before. It takes a couple of years just to sort of figure out, how do you really work with Kubernetes, right? In a production at a large scale. Right now, we are running about a 600 node cluster on Rafay and that's serving our customers. Like, one of the biggest thing that's actually happening on December 8th is we are running what we call a virtual hands on lab. >> A virtual? >> Hands on lab. >> Okay. >> For Elation. And they're probably going to be about 500 people is going to be attending it. It's like a webinar style. But what we do in that hands on lab is we will spin up an Elation instance for each attendee, right on the spot. Okay? Now, think about this enterprise software running and people just sign up for it and it's there for you, right on the spot. And that's the beauty of the software that we have been building. There's the beauty of the work that Rafay has helped us to do over the last few months. >> Okay. >> I think we need to charge them more money, I'm getting from this congregation. I'm going to go work on that. >> I'm going to let the two of you work that out later. All right. I don't want to get in the way of a big deal. But you mentioned that, we heard about it earlier that, it's you that would offer to your cert, to your clients, these services. I assume they have their different levels of tolerance and their different challenges, right? They've got their own complexities and their own organizational barriers. So how are you juggling that end of it? Because you're kind of learning as, well, not learning, but you're experiencing some of the thing. >> Right. Same things. And yet you've got this other client base that has a multitude of experiences that they're going through. >> Right. So I think, you know a lot of our customers, they are large enterprise companies. They got a whole bunch of data that they want work with us. So one of the thing that we have learned over the past few years is that we used to actually ship our software to the customers and then they would manage it for their privacy security reasons. But now, since we're running in the cloud, they're really happy about that because they don't need to juggle with the infrastructure and the software management and upgrades and things like that, we do it for them, right? And, that's the speed for them because now they are only interested in solving the problems with the data that they're working with. They don't need to deal with all these software management issues, right? So that frees our customers up to do the thing that they want to do. Of course it makes our job harder and I'm sure in turn it makes his job harder. >> We get a short end of the stick, for sure. >> That's why he is going to get more money. >> Exactly. >> Yeah, this is a great conversation. >> No, no, no. We'll talk about that. >> So, let's talk about the cloud then. How, in terms of being the platform where all this is happening and AWS, about your relationship with them as part of the startup program and what kind of value that brings to you, what does that do for you when you go out and are looking for work and what kind of cache that brings to you >> Talk about the AWS? >> Yes, sir. >> Okay. Well, so, the thing is really like of course AWS, a lot of programs in terms of making sure that as we move our customers into AWS, they can give us some, I wouldn't call it discount, but there's some credits that you can get as you move your workloads onto AWS. So that's a really great program. Our customers love it. They want us to do more things with AWS. It's a pretty seamless way for us to, as we were talking about or thinking about moving into the cloud, AWS was our number one choice and that's the only cloud that we are in, today. We're not going to go to any other place. >> That's it. >> Yeah. >> How would you characterize? I mean, we've already heard, from one side of the fence here, but. >> Absolutely. So for us, AWS is a make or break partner, frankly. As the EKS team knows very well, we support Azure's Kubernetes and Google's Kubernetes and the community Kubernetes as well. But the number of customers on our platform who are AWS native, either a hundred percent or a large percentage is, you know, that's the majority of our customer base. >> John: Yeah. >> And AWS has made it very easy for us in a variety of ways to make us successful and our customers successful. So Anant mentioned the credit program they have which is very useful 'cause we can, you know, readily kind of bring a customer to try things out and they can do that at no cost, right? So they can spin up infrastructure, play with things and AWS will cover the cost, as one example. So that's a really good thing. Beyond that, there are multiple programs at AWS, ISV accelerate, et cetera. That, you know, you got to over time, you kind of keep getting taller and taller. And you keep getting on bigger and bigger. And as you make progress, what I'm finding is that there's a great ecosystem of support that they provide us. They introduce us to customers, they help us, you know, think through architecture issues. We get access to their roadmap. We work very, very closely with the guest team, for example. Like the, the GM for Kubernetes at AWS is a gentleman named Barry Cooks who was my sponsor, right? So, we spend a lot of time together. In fact, right after this, I'm going to be spending time with him because look, they take us seriously as a partner. They spend time with us because end of the day, they understand that if they make their partners, in this case, Rafay successful, at the end of the day helps the customer, right? Anant's customer, my customer, their AWS customers, also. So they benefit because we are collectively helping them solve a problem faster. The goal of the cloud is to help people modernize, right? Reduce operational costs because data centers are expensive, right? But then if these complex solutions this is an enterprise product, Kubernetes, at the enterprise level is a complex problem. If we don't collectively work together to save the customer effort, essentially, right? Reduce their TCO for whatever it is they're doing, right? Then the cost of the cloud is too high. And AWS clearly understands and appreciates that and that's why they are going out of their air, frankly, to make us successful and make other companies successful in the startup program. >> Well. >> I would just add a couple of things there. Yeah, so, you know, cloud is not new. It's been there for a while. You know, people used to build things on their own. And so what AWS has really done is they have advanced technology enough where everything is really simple as just turning on a switch and using it, right? So, just a recent example, and I, by the way, I love managed services, right? So the reason is really because I don't need to put my own people to build and manage those things, right? So, if you want to use a search, they got the open search, if you want to use caching, they got elastic caching and stuff like that. So it's really simple and easy to just pick and choose which services you want to use and they're ready to be consumed right away. And that's the beautiful, and that that's how we can move really fast and get things done. >> Ease of use, right? Efficiency, saving money. It's a winning combination. Thanks for sharing this story, appreciate. Anant, Haseeb thanks for being with us. >> Yeah, thank you so much having us. >> We appreciate it. >> Thank you so much. >> You have been a part of the global startup program at AWS and startup showcase. Proud to feature this great collaboration. I'm John Walls. You're watching theCUBE, which is of course the leader in high tech coverage.

>>The Cube Presents UI Path Forward five. Brought to you by UI Path, >>Everybody. We're back in Las Vegas. The cube's coverage we're day one at UI Path forward. Five. Pascal Borne is here. He's an expert and bestselling author in the topic of AI and automation and the book Intelligent Automation. Welcome to the world of Hyper Automation, the first book on the topic. And of course, Ray Wong is back on the cube. He's the founder, chairman and principal analyst, Constellation Reese, also bestselling author of Everybody Wants To Rule the World. Guys, thanks so much for coming on The Cubes. Always a pleasure. Ray Pascal, First time on the Cube, I believe. >>Yes, thank you. Thanks for the invitation. Thank you. >>So what is artificial about artificial intelligence, >>For sure, not people. >>So, okay, so you guys are both speaking at the conference, Ray today. I think you're interviewing the co CEOs. What do you make of that? What's, what are you gonna, what are you gonna probe with these guys? Like, how they're gonna divide their divide and conquer, and why do you think the, the company Danielle in particular, decided to bring in Rob Sland? >>Well, you know what I mean, Like, you know, these companies are now at a different stage of growth, right? There's that early battle between RPA vendors. Now we're actually talking something different, right? We're talking about where does automation go? How do we get the decisioning? What's the next best action? That's gonna be the next step. And to take where UI path is today to somewhere else, You really want someone with that enterprise cred and experience the sales motions, the packages, the partnership capabilities, and who else better than Roblin? He, that's, he's done, he can do that in his sleep, but now he's gotta do that in a new space, taking whole category to another level. Now, Daniel on the other hand, right, I mean, he's the visionary founder. He put this thing from nothing to where he is today, right? I mean, at that point you want your founder thinking about the next set of ideas, right? So you get this interesting dynamic that we've seen for a while with co CEOs, those that are doing the operations, getting the stuff out the door, and then letting the founders get a chance to go back and rethink, take a look at the perspective, and hopefully get a chance to build the next idea or take the next idea back into the organization. >>Right? Very well said. Pascal, why did you write your book on intelligent automation and, and hyper automation, and what's changed since you've written that book? >>So, I, I wrote this book, An Intelligent Automation, two years ago. At that time, it was really a new topic. It was really about the key, the, the key, the key content of the, of the book is really about combining different technologies to automate the most complex end to end business processes in companies. And when I say capabilities, it's, we, we hear a lot about up here, especially here, robotic process automation. But up here alone, if you just trying to transform a company with only up here, you just fall short. Okay? A lot of those processes need more than execution. They need language, they need the capacity to view, to see, they need the capacity to understand and to, and to create insights. So by combining process automation with ai, natural language processing, computer vision, you give this capability to create impact by automating end to end processes in companies. >>I, I like the test, what I hear in the keynote with independent experts like yourself. So we're hearing that that intelligent automation or automation is a fundamental component of digital transformation. Is it? Or is it more sort of a back office sort of hidden in inside plumbing Ray? What do you think? >>Well, you start by understanding what's going on in the process phase. And that's where you see discover become very important in that keynote, right? And that's where process mining's playing a role. Then you gotta automate stuff. But when you get to operations, that's really where the change is going to happen, right? We actually think that, you know, when you're doing the digital transformation pieces, right? Analytics, automation and AI are coming together to create a concept we call decision velocity. You and I make a quick decision, boom, how long does it take to get out? Management committee could free forever, right? A week, two months, never. But if you're thinking about competing with the automation, right? These decisions are actually being done a hundred times per second by machine, even a thousand times per second. That asymmetry is really what people are facing at the moment. >>And the companies that are gonna be able to do that and start automating decisions are gonna be operating at another level. Back to what Pascal's book talking about, right? And there are four questions everyone has to ask you, like, when do you fully intelligently automate? And that happens right in the background when you augment the machine with a human. So we can find why did you make an exception? Why did you break a roll? Why didn't you follow this protocol so we can get it down to a higher level confidence? When do you augment the human with the machine so we can give you the information so you can act quickly. And the last one is, when do you wanna insert a human in the process? That's gonna be the biggest question. Order to cash, incident or resolution, Hire to retire, procure to pay. It doesn't matter. When do you want to put a human in the process? When do you want a man in the middle, person in the middle? And more importantly, when do you want insert friction? >>So Pascal, you wrote your book in the middle of the, the pandemic. Yes. And, and so, you know, pre pandemic digital transformation was kind of a buzzword. A lot of people gave it lip service, eh, not on my watch, I don't have to worry about that. But then it became sort of, you're not a digital business, you're out of business. So, so what have you seen as the catalyst for adoption of automation? Was it the, the pandemic? Was it sort of good runway before that? What's changed? You know, pre isolation, post isolation economy. >>You, you make me think about a joke. Who, who did your best digital transformation over the last years? The ceo, C H R O, the Covid. >>It's a big record ball, right? Yeah. >>Right. And that's exactly true. You know, before pandemic digital transformation was a competitive advantage. >>Companies that went into it had an opportunity to get a bit better than their, their competitors during the pandemic. Things have changed completely. Companies that were not digitalized and automated could not survive. And we've seen so many companies just burning out and, and, and those companies that have been able to capitalize on intelligent automation, digital transformations during the pandemic have been able not only to survive, but to, to thrive, to really create their place on the market. So that's, that has been a catalyst, definitely a catalyst for that. That explains the success of the book, basically. Yeah. >>Okay. Okay. >>So you're familiar with the concept of Stew the food, right? So Stew by definition is something that's delicious to eat. Stew isn't simply taking one of every ingredient from the pantry and throwing it in the pot and stirring it around. When we start talking about intelligent automation, artificial intelligence, augmented intelligence, it starts getting a bit overwhelming. My spy sense goes off and I start thinking, this sounds like mush. It doesn't sound like Stew. So I wanna hear from each of you, what is the methodical process that, that people need to go through when they're going through digital trans transmission, digital transformation, so that you get delicious stew instead of a mush that's just confused everything in your business. So you, Ray, you want, you want to, you wanna answer that first? >>Yeah. You know, I mean, we've been talking about digital transformation since 2010, right? And part of it was really getting the business model, right? What are you trying to achieve? Is that a new type of offering? Are you changing the way you monetize something? Are you taking existing process and applying it to a new set of technologies? And what do you wanna accomplish, right? Once you start there, then it becomes a whole lot of operational stuff. And it's more than st right? I mean, it, it could be like, well, I can't use those words there. But the point being is it could be a complete like, operational exercise. It could be a complete revenue exercise, it could be a regulatory exercise, it could be something about where you want to take growth into the next level. And each one of those processes, some of it is automation, right? There's a big component of it today. But most of it is really rethinking about what you want things to do, right? How do you actually make things to be successful, right? Do I reorganize a process? Do I insert a place to do monetization? Where do I put engagement in place? How do I collect data along the way so I can build better feedback loop? What can I do to build the business graph so that I have that knowledge for the future so I can go forward doing that so I can be successful. >>The Pascal should, should, should the directive be first ia, then ai? Or are these, are these things going to happen in parallel naturally? What's your position on that? Is it first, >>So it, so, >>So AI is part of IA because that's, it's, it's part of the big umbrella. And very often I got the question. So how do you differentiate AI in, I a, I like to say that AI is only the brain. So think of ai cuz I'm consider, I consider AI as machine learning, Okay? Think of AI in a, like a brain near jar that only can think, create, insight, learn, but doesn't do anything, doesn't have any arms, doesn't have any eyes, doesn't not have any mouth and ears can't talk, can't understand with ia, you, you give those capabilities to ai. You, you basically, you create a cap, the capability, technological capability that is able to do more than just thinking, learning and, and create insight, but also acting, speaking, understanding the environment, viewing it, interacting with it. So basically performing these, those end to end processes that are performed currently by people in companies. >>Yeah, we're gonna get to a point where we get to what we call a dynamic scenario generation. You're talking to me, you get excited, well, I changed the story because something else shows up, or you're talking to me and you're really upset. We're gonna have to actually ch, you know, address that issue right away. Well, we want the ability to have that sense and respond capability so that the next best action is served. So your data, your process, the journey, all the analytics on the top end, that's all gonna be served up and changed along the way. As we go from 2D journeys to 3D scenarios in the metaverse, if we think about what happens from a decentralized world to decentralized, and we think about what's happening from web two to web three, we're gonna make those types of shifts so that things are moving along. Everything's a choose your end venture journey. >>So I hope I remember this correctly from your book. You talked about disruption scenarios within industries and within companies. And I go back to the early days of, of our industry and East coast Prime, Wang, dg, they're all gone. And then, but, but you look at companies like Microsoft, you know, they were, they were able to, you know, get through that novel. Yeah. Ibm, you know, I call it survived. Intel is now going through their, you know, their challenge. So, so maybe it's inevitable, but how do you see the future in terms of disruption with an industry, Forget our industry for a second, all industry across, whether it's healthcare, financial services, manufacturing, automobiles, et cetera. How do you see the disruption scenario? I'm pretty sure you talked about this in your book, it's been a while since I read it, but I wonder if you could talk about that disruption scenario and, and the role that automation is going to play, either as the disruptor or as the protector of the incumbents. >>Let's take healthcare and auto as an example. Healthcare is a great example. If we think about what's going on, not enough nurses, massive shortage, right? What are we doing at the moment? We're setting five foot nine robots to do non-patient care. We're trying to capture enough information off, you know, patient analytics like this watch is gonna capture vitals from a going forward. We're doing a lot what we can do in the ambient level so that information and data is automatically captured and decisions are being rendered against that. Maybe you're gonna change your diet along the way, maybe you're gonna walk an extra 10 minutes. All those things are gonna be provided in that level of automation. Take the car business. It's not about selling cars. Tesla's a great example. We talk about this all the time. What Tesla's doing, they're basically gonna be an insurance company with all the data they have. They have better data than the insurance companies. They can do better underwriting, they've got better mapping information and insights they can actually suggest next best action do collision avoidance, right? Those are all the things that are actually happening today. And automation plays a big role, not just in the collection of that, that information insight, but also in the ability to make recommendations, to do predictions and to help you prevent things from going wrong. >>So, you know, it's interesting. It's like you talk about Tesla as the, the disrupting the insurance companies. It's almost like the over the top vendors have all the data relative to the telcos and mopped them up for lunch. Pascal, I wanna ask you, you know, the topic of future of work kind of was a bromide before, but, but now I feel like, you know, post pandemic, it, it actually has substance. How do you see the future of work? Can you even summarize what it's gonna look like? It's, it's, Or are we here? >>It's, yeah, it's, and definitely it's, it's more and more important topic currently. And you, you all heard about the great resignation and how employee experience is more and more important for companies according to have a business review. The companies that take care of their employee experience are four times more profitable that those that don't. So it's a, it's a, it's an issue for CEOs and, and shareholders. Now, how do we get there? How, how do we, how do we improve the, the quality of the employee experience, understanding the people, getting information from them, educating them. I'm talking about educating them on those new technologies and how they can benefit from those empowering them. And, and I think we've talked a lot about this, about the democratization local type of, of technologies that democratize the access to those technologies. Everyone can be empowered today to change their work, improve their work, and finally, incentivization. I think it's a very important point where companies that, yeah, I >>Give that. What's gonna be the key message of your talk tomorrow. Give us the bumper sticker, >>If you will. Oh, I'm gonna talk, It's a little bit different. I'm gonna talk for the IT community in this, in the context of the IT summit. And I'm gonna talk about the future of intelligent automation. So basically how new technologies will impact beyond what we see today, The future of work. >>Well, I always love having you on the cube, so articulate and, and and crisp. What's, what's exciting you these days, you know, in your world, I know you're traveling around a lot, but what's, what's hot? >>Yeah, I think one of the coolest thing that's going on right now is the fact that we're trying to figure out do we go to work or do we not go to work? Back to your other point, I mean, I don't know, work, work is, I mean, for me, work has been everywhere, right? And we're starting to figure out what that means. I think the second thing though is this notion around mission and purpose. And everyone's trying to figure out what does that mean for themselves? And that's really, I don't know if it's a great, great resignation. We call it great refactoring, right? Where you work, when you work, how we work, why you work, that's changing. But more importantly, the business models are changing. The monetization models are changing macro dynamics that are happening. Us versus China, G seven versus bricks, right? War on the dollar. All these things are happening around us at this moment and, and I think it's gonna really reshape us the way that we came out of the seventies into the eighties. >>Guys, always a pleasure having folks like yourself on, Thank you, Pascal. Been great to see you again. All right, Dave Nicholson, Dave Ante, keep it right there. Forward five from Las Vegas. You're watching the cue.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Okay. We're back to wrap up HPE discover 2022. The Cube's continuous coverage is day three. John furrier, Dave ante. We had a business friend that we met during the pandemic. A really interesting gentleman, norm Ette. He's the director of global technical marketing at Hewlett Packard enterprise, a real innovator norm. Great to see you. Thanks for making time for coming on >>The cube, gentlemen. Thank you. Thank you. I appreciate that. You're giving me the opportunity to bring it home. Yeah. You know, if I'm only gonna get one shot at it, it might as well be >>The last we always, we always like to bring the energy in the last segment because you know, the cube, we grind it out for three days. I mean, it's just such a great content injection. And so we love to wrap it up, especially with someone like yourself who can really help us convey the themes, but even more so when we look around here this entire ecosystem, you and your team built this. And so take us through that. >>Well, we did, you know, and it takes a village. You know, we have the core team, HPE global technical marketing, uh, which is my team. And then of course we're partnered with other parts of the, our marketing organizations on different pieces, different aspects. And then we have a tremendous team of vendors that we work with on a regular basis. Companies such as, you know, F two B and ivory and others that, you know, really kind of pitch in. And they're, they're kind of my, I call 'em my flex force. You know, we also have another group called promote live and we bring all these people together. And, and in addition, all the vendors, we have something like 380 employees that come from all different parts of the organization to, to land in Las Vegas, to man, these booths and staff, these, uh, staff, these exhibits. >>And so for one week, we get to really work as a, as a, a team, as a family, you know, there's no organizational borders, so to speak, you know, you know, we're a big company, everybody has, you know, different objectives and different things that they're focused on, but we get a chance to all get together and work as one, one team. And so that, that the people aspect is what's so exciting, I think this week. And I think I even saw some of your broadcast earlier. So I think it kind of, it kind of came through as well. Just the joy of, of being together, you know? Sure. Human beings <laugh> >>And, and H HP's got a new spring and its step, which so much focus brought to the table from Antonio and, you know, the team is the lining. >>Yeah, we do. And that's, you know, when you go, when we start talking about the design and you know, one of the things that, you know, we work on this months ahead of time. Yeah. Right. And so it's kinda like a spinning top, you know, we, we, we keep, we, we keep spinning that thing tightening up and then this week you put it on the table and just let it go. Yeah. Right. But it's that whole multi-month process of, of, of twisting that top around and getting it going and right at the middle and right at the centerpiece. And, uh, the core design principle and an ask from, uh, Antonio is that we make sure that we major on HPE, uh, GreenLake edge to cloud platform that, you know, it, it's a, obviously you've been talking about it all week. Yeah. Uh, we've been talking about it all week. It's a big focus of our company. And so right at the very center, we have our HPE GreenLake edge to cloud platform demonstration, and then everything in the showcase then radiates from that centerpiece, uh, you know, right, right. At, right at the nexus of all the activities. So the experience starts there and propagates its >>Way. Well, I wanna get into some of the themes and the set pieces you have here. Um, you are in technical marketing and this platform is a tech play. So it's not so much just solutions that you're enabling the theme this year is very much technical marketing. So there's edge, especially cloud data and edge is the big themes security's baked in throughout the whole set, right as well. And that messaging, but it's technical marketing right now. We had, you know, platform play uett packer is a platform. Google packer enterprise is a >>Platform. It is, and it's a, it is a, it's a software platform. Um, you, it, it really completes a cloud strategy. And when you really think about it, I, again, I know some of these numbers have been floating around. Um, but, uh, you know, 70% of all data is still staying OnPrem for good reasons, you know, and then 30% of it can be out there in the public cloud. Uh, so what you kind of have is an incomplete cloud strategy, if you will. And what's happened is that organizations have gotten spoiled a little bit by the cloud experience. Mm-hmm <affirmative> right. That, you know, I, you know, your, your dev teams say go, Hey, I just, I wanna work in a Azure. I wanna work in AWS. I love how I go through this process. Why can't I do that with my on-prem stuff? Why, you know, why, you know, I want that kind of experience. So it organizations are really being challenged about how to create that, that kind of service and that experience to their customers because expectations are not because >>Data ha it has to be inclusive. It can't be exclusive to just one part of the organization. >>Yeah. And so how did you, how did that impact obviously, cause GreenLake was coming together, you know, you got the multiple months in advance planning for this big event, right. A lot of lot work goes into it. What was some of the impact to the execution of this event, um, that you can share in terms of the set pieces? Some of the displays was there was there, I won't say radical cause it's not radical. It looks, it turned out great. But what are some of the popular things happening here? What worked, what resonated with customers and what was different from, from, uh, that GreenLake enabled you to do differently? >>Well, I mean, first the