(bright upbeat music) >> Hello and welcome to theCUBE's coverage of International Women's Day. I'm your host, John Furrier here in Palo Alto, California Studio and remoting is a great guest CUBE alumni, co-founder, technical co-founder and she's also the VP of Product at Platform9 Systems. It's a company pioneering Kubernetes infrastructure, been doing it for a long, long time. Madhura Maskasky, thanks for coming on theCUBE. Appreciate you. Thanks for coming on. >> Thank you for having me. Always exciting. >> So I always... I love interviewing you for many reasons. One, you're super smart, but also you're a co-founder, a technical co-founder, so entrepreneur, VP of product. It's hard to do startups. (John laughs) Okay, so everyone who started a company knows how hard it is. It really is and the rewarding too when you're successful. So I want to get your thoughts on what's it like being an entrepreneur, women in tech, some things you've done along the way. Let's get started. How did you get into your career in tech and what made you want to start a company? >> Yeah, so , you know, I got into tech long, long before I decided to start a company. And back when I got in tech it was very clear to me as a direction for my career that I'm never going to start a business. I was very explicit about that because my father was an entrepreneur and I'd seen how rough the journey can be. And then my brother was also and is an entrepreneur. And I think with both of them I'd seen the ups and downs and I had decided to myself and shared with my family that I really want a very well-structured sort of job at a large company type of path for my career. I think the tech path, tech was interesting to me, not because I was interested in programming, et cetera at that time, to be honest. When I picked computer science as a major for myself, it was because most of what you would consider, I guess most of the cool students were picking that as a major, let's just say that. And it sounded very interesting and cool. A lot of people were doing it and that was sort of the top, top choice for people and I decided to follow along. But I did discover after I picked computer science as my major, I remember when I started learning C++ the first time when I got exposure to it, it was just like a light bulb clicking in my head. I just absolutely loved the language, the lower level nature, the power of it, and what you can do with it, the algorithms. So I think it ended up being a really good fit for me. >> Yeah, so it clicked for you. You tried it, it was all the cool kids were doing it. I mean, I can relate, I did the same thing. Next big thing is computer science, you got to be in there, got to be smart. And then you get hooked on it. >> Yeah, exactly. >> What was the next level? Did you find any blockers in your way? Obviously male dominated, it must have been a lot of... How many females were in your class? What was the ratio at that time? >> Yeah, so the ratio was was pretty, pretty, I would say bleak when it comes to women to men. I think computer science at that time was still probably better compared to some of the other majors like mechanical engineering where I remember I had one friend, she was the single girl in an entire class of about at least 120, 130 students or so. So ratio was better for us. I think there were maybe 20, 25 girls in our class. It was a large class and maybe the number of men were maybe three X or four X number of women. So relatively better. Yeah. >> How about the job when you got into the structured big company? How did that go? >> Yeah, so, you know, I think that was a pretty smooth path I would say after, you know, you graduated from undergrad to grad school and then when I got into Oracle first and VMware, I think both companies had the ratios were still, you know, pretty off. And I think they still are to a very large extent in this industry, but I think this industry in my experience does a fantastic job of, you know, bringing everybody and kind of embracing them and treating them at the same level. That was definitely my experience. And so that makes it very easy for self-confidence, for setting up a path for yourself to thrive. So that was it. >> Okay, so you got an undergraduate degree, okay, in computer science and a master's from Stanford in databases and distributed systems. >> That's right. >> So two degrees. Was that part of your pathway or you just decided, "I want to go right into school?" Did it go right after each other? How did that work out? >> Yeah, so when I went into school, undergrad there was no special major and I didn't quite know if I liked a particular subject or set of subjects or not. Even through grad school, first year it wasn't clear to me, but I think in second year I did start realizing that in general I was a fan of backend systems. I was never a front-end person. The backend distributed systems really were of interest to me because there's a lot of complex problems to solve, and especially databases and large scale distributed systems design in the context of database systems, you know, really started becoming a topic of interest for me. And I think luckily enough at Stanford there were just fantastic professors like Mendel Rosenblum who offered operating system class there, then started VMware and later on I was able to join the company and I took his class while at school and it was one of the most fantastic classes I've ever taken. So they really had and probably I think still do a fantastic curriculum when it comes to distributor systems. And I think that probably helped stoke that interest. >> How do you talk to the younger girls out there in elementary school and through? What's the advice as they start to get into computer science, which is changing and still evolving? There's backend, there's front-end, there's AI, there's data science, there's no code, low code, there's cloud. What's your advice when they say what's the playbook? >> Yeah, so I think two things I always say, and I share this with anybody who's looking to get into computer science or engineering for that matter, right? I think one is that it's, you know, it's important to not worry about what that end specialization's going to be, whether it's AI or databases or backend or front-end. It does naturally evolve and you lend yourself to a path where you will understand, you know, which systems, which aspect you like better. But it's very critical to start with getting the fundamentals well, right? Meaning all of the key coursework around algorithm, systems design, architecture, networking, operating system. I think it is just so crucial to understand those well, even though at times you make question is this ever going to be relevant and useful to me later on in my career? It really does end up helping in ways beyond, you know, you can describe. It makes you a much better engineer. So I think that is the most important aspect of, you know, I would think any engineering stream, but definitely true for computer science. Because there's also been a trend more recently, I think, which I'm not a big fan of, of sort of limited scoped learning, which is you decide early on that you're going to be, let's say a front-end engineer, which is fine, you know. Understanding that is great, but if you... I don't think is ideal to let that limit the scope of your learning when you are an undergrad phrase or grad school. Because later on it comes back to sort of bite you in terms of you not being able to completely understand how the systems work. >> It's a systems kind of thinking. You got to have that mindset of, especially now with cloud, you got distributed systems paradigm going to the edge. You got 5G, Mobile World Congress recently happened, you got now all kinds of IOT devices out there, IP of devices at the edge. Distributed computing is only getting more distributed. >> That's right. Yeah, that's exactly right. But the other thing is also happens... That happens in computer science is that the abstraction layers keep raising things up and up and up. Where even if you're operating at a language like Java, which you know, during