first thing is that we, we kind of had a high touch experience at that center point, right. That nexus, the hub of the activity, the GreenLake edge to club platform, uh, demonstration. And it started with us just kind of, you know, having the strategy about first of all, if you sh, if you guys show this and I know, I think maybe you have, when you enter in, we've got like this big aha moment, right. And that aha moment is that platform right in the center, surrounded with wonderful visuals above, below, you know, behind, uh, all around it. But we, we, we had to think about, okay, now I'm staring at this thing. What am I, how am I gonna experience it? So, uh, when I say a high touch experience, we start with a, what I call a platform generalist that would greet you up front, engage in the conversation, you know, so realize that, you know, Dave is a network operations director, he's got some keen interests. >>He has some sort of peripheral idea about what the, uh, HPE GreenLake edge cloud platform is about, but what can it really do for him? You know, what can do, what can he use? How can he use it? So we start at that level of conversation, you know, socialize the core services, the attributes, you know, the, the technology that is actually enabling it. And then as we've identified in our conversation that you're a network geek, you know, and you want to understand, you've heard about Aruba, you know, how's Aruba central play into that. How do the networking services play into that? And so for then we take that, that, that big leap and go up two steps up onto the platform. And we go over to the network specialist, what I, what I'm calling a platform specialist, uh, who understands all the things about the platform, but then is peaked in networking. And we have that conversation and you see how the Aruba customer can benefit by this evolution, uh, and how the different platform services combine to give a holistic experience across a company. And so when I'm an it ops director, and I'm trying to service my network, guys, my storage guys, my compute guys, my external cloud services guys, that this is an environment that I can, so you >>Have an experience where they come in, they can easily move to a point quickly in the display, on the platform >>And it's tailored for them. Exactly. Right. Exactly. That's the exactly. Right. And so if I transition over to you, you know, and you're my, you know, you're my specialist, you know, you're not saying, Hey, Dave, what brings you here today? What are you today? <laugh>, you know, I, I mean, you're prequalified, it's a prequalified conversation. We jump into it. And then that specialist is armed with knowledge as to where, okay, this guy is really interested in switching technology and switches as well. Well, that's demo five 12. Mm-hmm <affirmative>, you know, let me have one of my colleagues take you over there. So then you're, you're escorted over to demo five 12 to go to the next level or perhaps, and this has happened throughout the week that people want to take a test drive of the environment. And so we have the HPE GreenLake living lab, and we have a, a test drive environment right there. >>And so we bring you right to that test drive, where you can, you know, kick the tires yourself, you fire up a live environment. We have a series of exercises that you're taken through. And, uh, I think I've just checked with one of my colleagues where like, well over, you know, well, over 1100 experiences of people doing that here. And that lab has 25 seats, but also externally. Yeah. So right off of hpe.com, that same test drive experience that we're doing here. People can launch at home. And so we got in this morning, there were like four guys logged in from New Zealand, you know, doing exercises, which is pretty neat. So, so when you ask me the question, what are the design considerations, uh, that HPE GreenLake that we baked in and thought through it's again, that, Hey, it's a, it's a big thing. Yeah. It's a big, it's an experience. Let's start with you just digesting the, you know, the comp basic concepts. Then let's talk about your persona and how it directly maps to what you can do. And then if you want to get deeper, you know, we have the solutions that we design behind it, solution demos, and, and if you wanna drive it, let you know, buckle up. Let's >>Go. Yeah, you get right to a spot, multiple monitors, great experience, high touch. Um, that's awesome. I gotta ask you another question. Cause you've been, you know, pre pandemic, you've been doing a lot of this technical marketing and events and then virtual hit right now. We're back face to face, right? It's clear, Dave and I were just talking about our, on our opening day, year on day. One, people love to see each other back. Every event we've been to face to face. People are energized to a level. We didn't even see. What are you seeing here in terms of performance? Obviously, you got sales people here, you got executives here, you got customers right. Face to face, right. >>Doing belly to belly, >>Belly to belly, as Dave says, that's a positive, what's it like, explain what it's like. >>Well, I mean, you don't, you never know what you got until it's gone, right? >>Yeah. >>You, and so people didn't really realize that, Hey, we really needed to have this kind of touch and this, this kind of activity. And it was funny because people be before the pandemic, there was also a push to do a lot of virtual stuff, you know, economies of scale. Yeah. You know, some of that stuff works. Teams are making decisions, but then it all goes away and people realize how valuable, you know, just the conversations were, you know, meeting >>Somebody, relationships, meeting >>Somebody for a coffee, you know, talking through different bumping into colleagues than that. You haven't seen for years, or you worked with somebody and now they're doing this. And then you realize you have some sort of synergy with each other and you know, you can still help each other. And just the, just, you know, just the discovery <laugh> of being at discover, you know, and running into these different types of things. So, uh, well >>You think about it norm, you know, we, we've done plenty of stuff virtually we have, but I think we've talked maybe four times this week. Yeah. You've seen you here walking around the hallways. We saw you last night, right? Yeah. You just, that just wouldn't happen in your little virtual >>World. Yeah. I mean, not at all. And during that virtual era, and I think we'll look back on that and we're still gonna do virtual stuff >>Course, and we're learning, >>It's got value, but I just want to thank you guys for just being the cube and the whole team, you know, Frank, everybody just tremendous partners through that because you can still look at that content that we produced together last year and it's still relevant. We're still sharing it. It still has impact. We, we point, you know, we tell people, Hey, here's call to action. You're leaving. Discover by the way, there's these three or four pieces out on the cube that really go with, go at this topic. >>Right. That GreenLake event we did last year was phenomenal. >>It was, it was, and it was a partnership with you guys. And I, I, you know, I, I speak on, on behalf of many of my colleagues here at HPE, we just wanna thank the cube for all the support, creativity, uh, and how we got through that >>All together. We we'll back at you because norm you were a real innovator when John and I first met you, we were like, Hey, this guy, actually, he's gonna, he's gonna push us to some new levels. Technical >>Marketing know >>That's our, our team marketing. Like our team was a little nervous, a lot nervous actually, because you know, you do, you are not only demanding, but you're super creative. Well, thank you. And so you, you helped us, you know, up, up our game. >>Yeah. Thanks a lot. Yeah. You know, Frank was getting, Hey, Frank, Dave, can you guys do this? You >>Know, so yeah, we were on the background. >>I mean, but we were, we were growing and surviving and thriving together and getting through it, but what's coming out. The other side now is a new format. You mentioned virtual. That's not going away. Hybrid is a steady state for all of us. Even the cube. Yeah. So the new protocols and the new standards are emerging. And I think the newness of it scares people also like how do you do it? Um, who, whose role is it to take the virtual and digital? So this whole new set of experiences still coming out. Yeah. What's your vision? How do you see this? Cause we're face to face clearly is what everyone wants from school kids to adults. Right. We want face to face. Right. How does digital fit in? >>Well, I mean, that's, that's a, that's a really tricky question. I'll give you a, a, I'll kind of back into the answer a little bit. Um, you guys can see this, right, right behind us. We had this whole backdrop here, greetings from the edge of virtual reality experience. Well, we built that. We built that during the COVID era, so we could have experiences with people remotely. Right. Uh, and we used it for our executive summit, you know, last year for the virtual discovery, we shipped those Oculus headsets to everybody. They, everybody jumped into it. And so I was sitting there being a host, you know, with four CTOs that were scattered all over the world. So we were in cyberspace together. Right. And so of course being good, uh, you know, good business people we realized, Hey, this is pretty fun. So let's dust it off and bring it out here for the more general public. >>So again, it was like a 200 person, you know, uh, executive level experience and all of that, but it had tremendous value, different types of experiences. I recommend you try it if you ever have the opportunity. Um, so that's a way that we start emerging virtual reality and digital experiences to try to keep that human connection, but now we're using it again. And everybody's in these little pod rooms, six of them together. So they're having this experience in cyberspace and they're having it physically. Yeah. And so I think some, and everyone's enjoying being together and still in cyber space together. So I think when we start to build assets and we start to look at different types of things and experiences, we gotta think, we, we gotta think through that now. Right. You know, how is this, how is this investment or this, this experience, how's it gonna translate, you know, outside of these four walls, right. And how can we use it outside of these four walls, uh, and create, you know, a more engaging experience. So that's a little bit of a backing into that answer, but I think I'm, I'm, >>It's emerging. It's >>Important. Well, I'm saying it more as an example of us thinking through and trying to leverage. Yeah. >>I love it though. I mean, you always, you've always been struck me as a visionary and I, I loved that answer and I can just see, it's just gonna progress by the end of the decade. This is gonna become right. Uh, a a, you know, a normal sort of practice, and we're gonna bring people in from the outside and interacting. I love what you were saying about, yeah. Even though we're here physically, we're actually creating a virtual world within this physical pod. We are. Where can people discover more about that? About, about, about the shows, the content that >>Was here? Well on hpe.com, you can just launch into discover. We have a tremendous amount of content that's been recorded, keynote sponsor sessions, the cube they're dialed in all kinds of different pieces of assets that we've done. Um, I'll plug just another couple of things just to, again, to talk about the connectivity of things that we're doing. So one of the projects that I lead, uh, I am very proud to lead is HPE space born and our space born computer space, born computer two, flying a most powerful machine, uh, computer to ever fly in space. Uh, we've been up there for a year. We've done 24 different experiments over the year to, for the benefit of the entire scientific community. Um, also, you know, doing things for the ISS national lab in NASA, our partners up there, but what we've got is we've built a scale replica of the Columbus module, right? So this is, you know, this is a 28 by 12 foot module. Hey, we're bringing her home seriously. >>They're gonna pull the plugs. They're gonna pull the >>Plug on me soon. Right. So anyway, so we have that module built, right? And this is, uh, we work with a Hollywood production company. We've had it before, but you know, we we've customized it. We have a live link to the ISS station in there. And, and so we're talking about everything that we're doing there, but also in this virtual reality experience, we have you going on a space walk, right. And so we've, we've captured that as well. So we've, we're tying this physical and virtual experience together. Uh, and, uh, so it's a fun project. So you can check that >>Out. We did exit scale together during the pandemic, and that's when I first really got into to space point. It was awesome to see frontier announced actually breaking through the exo scale barrier. We, we were on the cusp, but we, we now see it breaking through. So, yeah. Congratulations on that. Thank you >>Very much. And, you know, a couple, you know, just couple other things that we're doing, that's pretty exciting. I don't, I don't wanna give away all my tricks, uh, but you know, we've organized our demonstrations through the customer lenses. So we have these customer journeys that we see people that are using our technology, you know, so I'm, I'm not talking about the storage business unit or, you know, the networking business unit, but how are our customers really trying to, you know, advance AI and machine learning, for example, how are they actually trying to, you know, protect their data? You know, the different things, the business issues, the business issues. Yeah. And so we've organized our demos through that, and we have these, these pods and then satellites, and you, you, you give you walk through that whole thing and it's addressing different aspects of that. >>Um, and then another thing that we've done is we have tours here, uh, as well, where, cuz there's so much content that people can take tours and you know, 1400 people have taken those tours. Uh, you know, and these are guided tours, headsets, curated, big numbers, designated places to go. And we see big traffic the first day or so and by design. And so we hit the highlights and then they decide how to use their valuable time later in the showcase about what they want to deep dive on. And so that's been a tremendous success for >>Us. Well norm thanks for bringing us on the tour of discover. Yeah. Well and really, you know, sharing that with our audience and you've been an awesome partner. And as you say, a great innovator, hope I can't wait to see what's next. All right. >>You so much. Hey, thanks for letting me on here guys. Welcome to our pleasure. I'm somebody I made. You're a Cub >>Alumni alumni. You're alumni. Welcome to alumni. So >>Guys great. Our week. That's a wrap on on day three, uh, Dave Valant day, John furrier for Lisa Martin. Don't forget to go to Silicon angle.com where we've got all the news, all the interviews that we've done this week, get written up and posted on Silicon angle.com. The cube.net I publish every week. Uh, my breaking analysis on, on, on wikibon.com. It's on a podcast. So check that out. Thanks to everybody. Thanks for the crew. Everybody back at the office. Really appreciate it. Great job. And we'll see you next time. All right.

>>Hi, everybody. Welcome back to Caesars in Las Vegas. My name is Dave ante. We're here with the chairman and CEO of snowflake, Frank Luman. Good to see you again, Frank. Thanks for coming on. Yeah, >>You, you as well, Dave. Good to be with you. >>No, it's, it's awesome to be, obviously everybody's excited to be back. You mentioned that in your, in your keynote, the most amazing thing to me is the progression of what we're seeing here in the ecosystem and of your data cloud. Um, you wrote a book, the rise of the data cloud, and it was very cogent. You talked about network effects, but now you've executed on that. I call it the super cloud. You have AWS, you know, I use that term, AWS. You're building on top of that. And now you have customers building on top of your cloud. So there's these layers of value that's unique in the industry. Was this by design >>Or, well, you know, when you, uh, are a data clouding, you have data, people wanna do things, you know, with that data, they don't want to just, you know, run data operations, populate dashboards, you know, run reports pretty soon. They want to build applications and after they build applications, they wanna build businesses on it. So it goes on and on and on. So it, it drives your development to enable more and more functionality on that data cloud. Didn't start out that way. You know, we were very, very much focused on data operations, then it becomes application development and then it becomes, Hey, we're developing whole businesses on this platform. So similar to what happened to Facebook in many, in many ways, you know, >>There was some confusion I think, and there still is in the community of, particularly on wall street, about your quarter, your con the consumption model I loved on the earnings call. One of the analysts asked Mike, you know, do you ever consider going to a subscription model? And Mike got cut him off, then let finish. No, that would really defeat the purpose. Um, and so there's also a narrative around, well, maybe snowflake, consumption's easier to dial down. Maybe it's more discretionary, but I, I, I would say this, that if you're building apps on top of snowflake and you're actually monetizing, which is a big theme here, now, your revenue is aligned, you know, with those cloud costs. And so unless you're selling it for more, you know, than it costs more than, than you're selling it for, you're gonna dial that up. And that is the future of, I see this ecosystem in your company. Is that, is that fair? You buy that. >>Yeah, it, it is fair. Obviously the public cloud runs on a consumption model. So, you know, you start looking all the layers of the stack, um, you know, snowflake, you know, we have to be a consumption model because we run on top of other people's, uh, consumption models. Otherwise you don't have alignment. I mean, we have conversations, uh, with people that build on snowflake, um, you know, they have trouble, you know, with their financial model because they're not running a consumption model. So it's like square pack around hole. So we all have to align ourselves. So that's when they pay a dollar, you know, a portion goes to, let's say, AWS portion goes to the snowflake of that dollar. And the portion goes to whatever the uplift is, application value, data value, whatever it is to that goes on top of that. So the whole dollar, you know, gets allocated depending on whose value at it. Um, we're talking about. >>Yeah, but you sell value. Um, so you're not a SaaS company. Uh, at least I don't look at you that that way I I've always felt like the SAS pricing model is flawed because it's not aligned with customers. Right. If you, if you get stuck with orphaned licenses too bad, you know, pay us. >>Yeah. We're, we're, we're obviously a SaaS model in the sense that it is software as a service, but it's not a SaaS model in the sense that we don't sell use rights. Right. And that's the big difference. I mean, when you buy, you know, so many users from, you know, Salesforce and ServiceNow or whoever you have just purchased the right, you know, for so many users to use that software for this period of time, and the revenue gets recognized, you know, radically, you know, one month at a time, the same amount. Now we're not that different because we still do a contract the exact same way as SA vendor does it, but we don't recognize the revenue radically. We recognize the revenue based on the consumption, but over the term of the contract, we recognize the entire amount. It just is not neatly organized in these monthly buckets. >>You know? So what happens if they underspend one quarter, they have to catch up by the end of the, the term, is that how it works or is that a negotiation or it's >>The, the, the spending is a totally, totally separate from the consumption itself, you know, because you know how they pay for the contract. Let's say they do a three year contract. Um, you know, they, they will probably pay for that, you know, on an annual basis, you know, that three year contract. Um, but it's how they recognize their expenses for snowflake and how we recognize the revenue is based on what they actually consume. But it's not like you're on demand where you can just decide to not use it. And then I don't have any cost, but over the three year period, you know, all of that, you know, uh, needs to get consumed or they expire. And that's the same way with Amazon. If I don't consume what I buy from Amazon, I still gotta pay for it. You know, so, >>Well, you're right. Well, I guess you could buy by the drink, but it's way, way more expensive and nobody really correct. Does that, so, yep. Okay. Phase one, better simpler, you know, cloud enterprise data warehouse, phase two, you introduced the, the data cloud and, and now we're seeing the rise of the data cloud. What, what does phase three look like >>Now? Phase, phase three is all about applications. Um, and we've just learned, uh, you know, from the beginning that people were trying to do this, but we weren't instrumental at all to do it. So people would ODBC, you know, JDBC drivers just uses as database, right? So the entire application would happen outside, you know, snowflake, we're just a database. You connect to the database, you know, you read or right data, you know, you do data, data manipulations. And then the application, uh, processing all happens outside of snowflake. Now there's issues with that because we start to exfil trade data, meaning that we started to take data out of snowflake and, and put it, uh, in other places. Now there's risk for that. There's operational risk, there's governance, exposure, security issues, you know, all this kind of stuff. And the other problem is, you know, data gets Reed. >>It proliferates. And then, you know, data science tests are like, well, I, I need that data to stay in one place. That's the whole idea behind the data cloud. You know, we have very big infrastructure clouds. We have very big application clouds and then data, you know, sort of became the victim there and became more proliferated and more segment. And it's ever been. So all we do is just send data to the work all day. And we said, no, we're gonna enable the work to get to the data. And the data that stays in more in place, we don't have latency issue. We don't have data quality issues. We don't have lineage issues. So, you know, people have responded very, very well to the data cloud idea, like, yeah, you know, as an enterprise or an institution, you know, I'm the epicenter of my own data cloud because it's not just my own data. >>It's also my ecosystem. It's the people that I have data networking relationships with, you know, for example, you know, take, you know, uh, an investment bank, you know, in, in, in, in New York city, they send data to fidelity. They send data to BlackRock. They send data to, you know, bank of New York, all the regulatory clearing houses, all on and on and on, you know, every night they're running thousands, tens of thousands, you know, of jobs pushing that data, you know, out there. It just, and they they're all on snowflake already. So it doesn't have to be this way. Right. So, >>Yes. So I, I asked the guys before, you know, last week, Hey, what, what would you ask Frank? Now? You might remember you came on, uh, our program during COVID and I was asking you how you're dealing with it, turn off the news. And it was, that was cool. And I asked you at the time, you know, were you ever, you go on Preem and you said, look, I'll never say never, but it defeats the purpose. And you said, we're not gonna do a halfway house. Actually, you were more declarative. We're not doing a halfway house, one foot in one foot out. And then the guy said, well, what about that Dell deal? And that pure deal that you just did. And I, I think I know the answer, but I want to hear from you did a customer come to you and say, get you in the headlock and say, you gotta do this. >>Or it did happen that way. Uh, it, uh, it started with a conversation, um, you know, via with, uh, with Michael Dell. Um, it was supposed to be just a friendly chat, you know, Hey, how's it going? And I mean, obviously Dell is the owner of data, the main, or our first company, you know? Um, but it's, it, wasn't easy for, for Dell and snowflake to have a conversation because they're the epitome of the on-premise company and we're the epitome of a cloud company. And it's like, how, what do we have in common here? Right. What can we talk about? But, you know, Michael's a very smart, uh, engaging guy, you know, always looking for, for opportunity. And of course they decided we're gonna hook up our CTOs, our product teams and, you know, explore, you know, somebody's, uh, ideas and, you know, yeah. We had some, you know, starts and restarts and all of that because it's just naturally, you know, uh, not an easy thing to conceive of, but, you know, in the end it was like, you know what? >>It makes a lot of sense. You know, we can virtualize, you know, Dell object storage, you know, as if it's, you know, an S three storage, you know, from Amazon and then, you know, snowflake in its analytical processing. We'll just reference that data because to us, it just looks like a file that's sitting on, on S3. And we have, we have such a thing it's called an external table, right. That's, that's how we basically, it projects, you know, a snowflake, uh, semantic and structural model, you know, on an external object. And we process against it exactly the same way as if it was an internal, uh, table. So we just extended that, um, you know, with, um, with our storage partners, like Dell and pure storage, um, for it to happen, you know, across a network to an on-prem place. So it's very elegant and it, it, um, it becomes an, an enterprise architecture rather than just a cloud architecture. And I'm, I just don't know what will come of it. And, but I've already talked to customers who have to have data on premises just can't go anywhere because they process against it, you know, where it originates, but there are analytical processes that wanna reference attributes of that data. Well, this is what we'll do that. >>Yeah. I'm, it is interesting. I'm gonna ask Dell if I were them, I'd be talking to you about, Hey, I'm gonna try to separate compute from storage on prem and maybe do some of the, the work there. I don't even know if it's technically feasible. It's, I'll ask OI. But, um, but, but, but to me, that's an example of your extending your ecosystem. Um, so you're talking now about applications and that's an example of increasing your Tam. I don't know if you ever get to the edge, you know, we'll see, we're not quite quite there yet, but, um, but as you've said before, there's no lack of market for you. >>Yeah. I mean, obviously snowflake it it's, it's Genesis was reinventing database management in, in a cloud computing environment, which is so different from a, a machine environment or a cluster environment. So that's why, you know, we're, we're, we're not a, a fit for a machine centric, uh, environment sort of defeats the purpose of, you know, how we were built. We, we are truly a native solution. Most products, uh, in the clouds are actually not cloud native. You know, they, they originated the machine environments and you still see that, you know, almost everything you see in the cloud by the way is not cloud native, our generation of applications. They only run the cloud. They can only run the cloud. They are cloud native. They don't know anything else, >>You know? Yeah, you're right. A lot of companies would just wrap something in wrap their stack in Kubernetes and throw it into the cloud and say, we're in the cloud too. And you basically get, you just shifted. It >>Didn't make sense. Oh. They throw it in the container and run it. Right. Yeah. >>So, okay. That's cool. But what does that get you that doesn't change your operational model? Um, so coming back to software development and what you're doing in, in that regard, it seems one of the things we said about Supercloud is in order to have a Supercloud, you gotta have an ecosystem, you gotta have optionality. Hence you're doing things like Apache iceberg, you know, you said today, well, we're not sure where it's gonna go, but we offering options. Uh, but, but my, my question is, um, as it pertains to software developments specifically, how do you, so one of the things we said, sorry, I've lost my train there. One of the things we said is you have to have a super PAs in order to have a super cloud ecosystem, PAs layer. That's essentially what you've introduced here. Is it not a platform for our application development? >>Yeah. I mean, what happens today? I mean, how do you enable a developer, you know, on snowflake, without the developer, you know, reading the, the files out of snowflake, you know, processing, you know, against that data, wherever they are, and then putting the results set, God knows where, right. And that's what happens today. It's the wild west it's completely UN uncovered, right? And that's the reason why lots of enterprises will not allow Python anything anywhere near, you know, their enterprise data. We just know that, uh, we also know it from streamlet, um, or the acquisition, um, large acquisition that we made this year because they said, look, you know, we're, we have a lot of demand, you know, uh, in the Python community, but that's the wild west. That's not the enterprise grade high trust, uh, you know, corporate environment. They are strictly segregated, uh, today. >>Now do some, do these, do these things sometimes dribble up in the enterprise? Yes, they do. And it's actually intolerable the risk that enterprises, you know, take, you know, with things being UN uncovered. I mean the whole snowflake strategy and promises that you're in snowflake, it is a, an absolute enterprise grade environment experience. And it's really hard to do. It takes enormous investment. Uh, but that is what you buy from