some of my times of programming there was a period when it was popular, it already abstracts you so far away from the underlying system. So it can become very easier if you're doing, you know, Java script or UI programming that you really have no understanding of what's happening behind the scenes. And I think that can be pretty difficult. >> Yeah. It's easy to lean in and rely too heavily on the abstractions. I want to get your thoughts on blockers. In your career, have you had situations where it's like, "Oh, you're a woman, okay seat at the table, sit on the side." Or maybe people misunderstood your role. How did you deal with that? Did you have any of that? >> Yeah. So, you know, I think... So there's something really kind of personal to me, which I like to share a few times, which I think I believe in pretty strongly. And which is for me, sort of my personal growth began at a very early phase because my dad and he passed away in 2012, but throughout the time when I was growing up, I was his special little girl. And every little thing that I did could be a simple test. You know, not very meaningful but the genuine pride and pleasure that he felt out of me getting great scores in those tests sort of et cetera, and that I could see that in him, and then I wanted to please him. And through him, I think I build that confidence in myself that I am good at things and I can do good. And I think that just set the building blocks for me for the rest of my life, right? So, I believe very strongly that, you know, yes, there are occasions of unfair treatment and et cetera, but for the most part, it comes from within. And if you are able to be a confident person who is kind of leveled and understands and believes in your capabilities, then for the most part, the right things happen around you. So, I believe very strongly in that kind of grounding and in finding a source to get that for yourself. And I think that many women suffer from the biggest challenge, which is not having enough self-confidence. And I've even, you know, with everything that I said, I've myself felt that, experienced that a few times. And then there's a methodical way to get around it. There's processes to, you know, explain to yourself that that's actually not true. That's a fake feeling. So, you know, I think that is the most important aspect for women. >> I love that. Get the confidence. Find the source for the confidence. We've also been hearing about curiosity and building, you mentioned engineering earlier, love that term. Engineering something, like building something. Curiosity, engineering, confidence. This brings me to my next question for you. What do you think the key skills and qualities are needed to succeed in a technical role? And how do you develop to maintain those skills over time? >> Yeah, so I think that it is so critical that you love that technology that you are part of. It is just so important. I mean, I remember as an example, at one point with one of my buddies before we started Platform9, one of my buddies, he's also a fantastic computer scientists from VMware and he loves video games. And so he said, "Hey, why don't we try to, you know, hack up a video game and see if we can take it somewhere?" And so, it sounded cool to me. And then so we started doing things, but you know, something I realized very quickly is that I as a person, I absolutely hate video games. I've never liked them. I don't think that's ever going to change. And so I was miserable. You know, I was trying to understand what's going on, how to build these systems, but I was not enjoying it. So, I'm glad that I decided to not pursue that. So it is just so important that you enjoy whatever aspect of technology that you decide to associate yourself with. I think that takes away 80, 90% of the work. And then I think it's important to inculcate a level of discipline that you are not going to get sort of... You're not going to get jaded or, you know, continue with happy path when doing the same things over and over again, but you're not necessarily challenging yourself, or pushing yourself, or putting yourself in uncomfortable situation. I think a combination of those typically I think works pretty well in any technical career. >> That's a great advice there. I think trying things when you're younger, or even just for play to understand whether you abandon that path is just as important as finding a good path because at least you know that skews the value in favor of the choices. Kind of like math probability. So, great call out there. So I have to ask you the next question, which is, how do you keep up to date given all the changes? You're in the middle of a world where you've seen personal change in the past 10 years from OpenStack to now. Remember those days when I first interviewed you at OpenStack, I think it was 2012 or something like that. Maybe 10 years ago. So much changed. How do you keep up with technologies in your field and resources that you rely on for personal development? >> Yeah, so I think when it comes to, you know, the field and what we are doing for example, I think one of the most important aspect and you know I am product manager and this is something I insist that all the other product managers in our team also do, is that you have to spend 50% of your time talking to prospects, customers, leads, and through those conversations they do a huge favor to you in that they make you aware of the other things that they're keeping an eye on as long as you're doing the right job of asking the right questions and not just, you know, listening in. So I think that to me ends up being one of the biggest sources where you get tidbits of information, new things, et cetera, and then you pursue. To me, that has worked to be a very effective source. And then the second is, you know, reading and keeping up with all of the publications. You guys, you know, create a lot of great material, you interview a lot of people, making sure you are watching those for us you know, and see there's a ton of activities, new projects keeps coming along every few months. So keeping up with that, listening to podcasts around those topics, all of that helps. But I think the first one I think goes in a big way in terms of being aware of what matters to your customers. >> Awesome. Let me ask you a question. What's the most rewarding aspect of your job right now? >> So, I think there are many. So I think I love... I've come to realize that I love, you know, the high that you get out of being an entrepreneur independent of, you know, there's... In terms of success and failure, there's always ups and downs as an entrepreneur, right? But there is this... There's something really alluring about being able to, you know, define, you know, path of your products and in a way that can potentially impact, you know, a number of companies that'll consume your products, employees that work with you. So that is, I think to me, always been the most satisfying path, is what kept me going. I think that is probably first and foremost. And then the projects. You know, there's always new exciting things that we are working on. Even just today, there are certain projects we are working on that I'm super excited about. So I think it's those two things. >> So now we didn't get into how you started. You said you didn't want to do a startup and you got the big company. Your dad, your brother were entrepreneurs. How did you get into it? >> Yeah, so, you know, it was kind of surprising to me as well, but I think I reached a point of VMware after spending about eight years or so where I definitely packed hold and I could have pushed myself by switching to a completely different company or a different organization within VMware. And I was trying all of those paths, interviewed at different companies, et cetera, but nothing felt different enough. And then I think I was very, very fortunate in that my co-founders, Sirish Raghuram, Roopak Parikh, you know, Bich, you've met them, they were kind of all at the same journey in their careers independently at the same time. And so we would all eat lunch together at VMware 'cause we were on the same team and then we just started brainstorming on different ideas during lunchtime. And that's kind of how... And we did that almost for a year. So by the time that the year long period went by, at the end it felt like the most logical, natural next step to leave our job and to, you know, to start off something together. But I think I wouldn't have done that had it not been for my co-founders. >> So you had comfort with the team as you knew each other at VMware, but you were kind of a little early, (laughing) you had a vision. It's kind of playing out now. How do you feel right now as the wave is hitting? Distributed computing, microservices, Kubernetes, I mean, stuff you guys did and were doing. I mean, it didn't play out exactly, but directionally you were right on the line there. How do you feel? >> Yeah. You know, I think that's kind of the challenge and the fun part with the startup journey, right? Which is you can never predict how things are going to go. When we kicked off we thought that OpenStack is going to really take over infrastructure management space and things kind of went differently, but things are going that way now with Kubernetes and distributed infrastructure. And so I think it's been interesting and in every path that you take that does end up not being successful teaches you so much more, right? So I think it's been a very interesting journey. >> Yeah, and I think the cloud, certainly AWS hit that growth right at 2013 through '17, kind of sucked all the oxygen out. But now as it reverts back to this abstraction layer essentially makes things look like private clouds, but they're just essentially DevOps. It's cloud operations, kind of the same thing. >> Yeah, absolutely. And then with the edge things are becoming way more distributed where having a single large cloud provider is becoming even less relevant in that space and having kind of the central SaaS based management model, which is what we pioneered, like you said, we were ahead of the game at that time, is becoming sort of the most obvious choice now. >> Now you look back at your role at Stanford, distributed systems, again, they have world class program there, neural networks, you name it. It's really, really awesome. As well as Cal Berkeley, there was in debates with each other, who's better? But that's a separate interview. Now you got the edge, what are some of the distributed computing challenges right now with now the distributed edge coming online, industrial 5G, data? What do you see as some of the key areas to solve from a problem statement standpoint with edge and as cloud goes on-premises to essentially data center at the edge, apps coming over the top AI enabled. What's your take on that? >> Yeah, so I think... And there's different flavors of edge and the one that we focus on is, you know, what we call thick edge, which is you have this problem of managing thousands of as we call it micro data centers, rather than managing maybe few tens or hundreds of large data centers where the problem just completely shifts on its head, right? And I think it is still an unsolved problem today where whether you are a retailer or a telecommunications vendor, et cetera, managing your footprints of tens of thousands of stores as a retailer is solved in a very archaic way today because the tool set, the traditional management tooling that's designed to manage, let's say your data centers is not quite, you know, it gets retrofitted to manage these environments and it's kind of (indistinct), you know, round hole kind of situation. So I think the top most challenges are being able to manage this large footprint of micro data centers in the most effective way, right? Where you have latency solved, you have the issue of a small footprint of resources at thousands of locations, and how do you fit in your containerized or virtualized or other workloads in the most effective way? To have that solved, you know, you need to have the security aspects around these environments. So there's a number of challenges that kind of go hand-in-hand, like what is the most effective storage which, you know, can still be deployed in that compact environment? And then cost becomes a related point. >> Costs are huge 'cause if you move data, you're going to have cost. If you move compute, it's not as much. If you have an operating system concept, is the data and state or stateless? These are huge problems. This is an operating system, don't you think? >> Yeah, yeah, absolutely. It's a distributed operating system where it's multiple layers, you know, of ways of solving that problem just in the context of data like you said having an intermediate caching layer so that you know, you still do just in time processing at those edge locations and then send some data back and that's where you can incorporate some AI or other technologies, et cetera. So, you know, just data itself is a multi-layer problem there. >> Well, it's great to have you on this program. Advice final question for you, for the folks watching technical degrees, most people are finding out in elementary school, in middle school, a lot more robotics programs, a lot more tech exposure, you know, not just in Silicon Valley, but all around, you're starting to see that. What's your advice for young girls and people who are getting either coming into the workforce re-skilled as they get enter, it's easy to enter now as they stay in and how do they stay in? What's your advice? >> Yeah, so, you know, I think it's the same goal. I have two little daughters and it's the same principle I try to follow with them, which is I want to give them as much exposure as possible without me having any predefined ideas about what you know, they should pursue. But it's I think that exposure that you need to find for yourself one way or the other, because you really never know. Like, you know, my husband landed into computer science through a very, very meandering path, and then he discovered later in his career that it's the absolute calling for him. It's something he's very good at, right? But so... You know, it's... You know, the reason why he thinks he didn't pick that path early is because he didn't quite have that exposure. So it's that exposure to various things, even things you think that you may not be interested in is the most important aspect. And then things just naturally lend themselves. >> Find your calling, superpower, strengths. Know what you don't want to do. (John chuckles) >> Yeah, exactly. >> Great advice. Thank you so much for coming on and contributing to our program for International Women's Day. Great to see you in this context. We'll see you on theCUBE. We'll talk more about Platform9 when we go KubeCon or some other time. But thank you for sharing your personal perspective and experiences for our audience. Thank you. >> Fantastic. Thanks for having me, John. Always great. >> This is theCUBE's coverage of International Women's Day, I'm John Furrier. We're talking to the leaders in the industry, from developers to the boardroom and everything in between and getting the stories out there making an impact. Thanks for watching. (bright upbeat music)