us. Just having Python is not particularly hard. You know, we can do that in a week. This has taken us years to get it to this level, you know, of, of, you know, governance, security and, and, you know, having all the risks around exfiltration and so on, really understood and dealt with. That's also why these things run in private previews and public previews for so long because we have to squeeze out, you know, everything that may not have been, you know, understood or foreseen, you know, >>So there are trade offs of, of going into this snowflake cloud, you get all this great functionality. Some people might think it's a walled garden. How, how would you respond to that? >>Yeah. And it's true when you have a, you know, a snowflake object, like a snowflake, uh, table only snowflake, you know, runs that table. And, um, you know, that, that is, you know, it's very high function. It's very sort of analogous to what apple did, you know, they have very high functioning, but you do have to accept the fact that it's, that it's not, uh, you know, other, other things in apple cannot, you know, get that these objects. So this is the reason why we introduce an open file format, you know, like, like iceberg, uh, because what iceberg effectively does is it allows any tool, uh, you know, to access that particular object. We do it in such a way that a lot of the functionality of snowflake, you know, will address the iceberg format, which is great because it's, you're gonna get much more function out of our, you know, iceberg implementation than you would get from iceberg on its own. So we do it in a very high value addeds, uh, you know, manner, but other tools can still access the same object in a read to write, uh, manner. So it, it really sort of delivers the original, uh, promise of the data lake, which is just like, Hey, I have all these objects tools come and go. I can use what I want. Um, so you get, you get the best of both worlds for the most part. >>Have you reminds me a little bit of VMware? I mean, VMware's a software mainframe, it's just better than >>Doing >>It on your own. Yep. Um, one of the other hallmarks of a cloud company, and you guys clearly are a cloud company is startups and innovation. Um, now of course you see that in, in the, in the ecosystem, uh, and maybe that's the answer to my question, but you guys are kind of whale hunters, <laugh> your customers are, tend to be bigger. Uh, is the, is the innovation now the extension of that, the ecosystem is that by design. >>Oh, um, you know, we have a enormous, uh, ISV following and, um, we're gonna have a whole separate conference like this, by the way, just for, yeah. >>For developers. I hope you guys will up there too. Yeah. Um, you know, the, the reason that, that the ISV strategy is very important for, you know, for, for, for, for many reasons, but, you know, ISVs are the people that are really going to unlock a lot of the value and a lot of the promise of data, right? Because you, you can never do that on your own. And the problem has been that for ISVs, it is so expensive and so difficult to build a product that can be used because the entire enterprise platform infrastructure needs to be built by somebody, you know, I mean, are you really gonna run infrastructure, database, operations, security, compliance, scalability, economics. How do you do that as a software company where really you only have your, your domain expertise that you want to deliver on a platform. You don't wanna do all these things. >>First of all, you don't know how to do it, how to do it well. Um, so it is much easier, much faster when there is already platform to actually build done in the world of clout that just doesn't, you know, exist. And then beyond that, you know, okay, fine building. It is sort of step one. Now I gotta sell it. I gotta market it. So how do I do that? Well, in the snowflake community, you have already market <laugh>, there's thousands and thousands of customers that are also on self lake. Okay. So their, their ability to consume that service that you just built, you know, they can search it, they can try it, they can test it and decide whether they want to consume it. And then, you know, we can monetize it. So all they have to do is cash the check. So the net effecti of it is we drastically lowered the barriers to entry into the world, you know, of software, you know, two men or two women in a dog, and a handful of files can build something that then can be sold, sort of to, for software developers. >>I wrote a piece 2012 after the first reinvent. And I, you know, and I, and I put a big gorilla on the front page and I said, how do you compete with Amazon gorilla? And then one of my answers was you build data ecosystems and you verticalize, and that's, that's what you're doing >>Here. Yeah. There certain verticals that are farther along than others, uh, obviously, but for example, in financial, uh, which is our largest vertical, I mean, the, the data ecosystem is really developing hardcore now. And that's, that's because they so rely on those relationships between all the big financial institutions and entities, regulatory, you know, clearing houses, investment bankers, uh, retail banks, all this kind of stuff. Um, so they're like, it becomes a no brainer. The network affects kick in so strongly because they're like, well, this is really the only way to do it. I mean, if you and I work in different companies and we do, and we want to create a secure, compliant data network and connection between us, I mean, it would take forever to get our lawyers to agree that yeah, it's okay. <laugh> right now, it's like a matter of minutes to set it up. If we're both on snowflake, >>It's like procurement, do they, do you have an MSA yeah. Check? And it just sail right through versus back and forth and endless negotiations >>Today. Data networking is becoming core ecosystem in the world of computing. You know, >>I mean, you talked about the network effects in rise of the data cloud and correct. Again, you know, you, weren't the first to come up with that notion, but you are applying it here. Um, I wanna switch topics a little bit. I, when I read your press releases, I laugh every time. Cause this says no HQ, Bozeman. And so where, where do you, I think I know where you land on, on hybrid work and remote work, but what are your thoughts on that? You, you see Elon the other day said you can't work for us unless you come to the office. Where, where do you stand? >>Yeah. Well, the, well, the, the first aspect is, uh, we really wanted to, uh, separate from the idea of a headquarters location, because I feel it's very antiquated. You know, we have many different hubs. There's not one place in the world where all the important people are and where we make all the important positions, that whole way of thinking, uh, you know, it is obsolete. I mean, I am where I need to be. And it it's many different places. It's not like I, I sit in this incredible place, you know, and that's, you know, that's where I sit and everybody comes to me. No, we are constantly moving around and we have engineering hubs. You know, we have your regional, uh, you know, headquarters for, for sales. Obviously we have in Malaysia, we have in Europe, you know? And, um, so I wanted to get rid of this headquarters designation. >>And, you know, the, the, the other issue obviously is that, you know, we were obviously in California, but you know, California is, is no longer, uh, the dominant place of where we are resident. I mean, 40% of our engineering people are now in be Washington. You know, we have hundreds of people in Poland where people, you know, we are gonna have very stressed location in Toronto. Um, yeah. Obviously our customers are, are everywhere, right? So this idea that, you know, everything is happening in, in one state is just, um, you know, not, not correct. So we wanted to go to no headquarters. Of course the SCC doesn't let you do that. Um, because they want, they want you to have a street address where the government can send you a mail and then it becomes, the question is, well, what's an acceptable location. Well, it has to be a place where the CEO and the CFO have residency by hooker, by crook. >>That happened to be in Bozeman Montana because Mike and I are both, it was not by design. We just did that because we were, uh, required to, you know, you know, comply with government, uh, requirements, which of course we do, but that's why it, it says what it says now on, on the topic of, you know, where did we work? Um, we are super situational about it. It's not like, Hey, um, you know, everybody in the office or, or everybody is remote, we're not categorical about it. Depends on the function, depends on the location. Um, but everybody is tethered to an office. Okay. In words, everybody has a relationship with an office. There's, there's almost nobody, there are a few exceptions of people that are completely remote. Uh, but you know, if you get hired on with snowflake, you will always have an office affiliation and you can be called into the office by your manager. But for purpose, you know, a meeting, a training, an event, you don't get called in just to hang out. And like, the office is no longer your home away from home. Right. And we're now into hotel, right? So you don't have a fixed place, you know? So >>You talked in your keynote a lot about last question. I let you go customer alignment, obviously a big deal. I have been watching, you know, we go to a lot of events, you'll see a technology company tell a story, you know, about their widget or whatever it was their box. And then you'll see an outcome and you look at it and you shake your head and say, well, that the difference between this and that is the square root of zero, right. When you talk about customer alignment today, we're talking about monetizing data. Um, so that's a whole different conversation. Um, and I, I wonder if you could sort of close on how that's different. Um, I mean, at ServiceNow, you transformed it. You know, I get that, you know, data, the domain was okay, tape, blow it out, but this is a, feels like a whole new vector or wave of growth. >>Yeah. You know, monetizing, uh, data becomes sort of a, you know, a byproduct of having a data cloud you all of a sudden, you know, become aware of the fact that, Hey, Hey, I have data and be that data might actually be quite valuable to parties. And then C you know, it's really easy to then, you know, uh, sell that and, and monetize that. Cause if it was hard, forget it, you know, I don't have time for it. Right. But if it's relatively, if it's compliant, it's relatively effortless, it's pure profit. Um, I just want to reference one attribute, two attributes of what you have, by the way, you know, uh, hedge funds have been into this sort of thing, you know, for a long time, because they procure data from hundreds and hundreds of sources, right. Because they're, they are the original data scientists. >>Um, but the, the bigger thing with data is that a lot of, you know, digital transformation is, is, is finally becoming real. You know, for years it was arm waving and conceptual and abstract, but it's becoming real. I mean, how do we, how do we run a supply chain? You know, how do we run, you know, healthcare, um, all these things are become are, and how do we run cyber security? They're being redefined as data problems and data challenges. And they have data solutions. So that's right. Data strategies are insanely important because, you know, if, if the solution is through data, then you need to have, you know, a data strategy, you know, and in our world, that means you have a data cloud and you have all the enablement that allows you to do that. But, you know, hospitals, you know, are, are saying, you know, data science is gonna have a bigger impact on healthcare than life science, you know, in the coming, whatever, you know, 10, 20 years, how do you enable that? >>Right. I, I have conversations with, with, with hospital executives are like, I got generations of data, you know, clinical diagnostic, demographic, genomic. And then I, I am envisioning these predictive outcomes over here. I wanna be able to predict, you know, once somebody's gonna get what disease and you know, what I have to do about it, um, how do I do that? <laugh> right. The day you go from, uh, you know, I have a lot of data too. I have these outcomes and then do me a miracle in the middle, in the middle of somewhere. Well, that's where we come in. We're gonna organize ourselves and then unpack thats, you know, and then we, we work, we through training models, you know, we can start delivering some of these insights, but the, the promise is extraordinary. We can change whole industries like pharma and, and, and healthcare. Um, you know, 30 effects of data, the economics will change. And you know, the societal outcomes, you know, um, quality of life disease, longevity of life is quite extraordinary. Supply chain management. That's all around us right >>Now. Well, there's a lot of, you know, high growth companies that were kind of COVID companies, valuations shot up. And now they're trying to figure out what to do. You've been pretty clear because of what you just talked about, the opportunities enormous. You're not slowing down, you're amping it up, you know, pun intended. So Frank Luman, thanks so much for coming on the cube. Really appreciate your time. >>My pleasure. >>All right. And thank you for watching. Keep it right there for more coverage from the snowflake summit, 2022, you're watching the cube.

>> Narrator: theCUBE presents KubeCon and CloudNativeCon Europe 2022, brought to you by Red Hat, the Cloud Native Computing Foundation and its ecosystem partners. >> Welcome to Valencia, Spain, KubeCon, CloudNativeCon Europe 2022. I'm Keith Townsend, your host. And we're continuing the conversations around ecosystem cloud native, 7,500 people here, 170 plus show for sponsors. It is for open source conference, I think the destination. I might even premise that this may be, this may eventually roll to the biggest tech conference in the industry, maybe outside of AWS re:Invent. My next guest is Nick van Wiggeren. >> Wiggeren. >> VP engineering of PlanetScale. Nick, I'm going to start off the conversation right off the bat PlanetScale cloud native database, why do we need another database? >> Well, why don't you need another database? I mean, are you happy with yours? Is anyone happy with theirs? >> That's a good question. I don't think anyone is quite happy with, I don't know, I've never seen a excited database user, except for guys with really (murmurs) guys with great beards. >> Yeah. >> Keith: Or guys with gray hair maybe. >> Yeah. Outside of the dungeon I think... >> Keith: Right. >> No one is really is happy with their database, and that's what we're here to change. We're not just building the database, we're actually building the whole kind of start to finish experience, so that people can get more done. >> So what do you mean by getting more done? Because MySQL has been the underpinnings of like massive cloud database deployments. >> 100% >> It has been the de-facto standard. >> Nick: Yep. >> For cloud databases. >> Nick: Yep. >> What is PlanetScale doing in enabling us to do that I can't do with something like a MySQL or a SQL server? >> Great question. So we are MySQL compatible. So under the hood it's a lot of the MySQL you know and love. But on top of that we've layered workflows, we've layered scalability, we've layered serverless. So that you can get all of the the parts of the MySQL, that dependability, the thing that people have used for 20, 30 years, right? People don't even know a world before MySQL. But then you also get this ability to make schema changes faster. So you can kind of do your work quicker get to the business objectives faster. You can scale farther. So when you get to your MySQL and you say, well, can we handle adding this one feature on top? Can we handle the user growth we've got? You don't have to worry about that either. So it's kind of the best of both worlds. We've got one foot in history and we've got one foot in the new kind of cloud native database world. We want to give everyone the best of both. >> So when I think of serverless because that's the buzzy world. >> Yeah. >> But when I think of serverless I think about developers being able to write code. >> Yep. >> Deploy the code, not worry about VM sizes. >> Yep. >> Amount of disk space. >> Yep. >> CPU, et cetera. But we're talking about databases. >> Yep. >> I got to describe what type of disk I want to use. I got to describe the performance levels. >> Yep. >> I got all the descriptive stuff that I have to do about infrastructures. Databases are not... >> Yep. >> Keith: Serverless. >> Yep. >> They're the furthest thing from it. >> So despite what the name may say, I can guarantee you PlanetScale, your PlanetScale database does run on at least one server, usually more than one. But the idea is exactly what you said. So especially when you're starting off, when you're first beginning your, let's say database journey. That's a word I use a lot. The furthest thing from your mind is, how many CPUs do I need? How many disk iOS do I need? How much memory do I need? What we want you to be able to do is get started on focusing on shipping your code, right? The same way that Lambda, the same way that Kubernetes, and all of these other cloud native technologies just help people get done what they want to get done. PlanetScale is the same way, you want a database, you sign up, you click two buttons, you've got a database. We'll handle scaling the disk as you grow, we'll handle giving you more resources. And when you get to a spot where you're really starting to think about, my database has got hundreds of gigabytes or petabytes, terabytes, that's when we'll start to talk to you a little bit more about, hey, you know it really does run on a server, we ain't got to help you with the capacity planning, but there's no reason people should have to do that up front. I mean, that stinks. When you want to use a database you want to use a database. You don't want to use, 747 with 27 different knobs. You just want to get going. >> So, also when I think of serverless and cloud native, I think of stateless. >> Yep. >> Now there's stateless with databases, help me reconcile like, when you say it's cloud native. >> Nick: Yep. >> How is it cloud native when I think of cloud native as stateless? >> Yeah. So it's cloud native because it exists where you want it in the cloud, right? No matter where you've deployed your application on your own cloud, on a public cloud, or something like that, our job is to meet you and match the same level of velocity and the same level of change that you've got on your kind of cloud native setup. So there's a lot of state, right? We are your state and that's a big responsibility. And so what we want to do is, we want to let you experiment with the rest of the stateless workloads, and be right there next to you so that you can kind of get done what you need to get done. >> All right. So this concept of clicking two buttons... >> Nick: Yeah. >> And deploying, it's a database. >> Nick: Yep. >> It has to run somewhere. So let's say that I'm in AWS. >> Nick: Yep. >> And I have AWS VPC. What does it look like from a developer's perspective to consume the service? >> Yeah. So we've got a couple of different offerings, and AWS is a great example. So at the very kind of the most basic database unit you click, you get an endpoint, a host name, a password, and the username. You feed that right into your application and it's TLS secure and stuff like that, goes right into the database no problem. As you grow larger and larger, we can use things like AWS PrivateLink and stuff like that, to actually start to integrate more with your AWS environment, all the way over to what we call PlanetScale Managed. Which is where we actually deploy your data plan in your AWS account. So you give us some permissions and we kind of create a sub-account and stuff like that. And we can actually start sending pods, and hold clusters and stuff like that into your AWS account, give you a PrivateLink, so that everything looks like it's kind of wrapped up in your ownership but you still get the same kind of PlanetScale cloud experience, cloud native experience. >> So how do I make calls to the database? I mean, do I have to install a new... >> Nick: Great question. >> Like agent, or do some weird SQL configuration on my end? Or like what's the experience? >> Nope, we just need MySQL. Same way you'd go, install MySQL if you're on a Mac or app store to install MySQL on analytics PC, you just username, password, database name, and stuff like that, you feed that into your app and it just works. >> All right. So databases are typically security. >> Nick: Yep. >> When my security person. >> Nick: Yep. >> Sees a new database. >> Nick: Yep. >> Oh, they get excited. They're like, oh my job... >> Nick: I bet they do. >> My job just got real easy. I can find like eight or nine different findings. >> Right. >> How do you help me with compliance? >> Yeah. >> And answering these tough security questions from security? >> Great question. So security's at the core of what we do, right? We've got security people ourselves. We do the same thing for all the new vendors that we onboard. So we invest a lot. For example, the only way you can connect to a PlanetScale database even if you're using PrivateLink, even if you're not touching the public internet at all, is over TLS secured endpoint, right? From the very first day, the very first beta that we had we knew not a single byte goes over the internet that's not encrypted. It's encrypted at rest, we have audit logging, we do a ton internally as well to make sure that, what's happening to your database is something you can find out. The favorite thing that I think though is all your schema changes are tracked on PlanetScale, because we provide an entire workflow for your schema changes. We actually have like a GitHub Polar Request style thing, your security folks can actually look and say, what changes were made to the database day in and day out. They can go back and there's a full history of that log. So you actually have, I think better security than a lot of other databases where you've got to build all these tools and stuff like that, it's all built into PlanetScale. >> So, we started out the conversation with two clicks but I'm a developer. >> Nick: Yeah. >> And I'm developing a service at scale. >> Yep. >> I want to have a SaaS offering. How do I automate the deployment of the database and the management of the database across multiple customers? >> Yeah, so everything is API driven. We've got an API that you can use supervision databases to make schema changes, to make whatever changes you want to that database. We have an API that powers our website, the same API that customers can use to kind of automate any part of the workflow that they want. There's actually someone who did talk earlier using, I think, wwww.crossplane.io, or they can use Kubernetes custom resource definitions to provision PlanetScale databases completely automatically. So you can even do it as part of your standard deployment workflow. Just create a PlanetScale database, create a password, inject it in your app, all automatically. >> So Nick, as I'm thinking about scale. >> Yep. >> I'm thinking about multiple customers. >> Nick: Yep. >> I have a successful product. >> Nick: Yep. >> And now these customers are coming to me with different requirements. One customer wants to upgrade once every 1/4, another one, it's like, you know what? Just bring it on. Like bring the schema changes on. >> Yep. >> I want the latest features, et cetera. >> Nick: Right. >> How do I manage that with PlanetScale? When I'm thinking about MySQL it's a little, that can be a little difficult. >> Nick: Yeah. >> But how does PlanetScale help me solve that problem? >> Yeah. So, again I think it's that same workflow engine that we've built. So every database has its own kind of deploy queue, its own migration system. So you can automate all these processes and say, on this database, I want to change this schema this way, on this database I'm going to hold off. You can use our API to drive a view into like, well, what's the schema on this database? What's schema on this database? What version am I running on this database? And you can actually bring all that in. And if you were really successful you'd have this single plane of glass where you can see what's the status of all my databases and how are they doing, all powered by kind of the PlanetScale API. >> So we can't talk about databases without talking about backup. >> Nick: Yep. >> And recovery. >> Yep. >> How do I back this thing up and make sure that I can fall back? If someone deleted a table. >> Nick: Yep. >> It happens all the time in production. >> Nick: Yeah, 100%. >> How do I recover from it? >> So there's two pieces to this, and I'm going to talk about two different ways that we can help you solve this problem. One of them is, every PlanetScale database comes with backups built in and we test them fairly often, right? We use these backups. We actually give you a free daily backup on every database 'cause it's important to us as well. We want to be able to restore from backup, we want to be able to do failovers and stuff like that, all that is handled automatically. The other thing though is this feature that we launched in March called the PlanetScale Rewind. And what Rewind is, is actually a schema migration undo button. So let's say, you're a developer you're dropping a table or a column, you mean to drop this, but you drop the other one on accident, or you thought this column was unused but it wasn't. You know when you do something wrong, you cause an incident and you get that sick feeling in your stomach. >> Oh, I'm sorry. I've pulled a drive that was written not ready file and it was horrible. >> Exactly. And you kind of start to go, oh man, what am I going to do next? Everyone watching this right now is probably squirming in their seat a bit, you know the feeling. >> Yeah, I know the feeling >> Well, PlanetScale gives you an undo button. So you can click, undo migration, for 30 minutes after you do the migration and we'll revert your schema with all the data in it back to what your database looked like before you did that migration. Drop a column on accident, drop a table on accident, click the Rewind button, there's all the data there. And, the new rights that you've taken while that's happened are there as well. So it's not just a restore to a point in time backup. It's actually that we've replicated your rights sent them to both the old and the new schema, and we can get you right back to where you started, downtime solved. >> Both: So. >> Nick: Go ahead. >> DBAs are DBAs, whether they've become now reformed DBAs that are cloud architects, but they're DBAs. So there's a couple of things that they're going to want to know, one, how do I get my zero back up in my hands? >> Yeah. >> I want my, it's MySQL data. >> Nick: Yeah. >> I want my MySQL backup. >> Yeah. So you can just take backups off the database yourself the same way that you're doing today, right? MySQL dump, MySQL backup, and all those kinds of things. If you don't trust PlanetScale, and look, I'm all about backups, right? You want them in two different data centers on different mediums, you can just add on your own backup tools that you have right now and also use that. I'd like you to trust that PlanetScale has the backups as well. But if you want to keep doing that and run your own system, we're totally cool with that as well. In fact, I'd go as far as to say, I recommend it. You never have too many backups. >> So in a moment we're going to run Kube clock. So get your... >> Okay, all right. >> You know, stand tall. >> All right. >> I'll get ready. I'm going to... >> Nick: I'm tall, I'm tall. >> We're both tall. The last question before Kube clock. >> Nick: Yeah. >> It is, let's talk a little nerve knobs. >> Nick: Okay. >> The reform DBA. >> Nick: Yeah. >> They want, they're like, oh, this query ran a little bit slow. I know I can squeeze a little bit more out of that. >> Nick: Yeah. >> Who do they talk to? >> Yeah. So that's a great question. So we provide you some insights on the product itself, right? So you can take a look and see how are my queries performing and stuff like that. Our goal, our job is to surface to you all the metrics that you need to make that decision. 'Cause at the end of the day, a reform DBA or not it is still a skill to analyze the performance of a MySQL query, run and explain, kind of figure all that out. We can't do all of that for you. So we want to give you the information you need either knowledge or you know, stuff to learn whatever it is because some of it does have to come back to, what's my schema? What's my query? And how can I optimize it? I'm missing an index and stuff like that. >> All right. So, you're early adopter of the Kube clock. >> Okay. >> I have to, people say they're ready. >> Nick: Ooh, okay. >> All the time people say they're ready. >> Nick: Woo. >> But I'm not quite sure that they're ready. >> Nick: Well, now I'm nervous. >> So are you ready? >> Do I have any other choice? >> No, you don't. >> Nick: Then I am. >> But are you ready? >> Sure, let's go. >> All right. Start the Kube clock. (upbeat music) >> Nick: All right, what do you want me to do? >> Go. >> All right. >> You said you were ready. >> I'm ready, all right, I'm ready. All right. >> Okay, I'll reset. I'll give you, I'll give, see people say they're ready. >> All right. You're right. You're right. >> Start the Kube clock, go. >> Okay. Are you happy with how your database works? Are you happy with the velocity? Are you happy with what your engineers and what your teams can do with their database? >> Follow the dream not the... Well, follow the green... >> You got to be. >> Not the dream. >> You got to be able to deliver. At the end of the day you got to deliver what the business wants. It's not about performance. >> You got to crawl before you go. You got to crawl, you got to crawl. >> It's not just about is my query fast, it's not just about is my query right, it's about, are my customers getting what they want? >> You're here, you deserve a seat at the table. >> And that's what PlanetScale provides, right? PlanetScale... >> Keith: Ten more seconds. >> PlanetScale is a tool for getting done what you need to get done as a business. That's what we're here for. Ultimately, we want to be the best database for developing software. >> Keith: Two, one. >> That's it. End it there. >> Nick, you took a shot, I'm buying it. Great job. You know, this is fun. Our jobs are complex. >> Yep. >> Databases are hard. >> Yep. >> It is the, where your organization keeps the most valuable assets that you have. >> Nick: A 100%. >> And we are having these tough conversations. >> Nick: Yep. >> Here in Valencia, you're talking to the leader in tech coverage. From Valencia, Spain, I'm Keith Townsend, and you're watching theCUBE, the leader in high tech coverage. (upbeat music)

>> Announcer: theCUBE presents Dell Technologies World, brought to you by Dell. >> Hey everyone. Welcome back to theCUBE's live coverage of Dell Technologies World 2022, live from the Venetian in Las Vegas. Lisa Martin here with Dave Vellante. This is our second full day of coverage of theCUBE. Lots going on, lots of announcements. We always love talking to customers, hearing the voice of the customer, and we have a couple of guests, one from Dell Customer at Lowe's, John Dabek is here, the senior director of infrastructure. Ali Biers also joins us, marketing director of edge solutions at Dell Technologies. Welcome to the program. >> Thank you so much. >> Thank you for inviting us. Appreciate it. >> So John, let's go ahead and start with you. Let's talk about what the heck is going on in retail. Tremendous change, tremendous transformation, lot of pressures. The last two years have been quite influential. Talk to us about some of the trends that you're seeing in retail, some of the challenges that are going on. >> Absolutely, so COVID has put everything on steroids in terms of the omnichannel experience, so we no longer think of digital as something that's separate. It's all integrated with the store experience. So, interestingly enough, two thirds of our customers shop online before they come into the store, so that shows you the power of having the digital working in harmony with the store. >> So how does that affect your technology strategy? What changes do you see? >> That's a very good question, so we've had to accelerate a number of our new technologies to really create that frictionless experience for the customer. So for example, I'll give you a great example of a technology that we deploy today called pickup lockers. So you order online and then there's a set of pickup lockers right in the vestibule of the store. You go up and you scan it, the locker opens, and then you can take your merchandise and go on, so it's a great experience as to how the technology has changed, and everything from utilizing the mobile applications where customers can now text us when they're in the parking lot, we can deliver their merchandise. Michael Dell put it very well in terms of the strategy in his keynote yesterday. What he talked about was today it's the public cloud, it's the private cloud within the data centers, and it's the edge, and the edge has become very, very important for us because that's where we want to put all of our technologies in the store, closer to the store. >> Ali talk to us about from an overall a Dell vision lens perspective the challenges overall that you're seeing in retail and where the edge is really advantageous for organizations to be competitive. >> Yeah, I mean, really what you're seeing is you've got these incredibly savvy customers who really want to have an experience when they go into the store, and on the other hand, you have the retailer that wants to develop that loyalty but yet they're dealing with tremendous complexity in their footprint, as well as just the pace of change, so trying to modernize and do that at a really fast pace just like what John was talking about and still stick to all the imperatives like being secure and manageable at scale. It's really a big challenge. >> Yeah, and when you talk, Ali, about modernizing at a fast pace, the first 600 stores that we did with VxRail, and we'll go into a little more detail I'm sure about that, we did in three months with the help of Dell technology. >> Lisa: 600 stores in three months? >> In three months, right, and the key was zero disruptions in the store. Now we're talking about 100,000+ square foot stores, so we're talking big stores, and we have a very short window. We can go from midnight to 5:00 AM because 5:00 AM the contractors are there to pick up their materials and we have to be open and ready, so we didn't miss a beat. >> So that's interesting. I heard your CEO the other day talking about how you guys really focused on the contractors, especially during COVID. So that was also another shift. I mean, the volume from contractors probably increased 'cause we give them such great focus. So there's this concept of the intelligent factory. Is there a similar one with the intelligent store? >> John: Oh, without a doubt. So I'll give you an example. We have 140,000 mobile devices deployed in our stores for our employees that can do everything from find merchandise, talk, receive calls. You're going to the store to pick up mulch, and they can take the device and do a checkout from the device instead of you having to come into the store and then go out to pick up your mulch. It doesn't get better than that. >> I love that example cause that one's so relatable, and I think like once you start thinking about how all this to technology in the store can really help, so all of a sudden you know where your customers are spending their time in the store. You can position your customer service people to help in the aisles where people are getting stuck, so it really just puts so many more insights in the hands of retailers to be able to action and make decisions. >> You know, it's funny, sometimes people, when they talk to people in IT, technology like ourselves say, "You know, you guys always talk about, oh, permanent changes. Nah, it's going to be the same. You watch in a few years." Here's an example, there's no way we're ever going back. You know, it's permanent. >> It's permanent, and you know what? All the bad things about about COVID and the pandemic, the great thing is it really accelerated that omnichannel journey. It forced many retailers to do that, including Lowe's. >> Silver lining, but it also, from a forcing factor perspective, it was critical from a competitive standpoint. I mean, we have these expectations as consumers that we can have this consumer experience everywhere which means I want to be able to do my transaction in real time. I want to go onto the website and make sure that they have what I want inventory wise in real time. Real time we learned in the pandemic, not a nice to have anymore. >> No, absolutely. >> Lisa: That is a competitive advantage for every industry, especially retail. >> Yeah, and if you think about it, we have a mini data center inside the store with the VxRail, so it was very important for us because we were not able to leverage the new application development on the old platform, so we absolutely need the power of the new platform to enable the stores. It's very, very, critical. >> Paint a picture of what it's like inside of a store. I mean, what's the infrastructure look like, the apps that are running, the data flow? >> John: So if you picture a dedicated room for the technology, unfortunately in a store you don't build a data center, so it's a concrete floor, as you can imagine. But through the help of Dell, they've really helped us harden the environment as well, to put in technologies that help with intelligent power distribution units and other types of technology because we're making such a big investment that we don't want to have power be a disrupter. You get six nines on our network, six nines on our, on our compute infrastructure. We don't want power to be an impact. But in terms of the apps, everything that you need to run a store from a POS perspective runs in the environment, and it's being enhanced every day, because now the communication from the mobile device of the consumer to what happens in the store is integrating, so it really requires a lot of compute power. >> What I really like about the way you guys have done it too is that you guys have really thought about it in terms of planning for the future. So you thought about how to create that foundation that's really going to scale over time. >> And Ali you've brought up a good point because one of the things that we didn't anticipate when we started was the fact that we would need GPUs in the future. and the power of the GPU was required for things like video analytics, AI, and it came to light as we had one of our innovator, person in the lab saying, "Hey in the test system, we want 300 gigs of memory to do a test," and we're going like, oh my God, this would never run in production. So that's when we got into the whole concept of GPU so all of our stores are GPU enabled, so as we need them, we can add that to the store, but thanks for bringing that. >> That's really interesting. So for what, security? Other use cases? AI, you're saying. How are you applying that? Dig into that. >> It could be security, so think of having cameras in the store that watch what people do from a checkout perspective, and it's tied in with the system so it knows the weight of an item, it knows the cost of an item, and it's able to spot potential frauds and alert people. But to do that, you need video analytics, and that requires a lot of processing power. >> How much of that data do you persist? >> We could talk about that for another hour. >> Oh, okay. >> With respect to that. But generally we utilize the data to handle what we're looking to accomplish. We do capture other data for AI and other analytic purposes as well. >> Ali I think I interrupted you. >> Ali: Oh, no worries. I think one of the things about the edges, people have a tendency to go build a technology stack to address the business problem that they're trying to address in that moment, and it's usually driven by the people that are working in the store. They see an opportunity for advancement, but all of a sudden, if you have a lot of those, how now are you going to deploy it, secure it, manage it, and do them all separately? So I think what you're talking about is you've really figured out a way to do that across all those different use cases, and maybe even for the ones that you don't know exist yet so. >> And that's the good point is that we don't know what exists, because we have to, as we build it, we have to build the business case for what makes sense to put into the stores. So you you'll see a lot of continued innovation with inventory aids to help stock shelves, applications that help the customer journey. I saw some deployment of some new apps in the stores where we can tell where people are located real time in the store, so wouldn't it be great if you know that you can dispatch customer service personnel to that area and great opportunity to plus sell in that environment. >> I can't wait for my next trip to Lowe's. This is going to be so fantastic. But John, I got to ask you, you're sitting here with the marketing director, I'm a marketing girl myself, future proof. It's a term that is always interests me because it can mean so many different things. You're working with Dell, I've been working with Dell for a while, how is what you've architected for the connected store? Intelligence store, excuse me. How do you feel like when you don't know what's coming, but do you really feel like we've got a future-proof architecture capabilities and a partner that's going to allow us to scale and grow as things, obviously we couldn't have predicted what happened in the last two years. >> So not too recent in the past where you would primarily have appliances in stores and single purpose servers, separate storage. So now with the VxRail technology, you have hyper converged infrastructure. So things are virtualized, your storage is virtualized, your server host infrastructure is virtualized, and the power of the VxRail is that as we grow and have different needs, we can change out the processor, we can add memory, we can add storage all while we're still running in a store. >> Dave: Bring a GPU in if you need to, right? >> Bring a GPU in, so it was architected to handle the growth and the simplicity of running the store. So we only have a handful of people that manage the stores from a technology standpoint, and thanks to the the technologies that are provided. >> So you could scale it, and you got the blueprint, what's the network look like? >> And that's some good advice for folks who are looking at this. You have to address the network first, so we deployed a software defined network that gave us the capacity and the future growth capacity and the backup we're using. We're transferring to from 4G to 5G for backup purposes, and we're trying to figure out what's the role of 5G in the future? 'Cause it gives you tremendous flexibility. But remember the VxRail and the edge can run independently, so if the network goes down, we operate a store. >> Lisa: And you had that frictionless experience which as consumers, we all had this expectation that it's going to be frictionless, it's going to be seamless, I'm going to be able to get what I want. >> Absolutely. >> Not quite 24/7. Well, yeah, with online, yeah. >> With online, 24/7. >> So last question as we grab, and I wish we had more time to dig into this. What's next? What are some of the future directions as hopefully things return back to "normal". What are some of the things that Lowe's and Dell are going to do next together? >> We have to finish the stores. We'll be done by October. And by the way, we're experiencing supply chain issue, but not with Dell. We're having trouble getting network switches, but last week we had a breakthrough, and right now we're on track to finish all of the stores by October of 2022. But what's next? Continuing to now leverage the platform that we've put in place, to bring the applications and to start working with our innovators to experiment with the GPUs and put it into effect, and I'm sure Ali's got some great things planned as well on the edge with the technology which we're look to take advantage of. >> Yeah I mean, our goal is really to help customers to simplify their edge because it's incredibly complex. They're dealing with an ecosystem of partners, software, hardware, networking, so really being that partner that they can rely on, having that broad end to end portfolio, and being the person and the company that can architect and bring all of that together in a way that you can life cycle manage it over time. >> John: And the great thing is by being software defined, it's all seems very complicated, but it's simple to manage, and that's the key and that's the power that Dell brings to us. >> Simple to manage, famous last words. John, thank you, Ali you as well for joining us, sharing what Dell and Lowe's are doing together to really enable this intelligent store. I really can't wait for my next trip. (everyone laughing) >> Thank you so much. >> Yes, I got to hit the mulch pile. Want 'em to bring into my car's, it's too heavy to carry. Guys thank you so much for sharing your insights. We appreciate the story. >> Thank you. >> For our guests and Dave Vellante, I'm Lisa Martin. You're watching theCUBE live from Las Vegas at the Venetian. Day two of our coverage of Dell Tech World continues right after this short break. (soft music)

(bright upbeat music) >> Welcome, everyone, to this CUBE Conversation featuring Imply. I'm your host, Lisa Martin. Today, we are excited to be joined by FJ Yang, the co-founder and CEO of Imply. FJ, thanks so much for joining us today. >> Lisa, thank you so much for having me. >> Tell me a little bit about yourself and about Imply. >> Yeah, absolutely. So, I started Imply a couple years ago and before start the company, I was a technologist. So, I was a software engineer and software developer primarily specializing in distributed systems. And one of the projects I worked on, ultimately became kind of the centerpiece behind Imply. Imply, as a company is a database company. What we do is we provide developers a powerful tool in order to help them build various types of data analytic applications. We're also an open source company, where the company develops a popular open source project called Apache Druid. >> Got it, so database as a service for modern analytics applications. You're also one of the original authors of Apache Druid. Talk to me, gimme a timeline, Druid's 10-year history or so. What's the big picture? What's been the market evolution that you've seen? >> Yeah, absolutely. So, I moved out to Silicon Valley basically to try and work at a startup, 'cause I was enamored with startups and I thought they were the coolest thing ever. So, at one point, I basically joined the smallest startup I could find. It was a startup called Metamarkets, which actually doesn't exist anymore, it was ultimately acquired by Snapchat a couple years ago. But, I was one of the first employees there. And what we were trying to do at the time, was we were trying to build an analytics application, a user-facing application where people could slice and dice various types of data. At the time, the data sets we were working with were like online advertising, digital advertising data sets which were very large and complex. And, we really struggled to find a database that could basically power the kind of interactive and user experience that we know we want to provide our end customers. So, what ended up happening was we decided to build our own database and we were a three or five-person shop when we decided to build our own database, and that was Druid. And over time, we saw many other types of companies actually struggle with a similar set of problems, albeit with very different types of use cases and very different types of data sets. And, the Druid community kind of grew and evolved from that. And in my work in engaging with the community, what I saw was a market opportunity and a market gap and that's where Imply formed. >> Let's double click on that. You talked about why you built Druid, the problem you were looking to solve. But, talk to me about the role that Imply has. >> Right. So, Imply is a commercial company. What we do is we build kind of an end-to-end enterprise product around Druid as the core engine. Imply provides deployment, it deploys management, it provides security, and it also provides visualization and monitoring pieces around Druid as a core engine. What we aim to do at Imply is really enable developers to build various types of data applications with only the click of a few buttons and interacting with a simple set of APIs. So, the goal is, if you're a developer, you don't have to think about managing the database yourself, you don't have to think about the operational complexity at the database, but instead, what you do is just work with APIs and build your application. >> So, then what gives Druid its superpower? What makes Druid Druid? >> Yeah, so, Druid, the easiest way to think about it, is it's a really fast calculator and it's a very fast calculator for a whole lot of data. So, when you have a whole lot of data and you want to crunch numbers very, very quickly, Druid is very good at doing that. And, people always ask me this question, which is, what makes Druid special? And I always struggle with it, because it's never just one thing, it's actually layers, upon layers, upon layers of engineering. You start with fundamentals of how you maximally optimize the resources of any hardware. So, how do you maximize storage? How do you maximize compute? And then, there's a lot of optimizations around how do you store the data? How do you access that data in a very fast way once it's stored in order to run computations very quickly? So, unfortunately, there's no silver bullet about Druid, but maybe I can summarize in this way. Druid, it's like a search system, and a data warehouse, and a time series database all mixed together. And, that architecture enables it to be very, very quickly. And unfortunately, if you don't know what some of the components I'm talking about are, it's hard to describe where the secret sauce is (chuckling). >> Sometimes you want to keep that secret sauce secret. Talk to me about the overall data space, as we see these days, every company is a data company or if it's not, it needs to be to be successful. Where does Druid fit in the overall data space? Give us that picture of where it fits. >> Yeah, absolutely. So, it's pretty interesting that you see now in the public markets as well as the private markets, some of the hottest unicorns out there are actually data companies. And, I think what people are are understanding now for the first time, is just how vast and complex the data space is and also how large the market is as well. So for sure, there's many different components and pieces in the data space, and they oftentimes come together to form what's known as a data stack. So, data stack is basically kind of an architecture that has various systems and each of these systems are designed to do a certain set of things very, very well. For example, a company that recently went public is a company called Confluent, which mostly catered towards data transport, so getting data from one place to another. They're built around an open source engine called Apache Kafka. Databricks is another mega unicorn that's going to go public pretty soon. And they're built around an open source project called Spark, which is mainly used for data processing. Where we sit is on the data query side. So, what that means is we're a system in which people can store data and then access that data very, very quickly. And there's other systems that do that, but where our bread and butter is, is we're building some sort of application, where you have end users that are clicking buttons in order to get access to data, we're a platform that enables the best end user experience. We return queries very, very quickly with a consistent SLA, we immediately visualize data as soon as it's made available, and then we can support many, many, many concurrent end users to access the system at the same time. >> So, real time. One of the things I think that we learned during the pandemic, one of the many things is that access to real time data, it's no longer a nice to have, it is table stakes for, as I said, every company, these days is a data company. So with how you describe it, how should people think of Druid versus a data warehouse? >> Yeah. So, that's a great question. And obviously, data warehouses have been around since the 70s. In the B2B space, they're among the largest players that kind of exist in enterprise software. So, it's only natural that when you come up with sort of a new analytics database, that people compare it with what they already know, which is data warehouse. So, a lot of how we think about why we're different than data warehouse goes back to how I answered the previous question, and that we're focused right now, really, on powering different types of data applications. Data applications are UIs in which people are really accessing and getting insights from data by clicking buttons versus writing more complex equal queries. And when you click buttons and you get access to data, what you want in terms of an end user experience, is you want answers to questions to come back almost immediately. So you don't want to click a button and then see a spinning dial that goes on for minute and minutes before an answer comes back. You basically want results to come back immediately. You want that experience no matter what types of queries that you're issuing or how many people are issuing those queries. If you have thousands, if not tens of thousands of people that are trying to access data exact same time, you want to give a consistent user experience like Google, which is one of my favorite products. There're millions of people that use Google, and ask questions and they get their answers back immediately. So we try to provide that same experience, but instead of a generic search engine, what we're doing is we're providing a system that basically answers questions on data and users get a very interactive and fast experience when asking questions. And that's something that I think is very different than what data warehouses are primarily specialized in. Data warehouses are really designed to be systems in which people write very large complex sequel queries that might take minutes or hours sometimes to run. But the experience of using a data warehouse to power and application is not a great one. >> So, I'm just curious, FJ, in the last couple of years, with, as I mentioned before the access to real time data no longer a nice to have, but it's something business critical for so many industries, did you see any industries in particular in the recent years that were really primed candidates for what Druid would can deliver? >> Yeah, that's a great question. And you can imagine that the industries that really heavily rely on fast decision making are the ones that are earliest to adopt technologies like this. So, in the security space, and the observability space, as well as working with networking and various forms of backend kind of metrics data, this system has been very popular and it's been popular because people need to triage (indistinct) as they occur, they need to resolve problems, and they also need immediate visibility, as well as very fast queries on data. Another space is online advertising. Online advertising, nowadays is almost entirely programmatic and digital. So, response times are critical in order to make decisions. And that's where Druid was actually born. It was born for advertising before it kind of went everywhere else. We're seeing it more in fraud protection, fraud prevention as well as fraud diagnostics nowadays. We're seeing it in retail as well, which is pretty interesting. And, the goal, of course, is I believe every industry and every vertical needs the capabilities that we provide. So hopefully, we see a whole lot more use cases in the near future. >> Right, it's absolutely horizontal these days. So, 10-year history, you've got a community of thousands, what's the future of Druid? What do you see when you open the crystal ball and look now down the 12 months, 18 months road? >> Yeah. So, I think as a technologist, your goal as the technologist, at least for me, is to try and create technology that has as much applicability as possible and solves problems for as many people as possible. That's always the way I think about it. So, I want to do good engineering and I want to build good systems. And I think what the hallmark of a really good system is you can solve all different types of problems and condense all these different problems, actually into the same set of models and the same set of principles. And, a thing that makes me most excited about Druid is the many, many different industries that it's found value and the many different use cases it's found value. So, if I were to give 30,000 foot roadmap, that's what we're trying to do with the next generation of Druid. We're actually doing a pretty major engine upgrade right now, and pretty major overhaul the entire system. And the goal of that is to take all the learnings that we've had over the last decade and to create something new that can solve an expanded set of problems that we've heard from the community and from other places as well. >> Excellent. FJ, exciting work that you've done the last 10 years. Congratulations on that. Looking forward to the roadmap that you talked about. Thanks for sharing what Druid is, the Imply connection, and all the different use cases where it applies. We appreciate your insights. >> Appreciate you having me on the show. Thank you very much. >> My pleasure. For FJ Yang, I'm Lisa Martin. You're watching this CUBE Conversation, the leader in live tech enterprise coverage. (bright upbeat music)