>>Hello, brilliant humans and welcome back to Las Vegas, Nevada, where we are live from the AWS Reinvent Show floor here with the cube. My name is Savannah Peterson, joined with Dave Valante, and we have a very exciting conversation with you. Two, two companies you may have heard of. We've got AWS and Red Hat in the house. Manu and Joel, thank you so much for being here. Love this little fist bump. Started off, that's right. Before we even got rolling, Manu, you said that you wanted this to be the best segment of, of the cubes airing. We we're doing over a hundred segments, so you're gonna have to bring the heat. >>We're ready. We're did go. Are we ready? Yeah, go. We're ready. Let's bring it on. >>We're ready. All right. I'm, I'm ready. Dave's ready. Let's do it. How's the show going for you guys real quick before we dig in? >>Yeah, I think after Covid, it's really nice to see that we're back into the 2019 level and, you know, people just want to get out, meet people, have that human touch with each other, and I think a lot of trust gets built as a functional that, so it's super amazing to see our partners and customers here at Reedman. Yeah, >>And you've got a few in the house. That's true. Just a few maybe, maybe a couple >>Very few shows can say that, by the way. Yeah, it's maybe a handful. >>I think one of the things we were saying, it's almost like the entire Silicon Valley descended in the expo hall area, so >>Yeah, it's >>For a few different reasons. There's a few different silicon defined. Yeah, yeah, yeah. Don't have strong on for you. So far >>It's, it's, it is amazing. It's the 10th year, right? It's decade, I think I've been to five and it's, it grows every single year. It's the, you have to be here. It's as simple as that. And customers from every single industry are here too. You don't get, a lot of shows have every single industry and almost every single location around the globe. So it's, it's a must, must be >>Here. Well, and the personas evolved, right? I was at reinvent number two. That was my first, and it was all developers, not all, but a lot of developers. And today it's a business mix, really is >>Totally, is a business mix. And I just, I've talked about it a little bit down the show, but the diversity on the show floor, it's the first time I've had to wait in line for the ladies' room at a tech conference. Almost a two decade career. It is, yeah. And it was really refreshing. I'm so impressed. So clearly there's a commitment to community, but also a commitment to diversity. Yeah. And, and it's brilliant to see on the show floor. This is a partnership that is robust and has been around for a little while. Money. Why don't you tell us a little bit about the partnership here? >>Yes. So Red Hand and AWS are best friends, you know, forever together. >>Aw, no wonder we got the fist bumps and all the good vibes coming out. I know, it's great. I love that >>We have a decade of working together. I think the relationship in the first phase was around running rail bundled with E two. Sure. We have about 70,000 customers that are running rail, which are running mission critical workloads such as sap, Oracle databases, bespoke applications across the state of verticals. Now, as more and more enterprise customers are finally, you know, endorsing and adopting public cloud, I think that business is just gonna continue to grow. So a, a lot of progress there. The second titration has been around, you know, developers tearing Red Hat and aws, Hey, listen, we wanna, it's getting competitive. We wanna deliver new features faster, quicker, we want scale and we want resilience. So just entire push towards devs containers. So that's the second chapter with, you know, red Hat OpenShift on aws, which launched as a, a joint manage service in 2021 last year. And I think the third phase, which you're super excited about, is just bringing the ease of consumption, one click deployment, and then having our customers, you know, benefit from the joint committed spend programs together. So, you know, making sure that re and Ansible and JBoss, the entire portfolio of Red Hat products are available on AWS marketplace. So that's the 1, 2, 3, it of our relationship. It's a decade of working together and, you know, best friends are super committed to making sure our customers and partners continue successful. >>Yeah, that he said it, he said it perfectly. 2008, I know you don't like that, but we started with Rel on demand just in 2008 before E two even had a console. So the partnership has been there, like Manu says, for a long time, we got the partnership, we got the products up there now, and we just gotta finalize that, go to market and get that gas on the fire. >>Yeah. So Graviton Outpost, local zones, you lead it into all the new stuff. So that portends, I mean, 2008, we're talking two years after the launch of s3. >>That's right. >>Right. So, and now look, so is this a harbinger of things to come with these new innovations? >>Yeah, I, I would say, you know, the innovation is a key tenant of our partnership, our relationship. So if you look at from a product standpoint, red Hat or Rel was one of the first platforms that made a support for graviton, which is basically 40% better price performance than any other distribution. Then that translated into making sure that Rel is available on all of our regions globally. So this year we launched Switzerland, Spain, India, and Red Hat was available on launch there, support for Nitro support for Outpost Rosa support on Outpost as well. So I think that relationship, that innovation on the product side, that's pretty visible. I think that innovation again then translates into what we are doing on marketplace with one click deployments we spoke about. I think the third aspect of the know innovation is around making sure that we are making our partners and our customers successful. So one of the things that we've done so far is Joe leads a, you know, a black belt team that really goes into each customer opportunity, making sure how can we help you be successful. We launched and you know, we should be able to share that on a link. After this, we launched like a big playlist, which talks about every single use case on how do you get successful and running OpenShift on aws. So that innovation on behalf of our customers partners to make them successful, that's been a key tenant for us together as >>Well. That's right. And that team that Manu is talking about, we're gonna, gonna 10 x that team this year going into January. Our fiscal yield starts in January. Love that. So yeah, we're gonna have a lot of no hiring freeze over here. Nope. No ma'am. No. Yeah, that's right. Yeah. And you know what I love about working with aws and, and, and Manu just said it very, all of that's customer driven. Every single event that we, that he just talked about in that timeline, it's customer driven, right? Customers wanted rail on demand, customers want JBoss up in the cloud, Ansible this week, you know, everything's up there now. So it's just getting that go to market tight and we're gonna, we're gonna get that done. >>So what's the algorithm for customer driven in terms of taking the input? Because if every customers saying, Hey, I this a >>Really similar >>Question right up, right? I, that's what I want. And if you know, 95% of the customers say it, Jay, maybe that's a good idea. >>Yeah, that's right. Trends. But >>Yeah. You know, 30% you might be like, mm, you know, 20%, you know, how do you guys decide when to put gas on the fire? >>No, that, I think, as I mentioned, there are about 70,000 large customers that are running rail on Easy Two, many of these customers are informing our product strategy. So we have, you know, close to about couple of thousand power users. We have customer advisory booths, and these are the, you know, customers are informing us, Hey, let's get all of the Red Hat portfolio and marketplace support for graviton, support for Outpost. Why don't we, why are we not able to dip into the consumption committed spend programs for both Red Hat and aws? That's right. So it's these power users both at the developer level as well as the guys who are actually doing large commercial consumption. They are the ones who are informing the roadmap for both Red Hat and aws. >>But do, do you codify the the feedback? >>Yeah, I'm like, I wanna see the database, >>The, I think it was, I don't know, it was maybe Chasy, maybe it was Besos, that that data beats intuition. So do you take that information and somehow, I mean, it's global, 70,000 customers, right? And they have different weights, different spending patterns, different levels of maturity. Yeah. Do you, how do you codify that and then ultimately make the decision? Yeah, I >>If, I mean, well you, you've got the strategic advisory boards, which are made up of customers and partners and you know, you get, you get a good, you gotta get a good slice of your customer base to get, and you gotta take their feedback and you gotta do something with it, right? That's the, that's the way we do it and