(bright upbeat music) >> Welcome to theCUBE's continuous coverage of "AWS re:Invent 2021". I'm Dave Nicholson, and here at theCUBE, we're running one of the most important largest events in tech industry history with two live sets right here, live in Las Vegas, along with our two studios. And I'm delighted here in our studio to welcome Scott Warren US AWS practice, vice president for Capgemini. Welcome. >> Thank you. >> Dave: How's the show been going for you so far? >> Very, very good so far. It's great to be back in person. >> So tell me about your role at Capgemini. What you focus on. You're responsible for the relationship with AWS? >> Absolutely. So managing the relationship with AWS and how we partner, and then probably more importantly, kind of how we go to market with the AWS offering for our customers. So kind of understanding what the customer demand is, how we can help accelerate and get them moving faster out to the cloud, and then building that up as well as kind of industry specific offers on how we can accelerate cloud adoption. >> So when you talk about acceleration often in an organization like yours, there is the tug of war between the spoke solution hearing and pre-packaged things that serve to be accelerators. How do you go about balancing those things and tell us about some of the accelerators that you've developed? >> Absolutely. I think it's always kind of going to be a hybrid between the bespoken out of the box solutions. The out of the box solutions are inevitably always going to take some sort of customization or something like that to make them applicable within a customer's environment. But we all know it's very time consuming and expensive to build something completely bespoke from the ground up. So the way we really address that is we've built something at Capgemini we called it the cloud boost library. It is an online get lab library of thousands of code templates, infrastructure as code snippets that solve deploying your infrastructure and provision your infrastructure on the cloud, microservice design for healthcare and financial services and manufacturing and automotive. >> So industry specific? >> Not just specific and cloud in general. And so we bring that to every cloud engagement we work on. It's our real motto around that is we should never be starting on zero, starting from ground zero and anything we push out to AWS and we can always borrow, steal, modify, and change part of that library specific to that customer demand and need, and really speed up the implementation and get them out to AWS faster. >> Can you kind of double click on that? Give us an example of an accelerator inaction. You don't have to necessarily, if you've got a customer name, fantastic, or you can keep it generic. >> Yeah, absolutely. So we work for a big financial services company that's doing kind of an online data dissemination system, so thousands of public API is to disseminate data out to their customers and partners and vendors and things like that. So we were able to use that library to kind of get the framework for every single one of those APIs. A template, a kind of base function for that, and then use that kind of repeatably across those thousands of API. So we never really started from zero and said, provided 70, 80% kind of efficiency gain on that project versus kind of building it from the ground up. >> So with a customer like that, how did the initial engagement start? Was this a preexisting Capgemini relationship? Was this AWS at the table strategizing bringing in Capgemini. How does that work with your relationships with customers? >> So this was an existing customer of ours that we'd been doing application management in their data center for years. And several years ago, they had a kind of a leadership change happened and a new CTO came in and he laid down the edict that they're now a cloud first organization. So of course all his direct reports and managers started asking, what does that really mean? And they came to us as a trusted partner. And so we started walking them through our framework and template of how we bring our customers from ground zero completely in the data center, completely to a cloud first organization. And at that same time, we also began engaging our counterparts at AWS because we want to make sure we're in lockstep with what they're doing at AWS and kind of one consistent message out to our customer and doing the things the way they want them to be done. We want to unlock the funding programs available from AWS to incentivize that customer, to move out to the cloud. And then really having that kind of three legged partnership with us, the customer and AWS, puts them on the right path for success and in faster adoption of the cloud. >> Capgemini didn't just roll out of college a couple of years ago. (laughs) >> Been around a while. Been around a while. >> So you have an interesting perspective because you just mentioned being involved in the management of a customer's environment and IT landscape that is outside the purview of cloud, at least at some stage of the game. How do you turn being a legacy provider of services into a superpower instead of a liability? >> Absolutely. Yeah. >> How do you do that? And the reason why I say that superpower is because you said cap earlier and I thought in America, but it's a serious question. Some would say, well, Capgemini legacy. No, no, no. What's your reply? >> Absolutely. So what we found is the most important thing about a move to the cloud is understanding the entire application portfolio and landscape and the best way to move into the cloud. Some applications that are very prime for lift and shift. We just want to get them out of the data center, into the cloud very quickly. Other ones that are very mission critical on customer facing very important for the future of an organization. Really need to be looked at with a more modern lens in the clouds. How do we modernize this, make it cost effective, and in a long-term asset, that's going to run in the cloud in a PaaS or SaaS based service offering rather than just IaaS. So all of the legacy work under the previous work we've done for our customers, we understand their application and in data center landscape better, they do in most scenarios. So having all of that data allows us to feed that into kind of some of our tooling around assessing applications and figuring out the best migration path or modernization path. So all of that legacy knowledge kind of puts us in the driver's seat for being the best partner to actually help them with that cloud modernization. >> So with your AWS responsibility as part of Capgemini, it's a bit like having a foot on the dock and a foot on the boat? >> Scott: Yep. >> In terms of an individual customer's requirements, obviously Capgemini can continue to manage what we would refer to as legacy infrastructure while helping to modernize and migrate to cloud. What about this sort of combination of the two that represents the future specifically, AWS is support of hybrid cloud technology. The idea of Outposts, is that something that you are involved with? >> Absolutely. We're seeing kind of Outpost adoption trend up recently, actually. So when we see in certain sectors where a lot of kind of work is being done on the edge, a great example is an agriculture company we work for that has field in soil and weather sensors all over the planet. So monitoring the moisture in the soil, the nitrogen levels, the wind air pressure and temperature and humidity. And oftentimes those fields are in very remote disconnected locations. So we're seeing things like Outpost and snowball edge and different services like that become more and more prevalent for those edge use cases where compute can actually be done on the field and decisions can be made by the farmers that are planters in the field like real time. And then when connectivity comes back around, they can actually beam that back to AWS if necessary. The other kind of scenario we see Outposts really being prevalent is in very sensitive data scenarios. So we have customers in federal government work or things like that. There's just some data due to regulatory compliance that cannot be on the public cloud node yet, yet being the key word there. So Outposts becomes really important in those scenarios where the vast majority of the data and the assets go out to AWS, but the very, very sensitive data due to regulatory reasons, we keep in the Outpost can still kind of harness the power of AWS on that. >> You know, that brings up another interesting subject, the difference between where technology actually exists today and where people exist culturally today in terms of their acceptance and adoption of technology. There are absolutely cases where data residency, data governance requires that it be onsite. >> Scott: Absolutely. >> Then again, there are a lot of cases where people are just concerned about not having their arms around the data. So the perception that it isn't as safe in the cloud, as it is in the customer's data center is often a misguided, >> Scott: Very much so. >> Perception. So that's obviously an inhibiting factor to cloud adoption in some way. What are some of the other things that you see that are headwinds? Because it's been talked about widely here 80% or more of IT spend is still what we would think of as on-premises. >> Scott: Data center. Yeah. >> Not cloud. Those lines are being blurred with things like Outpost. I contend that in five years, when we talk about cloud, that's going to be sort of an irrelevant term. >> Yeah. >> It's really like, well, because it doesn't matter where it is. It's all virtualized. >> Compute and storage somewhere. Yeah. >> The headwinds that you're seeing. And again, they can be irrational headwinds or they can be technical bottlenecks. >> Yeah. I think the biggest one is business understanding what the cloud is and them adopting it. I've had a couple meetings that were a new thing for me this week, where I met with the chief marketing officer for one of our customers. So we're meeting with CTO, CIO, VPs, directors in the IT space, but this marketing officer wanted to meet with us. And she was kind of very cloud knowledgeable. She understood IaaS, SaaS, PaaS and the costing models of cloud consumption and some of the services. In her organization is kind of already all in on AWS. And she had seen this happen, this transformation happened on the IT side. And she wanted to know how can I, as the head of my marketing department start to harness the power of the public cloud to drive business outcomes within my area. And that was a really interesting conversation for me and kind of got me thinking that I think the business is going to start understanding, and that the lines between IT and business are going to begin to get blurred a little bit with the power of AWS and other hyperscalers and all the capability that's available to our customers once they get moved out there. >> In today's keynote, Swami talked a lot about data and the data-driven companies, or rather companies that are not data-driven. >> Yep. >> Are going to be left behind. And I thought it was interesting in the survey. He mentioned 9% of companies reported not looking at data at all for their decision-making process. We need a list of those companies so we can short their stocks. (laughs) And we can help them out. (laughs) Or you can help out, or you can help them out. Exactly. I'll refer a half to you, and I'll short the rest. How's that feel? Is that a deal? So within your world of things you do with AWS, with Capgemini on behalf of the customers, what are some of the tip of the spear things that are the most exciting from a buzz perspective and what are sort of the next gen things that you're thinking of? It could be something you literally just heard about announced over the last couple of days. What does the future hold? >> Absolutely. We kind of look at that is what we classify our intelligent industry offering. And so it's really industry specific offers and services that are going to kind of change how specific industries do business. A really good example is we do a lot with the automotive industry. We started working with the OEMs that are kind of producing electric vehicles and autonomous driving vehicles. And we've actually built a framework that lives on top of AWS called connected mobility solutions. So connecting all of the driverless functions of a car back to the mothership or the cloud, the cloud instance. And I think things like that are really kind of tip of the spear where it's, again, out on the edge, not in a data center or in a cloud, but gathering all that data from connected devices in different areas and kind of how we're going to manage that and enable that and make it secure and safe and reliable and things like that. >> Yeah. Yeah. I have direct experience with some of that. I have a car that won't allow me to access all of its self-driving features. I bet I can guess because of the way I drive. (laughs) Yep. The cloud is not all wonderful. It's not all lollipops and rainbows. There is a bit of a downside to it if you're a crazy maniac like myself. So Capgemini, hasn't just been a standalone organization. You've absorbed and merged with all sorts of different organizations. I imagine you have organizations that are specifically focused on AWS in addition to other clouds. >> Scott: Absolutely. I can manage that culturally. >> That's a good question. So three years ago, me as the Capgemini group as a whole entered into a three-year partnership called Project Liberty with AWS. And it was a three-year plan we had targets and numbers on both sides, but it really kind of unified how we were going to do AWS and cloud work across the Capgemini organization, all working under one program towards one common goal, on developing accelerators and solutions and go to market offerings, kind of with one thing in mind to drive that AWS partnership and growth. So that's really been kind of the big driver for us within Capgemini over the past three years, is that what we call Project Liberty internally. And then just recently about a year and a half, maybe two years ago, we acquired one of the world's leading digital engineering firms called Altron. Big presence in Europe, Southeast Asia and North America. And they brought kind of a whole new flavor of how we do cloud when we're talking about digital twin in the cloud, on the factory floor and actually engineering of products and in driverless vehicles and electric vehicles and things like that. So bringing all training and being able to include them in our overall kind of cloud AWS message and bringing their book of offers in has really expanded our offering as well. >> How has talent recruitment and acquisition been for you guys? Are you faced with the same challenges that others are? Which is we need educated people. Give the pitch, so my kids hear it. So they understand. The graduate was plastics, right? That's the future? >> Yeah. >> Cloud services, without Capgemini, all the technology that AWS produces is essentially worthless. If you can't connect it to business value and outcome, and that's what you do. So how has that looked for you? >> Yeah, we hae the same talent challenges as everyone right now. So we're really taking the thought process of let's take people who aren't traditionally in the technology field and begin training them up on the cloud and the different technology areas. >> You do that at Capgemini? >> We do that at Capgemini, yeah. So we're running in conjunction with AWS big boot camps where we bring people in and- >> Who are this people? Not to interrupt, just a few seconds left. What's the profile of somewhere? >> Yeah. So a lot of- >> I want to hear the unconventional ones, not the computer science person who doesn't know cloud. Who are you bringing in on this one? >> New college hires who majored in the non-related IT field completely psychology, social sciences, whatever it may be. But who had the aptitude and then kind of the one to learn cloud in IT. So we bring them in. And then looking in our Capgemini Organization internally at our recruiting organization, our marketing organization, our partnership organization, and some of those people who are early on in their careers and may want to pivot to the technology side. We're starting to ramp them up as well. So it's been a very effective program for us. And I think something we're going to continue to invest in further. >> That's a very satisfying part of what you do to be a part of. >> Absolutely. >> Well, Scott, I got to tell you it's been a great conversation. For the rest of us here at theCUBE our continuous coverage continues here at AWS re:Invent 2021. I'm Dave Nicholson signing off for a moment. But keep it right here theCUBE is your technology hybrid event leader. (upbeat music)

>> We're back at AWS reinvent 2021. You're watching theCUBE. We're here live with one of the first live events, very few live events this year. It's the biggest hybrid event really of the year, of the season. Hopefully it portends a great future. We don't know it's a lot of uncertainty, but AWS said they're going to go for it. Close to 30,000 people here, Chris Wiborg is here. He's the VP of product marketing at Cohesity. Chris, great to see you face to face man. >> It's great to see you live again Dave. You understand that. >> Over the last couple of years we've had a lot of virtual meetup, hang out, and we talk every other quarter. >> Yeah. >> So it's great to see. Wow. You know, we were talking before the show. Well, we didn't really know what it was going to be like. I don't think AWS knew. >> No. >> It's like everything these days. >> You know, we did our own virtual event back in October because that was the time. And this is the first thing we've been back to live. And I was wondering, what's going to be like when I show up, but it's great to see all the folks that are here. >> Yeah. So I could see the booth. You know, you guys have had some good traffic. >> We have, yeah. >> A lot of customers here, obviously huge ecosystem. This, you know, the "flywheel keeps going". >> Yeah. You and I had a conversation recently about data management. It's something that you guys have put a stake in the ground. >> Absolutely. >> Saying, you know, we're not just backup, we're a good data management. It's fuzzy to a lot of people, we've had that conversation, but you're really starting to, through customer feedback, hone that message and the product portfolio. So let's start from the beginning. What is data management to cohesity? >> Well, so for us it's about the data lifecycle, right? And you heard a little bit about this actually during the keynote today, right? >> Right. >> When you think about the various services, you need to apply to data along the way to do basic things like protect it, be able to make sure you can recover from disasters, obviously deal with security today given the prevalence of ransomware out there, all the way down to at the end, how do you get more value out of it? And we do that in some cases with our friends from AWS using some of their AIML services. >> So your view of data may mean, it's kind of stops at the database right underneath. There's an adjacency to security that we've talked about. >> Yeah, very much. >> Data protection is now becoming an increasingly important component of a security strategy. >> It is. >> It's not a direct security play, but it's just the same way that it's not just the SecOps team has to worry about security anymore. It's kind of other parts of the organization. Talk about that a little bit. >> Yeah, well, we actually had a customer advisory board about two months or so ago now. And we talked to many of our customers there, and one of them I won't name, a large financial institution. We asked them, you know, where did we stand in your spend these days? And he's able to tell you, a while back about a year ago, having new backup and recovery is a starting point was kind of on the wishlist. And he said today it's number two. And I said, well why? He said well, because of ransomware, right? You'd be able to come back from that and ask, well, great, what's number one? He said, well, endpoint security. So there you are, number one and number two, right? Top of mind for customers these days in dealing with really the scourge that's affecting so many organizations out there. And I think where you're going, you starting to see these teams work together in a way that perhaps they hadn't before, or you've got the SecOps team, you've got the IT operations team. And while exactly your point, we don't position ourselves as just a data security company, that's part of what we do. We are part of that strategy now where if you have to think about the various stages and dealing with that, defending your backups, 'cause that's often the first point of attack now for the bad guys. Being able to detect what's going on through AI and the anomaly detection and such, and then being able to rapidly recover, right? In the recover phase, that's not something that security guys spend time on necessarily, but it's important for the business to be able to bring themselves back when they're subject to an attack, and that's where we come in in spades. >> Yeah. So the security guys are busy trying to figure out, okay, what happened? How do we stop it from happening again? >> There's another business angle which is okay, how do we get back up and running? How much data did we lose? Ideally none. How fast can we get it back up? That's that's another vector that's now becoming part of that broader security stack. >> That's right. I mean, I think if you look at the traditional NIST cybersecurity framework, right? Stage five has always been the recover piece. And so this is where we're working with some of the players in the security space. You may see an announcement we did with Cisco around secure access recently. Where, you know, we're working together, not only to unite two tribes within large organizations. Right? The SecOps and ITOps guys. But then bringing vendors together because it's through that, that really, we think we're going to solve that problem best. >> Before we get into the portfolio, and I want to talk about how you've evolved that, let's talk a little about ransomware, it's in the news. You know, I just wrote a piece recently and just covered some of the payments that have made. I mean, I think the biggest is 40 million, but many tens of millions here and there. And it was, you know, one case, I think it was the Irish health service did not pay, thus far hasn't paid, but it's costing him $600 million to recover as the estimate. So this is serious threat. And as I've said, many times on theCUBE, exactly anybody can be a ransomware as they go on the dark web. >> Ransomware is a service. >> Right, ransomware is a service. Hey, can you set up a help desk for me to help me negotiate? And I'm going to put a stick into a server and you know, I hope that individual gets arrested but you never know. Okay. So now it's top of mind, what are you guys doing? First of all, what are you seeing from customers? How are they responding? What are you guys doing to help? >> Well, I think you're right. First of all, it's just a huge problem. I think the latest stat I saw was something like every 11 seconds there's a new attack because I can go into your point with a credit card, sign up as a service and then launch an attack. And the average payment is around 4.2 million or such, but there's some that are obviously lots bigger. And I think what's challenging is beyond the costs of recovering and invent itself is there's also the issue around brand and reputation, and customer service. And all these downstream effects that I think, you know, the IT guys don't think about necessarily. We talked to one customer or a regional hospital where the gentleman there told me that what he's starting to see after the fact is now, you've actually got class action suits from patients coming after them saying like, "Hey you, you let my data get stolen. Right? Can you imagine no IT guys thinking about that. So the cost is huge. And so it's not just an issue I think that was once upon a time just for ITOps or SecOps through the CIO, even it's even past the board level now if you can imagine. It's something the general public worries about and we actually did a survey recently where we asked people on the consumer side, are you more or less likely to do business with companies if you know they've been subject to ransomware or attacks? And they said, no, we are concerned about that, we are more reticent to do business with people as consumers if they're not doing the right things to defend their business against ransomware. Fascinating. Right? It's long past the tipping point where this is an IT only issue. >> So, high-level strategy. So we talk about things like air gaps, when I talked about your service to ensure immutability, >> Yeah, yeah. >> And at 50,000 foot level, what's the strategy then I want to get into specifics on it. >> Let's talk a little bit about, so the evolution of the attack, nature of attacks, right? So once upon a time, this is in the distant past now, the bad guys that you used to come after your production data, right? And so that was pretty easy to fix with companies like us. It's just restore from backup. They got a little smarter< let's call that ransomware 2.0, right? Where now, they say, let's go after the backup first and encrypt or destroy that. And so there, to your point, you need immutability down to the file system level. So you can't destroy the backup. You got to defend the backup data itself. And increasingly we're seeing people take in isolation in a different way than they used to. So you probably recall the sort of standard three, two, one rule, right? >> Yeah, sure. >> Where the one traditionally meant, take that data offsite on magnetic tape, send it to Iron mountain for example, and then get the data back when I need it. Well, you know, if your business is at risk, trying to recover from tape, it just takes too long. That's just no reason. >> It can be weeks. >> It can be weeks and you've got to locate the tapes, you got to ship them, then you got to do the restore. And just because of the physical media nature, it takes a while. So what we're starting to see now is people figuring out how to use the cloud as a way to do that and be able to have effectively that one copy stored offsite in a different media, and use the cloud for that. And so one of the things we announced actually back in our show in October, was a new service that allows you to do just that. We're calling it for now Project Fort Knox. We're not sure if that name is going to work globally, right? But the idea is a bunker, an isolated copy of the data in the cloud that's there, that can restore quickly. Now, is it as fast as having a local replica copy? Of course not. But, it's way better than tape. And this is a way to really give you that sort of extra layer of insurance on top of what you're already doing probably to protect your data. >> And I think that's the way to think of it. It's an extra layer. It's not like, hey, do this instead of tape, you're still going to do tape, you know. >> There's some that do that for all sorts of reasons, including compliance and governance and regulatory ones. Right? >> Yeah. >> And, you know, even disaster recovery scenarios of the worst case, I hope I never have to go through it. Yeah, you could go to the cloud. >> That's right. >> So, local copy is the best. If that's not there, you've got your air gap copy in the cloud. >> Yap. >> If that's not there for some crazy reason. >> We have a whole matrix we've been sharing with our customers recently with a different options. Right? And it's actually really interesting the conversation that occurs between the IT operations folks, and the SecOps folks back to that. So, you know, some SecOps folks, if they could, they just unplug everything from the network, it's safe. Right? But they can't really do business that way. So it's always a balance of what's the return that you need to meet. And by return I mean, coming back from an attack or disaster versus the security. And so again, think of this as an extra layer that gives you that ability to sleep better at night knowing that you've got a third, a tertiary copy, stored somewhere offsite in a different media, but you can bring it back at the same time. >> How have you evolve your portfolio to deal with both the data management trends that we've talked about and the cyber threats. >> Yeah. Well, a number of things. So amongst the other announcements we made back in October is DR. So DR is not a security thing per se, you know, who gets paged when something goes wrong? It's not the info SEC guys for DR, it's the ITOps guys. And so we've always had that capability, but one of the things we announced is be able to do that to do that to the cloud now in AWS. So, instead of site to site, being able to do it site to cloud, and for some organizations, that is all about being able to maybe eliminate a secondary site, you know, smaller organizations, others that are larger enterprises, they probably have a hybrid strategy where that's a part of their strategy now. And the value there is, it's an OpEx cost, right? It's not CapEx anymore. And so again, you lower your cost of operations. So that's one thing in the data management side. On the security side, another thing we announced was yet another service that runs in AWS, we call Cohesity Data Govern. And this is a way to take a look at your data before something ever occurs. One of the key things in dealing with ransomware is hygiene is prevention, right? And so you sort of have classically security folks that are trying to protect your data, and then another set of folks, certainly a large enterprise that are more on the compliance regulatory front, wanting to know where your PII is, your private sensitive data. And we believe those things need to come together. So this data governance product actually does that. It takes a look at first classifying your data, and then being able to detect anomalies in terms of who's coming in from where to get to it, to help you proactively understand what's at threat, and first of all, you know, where your crown jewels really are and make sure that you're protecting those appropriately and maybe modifying access policies If you have set up in your existing native applications,. So it's a little bit of awareness, a little bit prevention, and then when things start to go wrong, another layer that helps you know what's wrong. >> I love that the other side of the coin, I mean, you going to get privacy as a service along with my data protection as a service, know that's a better model. Tight on time sir, but the last question. >> Sure. >> The ecosystem. >> Yeah. >> So you mentioned endpoint security, I know identity access is cloud security, and since the remote work has really escalated, we talk about the ecosystem and some of the partnerships that you're enabling, API integration. >> Yeah, totally. So, you know, we have this, what we call our threat defense model, has got four layers to it. One is the core, is all about resiliency. You need to assume failure. We have, you know, the ability to fail over, fail back down our file system. It has to be immutable to keep the bad guys out. You have to have encryption, basic things like that. The next layer, particularly in this world of zero trust. Right? Is you have to have various layers access control, obvious things like multifactor authentication, role-based access control, as well as things like quorum features. It's the two keys in the safety deposit box to unlock it. But that's not enough. The third layer is AI powered anomaly detection, and being able to do data classification and stuff and such. But then the fourth layer, and this was beyond just us, is the ability to easily integrate in that ecosystem. Right? So I'll go back to the Cisco example I gave you before. We know that despite having our own admin console, there's no SecOps person that's going to be looking at that. They're going to look at something like a SecureAX, or maybe a Palo Alto XR, and be able to pull signals from different places including endpoints, including firewall. >> You going to feed that. >> Exactly. So we'll send signals over that, they can get a better view and then because we're all API based, they can actually invoke the remedy on their side and initiate the workflow that then triggers us to do the right thing from a data protection standpoint, and recovery standpoint. >> It's great to have you here. Thanks so much for coming on. >> It's good to see you again live today. >> See you in the evolution of cohesity. Yes, absolutely. Hopefully we do this a lot in 2022, Chris. >> Absolutely, looking forward to. >> All right. Me too. All right, thank you for watching this is theCUBE's coverage, AWS reinvent. We are the leader in high tech coverage, we'll be right back.

(bright music) (logo whooshing) >> Welcome everyone to theCUBEs continuing coverage of AWS 2021. I'm your host, Lisa Martin. We are excited to be running one of the industry's most important and largest hybrid tech events of the year with AWS and its ecosystem partners. We have two live sets, two remote studios, we've got over a hundred guests on the program, and we're going to be talking about the next decade of cloud innovation. We are pleased to welcome back one of our alumni to the program, Rob Lee, the CTO of Pure Storage. Rob, thank you so much for joining us today. >> Good to see you again, Lisa, and thanks for having me. >> Likewise and I was stalking you on LinkedIn. Looks like you've got a promotion since I last saw you. Congratulations >> Thank you. >> on your appointment as a CTO. >> No, thank you very much. Very excited to be taking the reins and for all the great stuff that's ahead of us. >> Lot of great stuff, I'm sure. I also saw that once again, Pure has been named a leader in several gartner magic quadrants for primary storage, for distributed file storage, and object storage. Lots of great things continuing to go on from the orange side. Let's talk about hybrid. I've seen so much transformation and acceleration in the last 20 plus months, but I'd love to see what you guys are seeing with respect to your customers and their hybrid cloud strategies. What problems are they in this dynamic day and age are they looking to solve? >> Yeah, absolutely. I think, all in all, I think, you know, customers are definitely maturing in their understanding and approach to all things around cloud. And I think when it comes to their approach towards hybrid cloud, one of the things that we're seeing is that customers are really, you know, focusing extra hard and just trying to make sure that they're making the best use of all their IT tools. And what that means is, you know, not just looking at hybrid cloud as a way to connect from on-prem to the cloud, but really being able to make use of and make the most use out of each, you know, each of the services and capabilities of the environments that they're operating in. And so a lot of times that means, you know, commonality in how they're operating, whether it's on-premise or in cloud, it means the flexibility that that commonality allows them in terms of planning and optionality to move parts of their application or environments between premise and cloud. You know, and I think overall, you know, we look at this as, you know, really a couple specific forces that customers are looking for. One is, you know, I think they're looking for ways to bring a lot more of the operating model and what they're used to in the cloud, into their own data center. And at the same time, they're looking to be able to bridge more of how they operate the applications they're powering and running in their own data centers today and be able to bridge and bring those into the cloud environments. And then lastly, I'd say that, you know, as customers, I think, you know, today are kind of one foot in their more traditional application environments and the other foot largely planted in developing and building some of their newer applications built on cloud native technologies and architectures driven by containers and Kubernetes, you know, a big focus area for customers, whether it's on-prem or in cloud or increasingly hybrid is, you know, supporting and enabling those cloud native application development projects. And that's certainly an area that you've seen Pure focus in as well. And so I think it's really those three things. One is customers looking for ways to bring more of the cloud model into their data center, two is being able to bring more of what they're running in their data center into the cloud today, and then three is building their new stuff and increasingly planning to run that across multiple environments, prem, cloud, and across clouds. >> So, Rob, talk to me about where Pure fits in the hybrid cloud landscape that your customers are facing in this interesting time we're living in. >> Yeah, absolutely. You know, we're really focused on meeting customer's needs in all three of the areas that I just articulated and so this starts with bringing more of the cloud operating model into customers' data centers. And, you know, we start by focusing on, you know, automation, simplicity of management, delivering infrastructure as code, a lot of the attributes that customers are used to in a cloud environment. In many ways, as you know, this is a natural evolution of where Pure has been all along. We started by bringing a lot of the consumer-like simplicity into our products and enterprise data centers. And now, we're just kind of expanding that to bring more of the cloud simplicity in. You know, we're also, this is an area where we're working with our public cloud partners such as AWS in embracing their management models. And so you saw, you know, you saw us do this as a storage launch partner for AWS Outposts and that activity is certainly continuing on. So customers that are looking for cloud-like management, whether they want to build that themselves and customize it to their needs or whether they want to simply use cloud providers management plans and extend those onto their premise, have both options to do that. You know, we're also, as you know, very committed to helping customers be able to move or bridge their traditional applications from their data center into the public cloud environments through products like Cloud Block Store. This is an area where we've helped numerous customers, you know, take the existing applications and more importantly, the processes and how the environments are set up and run that they're used to running in their data center production environments bridge those now into public cloud environments. And whether that's in AWS or in Microsoft Azure as well. And then thirdly with Portworx, right? This is where, you know, we're really focused on helping customers, not just by providing them with the infrastructure they need to build their containerized cloud native applications on, but then also marrying with that infrastructure, that storage infrastructure, the data flow operations such as backup, TR, migration that go along with that storage infrastructure, as well as now application management capabilities, which we recently announced during our launch event in September with Portworx Data Services. So really a lot of activities going on across the board, but I would say definitely focused on those three key areas that we see customers really looking to crack as they, I would say balance the cloud environments and their data center environments in this hybrid world. >> And I'm curious what you're saying, you know, the focus being on data. >> Customers, you know, definitely recognize the data is their lifeblood is kind of, you know, contains a lot of the, you know, the value that they're looking to extract, whether it's in a competitive advantage, whether it's in better understanding their customers, you know, and or whether it's in product development, faster time to market. I think that, you know, we're definitely seeing more of an elevated realization and appreciation for not just how valuable that it is, but, you know, how much gravity it holds, right? You know, customers that are realizing, "Hey, if I'm collecting all this data in my on-prem location, maybe it's not quite that feasible or sensible to ship all that data into a public cloud environment to process. Maybe I need to kind of look at how I build my hybrid strategy around data being generated here, services living over here, and how do I bridge those two, you know, two locations." I think you add on top of that, you know, newer, I would say realization of security and data governance, data privacy concerns. And that certainly has customers, I think, you know, thinking a lot more intently about, you know, their data management, not just their data collection and data processing and analysis strategy, but their overall data managements, governance, and security strategies. >> Yeah, we've talked a lot about security in this interesting time that we're living in. The threat landscape has changed massively. Ransomware is a household word and it's a matter of when versus if. As customers are looking at these challenges that they're combating, how are you helping them address those data security concerns as they know that, you know, we've got this work from anywhere that's hybrid work environment, that's going to process for probably some time, but that security and ensuring that the data that's driving the revenue chain is secure and accessible, but protected no matter where it is? >> Yeah, absolutely. And I think you said it best when you said it's a matter of when, not if, right? And I think, you know, we're really focused on helping customers plan for and have, you know, plan for it and have a very quick reaction remediation strategy, right? So, you know, customers that I would say historically have focused on perimeter security have focused on preventing an attack, and that's great, and you need to do that, but you also need to plan for, hey, if something happens where, you know, as we just said, when something happens, what is your strategy for remediating that, what is your strategy for getting back online very quickly? And so this is an area where, you know, we've helped countless customers, you know, form robust strategies for, you know, true disaster recovery from a security or ransomware since. We do this by through our safe mode features, which are available across all of our products. And, you know, quite simply, this is our capability to take read-only snapshots and then couple them with a heightened level of security that effectively locks these snapshots down and takes the control of the snapshots away from not just customer admins, but potential ransomware or malware, right? You know, if you look at the most recent ransomware attacks that have hit the industry, they've gotten more and more sophisticated where the first action, a lot of these ransomware pieces of software taking are going after the backups. They go after the backups first and they take down the production environment. Well, we stopped that chain or in the security world what's called the kill chain, we stopped that chain right at the first step by protecting those backups in a way that, you know, no customer admin, whether it's a true admin, a malicious admin, or a piece of software, a malware that's acting as an admin, has the ability to remove that backup. And, you know, that's a capability that's actually become one of our most popular and most quickly adopted features across the portfolio. >> That's key. I saw that. I was reading some reports recently about the focus of ransomware on backups and the fact that you talked about it, it's becoming more sophisticated. It's also becoming more personal. So as data volumes continue to grow and companies continue to depend on data as competitive advantage differentiators and, of course, a source of driving revenue, ensuring that the backups are protected, and the ability to recover quickly is there is that is table stakes, I imagine for any organization, regardless of industry. >> Absolutely, and I think, you know, I think overall, if we look at just the state of data protection, whether it's protecting against security threats or whether it's protecting against, you know, infrastructure failures or whatnot, I would say that the state of data protection has evolved considerably over the last five years, right? You go back 5, 10 years and people are really fixated on, "Hey, how quickly can I back here? How quickly can I back this environment up, and how can I do it in a most cost-effective manner?" Now people are much more focused on, "Hey, when something goes wrong, whether it's a ransomware attack, whether it's a hurricane that takes out a data center, I don't really care what it is." When something goes wrong, how quickly can I get back online because chances are, you know, every customer now is running an online service, right? Chances are, you've got customers waiting for you. You've got SLAs, you've got transactions that can't complete if you don't get this environment back up. And we've seen this, you know, throughout the industry over the last couple of years. And so, you know, I think that maturing understanding of what true data protection is is something that has A, driven, you know, a new approach from customers to and a new focus on this area of their infrastructure. And B I think it is also, you know, found a new place for, you know, performance and reliability, but really all of it, the properties of, you know, Pures products in this space. >> Last question, Rob, for you, give me an example, you can just mention it by industry or even by use case of a joint AWS Pure customer where you're really helping them create a very successful enterprise-grade hybrid cloud environment? >> Yeah, no, absolutely. You know, so we've got countless customers that, you know, I could point to. You know, I think one that I would or one space that we're particularly successful in that I would highlight are, you know, SAS companies, right? So companies that are, you know, are building modern SAS applications. And in one particular example I can think of is, you know, a gaming platform, right? So this is a company that is building out a scale-out environment, you know, is a very rapidly growing startup. And certainly is looking to AWS, looking to the public cloud environments, you know, as a great place to scale. But at the same time, you know, needs more capabilities than, you know, are available in the container storage for, you know, infrastructure that was available in the public cloud environment. They need more capabilities to be able to offer this global service. They need more capabilities to, you know, really provide the 24 by 7 by 365 around the world service that they have, especially dealing with high load bursts in different GEOS and just a very, very dynamic global environment. And so this is an area where, you know, we've been able to, you know, help the customer with Portworx. Be able to provide these capabilities by augmenting that AWS or the cloud environment is able to offer, you know, with the storage level replication and high availability and all of the enterprise capabilities, autoscaling, performance management, all the capabilities that they need to be able to bridge the service across multiple regions, multiple environments, and, you know, potentially over time, you know, on-premise data center locations as well. So that's just one of many examples, you know, but I think that's a great example where, you know, as customers are starting out, the public cloud is a great place to kind of get started. But then as you scale, whether it's because of bursty load, whether it's because of a data volume, whether it's because of compute volume and capacity, you know, customers are looking for either more capabilities, you know, more connectivity to other sites, potentially other cloud environments or data center environments. And that's where a more environment or cloud agnostic infrastructure layer such as Portworx is able to provide comes in very handy. >> Got it. Rob, thanks so much for joining me on the program today at re:Invent, talking about the Pure AWS relationship, what's going on there and how you're helping customers navigate, and then a very fast-paced, accelerating hybrid world. We appreciate you coming back on the program. >> Great, thanks for having me. Good to see you again. >> Likewise. Good to see you too. Per Rob Lee, I'm Lisa Martin. You're watching theCUBES continuous coverage of AWS re:Invent 2021. (calm music)

>>Welcome back to the cubes coverage of Couchbase connect online, where the theme of the event is, or is modernized now. Yes, let's talk about that. And with me is Ravi, who's the senior vice president of engineering and the CTO at Couchbase Ravi. Welcome. Great to see you. >>Thank you so much. I'm so glad to be here with you. >>I asked you what the new requirements are around modern applications. I've seen some, you know, some of your comments, you gotta be flexible, distributed, multimodal, mobile edge. It, that those are all the very cool sort of buzz words, smart applications. What does that all mean? And how do you put that into a product and make it real? >>Yeah, I think what has basically happened is that, uh, so far, uh, it's been a transition of sorts. And now we are come to a point where, uh, the tipping point and the tipping point has been, uh, uh, more because of COVID and there COVID has pushed us to a world where we are living, uh, in a sort of, uh, occasionally connected manner where our digital, uh, interactions, precede our physical interactions in one sense. So it's a world where we do a lot more stuff that's less than, uh, in a digital manner, as opposed to sort of making a more specific human contact that has really been the, uh, sort of accelerant to this modernized. Now, as a team in this process, what has happened is that so far all the databases and all the data infrastructure that we have built historically, are all very centralized. >>They're all sitting behind. Uh, they used to be in mainframes from where they came to like your own data centers, where we used to run hundreds of servers to where they're going now, which is the computing marvelous change to consumption-based computing, which is all cloud oriented now. And so, uh, but they are all centralized still. Uh, but where our engagement happens with the data is, uh, at the edge, uh, at your point of convenience at your point of consumption, not where the data is actually sitting. So this has led to, uh, you know, all those buzzwords, as you said, which is like, oh, well we need a distributed data infrastructure, where is the edge? Uh, but it just basically comes down to the fact that the data needs to be where you are engaging with it. And that means if you are doing it on your mobile phone, or if you are sitting, uh, doing something in your body or traveling, or whether you are in a subway, whether you're in a plane or a ship, wherever the data needs to come to you, uh, and be available as opposed to every time you going to the data, which is centrally sitting in some place. >>And that is the fundamental shift in terms of how the modern architecture needs to think, uh, when they, when it comes to digital transformation and, uh, transitioning their old applications to, uh, the, the modern infrastructure, because that's, what's going to define your customer experiences and your personalized experiences. Uh, otherwise people are basically waiting for that circle of death that we all know, uh, and blaming the networks and other pieces. The problem is actually, the data is not where you are engaging with. It has got to be fetched, you know, seven seas away. Um, and that is the problem that we are basically solving in this modern modernization of that data, data infrastructure. >>I love this conversation and I love the fact that there's a technical person that can kind of educate us on, on this, because date data by its very nature is distributed. It's always been distributed, but w w but distributed database has always been incredibly challenging, whether it was a global SIS Plex or an eventual consistency of getting recovery for a distributed architecture has been extremely difficult. You know, I hate that this is a terrible term, lots of ways to skin a cat, but, but you've been the visionary behind this notion of optionality, how to solve technical problems in different ways. So how do you solve that, that problem of, of, of, uh, of, uh, of a super rock solid database that can handle, you know, distributed data? Yes. >>So there are two issues that you're a little too over there with Forrest is the optionality piece of it, which is that same data that you have that requires different types of processing on it. It's almost like fractional distillation. It is, uh, like your crude flowing through the system. You start all over from petrol and you can end up with Vaseline and rayon on the other end, but the raw material, that's our data in one sense. So far, we never treated the data that way. That's part of the problem. It has always been very purpose built and cast first problem. And so you just basically have to recast it every time we want to look at the data. The first thing that we have done is make data that fluid. So when you're actually, uh, when you have the data, you can first look at it to perform. >>Let's say a simple operation that we call as a key value store operation. Given my ID, give him a password kind of scenarios, which is like, you know, there are customers of ours who have billions of user IDs in their management. So things get slower. How do you make it fast and easily available? Log-in should not take more than five minutes. Again, this is a, there's a class of problem that we solve that same data. Now, eventually, without you ever having to, uh, sort of do a casting it to a different database, you can now do a solid, uh, acquire. These are classic sequel queries, which is our next magic. We are a no SQL database, but we have a full functional sequel. The sequel has been the language that has talked to data for 40 odd years successfully. Every other database has come and try to implement their own QL query language, but they've all failed only sequel as which stood the test of time of 40 odd years. >>Why? Because there's a solid mathematics behind it. It's called a relational calculus. And what that helps you is, is, uh, basically, uh, look at the data and any common tutorial, uh, any, uh, any which way you look at the data. All it will come, uh, the data in a format that you can consume. That's the guarantee sort of gives you in one sense. And because of that, you can now do some really complex in the database signs, what we call us, predicate logic on top of that. And that gives you the ability to do the classic relational type queries, select star from where Canada stuff, because it's at an English level, it becomes easy to, so the same data, you didn't have to go move it to another database, do your, uh, sort of transformation of the data and all this stuff. Same day that you do this. >>Now, that's where the optionality comes in. Now you can do another piece of logic on top of this, which we call search. This is built on this concept of inverted index and TF IDF, the classic Google in a very simple terms, but Google tokenized search, you can do that in the same data without you ever having to move the data to a different format. And then on top of it, they can do what is known as a eventing or your own custom logic, which we all which we do on a, on programming language called Java script. And finally analytics and analytics is the ability to query the operational data in a different way. I'll talk budding. What was my sales of this widget year over year on December 1st week, that's a very complex question to ask, and it takes a lot of different types of processing. >>So these are different types of that's optionality with different types of processing on the same data without you having to go to five different systems without you having to recast the data in five different ways and find different application logic. So you put them in one place. Now is your second question. Now this has got to be distributed and made available in multiple cloud in your data center, all the way to the edge, which is the operational side of the, uh, the database management system. And that's where the distributed, uh, platform that we have built enables us to get it to where you need the data to be, you know, in a classic way, we call it CDN in the data as in like content delivery networks. So far do static, uh, uh, sort of moving of static content to the edges. Now we can actually dynamically move the data. Now imagine the richness of applications you can develop. >>The first part of the, the answer to my question, are you saying you could do this without skiing with a no schema on, right? And then you can apply those techniques. >>Uh, fantastic question. Yes. That's the brilliance of this database is that so far classically databases have always demanded that you first define a schema before you can write a single byte of data. Couchbase is one of the rare databases. I, for one don't know any other one, but there could be, let's give the benefit of doubt. It's a database which writes data first and then late binds to schema as we call it. It's a schema on read things. So because there is no schema, it is just a on document that is sitting inside. And Jason is the lingua franca of the web, as you very well know by now. So it just Jason that we manage, you can do key lookups of the Jason. You can do full credit capability, like a classic relational database. We even have cost-based optimizers and the other sophisticated pieces of technology behind it. >>You can do searching on it, using the, um, the full textual analysis pipeline. You can do ad hoc wedding on the analytic side, and you can write your own custom logic on it using our eventing capabilities. So that's, that's what it allows because we keep the data in the native form of Jason. It's not a data structure or a data schema imposed by a database. It is how the data is produced. And on top of it, we bring different types of logic, five different types of it's like the philosophy is bringing logic to data as opposed to moving data to logic. This is what we have been doing, uh, in the last 40 years because we developed various, uh, database systems and data processing systems of various points. In time in our history, we had key value stores. We had relational systems, we had search systems, we had analytical systems. >>We had queuing systems, all the systems, if you want to use any one of them, our answer has always been, just move the data to that system. Versus we are saying that do not move the data as we get bigger and bigger and data just moving this data is going to be a humongous problem. If you're going to be moving petabytes of data for this is not one to fly instead, bring the logic to the data. So you can now apply different types of logic to the data. I think that's what, in one sense, the optionality piece of this, >>As you know, there's plenty of schema-less data stores. They're just, they're called data swamps. I mean, that's what they, that's what they became, right? I mean, so this is some, some interesting magic that you're applying here. >>Yes. I mean, the one problem with the data swamps as you call them is that that was a little too open-ended because the data format itself could change. And then you do your, then everything became like a game data casting because it required you to have it in seven schema in one sense at the end of the day, for certain types of processing. So in that where a lot of gaps it's probably flooded, but it not really, uh, how do you say, um, keep to the promise that it actually meant to be? So that's why it was a swamp I need, because it was fundamentally not managing the data. The data was sitting in some file system, and then you are doing something, this is a classic database where the data is managed and you create indexes to manage it, and you create different types of indexes to manage it. You distribute the index, you distribute the data you have, um, like we were discussing, you have acid semantics on top of, and when you, when you put all these things together, uh, it's, it's, it's a tough proposition, but they have solved some really tough problems, which are good computer science stuff, computer science problems that we have to solve to bring this, to bring this, to bear, to bring this to the market. >>So you predicted the trend around multimodal and converged, uh, databases. Um, you kind of led Couchbase through that. I want to, I always ask this question because it's clearly a trend in the industry and it, it definitely makes sense from a simplification standpoint. And, and, and so that I don't have to keep switching databases or the flip side of that though, Ravi. And I wonder if you could give me your opinion on this is kind of the right tool for the right job. So I often say isn't that the Swiss army knife approach, we have a little teeny scissors and a knife. That's not that sharp. How do you respond to that? Uh, >>A great one. Um, my answer is always, I use another analogy to tackle that, but is that, have you ever accused a smartphone of being a Swiss army knife? No. No. Nobody does that because it's actually 40 functions in one is what a smartphone becomes. You never call your iPhone or your Android phone, a Swiss army knife, because here's the reason is that you can use that same device in the full capacity. That's what optionality is. It's not, I'm not, it's not like your good old one where there's a keyboard hiding half the screen, and you can do everything only through the keyboard without touching and stuff like that. That's not the whole devices available to you to do one type of processing when you want it. When you're done with that, it can do another completely different types of processing. Like as in a moment, it could be a Tom, Tom telling you all the directions, the next one, it's your PDA. >>Third one, it's a fantastic phone. Uh, four, it's a beautiful camera, which can do your f-stop management and give you a nice SLR quality picture. Right? So next moment is a video camera. People are shooting movies with this thing in Hollywood, these days for God's sake. So it gives you the full power of what you want to do when you want it. And now, if you just taught that iPhone is a great device or any smartphone is a great device, because you can do five things in one or 50 things in one, and at a certain level, they missed the point because what that device really enabled is not just these five things in one place. It becomes easy to consume and easy to operate. It actually started the app is the economy. That's the brilliance of bringing so many things in one place, because in the morning, you know, I get the alert saying that today you got to leave home at eight 15 for your nine o'clock meeting. >>And the next day it might actually say 8 45 is good enough because it knows where the phone is sitting. The geo position of it. It knows from my calendar where the meeting is actually happening. It can do a traffic calculation because it's got my map and all of the routes. And then it's gone there's notification system, which eventually pops up on my phone to say, Hey, you got to leave at this time. Now five different systems have to come together and they can because the data is in one place without that, you couldn't even do this simple function, uh, in a, in a sort of predictable manner in a, in a, in a manner that's useful to you. So I believe a database which gives you this optionality of doing multiple data processing on the same set of data allows you will allow you to build a class of products, which you are so far been able to struggling to build, because half the time you're running sideline to sideline, just, you know, um, integrating data from one system to the other. >>So I love the analogy with the smartphone. I w I want to, I want to continue it and double click on it. So I use this camera. I used to, you know, my kid had a game. I would bring the, the, the big camera, the 35 millimeter. So I don't use that anymore no way, but my wife does, she still uses the DSLR. So is, is there a similar analogy here? That those, and by the way, the camera, the camera shop in my town went out of business, you know? And so, so, but, but is there, is that a fair, where, in other words, those specialized databases, they say there still is a place for them, but they're getting >>Absolutely, absolutely great analogy and a great extension to the question. That's, that's the contrarian side of it in one sense is that, Hey, if everything can just be done in one, do you have a need for the other things? I mean, you gave a camera example where it is sort of, it's a, it's a slippery slope. Let me give you another one, which is actually less straight to the point better. I've been just because my, I, I listened to half of the music on the iPhone. Doesn't stop me from having my full digital receiver. And, you know, my Harman Kardon speakers at home because they haven't, they produce a kind of sounded immersive experience. This teeny little speaker has never in its lifetime intended to produce, right? It's the convenience. Yes. It's the convenience of convergence that I can put my earphones on and listen to all the great music. >>Yes, it's 90% there or 80% there. It depends on your audio file mess of your, uh, I mean, you don't experience the super specialized ones do not go away. You know, there are, there are places where, uh, the specialized use cases will demand a separate system to exist, but even there that has got to be very closed. Um, how do you say close, binding or late binding? I should be able to stream that song from my phone to that receiver so I can get it from those speakers. You can say that, oh, there's a digital divide between these two things done, and I can only play CDs on that one. That's not how it's going to work going forward. It's going to be, this is the connected world, right? As in, if I'm listening to the song in my car and then step off the car and walk into my living room, that's same songs should continue and play in my living room speakers. Then it's a world because it knows my preference and what I'm doing that all happened only because of this data flowing between all these systems. >>I love, I love that example too. When I was a kid, we used to go to Twitter, et cetera. And we'd to play around with, we take off the big four foot speakers. Those stores are out of business too. Absolutely. Um, now we just plug into Sonos. So that is the debate between relational and non-relational databases over Ravi. >>I believe so. Uh, because I think, uh, what had happened was the relational systems. Uh, I've been where the norm, they rule the roost, if you will, for the last 40 odd years, and then gain this no sequel movement, which was almost as though a rebellion from the relational world, we all inhibited, uh, uh, because we, it was very restrictive. It, it had the schema definition and the schema evolution as we call it, all those things, they were like, they required a committee, they required your DBA and your data architect. And you have to call them just to add one column and stuff like that. And the world had moved on. This was the world of blogs and tweets and, uh, you know, um, mashups and, um, uh, uh, a different generation of digital behavior, digital, native people now, um, who are operating in these and the, the applications, the, the consumer facing applications. >>We are living in this world. And yet the enterprise ones were still living in the, um, in the other, the other side of the divide. So all came this solution to say that we don't need SQL. Actually, the problem was never sequel. No sequel was, you know, best approximation, good marketing name, but from a technologist perspective, the problem was never the query language, no SQL was not the problem, the schema limitations, and the inability for these, the system to scale, the relational systems were built like, uh, airplanes, which is that if, uh, San Francisco Boston, there is a flight route, it's so popular that if you want to add 50 more seats to it, the only way you can do that is to go back to Boeing and ask them to get you a set in from 7 3 7 2 7 7 7, or whatever it is. And they'll stick you with a billion dollar bill on the alarm to somehow pay that by, you know, either flying more people or raising the rates or whatever you have to do. >>These are called vertically scaling systems. So relational systems are vertically scaling. They are expensive. Versus what we have done in this modern world, uh, is make the system how it is only scaling, which is more like the same thing. If it's a train that is going from San Francisco to Boston, you need 50 more people be my guests. I'll add one more coach to it, one more car to it. And the better part of the way we have done this year is that, and we have super specialized on that. This route actually requires three, three dining cars and only 10 sort of sleeper cars or whatever. Then just pick those and attach the next route. You can choose to have ID only one dining car. That's good enough. So the way you scale the plane is also can be customized based on the route along the route, more, more dining capabilities, shorter route, not an abandoned capability. >>You can attach the kind of coaches we call this multi-dimensional scaling. Not only do we scale horizontally, we can scale to different types of workloads by adding different types of coaches to it quite. So that's the beauty of this architecture. Now, why is that important? Is that where we land eventually is the ability to do operational and analytical in the same place. This is another thing which doesn't happen in the past, because you would say that I cannot run this analytical Barre because then my operational workload will suffer. Then my friend, then we'll slow down millions of customers that impacted that problem. We will solve the same data in which you can do analytical buddy, an operational query because they're separated by these cars, right? As in like we, we fence the, the, the resources, so that one doesn't impede the other. So you can, at the same time, have a microsecond 10 million ops per second, happening of a key value or equity. >>And then yet you can run this analytical body, which will take a couple of minutes to run one, not impeding the other. So that's in one sense, sort of the, part of the, um, uh, problems that we have solved here is that relational versus, uh, uh, the no SQL portion of it. These are the kinds of problems we have to solve. We solve those. And then we yet put back the same quality language on top. Y it's like Tesla in one sense, right underneath the surface is where all the stuff that had to be changed had to change, which is like the gasoline, uh, the internal combustion engine, uh, I think gas, uh, you says, these are the issues we really wanted to solve. Um, so solve that, change the engine out, you don't need to change the steering wheel or the gas pedal or the, you know, the battle shifters or whatever else you need, or that are for your shifters. >>Those need to remain in the same place. Otherwise people won't buy it. Otherwise it does not even look like a car to people. So, uh, even when you feed people the most advanced technology, it's got to be accessible to them in the manner that people can consume. Only in software, we forget this first design principle, and we go and say that, well, I got a car here, you got the blue harder to go fast and lean back for, for it to, you know, uh, to apply a break that's, that's how we seem to define, uh, design software. Instead, we should be designing them in a manner that it is easiest for our audience, which is developers to consume. And they've been using SQL for 40 years or 30 years. And so we give them the steering wheel on the, uh, and the gas bottle and the, um, and the gear shifter is by putting cul back on underneath the surface, we have completely solved, uh, the relational, uh, uh, limitations of schema, as well as scalability. >>So in, in, in that way, and by bringing back the classic acid capabilities, which is what relational systems, uh, we accounted on and being able to do that with the sequel programming language, we call it like multi-state SQL transaction. So to say, which is what a classic way all the enterprise software was built by putting that back. Now, I can say that that debate between relational and non-relational is over because this has truly extended the database to solve the problems that the relational systems had to grow up the salt in the modern times, but rather than get, um, sort of pedantic about whether it's, we have no SQL or sequel or new sequel, or, uh, you know, any of that sort of, uh, jargon, oriented debate, uh, this, these are the debates of computer science that they are actually, uh, and they were the solve and they have solved them with, uh, the latest release of $7, which we released a few months ago. >>Right, right. Last July, Ravi, we got to leave it there. I, I love the examples and the analogies. I can't wait to be face to face with you. I want to hang with you at the cocktail party because I've learned so much and really appreciate your time. Thanks for coming to the cube. >>Fantastic. Thanks for the time. And the Aboriginal Dan was, I mean, very insightful questions really appreciate it. Thank you. >>Okay. This is Dave Volante. We're covering Couchbase connect online, keep it right there for more great content on the cube.