codify it at the product level, I'm sure open source. That's, that's basically how we work at the product level, right? The most elegant solution in open source wins. And that's, that's pretty much how we do that at the, >>I would just add, I think it's also just the implicit trust that the two companies had built with each other, working in the trenches, making our customers and partners successful over the last decade. And Alex, give an example. So that manifests itself in context of like, you know, Amazon and Red Hat just published the entire roadmap for OpenShift. What are the new features that are becoming over the next six to nine to 12 months? It's open source available on GitHub. Customers can see, and then they can basically come back and give feedback like, Hey, you know, we want hip compliance. We just launched. That was a big request that was coming from our >>Customers. That is not any process >>Also for Graviton or Nvidia instances. So I I I think it's a, >>Here's the thing, the reason I'm pounding on this is because you guys have a pretty high hit rate, and I think as a >>Customer, mildly successful company >>As, as a customer advocate, the better, you know, if, if you guys make bets that pay off, it's gonna pay off for customers. Right. And because there's a lot of failures in it. Yeah. I mean, let's face it. That's >>Right. And I think, I think you said the key word bets. You place a lot of small bets. Do you have the, the innovation engine to do that? AWS is the perfect place to place those small bets. And then you, you know, pour gas on the fire when, when they take off. >>Yeah, it's a good point. I mean, it's not expensive to experiment. Yeah. >>Especially in the managed service world. Right? >>And I know you love taking things to market and you're a go to market guy. Let's talk gtm, what's got your snow pumped about GTM for 2023? >>We, we are gonna, you know, 10 x the teams that's gonna be focused on these products, right? So we're gonna also come out with a hybrid committed spend program for our customers that meet them where they want to go. So they're coming outta the data center going into a cloud. We're gonna have a nice financial model for them to do that. And that's gonna take a lot of the friction out. >>Yeah. I mean, you've nailed it. I, I think the, the fact that now entire Red Hat portfolio is available on marketplace, you can do it on one click deployment. It's deeply integrated with Amazon services and the most important part that Joel was making now customers can double dip. They can drive benefit from the consumption committed spend programs, both from Red Hat and from aws, which is amazing. Which is a game changer That's right. For many of our large >>Customers. That's right. And that, so we're gonna, we're gonna really go to town on that next year. That's, and all the, all the resources that I have, which are the technology sellers and the sas, you know, the engineers we're growing this team the most out that team. So it's, >>When you say 10 x, how many are you at now? I'm >>Curious to see where you're headed. Tell you, okay. There's not right? Oh no, there's not one. It's triple digit. Yeah, yeah. >>Today. Oh, sweet. Awesome. >>So, and it's a very sizable team. They're actually making sure that each of our customers are successful and then really making sure that, you know, no customer left behind policy. >>And it's a great point that customers love when Amazonians and Red Hats show up, they love it and it's, they want to get more of it, and we're gonna, we're gonna give it to 'em. >>Must feel great to be loved like that. >>Yeah, that's right. Yeah. Yeah. I would say yes. >>Seems like it's safe to say that there's another decade of partnership between your two companies. >>Hope so. That's right. That's the plan. >>Yeah. And I would say also, you know, just the IBM coming into the mix here. Yeah. I, you know, red Hat has informed the way we have turned around our partnership with ibm, essentially we, we signed the strategic collaboration agreement with the company. All of IBM software now runs on Rosa. So that is now also providing a lot of tailwinds both to our rail customers and as well as Rosa customers. And I think it's a very net creative, very positive for our partnership. >>That's right. It's been very positive. Yep. Yeah. >>You see the >>Billboards positive. Yeah, right. Also that, that's great. Great point, Dave. Yep. We have a, we have a new challenge, a new tradition on the cube here at Reinvent where we're, well, it's actually kind of a glamor moment for you, depending on how you leverage it. We're looking for your 32nd hot take your Instagram reel, your sizzle thought leadership, biggest takeaway, most important theme from this year's show. I know you want, right, Joel? I mean, you TM boy, I feel like you can spit the time. >>Yeah. It is all about Rosa for us. It is all in on that, that's the native OpenShift offering on aws and that's, that's the soundbite we're going go to town with. Now, I don't wanna forget all the other products that are in there, but Rosa is a, is a very key push for us this year. >>Fantastic. All right. Manu. >>I think our customers, it's getting super competitive. Our customers want to innovate just a >>Little bit. >>The enterprise customers see the cloud native companies. I wanna do what these guys are doing. I wanna develop features at a fast clip. I wanna scale, I wanna be resilient. And I think that's really the spirit that's coming out. So to Joel's point, you know, move to worlds containers, serverless, DevOps, which was like, you know, aha, something that's happening on the side of an enterprise is not becoming mainstream. The business is demanding it. The, it is becoming the centerpiece in the business strategy. So that's been really like the aha. Big thing that's happening here. >>Yeah. And those architectures are coming together, aren't they? That's correct. Right. You know, VMs and containers, it used to be one architecture and then at the other end of the spectrum is serverless. People thought of those as different things and now it's a single architecture and, and it's kind of right approach for the right job. >>And, and a compliments say to Red Hat, they do an incredible job of hiding that complexity. Yeah. Yes. And making sure that, you know, for example, just like, make it easier for the developers to create value and then, and you know, >>Yeah, that's right. Those, they were previously siloed architectures and >>That's right. OpenShift wanna be place where you wanna run containers or virtual machines. We want that to be this Yeah. Single place. Not, not go bolt on another piece of architecture to just do one or the other. Yeah. >>And hey, the hybrid cloud vision is working for ibm. No question. You know, and it's achievable. Yeah. I mean, I just, I've said unlike, you know, some of the previous, you know, visions on fixing the world with ai, hybrid cloud is actually a real problem that you're attacking and it's showing the results. Agreed. Oh yeah. >>Great. Alright. Last question for you guys. Cause it might be kind of fun, 10 years from now, oh, we're at another, we're sitting here, we all look the same. Time has passed, but we are not aging, which is a part of the new technology that's come out in skincare. That's my, I'm just throwing that out there. Why not? What do you guys hope that you can say about the partnership and, and your continued commitment to community? >>Oh, that's a good question. You go first this time. Yeah. >>I think, you know, the, you know, for looking into the future, you need to look into the past. And Amazon has always been driven by working back from our customers. That's like our key tenant, principle number 1 0 1. >>Couple people have said that on this stage this week. Yeah. >>Yeah. And I think our partnership, I hope over the next decade continues to keep that tenant as a centerpiece. And then whatever comes out of that, I think we, we are gonna be, you know, working through that. >>Yeah. I, I would say this, I think you said that, well, the customer innovation is gonna lead us to wherever that is. And it's, it's, it's gonna be in the cloud for sure. I think we can say that in 10 years. But yeah, anything from, from AI to the quant quantum computing that IBM's really pushing behind that, you know, those are, those are gonna be things that hopefully we show up on a, on a partnership with Manu in 10 years, maybe sooner. >>Well, whatever happens next, we'll certainly be covering it here on the cube. That's right. Thank you both for being here. Joel Manu, fantastic interview. Thanks to see you guys. Yeah, good to see you brought the energy. I think you're definitely ranking high on the top interviews. We >>Love that for >>The day. >>Thank >>My pleasure >>Job, guys. Now that you're competitive at all, and thank you all for tuning in to our live coverage here from AWS Reinvent in Las Vegas, Nevada, with Dave Valante. I'm Savannah Peterson. You're watching The Cube, the leading source for high tech coverage.