>>Well, hi everybody. I'm John Walls here and welcome back to the cubes, continuing coverage and splunk.com 21. And we've talked a lot about data, obviously, um, and a number of partnerships and the point of resources that it's going on in this space. And certainly a very valuable partnership that Splunk has right now is one with Intel. And with me to talk a little bit more about that is Rick Echavarria, who is the vice president of sales and the marketing group at Intel. Rick. Good to see it today. Thanks for joining us on the queue. It's >>Good to see you, John, and thanks for having us. >>You bet. No glad to have you as part of the.com coverage as well. Um, well, first off, let's just for folks at home, uh, who would like to learn more about this relationship, the Splunk Intel partnership, if you would give us that the 30,000 foot picture of it right now, in terms of, of how it began and how it's evolved to the point where it resides today. >>Yeah. Uh, sure. Glad to do that. You know, Splunk is had for many years, uh, position as, as one of the world's best, uh, security information and event management platform. So just like many customers in the cybersecurity space, they're probably trying to retire their technical debt. And, and what are the areas of important focuses to SIM space, right? The SIM segment within cybersecurity. And so the initial engagement between Intel and Splunk started with the information security group at Intel, looking to, again, retire the technical debt, bring next generation SIM technology. And that started, uh, the engagement with Splunk again, to go solve the cybersecurity challenges. One of the things that we quickly learned is that, uh, those flung offers a great platform, you know, from a SIM point of view, as you know, the cyber security segment, the surface area of attack, the number of attacks kids were increased. >>And we quickly realized that this needed to be a collaboration in order for us to be able to work together, to optimize our infrastructure. So it could scale, it could be performance, it could be reliable, uh, to protect Intel's business. And as we started to work with Splunk, we realized, Hey, this is a great opportunity. Intel is benefiting from it. Why don't we start working together and create a reference architecture so that our joint customers also benefit from the collaboration that we have in the cybersecurity space, as we were building the Intel cybersecurity infrastructure platform. So that re that was really the beginning of, uh, of the collaboration around described here and a little bit more, >>Right? So, so you had this, this good working relationship and said, Hey, why don't we get together? Let's get the band together and see what we can do for our car joint clients down the road. Right. So, so what about those benefits that, because you've now you've got this almost as force multiplier right. Of, of Intel's experience. And then what Splunk has been able to do in the data analytics world. Um, what kind of values are being derived, do you think with that partnership? >>Well, obviously we feel much better about our cyber security posture. Um, and, uh, and what's sort of interesting, John, is that we realized that we were what started out as a conversation on SIM. Uh, it really turned out to be an opportunity for us to look at Splunk as a data platform. And, you know, in the technology world, you sometimes hear people talk about the horizontal capabilities. Then the vertical usage is really the security. Uh, the SIM technology. It really became one of several, sorry about the noise in the background. One, uh, became a vertical application. And then we realized that we can apply this platform to some other usages. And in addition to that, you know, when you think about cybersecurity and what we use for SIM that tends to be part of your core systems in it, we started to explore what can we do with what could we do with other data types for other different types of applications. >>And so what we, what we decided to do is we would go explore usages of this data at the edge, uh, of, of the network, and really started to move into much more of that operational technology space. When we realized that Splunk could really, uh, that we could integrate that we can ingest other types of data. And that started a second collaboration around our open Vino technology and our AI capabilities at the edge with the ingestion and the machine learning capabilities of Splunk, so that we can take things like visual data and start creating dashboards for, for example, uh, managing the flow of people, you know, especially in COVID environment. So, uh, and understanding utilization of spaces. So it really started with SIM is moved to the edge. And now we realized that there's a continuum in this data platform that we can build other usages around. >>What was that learning curve like when you went out to the edge, because a lot of people are talking about it, right. And there was a lot of banter about this is where we have to be, but you guys put your money where your mouth was, right? Yeah. You went out, you, you explored that frontier. And, and so what was that like? And, and, and what I guess maybe kind of being early in, uh, what advantage do you think that has given you as that process has matured a little bit? >>Well, it's really interesting John, because what really accelerated our engagement with Splunk in that space was the pandemic. And we had, uh, in 2020 Intel announced the pandemic response technology initiative, where we decided we were going to invest $50 million in accelerating technologies and solutions and partnerships to go solve some of the biggest challenges that depend on them. It was presenting to the world at large. And one of those areas was around companies trying to figure out how to, how to manage spaces, how to manage, you know, the number of people that are in a particular space and social distancing and things of that nature. And, you know, we ended up engaging with Splunk and this collaboration, again, to start looking at visual data, right, integrating that with our open Vino platform and again, their machine learning and algorithms, and start then creating what you would call more operational technology types of application based on visual data. Now these will have other applications that could be used for security usages. It could be used for, again, social distancing, uh, the utilization of acids, but their pandemic and that program that ends the launch is really what became the catalyst for our collaboration with Splunk that allowed us to expand into space. >>Right. And you've done a tremendous amount of work in the healthcare space. I mean, especially in the last year and a half with Penn and the pandemic, um, can you give just a couple of examples of that maybe the variety of uses and the variety of, uh, processes that you've had an influence in, because I think it's pretty impressive. >>Yeah. We, um, there's quite a bit of breadth in the types of solutions we've deployed as part of the pandemic response. John, you can think of some of the, I wouldn't call these things basic things, but you think about telehealth and that improving the telehealth experience all the way to creating privacy aware or sorry, solutions for privacy sensitive usage is where you're doing things like getting multiple institutions to share their data with the right privacy, uh, which, you know, going back to secure and privacy with the right, uh, protections for that data, but being allowed, allowing organization a and organization B partner together use data, create algorithms that both organizations benefit from it. An example of that is, is work we've done around x-ray, uh, and using x-rays to detect COVID on certain populations. So we've gone from those, you know, data protection, algorithm, development, development type of solutions to, to work that we've done in tele-health. So, uh, and, and a lot of other solutions in between, obviously in the high-performance, uh, space we've invested in high-performance computing for, to help the researchers, uh, find cures, uh, for the current pandemic and then looking at future pandemic. So it's been quite a breadth of, uh, uh, of solutions and it's really a Testament also to the breadth of Intel's portfolio and partnerships to be able to, uh, enable so much in such a short amount of time. >>I totally agree, man. Just reading it a little bit about it, about that work, and you talk about the, the breadth of that, the breadth and the depth of that is certainly impressive. So just in general, we'll just put healthcare in this big lump of customers. So what, what do you think the value proposition of your partnership with Splunk is in terms of providing, you know, ultimate value to your customers, because you're dealing with so many different sectors. Um, but if you could just give a summary from your perspective, this is what we do. This is why this power. >>Yeah. Well, customers, uh, talk about transformation. You know, there's a lot of conversation around transformation, right before the pandemic and through and center, but there's a lot of talk about companies wanting to transform and, you know, in order to be able to transform what are the key elements of that is, uh, to be able to capture the right data and then take, turn that data into the right outcomes. And that is something that requires obviously the capabilities and the ability to capture, to ingest, to analyze the data and to do that on an infrastructure that is going to scale with your business, that is going to be reliable. And that is going to be, to give you the flexibility for the types of solutions that you're wanting to apply. And that's really what this blog, uh, collaboration with Intel is going to do. It's, it's just a great example, John, uh, of the strategy that our CEO, pat Gelsinger recently talked about the importance of software to our business. >>This plump collaboration is right in the center of that. They have capabilities in SIM in it observability, uh, in many other areas that his whole world is turning data into, you know, into outcomes into results. But that has to be done on an infrastructure that again, will scale with your business, just like what's the case with Intel and our cybersecurity platform, right? We need to collaborate to make sure that this was going to scale with the demand demands of our business, and that requires close integration of, of hardware and software. The other point that I will make is that the, what started out as a collaboration with between Intel and Splunk, it's also expanding to other partners in the ecosystem. So I like to talk to you a little bit on a work stream that we have ongoing between Intel Splunk, HPE and the Lloyd. >>And why is that important is because, uh, as customers are deploying solutions, they're going to be deploying applications and they're going to have data in multiple environments on premise across multiple clouds. And we have to give, uh, these customers the ability to go gather the data from multiple sources. And that's part of the effort that we're developing with HPE and the Lloyd's will allow people to gather data, perform their analytics, regardless, regardless of their where their data is and be able to deploy the Splunk platform across these multiple environments, whether it's going to be on prem or it's going to be in a pure cloud environment, or it's going to be in a hybrid with multiple clouds, and you're willing to give our customers the most flexibility that we can. And that's where that collaboration with Deloitte and HP is going to come into play. >>Right. And you understand Splunk, right? You will get the workload. I mean, it's, it's totally, there's great familiarity there, which is a great value for that customer base, because you could apply that. So, so, um, obviously you're giving us like multiple thumbs up about the partnership. What excites you the most about going forward? Because as you know, it's all about, you know, where are we going from here? Yes. Now where we've been. So in terms of where you're going together in that partnership, well, what excites you about that? >>Well, first of all, we're excited because it's just a great example of the value that we can deliver to customers when you really understand their pain points and then have the capability to integrate solutions that encompass software and hardware together. So I think that the fact that we've been able to do the work on, on that core SIM space, where we now have a reference architecture that shows how you could really scale and deliver that a Splunk solution for your cybersecurity needs in a, in a scale of one reliable and with high levels of security, of course. And the fact that we then also been able to co-develop fairly quickly solutions for the edge, allows customers now to have that data platform that can scale and can access a lot of different data types from the edge to the cloud. That is really unique. I think it provides a lot of flexibility and it is applicable to a lot of vertical industry segments and a lot of customers >>And be attractive to a lot of customers. That's for sure rec edge of area. We appreciate the time, always a good to see you. And we certainly appreciate your joining us here on the cube to talk about.com for 21. And your relationship with the folks at Splunk. >>Yeah. Thank you, John. >>You bet. Uh, talking about Intel spot, good partnership. Long time, uh, partnership that has great plans going forward, but we continue our coverage here of.com 21. You're watching the cube.

(bright upbeat music) >> Oh welcome here to theCUBE's coverage, continuing coverage of AnsibleFest 2021. It's a pleasure to have you with us today and also to join us today is Stephen Elliott, who is the Group Vice President of Management Software and DevOps at IDC. Stephen Good to see you today, thanks for being here on theCUBE. >> Hey thanks John, it's great to be here. >> You bet, good no, thank you again for the time. Well let's just jump right in, I know this is right in your sweet spot. You know, talk about IT automation. You've done a lot of research on this, but let's just talk about overall if you will. Give us that 30-foot perspective of what you're seeing in terms of your research, when we talk about IT automation these days, and configuration management. >> Sure, yeah. Yeah I know, I mean, it's been fascinating to watch with COVID the acceleration of the investments in automation across the board. And really our enterprise IT inquiry that we've taken, it really is just fascinating to see. Whether it's network automation, looking at self-service configuration, looking at provisioning, looking at a patch. I mean, you name the manual toil that enterprise IT organizations are, you know, looking to automate, and we're just finding tremendous investment themes across those areas. I think on top of that, there's been a lot of acceleration of this idea of DevOps, of driving automation across development and operations teams, and in certainly realizing that it's really hard to hire great people. And so we're seeing that companies are utilizing automation as a way to drive your career development, training across teams, and then certainly as a way to augment their teams to help these teams scale when they have difficulties hiring more and more staff. >> Yeah well let's take that first one, that last point first here, I think that's a certainly invaluable point, and that we've heard a lot about labor all over in all sectors right about, you know, finding the right talent for the task. So, in terms of this process, IT automation, and you're talking about maybe some companies being so much short handed or trying to fine-tune their labor needs or whatever. Tell me a little bit more about that in terms of automation and how this helps that process rather than hinders it. >> Yeah, you know, it's interesting, sometimes when IT executives talk about automation, they talk about staff replacement. And actually for the lean forward companies, for most companies that make these investments. That's not the case at all. It's actually an augmentation strategy where they realize, look it's really hard to find great talent. We have an opportunity to take the talent we have, apply new skills, look at automation as a way to get existing teams more productive, as well as an opportunity to learn new skills across teams. You know, whether it's development, operations, site reliability engineering, IT ops, et cetera, networking, you know, we're seeing organizations have a much more impact, you know, much more impactful opportunity to do staff development. And so this helps with scale, it also just helps give organizations, you know, the opportunity to move people across teams, particularly if you've decided that there's one type of automation that you want to utilize, one type of configuration language. It makes things very interesting when you have, you know, an operations person who might want to become a site reliability engineer, or, you know, a DevOps team that understands they have to utilize automation, maybe they want to utilize it, you know, a common framework for that. So, we're seeing executives really look at this as, this isn't about staff replacement at all, it's actually quite the opposite. It's about retention, it's about career training and development, it's about, you know, being able to share staff across teams, and then certainly, you know, this whole notion of augmentation and increasing productivity have organizations realize that, you know, with these generally net new models, you know, containers, microservices, public cloud, DevOps, software defined infrastructure, you know, agile, all these different organizational constructs, and types of technology architectures are driving up complexity. So the ability to simplify that through automation, the ability to drive higher returns on investment through automated processes and workflows, you know, it's really striking a chord with executive teams. >> And this is obviously I think just part of this natural trend, right? As the complexity, the networks and operations has increased, finding efficiencies through automation, that's just kind of this natural flow. Has it been pande-- or how has it been pandemic driven to a certain respect then? You touched on that earlier with your first comments, but what have you seen let's say over the past year at how companies have been reacting to that environment into their business operations? >> Yeah, I know it's been interesting from the C-suite down particularly, where CEOs have really started to realize that often their business architecture is in fact their technology architecture. And the pandemic has forced the C-suite to change their customer engagement models more often than not. So many, you know, B2B companies now had to become B2C. And so, you know, many companies had to pull back, or scale back their operations in the case of, you know, hotel, lodging, airlines. Where they really had to realize, wow, you know, we've got to figure out something because, you know, we're not going to fill capacity. So, you had a lot of CEOs and CIOs recognize that their technology architecture in fact can help make these adjustments. And part of that is driving automated, you know, work streams, whether it's through, you know, new digital services, whether it's through, you know, faster provisioning of infrastructure for their DevOps and development application teams, whether it's driving higher levels of system reliability, which as we all know, you know, customers are pretty impatient. So if digital services aren't working, you're going to move on to something else pretty quickly and give, you know, a competitor, you know, revenue opportunity. So, I think a lot of those swim lane, you know, a lot of those tailwinds, I should say, have really struck a chord in the C-suite and has really driven investments that are driving, you know, core modernization, application modernization, customer engagement models, and business models that, you know, were around 24 months ago. We're finding that the focus on reliability of systems, you know, across the applications to involve systems and networks that are, you know, public-private are really, you know, having that transparency. These things are the foundation. You know, you think about building a house, these are foundational capabilities that from an operations perspective, from a development perspective have really helped shape a lot of the thinking and investment themes that the C-suite now, because COVID accelerated a lot of these modernization projects have really driven, you know, positive outcomes for. >> When you talk about impatience, there's also kind of a, I guess, a queasiness you might say, or some anxiety about any kind of change, you know, and as you're talking about these automated processes, and bringing the whole new realm of opportunity at the business. And so also introduces maybe some angst, I would think a little bit, or what are you telling and what do you see in clients? And what kind of advice are you giving them in terms of their IOT automation decisions and about deploying these really massive changes in some respects to how they conduct the business? >> Yeah I know it's a great question, and we get that quite often. What we advise are a couple of starting points. You know first and foremost, most organizations are automating something somewhere. And particularly with DevOps teams, development, SREs, operations, infrastructure platform teams, networking teams. You know, these teams have a lot of opportunity to automate their toil. And so you have to start somewhere. So pick a use case that, you know you can win, you can get great benefits and a high return on that investment. And as you sort of go through that at the team or departmental level, start then to think about what are additional processes, you know, across your peer group. You know, maybe you're a networking you should be talking to operations, maybe an Ops talking to the DevOps teams and development, et cetera. And really start to highlight some additional ways that you can utilize that singular platform and reach across, you know, your peer groups to drive your more integrated, more automated processes. And these are types of use cases that run the gamut. So from a development standpoint, these would be, you know application release, it would look at CICD, you know, pipeline deployments, et cetera. Of course, you know, manual, moving from manual automated testings, or hot button issue. But from an operational perspective, many of those processes interlock, right with provisioning, with security mechanisms and processes. And then of course, you know, the involvement of the network in terms of, you know, configuration, which is a common issue. So things like configuration, provisioning, self-service, you know, the interlock of security mechanisms. A lot of these are pretty common themes regardless of the team, you know, and regardless of the outcome that's, you know, required. So I think first and foremost, start small, but think big. Secondly think about a potential platform play as it relates to automation. The third piece is make sure you get the right peer groups involved and the key stakeholders. You know, this isn't something you just flip the switch and boom, you know, you're successful. This will take a little bit of time and it's impactful in terms of the team, impactful in terms of the processes and of course, you know, the technology. So having a strong leader and, you know, set of key stakeholders who can drive this to fruition, can really, you know, not only get great wins from the business perspective, but also really drive, you know, a continuous improvement model and drive that theme of automation, you know, particularly as it relates to agile and DevOps and site reliability engineering. It can really play an important role in helping scale out those successes that many of those teams are already sort of built. So it's the extension of the investment but at the same time, it just makes for, you know, a continual cycle of improvement opportunities for these teams to drive further automation across their particular processes. >> Well, this is obviously based on a lot of the AnsibleFest coverage, I talked about that off the, on the outset of the interview. And so let's just focus on Red Hat for a little bit here. First off, give me your take, give me your 2 cents on Red Hat in terms of, you know, how they're doing, and obviously some big announcements, you know, port works and then some on the Ansible Platform. So, first off give me a little idea on Red Hat, and then let's drill down to the news they're making on their announcements. >> Sure, yeah it's interesting, you know, Red Hat Ansible is continuously doing very well in the marketplace. Both from an adoption perspective, as well as just, you know, continuing to get more net new logos. In addition to that, you know, post the Red Hat IBM acquisition, IBM continues to take advantage of Ansible across its portfolio. So, you know, we're seeing further reach into the market into accounts that are both IBM and Red Hat related. I think another piece too, we've recently did some work around, you know, business value of Red Hat Ansible Automation Platform. And a lot of those customers really talked to us about this notion of, you know, starting small, but also thinking more broadly across what type of returns they could get from the platform as well as, you know, it's not just about cost reduction, right? It's really about cost containment, it's about acceleration of your pipelines, it's about driving higher levels of system reliability. So, the other thing we found our customers are really recognizing, it's a balance of business and technical metrics that they want to sort of choose to drive and measure their success. But also at the same point, it's a recognition on the part of Red Hat and their product and development teams they'd really listen to a lot of customers, gotten, you know, features in and really started to think about this breadth of how automation can support, not just operations, but development. You know, this idea of autonomous automation, you know, being able to empower different sets of personas or customers to drive, you know, faith and trust in a product to say, hey, we want to automate a particular piece of a process. And we're just going to, you know, build up the policy, inherently use the templates and boom turn it on and, you know, set it and forget it. So that, that's, you know, a coming wave where customers are starting to, you know, work with Red Hat and particularly the Ansible Platform to understand what does that mean? You know, how do we execute that? And then, you know, as we get more comfortable with turning on that more autonomous perspective, you know, how can we then spread that idea out to different teams? So, you know, we're seeing a lot of these themes and as we talk to customers, you know, hearing a lot of good feedback with regards to, you know, Red Hat and IBM taking advantage of the technology, as well as more importantly customers getting, you know, significant value and returns from the platform itself. >> Right, well Stephen, I appreciate the insights. Certainly it's an interesting future awaiting off course the world of IT automation, a lot more intelligence, right? A lot more autonomy, a lot more challenges, but I'm sure Red Hat is very much up to that. And thank you for being with us here today on theCUBE. >> Hey thank you John it great to be here. >> You bet, Stephen Elliot joining us from IDC talking about Red Hat and Ansible and we'll continue with more coverage a little bit later on theCUBE. Thanks for joining this segment with Stephen Elliott. (bright upbeat music)