(soft electronic music) >> Okay, we're back with Tim Yocum who is the Director of Engineering at InfluxData. Tim, welcome, good to see you. >> Good to see you, thanks for having me. >> You're really welcome. Listen, we've been covering opensource software on theCUBE for more than a decade and we've kind of watched the innovation from the big data ecosystem, the cloud is being built out on opensource, mobile, social platforms, key databases, and of course, InfluxDB. And InfluxData has been a big consumer and crontributor of opensource software. So my question to you is where have you seen the biggest bang for the buck from opensource software? >> So yeah, you know, Influx really, we thrive at the intersection of commercial services and opensource software, so OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service from our core storage engine technologies to web services, templating engines. Our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants. And like you've mentioned, even better, we contribute a lot back to the projects that we use, as well as our own product InfluxDB. >> But I got to ask you, Tim, because one of the challenge that we've seen, in particular, you saw this in the heyday of Hadoop, the innovations come so fast and furious, and as a software company, you got to place bets, you got to commit people, and sometimes those bets can be risky and not pay off. So how have you managed this challenge? >> Oh, it moves fast, yeah. That's a benefit, though, because the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we tend to do is we fail fast and fail often; we try a lot of things. You know, you look at Kubernetes, for example. That ecosystem is driven by thousands of intelligent developers, engineers, builders. They're adding value every day, so we have to really keep up with that. And as the stack changes, we try different technologies, we try different methods. And at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's something that we just do every day. >> So we have a survey partner down in New York City called Enterprise Technology Research, ETR, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes, is one of the areas that is kind of, it's been off the charts and seen the most significant adoption and velocity particularly along with cloud, but really, Kubernetes is just, you know, still up and to the right consistently, even with the macro headwinds and all of the other stuff that we're sick of talking about. So what do you do with Kubernetes in the platform? >> Yeah, it's really central to our ability to run the product. When we first started out, we were just on AWS and the way we were running was a little bit like containers junior. Now we're running Kubernetes everywhere at AWS, Azure, Google cloud. It allows us to have a consistent experience across three different cloud providers and we can manage that in code. So our developers can focus on delivering services not trying to learn the intricacies of Amazon, Azure, and Google, and figure out how to deliver services on those three clouds with all of their differences. >> Just a followup on that, is it now, so I presume it sounds like there's a PaaS layer there to allow you guys to have a consistent experience across clouds and out to the edge, wherever. Is that correct? >> Yeah, so we've basically built more or less platform engineering is this the new, hot phrase. Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on and they only have to learn one way of deploying their application, managing their application. And so that just gets all of the underlying infrastructure out of the way and lets them focus on delivering Influx cloud. >> And I know I'm taking a little bit of a tangent, but is that, I'll call it a PaaS layer, if I can use that term, are there specific attributes to InfluxDB or is it kind of just generally off-the-shelf PaaS? Is there any purpose built capability there that is value-add or is it pretty much generic? >> So we really build, we look at things with a build versus buy, through a build versus buy lens. Some things we want to leverage, cloud provider services, for instance, POSTGRES databases for metadata, perhaps. Get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can deliver on, that has consistency, that is all generated from code. that we can, as an SRE group, as an OPS team, that we can manage with very few people, really, and we can stamp out clusters across multiple regions in no time. >> So sometimes you build, sometimes you buy it. How do you make those decisions and what does that mean for the platform and for customers? >> Yeah, so what we're doing is, it's like everybody else will do. We're looking for trade-offs that make sense. We really want to protect our customers' data, so we look for services that support our own software with the most up-time reliability and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team and of course, for our customers; you don't even see that. But we don't want to try to reinvent the wheel, like I had mentioned with SQL datasource for metadata, perhaps. Let's build on top of what of these three large cloud providers have already perfected and we can then focus on our platform engineering and we can help our developers then focus on the InfluxData software, the Influx cloud software. >> So take it to the customer level. What does it mean for them, what's the value that they're going to get out of all these innovations that we've been talking about today, and what can they expect in the future? >> So first of all, people who use the OSS product are really going to be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you, but then you want to scale up. We have some 270 terabytes of data across over four billion series keys that people have stored, so there's a proven ability to scale. Now in terms of the opensource software and how we've developed the platform, you're getting highly available, high cardinality time-series platform. We manage it and really, as I had mentioned earlier, we can keep up with the state of the art. We keep reinventing, we keep deploying things in realtime. We deploy to our platform every day, repeatedly, all the time. And it's that continuous deployment that allow us to continue testing things in flight, rolling things out that change, new features, better ways of doing deployments, safer ways of doing deployments. All of that happens behind the scenes and like we had mentioned earllier, Kubernetes, I mean, that allows us to get that done. We couldn't do it without having that platform as a base layer for us to then put our software on. So we iterate quickly. When you're on the Influx cloud platform, you really are able to take advantage of new features immediately. We roll things out every day and as those things go into production, you have the ability to use them. And so in the then, we want you to focus on getting actual insights from your data instead of running infrastructure, you know, let us do that for you. >> That makes sense. Are the innovations that we're talking about in the evolution of InfluxDB, do you see that as sort of a natural evolution for existing customers? Is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >> Yeah, it