(upbeat music) >> Narrator: From around the globe, it's theCUBE, with digital coverage of Postgres Vision 2021, brought to you by EDB. >> Well, good day, everybody. John Walls here on theCUBE, and continuing our CUBE conversation as part of Postgres Vision 2021, sponsored by EDB, with EDB Chief Technology Officer, Mr. Mark Linster. Mark, good morning to you. How are you doing today? >> I'm doing very fine, very good, sir. >> Excellent. Excellent. Glad you could join us. And we appreciate the time, chance, to look at what's going on in this world of data, which, as you know, continues to evolve quite rapidly. So let's just take that 30,000-foot perspective here to begin with here, and let's talk about data, and management, and what Postgres is doing in terms of accelerating all these innovative techniques, and solutions, and services that we're seeing these days. >> Yeah, so I think it's really... It's a fantastic confluence of factors that we've seen in Postgres, or are seeing in Postgres today, where Postgres has really, really matured over the last couple of years, where things like high availability, parallel processing, use of very high core counts, et cetera, have come together with the drive towards digital transformation, the enormous amounts of data that businesses are dealing with today, so, and then the third factor's really the embracing of open source, right? I mean, Linux has shown the way, and has shown that this is really, really possible. And now we're seeing Postgres as, I think, the next big open source innovation, after Linux, achieving the same type of transformation. So it's really, it's a maturing, it's an acceptance, and the big drive towards dealing with a lot more data as part of digital transformation. >> You know, part of that acceptance that you talk about is about kind of accepting the fact that you have a legacy system that maybe, if you're not going to completely overhaul, you still have to integrate, right? You've got to compliment and start this kind of migration. So in your perspective, or from your perspective, what kind of progress is Postgres allowing in the mindset of CTOs among your client base, or whatever, that their legacy systems can function in this new environment, that all is not lost, and while there is some, perhaps, catching up to do, or some patching you have to do here and there, that it's not as arduous, or not as complex, as might appear to be on the face. >> Well, I think there's, the maturing of Postgres that has really really opened this up, right? Where we're seeing that Postgres can handle these workloads, right? And at the same time, there's a growing number of success cases where companies across all industries, financial services, insurance, manufacturing, retail are using Postgres. So, so you're no longer, you're no longer the first leader who's taken a higher risk, right? Like, five or 10 years ago, Postgres knowledge was not readily available. So if you want Postgres, it was really hard to find somebody who could support you, right? Or find an employee that you could hire who would be the Postgres expert. That's no longer the case. There's plenty of books about Postgres. There's lots of conferences about Postgres. It's a big meetup topic. So, getting know how and getting acceptance amongst your team to use Postgres has become a lot easier, right? At the same time, over 90% of all enterprises today use open source in one way or the other. Which basically means they have open source policies. They have ways to bring open source into the development stream. So that makes it possible, right? Whereas before it was really hard, you had to have an individual who would be evangelized to go, get open source, et cetera, now open source is something that almost everybody is using. You know, from government to financing services, open sources use all over the place, right? So, so now you have something that really matured, right? There's a lot of references out there and then you have the policies that make it possible, right? You have the success stories and now all the pieces have come together to deal with this onslaught of data, right? And then maybe the last thing that that really plays a big role is the cloud. Postgres runs everywhere, right? I mean, it runs from an Arduino to Amazon. Everywhere. And so, which basically means if you want to drive agile business transformation, you call Postgres because you don't have to decide today where it's going to run. You're not locking into a vendor. You're not locking into a limited support system. You can run this thing anywhere. It'll run on your laptop. It'll run on every cloud in the world. You can have it managed, you can have it hosted. You can add have every flavor you want and there's lots of good Postgres support companies out there. So all of these factors together is really what makes us so interesting, right? >> Kubernetes and this marriage, this complimentary, you know relationship right now with Kubernetes, what has that done? You think in terms of providing additional services or at least providing perhaps a new approach or new philosophies, new concepts in terms of database management? >> Well, it's maybe the most the most surprising thing or surprising from the outside. Probably not from the inside, but you think that that Postgres this now 25 year old, database twenty-five year old open source project would be kind of like completely, you know, incompatible with Kubernetes, with containers. But what really happens is Postgres in containers today is the number one database, after Engine X. It is the number two software that is being deployed in containers. So it's really become the workhorse of the whole microservices transformation, right? A 25 year old software, well, it has a very small footprint. It has a lot of interesting features like GIS, document processing, now graph capabilities, common table expressions all those things that are really like cool for developers. And that's probably what leads it to be the number one database in containers. So it's absolutely compatible with Kubernetes. And the whole transformation towards microservices is is like, you know, there's nothing better out there. It runs everywhere and has the most innovative technologies in it. And that's what we're seeing. Also, you go to the annual stack overflow survey of developers, right? It's been consistently number one or number two most loved and most used database, right? So, so what's amazing is that it's this relatively old technology that is, you know, beating everybody else in this digital transformation and then the adoption by developers. >> Just like old dog new tricks, right? It's still winning, right? >> Yeah, yeah, and, and, you know, the elephant is the symbol and this elephant does dance. >> Still dancing that's right. You know, and this is kind of a loaded question but there are a lot of databases out there, a lot of options, obviously from your perspective, you know, Postgres is winning, right? And, and, and from the size of the marketplace it is certainly leading RA leader. In your opinion, you know, what, what is this confluence of factors that have influenced this, this market position if you will, of Postgres or market acceptance of Postgres? >> It's, I mean, it's the, it's a maturing of the core. As I said before, that the transaction rates et cetera, Postgres can handle, are growing every year and are growing dramatic, right? So that's one thing. And then you have it, that Postgres is really, I think, the most reliable and relational database out there as what is my opinion, I'm biased, I guess. And, and it's, it's super quality code but then you add to that the innovation drive. I mean, it was the first one out there with good JSONB support, right? And now it's brought in JSON Path as as part of the new SQL standard. So now you can address JSON data inside your database and the same way you do it inside your browser. And that's pretty cool for developers. Then you combine that with PostGIS, right, which is, I think the most advanced GIS system out there in database. Now, now you got relations, asset compliant, GIS and document. You may say what's so cool about that. Well, what's cool about it is I can do absolutely reliable asset compliant transactions. I can have a fantastic personalization engine through JSONB, and then all my applications need to know where is the transaction? Where is the next store? How far away I'm a form of the parking spot? Right? So now I got a really really nice recipe to put the applications of the future together. You add onto that movements toward supporting graph and supporting other capabilities inside the database. So now you got, you got capability, you've got reliability and you got fantastic innovation. I mean, there's nothing better out there. >> Let's hit the security angle here, 'cause you talked about the asset test, and certainly, you know, those, that criteria is being met. No question about that, whether it's isolation, durability, consistency, whatever, but, but security, I don't have to tell you what a growing concern this is. It's already paramount, but we're seeing every day write stories about, about intrusions and and invasions, if you will. So in terms of providing that layer of security that everybody's looking for right now, you know, this this ultra impenetrable force, if you will, what in your mind, what's Postgres allowing for, in that respect in terms of security, peace of mind, and maybe a little additional comfort that everybody in your space is looking for these? >> So, so look at, look at security with a database like, like multiple layers, right? There's not just, you don't do security only one place. It's like when you go into a bank branch, right? I mean, they do lock the door, they have a camera, there is a gate in front of the safe, there's a safe door. And inside the safe, there is still, again safety deposit boxes with individual locks. The same applies to Postgres, right? Where let's say we start at the heart of it where we can secure and protect tables and data. We're using access control lists and groups and usernames, et cetera. Right? So that's, that's at the heart of it. But then outside of that, we can encrypt the data when on disk or when it's in transit on disk. Most people use the Linux disc encryption systems but there's also good partners out there, like like more metric or others that we work with, that that provide security on disk. And then you go out from there and then you have the securing of the database itself again through the log-ins and the groups. You go out from there and now you have the securing of the hosts that the database is sitting on. Then you'll look at securing the data on the networks through SSL and certificates, et cetera. So that basically there's a multi-layer security model layer that positions Postgres extremely well. And then maybe the last thing is to say it certainly integrates very well with ELDAP, active directory, Kerberos, all the usual suspects that you would use to secure technology inside the enterprise or in an open network, like where people work from home, et cetera. >> You talked about the history about this 25 year old technology, you know, founded back at Cal Berkeley, you know, probably almost some 30 years ago and certainly has evolved. And, and as you have pointed out now as a very mature technology, what do you see though in terms of growth from here? Like, where does it go from here in the next 18 months, 24 months, what what do you think is that next barrier, that challenge that that you think the technology and this open source community wants to take on? >> Well, I think there's there's the continuous effort of making it faster, right? That always happens, right? Every database wants to be faster do more transactions per second, et cetera. And there's a lot of work that has been done there. I mean, just in the last couple of years, Postgres performance has increased by over 50%. Right? So, so transactions per second and that kind of scalability that is going to continue to be, to be a focus, right? And then the other one is leading the implementation of the SQL standards, right? So there'd be the most advanced database, the most innovative database, because, remember for many years now, Postgres has come up with a new release on an annual basis. Other database vendors are now catching up to that, but Postgres has done that for years. So innovation has always been at the heart of it. So we started with JSONB, Key value pair came even before that, PostGis has been around for a long time, graph extensions are going to be the next thing, ingestion of time series data is going to, is going to happen. So there's going to be an ongoing stream of innovations happening. But one thing that I can say is because Postgres is a pure open source project. There's not a hard roadmap, like where it's going to go but where it's going to go is always driven by what people want to have, right? There is no product management department. There's no, there's no great visionary that says, "Oh, this is where we're going to go." No, no. What's going to happen is what people want to have, right? If companies or contributors want to have a certain feature because they need it, well, that's how it's going to happen. And that's really been at the heart of this since Mike Stonebraker, who's an advisor to EDB today, invented it. And then, you know, the open source project got created. This has always been the movement to only focus on things that people actually want to have because if nobody wants to have it, we're just not going to build it because nobody wants it. Right? So when you asked me for the roadmap I believe it's going to be, you know, faster, obviously, always faster, right? Everybody wants faster. And then there's going to be innovation features like making the document stored even better, graph ingestion of large time series, et cetera. That's really what I believe is going to drive it forward. >> Wow. Yeah, the market has spoken and as you point out the market will continue to speak and, and drive that bus. So Mark, thank you for the time today. We certainly appreciate that. And wish EDB continued success at Postgres vision 2021. And thanks for the time. >> Thanks John, it was a pleasure. >> You bet. Mark Linster, joining us, the CTO at EDB. I'm John Walls, you've been watching theCUBE. (upbeat music)

(bright upbeat music) >> Hey, welcome to theCUBE's coverage of Pure Accelerate 2021. I'm Lisa Martin, please stay welcoming back one of our alumni Murli Thirumale is here, the VP & GM of the Cloud Native Business Unit at Pure Storage, Murli, welcome back. >> Lisa, it's great to be back at theCUBE, looking forward to discussion. >> Likewise, so it's been about six months or so since the Portworx acquisition by Pure Storage, give us a lay of the land, what's been going on? What are some of the successes, early wins, and some of the lessons that you've learned? >> Yeah, this is my third time being in Cloud, being a serial entrepreneur. So I've seen this movie before, and I have to say that this is really a lot of good anticipation followed by actually a lot of good stuff that has happened since, so it's been really a great ride so far. And when, let me start with the beginning, what the fundamental goal of the acquisition were, right? The couple of major goals, and then I can talk about how that integration is going. Really, I think from our viewpoint, from the Portworx viewpoint, the goal of the acquisition, from our view, was really to help turbocharge in our growth, we had really a very, very good product that was well accepted and established at customers, doing well as far as industry acceptance was concerned. And frankly, we had some great reference customers and some great installs expanding pretty well. Our issue was really how fast can we turbocharge that growth because as everybody knows, for a startup, the expensive part of an expansion is really on the go-to-market and sales side. And frankly, the timing for this was critical for us because the market had moved from the Kubernetes' market, has moved from sort of the innovator stage to the early majority stage. So from the Pure side, I think this made a lot of sense for them, because they have been looking for how they can expand their subscription models, how they can move to add more value from the array based business that there really have been a wonderful disruptor and to add more value up the stack, and that was the premise of the acquisition. One of the things that I paid a lot of attention to, as anybody does in acquisitions, is not just the strategy but really to understand if there was a culture fit between the teams, because a lot of the times acquisitions don't work because of the poor culture fit. So now let me kind of fast forward little bit and say, "Hey, what we know looking back in about six to eight months into it, how has it turning out so far?" And things have been just absolutely wonderful. Let me actually start with the culture fit, because that often is ignored and is one of the most important parts, right? The resonance in the culture between the two companies is just off the charts, right? It actually starts with what I would call a dramatic kind of customer first orientation, it's something we always had at Portworx. I always used to tell our customers with a startup you end up kind of, you buy the product, but you get the team, right? That's what happens with early stage startups, but Pure is sort of the same way, they are very focused on customer. So the customer focus is a very very useful thing that pulls us together. The second thing that's been really heartwarming to see has been really the focus on product excellence. Pure made it's dramatic entry into the market using Flash, and being the best Flash-based solution, and now they've expanded into many, many different areas. And Portworx also had a focus on product excellence, and so that has kind of moved the needle forward for both of us. And then I think the third thing is really a focus on the team winning, and not just an individual, right? And look, in these COVID times, this has been a tough year for everybody, I think it's, to some extent, even as we onboard new people, it's the culture of the team, the ability to bring new people onboard, and buy the culture, and make progress, all of that is really a function of how well the team is, 'we' is greater than 'me' type of a model, and I think that both these three values of customer first, high focus on product excellence, and the value in the team, including the resellers and the customers as part of the team, has really been the cornerstone, I think, of our success in the integration. >> That's outstanding because, like you said, this is not your first rodeo launching, coming out of stealth and launching and getting acquired, but doing so during one of the most challenging times in the last 100 years in our history while aligning cultures, I think that says a lot about the leadership on the Portworx side and the Pure side. >> I have to say, right? This is one of those amazing things, many people now that having been acquired can say this, really, most of the diligence, the transactions, all of that were done over Zoom, right? So, and then of course, everything since then is we're still in Zoom paradise. And so I think it really is a testament to the modern tools and stuff that we have that enable that. Now, let me talk a little bit about the content of what has happened, right? So strategically, I think the three areas that I think we've had huge synergy and seeing the benefits are first and foremost on the product side. A little later, I'd like to talk a little bit about some of the announcements we're making, but essentially, Pure had this outstanding core storage infrastructure product, well-known in the industry, very much Flash-oriented, part of the whole all Flash era now. And Portworx really came in with the idea of driving Kubernetes and Cloud Native workloads, which are really the majority of modern workloads. And what we found since then is that the integration of having really a more complete stack, which is really centered around what used to be an IT infrastructure of purchase, and what is in fact, for Kubernetes, a more DevOps oriented purchase. And that kind of a combination of being able to provide that combo in one package is something that we've been working very hard on in the last six months. And I'll mention some of the announcements, but we have a number of integrations with FlashArray and FlashBlade and other Pure products that we're able to highlight. So product integration for sure has been an area of some focus, but against a lot of progress. The second one is really customer synergy. I kind of described to our team when we got acquired, I said it's, for us, it's, being acquired by Pure is like strapping a rocket ship to ourselves as a small company, because we now have access to a huge customer footprint. Pure has over 8,000 customers, hugely amazingly high, almost unbelievable NPS score with customers, one of the best in the IT industry. And I think we are finding that with the deployment of containers becoming more ubiquitous, right? 80, 90% of customers in the enterprise are adopting Kubernetes and Containers. And therefore these 8,000 customers are a big huge target, they got a big target sign for both of us to be able to leverage. And so we've had a number of things that we're doing to address and use the Pure sales team to get access to them. The Pure channel of course is also part of that, Pure is 100% channel organization, which is great. So I think the synergy on the customer side with being able to have a solution that works for infrastructure and for DevOps has been a big area. In this day and age, Kubernetes is an area, for many of your listeners who are very, very familiar with Kubernetes, customers struggle, not just with day zero, but day one, day two, day three, right? It's how do you put it in production. And support, and integrating, and the use of Kubernetes and containers, putting that stack together is a big area. So support is a big area of pain for customers, and it's an area that, again, for a Portworx viewpoint, now we've expanded our footprint with a great support organization that we can bring to bear 24 by seven around the globe. Portworx is running on a lot of mission critical applications in big industries like finance and retail, and these types of things, really, support is a big area. And then the last thing I will just say is the use cases are usually synergistic, right? And we'll talk a little bit more about use cases as we go along here, but really there's legacy apps, right? In an interesting way, there's 80% of, IT spending is still on legacy apps, if you will, in that stack. However, 80% of all the new applications are being deployed on this modern app stack, right? >> Right. >> With all these open-source type of products and technologies. And most of that stack, most of the modern app stack is containerized. The 80, 85% of those applications really are where customers have chosen containers and Kubernetes as the as the mechanism to deliver those apps. And therefore Pure products like FlashBlade were very, very focused with fast recovery for these kind of modern apps, which are the stack of AI, and personalization, and all the modern digital apps. And I think those things can align well with the Portworx offering. So really around the areas of culture, customers, product synergy, support, and finally use cases, are all kind of been areas of huge progress for us. >> It also seems to me that the Portworx acquisition gives Pure a foray, a new buying center with respect to DevOps, talk to me a little bit about that as an opportunity for Pure. >> Yeah, the modern world is one where the enterprise itself has segmented into whole lot of new areas of spending and infrastructure ownership, right? And in the old days it used to be the network, storage, compute, and apps, sort of the old model of the world. And of course the app model has moved on, and then certainly there's a lot of different ways, web apps, the three tier apps, and the web apps, and so on. But the infrastructure world has morphed really into a bunch of other sub-segments, and some of it is still traditional hardware, but then even that is being cloudified, right? Because a lot of companies like Pure have taken their hardware array offerings and are offering that as a cloud-like offering where you can purchase it as a service, and in fact, Pure is offering a set of solutions called Evergreen that allow you to not even, you're just under subscription, you get your hardware refresh bundled in, very, very innovative. So you have now new buying centers coming in, in addition to the old traditional IT, there is sort of this whole, what used to be in the old ways called middleware, now has kind of morphed into this DevSecOps set of folks, right? Which is DevOps it's ITOps, and even security is a big part of that, the CISO Organization has that kind of segment. And so these buying centers often have new budgets, right? It turns out that, for example, to contrast, the Portworx budget really comes from entirely different budget, right? Our top two budget sources are usually CIO initiatives, they're not from the traditional storage budget, it comes from things like move to cloud or business transformation. And those set of folks, that set of customers, is really born in a different era, so to speak. You know, Lisa, they come, and I come from the old world, so I would say that I'm kind of more of an oldie, hopefully a Goldie, but an oldie. These folks are born in the post-DevOps, post-cloud, post-open-source world, right? They are used to brand new tools, get-ops, the way that everything's run on the cloud, it's on demand. So what we bring to Pure is really the ability to take their initiatives, which were around infrastructure, and cloudifying infrastructure to now adding two layers on top of that, right? So what Portworx adds to Pure is the access to the new automation layer of middleware. Kubernetes is nothing but really an automation of model for containers and for infrastructure now. And then the third layer is on top of us, is what I would call SaaS, the SaaSified layer, and as a service layer. And so we bring the opportunity to get those SaaS-like budgets, the DevOps budgets, and the DevOps and the SaaS kind of buyers, and together the business has very different models to it. In addition to not just a different technologies, the buying behavior is different, it's based on a consumption model, it's a subscription business. So it really is a change for new budgets, new buyers, and new financial models, which is a subscription model, which as you know, is valued much more highly by Wall Street nowadays compared to say some of the older hardware models. >> Well, Murli, when we talk about storage, we talk about data or the modern data experience. The more and more data that's being produced, the more value potentially there is for organizations, I think we saw, we learned several lessons in the last year, and one of them is that being able to glean insights from data in real-time or near real-time is, for many businesses, no longer a nice to have, it's really table stakes, it was for survival of getting through COVID, it is now in terms of identification of new business models, but it elevates the data conversation up to the C-suite, the board going, "Is our data protected? Is it secure? Can we access it?" And, "How do we deliver a modern data experience to our customers and to our internal employees?" So with that modern data experience, and maybe the elevation about conversation lengths, talk to me about some of the things that you're announcing at Accelerate with respect to Portworx. >> Yeah, so there are two sets of announcements. To be honest actually, this is a pretty exciting time for us, we're in theCUBE Cone time and the Accelerate time. And so let me kind of draw a circle around both those sets of announcements, if you will, right? So let's start perhaps with just the sets of things that we are announcing at Accelerate, right? This is kind of the first things that are coming up right now. And I'll tell you, there are some very, very exciting things that we're doing. So the majority of the announcements are centered around a release that we have called 2.8, so Portworx says, "We've been in the market now for well over five years with the product that really has been well deployed in very large global 2K enterprises." So the three or four major announcements, one of them is what I was talking about earlier, the integration of true Kubernetes applications running on Pure Storage. So we have a Cloud Native, a Native implementation of Portworx running on FlashArray and FlashBlade, where essentially when users now provision a container volume to Portworx, the storage volumes are magically created on FlashArray and FlashBlade, right? It's the idea of, without having to interface, so a DevOps engineer can deploy storage as code by provisioning volumes using Kubernetes without having to go issue a trouble ticket or a service ticket for a PureArray. And Portworx essentially access a layer between Kubernetes and the PureArray, and we allow configuration of volumes on the storage volumes of the PureArray directly. So essentially now on FlashArray, these volumes now receive the full suite of Portworx Storage Management features, including Kubernetes DR, backup, security, auto scaling, and migration. So that is a first version of this integration, right? The second one, it's, I am, is a personal favorite of mine, it's very, very exciting, right? When we came into Pure, we discovered that Pure already had this software solution called Pure as a service, it was essentially a Pure1 service that allowed for continuous call home, and log and diagnostic information, really an awesome window for customers to be able to see what their array utilization is like, complete observability, end-to-end on capacity, what's coming up, and allowed for proactive addressing of outages, or issues, or being able to kind of see it before it happen. The good news now is Portworx is integrated with Pure1, and so now customers have a unified observability stack for their Kubernetes applications using Portworx and FlashArray and FlashBlade in the Pure1 portal. So we are in the Pure1 portal now really providing end-to-end troubleshooting of issues and deployment, so very, very exciting, something that I think is a major step forward, right? >> Absolutely, well that single pane of glass is critical for management, so many companies waste a lot of time and resources managing disparate disconnected systems. And again, the last year has taught us so many businesses, there wasn't time, because there's going to be somebody right behind you that's going to be faster and more nimble, and has that single pane of glass unified view to be able to make better decisions. Last question, really, before we wrap here. >> Yeah. >> I can hear your momentum, I can feel your momentum through Zoom here. Talk to me about what's next, 'cause I know that when the acquisition happened about, we said six months or so ago, you said, "This is a small step in the Portworx journey." So what's ahead? >> Lisa, great question. I can state 10 things, but let me kind of step up a little bit at the 10,000 foot level, right? In one sense, I think no company gets to declare victory in this ongoing battle and we're just getting started. But if I had to kind of say, "What are some of the major teams that we have been part of and have been able to make happen in addition to take advantage of?" Pure obviously took advantage of the Flash wave, and they moved to all Flash, that's been a major disruptor with Pure being the lead. For Portworx, it has been really the move to containers and data management in an automated form, right? Kubernetes has become sort of not just a container orchestrator looking North, but looking southbound, is orchestrating infrastructure, we are in the throws of that revolution. But if you think about it, the other thing that's happening is all of this is in the service of, if you're a CIO, you're in the service of lines of businesses asking for a way to run their applications in a multicloud way, run their applications faster. And that is really the, as a service revolution, and it feels a little silly to almost talk about it as a service in that it's this late in the Cloud era, but the reality is that's just beginning, right? As a service revolution dramatically changed the IaaS business, the infrastructure business. But if you look at it, data services as a, data as a service is something that is what our customers are doing, so our customers are taking Pure hardware, Portworx software, and then they are building them into a platform as a service, things like databases as a service. And what we are doing, you will see some announcements from us in the second half of this year, terribly exciting, I just can't wait for it, where we're going to be actually moving forward to allow our customers to more quickly get to data services at the push of a button, so to speak, right? So- >> Excellent. >> The idea of database as a service to offer messaging as a service, search as a service, streaming as a service, and then finally some ML kind of AI as a service, these five categories of data services are what you should be expecting to see from Portworx and Pure going forward in the next half. >> Big potential there to really kick the door wide open on the total adjustable market. Well, Murli, it's been great to have you on the program, I can't wait to have you on next 'cause I know that there's so much more, like I said, I can feel your momentum through our virtual experience here. Thank you so much for joining us and giving us the lay of the land of what's been happening with the Portworx acquisition and all of the momentum and excitement that is about to come, we appreciate your time. >> Thank you, Lisa. Cheers to a great reduced COVID second half of the year. >> Oh, cheers to that. >> Yeah cheers, thanks. >> From Murli Thirumale, I'm Lisa Martin, you're watching theCUBE's coverage of Pure Accelerate. (bright upbeat music)