really is. It's a little bit of both. Any engineer will say, "Well it depends." So cloud-native technologies are really the hot thing, IoT, industrial IoT especially. People want to just shove tons of data out there and be able to do queries immediately and they don't want to manage infrastructure. What we've started to see are people that use the cloud service as their datastore backbone and then they use edge computing with our OSS product to ingest data from say, multiple production lines, and down-sample that data, send the rest of that data off to Influx cloud where the heavy processing takes place. So really, us being in all the different clouds and iterating on that, and being in all sorts of different regions, allows for people to really get out of the business of trying to manage that big data, have us take care of that. And, of course, as we change the platform, endusers benefit from that immediately. >> And so obviously you've taken away a lot of the heavy lifting for the infrastructure. Would you say the same things about security, especially as you go out to IoT at the edge? How should we be thinking about the value that you bring from a security perspective? >> We take security super seriously. It's built into our DNA. We do a lot of work to ensure that our platform is secure, that the data that we store is kept private. It's, of course, always a concern, you see in the news all the time, companies being compromised. That's something that you can have an entire team working on which we do, to make sure that the data that you have, whether it's in transit, whether it's at rest is always kept secure, is only viewable by you. You look at things like software bill of materials, if you're running this yourself, you have to go vet all sorts of different pieces of software and we do that, you know, as we use new tools. That's something, that's just part of our jobs to make sure that the platform that we're running has fully vetted software. And you know, with opensource especially, that's a lot of work, and so it's definitely new territory. Supply chain attacks are definitely happening at a higher clip that they used to but that is really just part of a day in the life for folks like us that are building platforms. >> And that's key, especially when you start getting into the, you know, that we talk about IoT and the operations technologies, the engineers running that infrastrucutre. You know, historically, as you know, Tim, they would air gap everything; that's how they kept it safe. But that's not feasible anymore. Everything's-- >> Can't do that. >> connected now, right? And so you've got to have a partner that is, again, take away that heavy lifting to R&D so you can focus on some of the other activities. All right, give us the last word and the key takeaways from your perspective. >> Well, you know, from my perspective, I see it as a two-lane approach, with Influx, with any time-series data. You've got a lot of stuff that you're going to run on-prem. What you had mentioned, air gapping? Sure, there's plenty of need for that. But at the end of the day, people that don't want to run big datacenters, people that want to entrust their data to a company that's got a full platform set up for them that they can build on, send that data over to the cloud. The cloud is not going away. I think a more hybrid approach is where the future lives and that's what we're prepared for. >> Tim, really appreciate you coming to the program. Great stuff, good to see you. >> Thanks very much, appreciate it. >> Okay in a moment, I'll be back to wrap up today's session. You're watching theCUBE. (soft electronic music)

>>This past May, The Cube in collaboration with Influx data shared with you the latest innovations in Time series databases. We talked at length about why a purpose built time series database for many use cases, was a superior alternative to general purpose databases trying to do the same thing. Now, you may, you may remember the time series data is any data that's stamped in time, and if it's stamped, it can be analyzed historically. And when we introduced the concept to the community, we talked about how in theory, those time slices could be taken, you know, every hour, every minute, every second, you know, down to the millisecond and how the world was moving toward realtime or near realtime data analysis to support physical infrastructure like sensors and other devices and IOT equipment. A time series databases have had to evolve to efficiently support realtime data in emerging use cases in iot T and other use cases. >>And to do that, new architectural innovations have to be brought to bear. As is often the case, open source software is the linchpin to those innovations. Hello and welcome to Evolving Influx DB into the smart Data platform, made possible by influx data and produced by the Cube. My name is Dave Valante and I'll be your host today. Now in this program we're going to dig pretty deep into what's happening with Time series data generally, and specifically how Influx DB is evolving to support new workloads and demands and data, and specifically around data analytics use cases in real time. Now, first we're gonna hear from Brian Gilmore, who is the director of IOT and emerging technologies at Influx Data. And we're gonna talk about the continued evolution of Influx DB and the new capabilities enabled by open source generally and specific tools. And in this program you're gonna hear a lot about things like Rust, implementation of Apache Arrow, the use of par k and tooling such as data fusion, which powering a new engine for Influx db. >>Now, these innovations, they evolve the idea of time series analysis by dramatically increasing the granularity of time series data by compressing the historical time slices, if you will, from, for example, minutes down to milliseconds. And at the same time, enabling real time analytics with an architecture that can process data much faster and much more efficiently. Now, after Brian, we're gonna hear from Anna East Dos Georgio, who is a developer advocate at In Flux Data. And we're gonna get into the why of these open source capabilities and how they contribute to the evolution of the Influx DB platform. And then we're gonna close the program with Tim Yokum, he's the director of engineering at Influx Data, and he's gonna explain how the Influx DB community actually evolved the data engine in mid-flight and which decisions went into the innovations that are coming to the market. Thank you for being here. We hope you enjoy the program. Let's get started. Okay, we're kicking things off with Brian Gilmore. He's the director of i t and emerging Technology at Influx State of Bryan. Welcome to the program. Thanks for coming on. >>Thanks Dave. Great to be here. I appreciate the time. >>Hey, explain why Influx db, you know, needs a new engine. Was there something wrong with the current engine? What's going on there? >>No, no, not at all. I mean, I think it's, for us, it's been about staying ahead of the market. I think, you know, if we think about what our customers are coming to us sort of with now, you know, related to requests like sql, you know, query support, things like that, we have to figure out a way to, to execute those for them in a way that will scale long term. And then we also, we wanna make sure we're innovating, we're sort of staying ahead of the market as well and sort of anticipating those future needs. So, you know, this is really a, a transparent change for our customers. I mean, I think we'll be adding new capabilities over time that sort of leverage this new engine, but you know, initially the customers who are using us are gonna see just great improvements in performance, you know, especially those that are working at the top end of the, of the workload scale, you know, the massive data volumes and things like that. >>Yeah, and we're gonna get into that today and the architecture and the like, but what was the catalyst for the enhancements? I mean, when and how did this all come about? >>Well, I mean, like three years ago we were primarily on premises, right? I mean, I think we had our open source, we had an enterprise product, you know, and, and sort of shifting that technology, especially the open source code base to a service basis where we were hosting it through, you know, multiple cloud providers. That was, that was, that was a long journey I guess, you know, phase one was, you know, we wanted to host enterprise for our customers, so we sort of created a service that we just managed and ran our enterprise product for them. You know, phase two of this cloud effort was to, to optimize for like multi-tenant, multi-cloud, be able to, to host it in a truly like sass manner where we could use, you know, some type of customer activity or consumption as the, the pricing vector, you know, And, and that was sort of the birth of the, of the real first influx DB cloud, you know, which has been really successful. >>We've seen, I think like 60,000 people sign up and we've got tons and tons of, of both enterprises as well as like new companies, developers, and of course a lot of home hobbyists and enthusiasts who are using out on a, on a daily basis, you know, and having that sort of big pool of, of very diverse and very customers to chat with as they're using the product, as they're giving us feedback, et cetera, has has, you know, pointed us in a really good direction in terms of making sure we're continuously improving that and then also making these big leaps as we're doing with this, with this new engine. >>Right. So you've called it a transparent change for customers, so I'm presuming it's non-disruptive, but I really wanna understand how much of a pivot this is and what, what does it take to make that shift from, you know, time series, you know, specialist to real time analytics and being able to support both? >>Yeah, I mean, it's much more of an evolution, I think, than like a shift or a pivot. You know, time series data is always gonna be fundamental and sort of the basis of the solutions that we offer our customers, and then also the ones that they're building on the sort of raw APIs of our platform themselves. You know, the time series market is one that we've worked diligently to lead. I mean, I think when it comes to like metrics, especially like sensor data and app and infrastructure metrics, if we're being honest though, I think our, our user base is well aware that the way we were architected was much more towards those sort of like backwards looking historical type analytics, which are key for troubleshooting and making sure you don't, you know, run into the same problem twice. But, you know, we had to ask ourselves like, what can we do to like better handle those queries from a performance and a, and a, you know, a time to response on the queries, and can we get that to the point where the results sets are coming back so quickly from the time of query that we can like limit that window down to minutes and then seconds. >>And now with this new engine, we're really starting to talk about a query window that could be like returning results in, in, you know, milliseconds of time since it hit the, the, the ingest queue. And that's, that's really getting to the point where as your data is available, you can use it and you can query it, you can visualize it, and you can do all those sort of magical things with it, you know? And I think getting all of that to a place where we're saying like, yes to the customer on, you know, all of the, the real time queries, the, the multiple language query support, but, you know, it was hard, but we're now at a spot where we can start introducing that to, you know, a a limited number of customers, strategic customers and strategic availability zones to start. But you know, everybody over time. >>So you're basically going from what happened to in, you can still do that obviously, but to what's happening now in the moment? >>Yeah, yeah. I mean if you think about time, it's always sort of past, right? I mean, like in the moment right now, whether you're talking about like a millisecond ago or a minute ago, you know, that's, that's pretty much right now, I think for most people, especially in these use cases where you have other sort of components of latency induced by the, by the underlying data collection, the architecture, the infrastructure, the, you know, the, the devices and you know, the sort of highly distributed nature of all of this. So yeah, I mean, getting, getting a customer or a user to be able to use the data as soon as it is available is what we're after here. >>I always thought, you know, real, I always thought of real time as before you lose the customer, but now in this context, maybe it's before the machine blows up. >>Yeah, it's, it's, I mean it is operationally or operational real time is different, you know, and that's one of the things that really triggered us to know that we were, we were heading in the right direction, is just how many sort of operational customers we have. You know, everything from like aerospace and defense. We've got companies monitoring satellites, we've got tons of industrial users, users using us as a processes storing on the plant floor, you know, and, and if we can satisfy their sort of demands for like real time historical perspective, that's awesome. I think what we're gonna do here is we're gonna start to like edge into the real time that they're used to in terms of, you know, the millisecond response times that they expect of their control systems, certainly not their, their historians and databases. >>I, is this available, these innovations to influx DB cloud customers only who can access this capability? >>Yeah. I mean commercially and today, yes. You know, I think we want to emphasize that's a, for now our goal is to get our latest and greatest and our best to everybody over time. Of course. You know, one of the things we had to do here was like we double down on sort of our, our commitment to open source and availability. So like anybody today can take a look at the, the libraries in on our GitHub and, you know, can ex inspect it and even can try to, you know, implement or execute some of it themselves in their own infrastructure. You know, we are, we're committed to bringing our sort of latest and greatest to our cloud customers first for a couple of reasons. Number one, you know, there are big workloads and they have high expectations of us. I think number two, it also gives us the opportunity to monitor a little bit more closely how it's working, how they're using it, like how the system itself is performing. >>And so just, you know, being careful, maybe a little cautious in terms of, of, of how big we go with this right away, just sort of both limits, you know, the risk of, of, you know, any issues that can come with new software rollouts. We haven't seen anything so far, but also it does give us the opportunity to have like meaningful conversations with a small group of users who are using the products, but once we get through that and they give us two thumbs up on it, it'll be like, open the gates and let everybody in. It's gonna be exciting time for the whole ecosystem. >>Yeah, that makes a lot of sense. And you can do some experimentation and, you know, using the cloud resources. Let's dig into some of the architectural and technical innovations that are gonna help deliver on this vision. What, what should we know there? >>Well, I mean, I think foundationally we built the, the new core on Rust. You know, this is a new very sort of popular systems language, you know, it's extremely efficient, but it's also built for speed and memory safety, which goes back to that us being able to like deliver it in a way that is, you know, something we can inspect very closely, but then also rely on the fact that it's going to behave well. And if it does find error conditions, I mean we, we've loved working with Go and, you know, a lot of our libraries will continue to, to be sort of implemented in Go, but you know, when it came to this particular new engine, you know, that power performance and stability rust was critical. On top of that, like, we've also integrated Apache Arrow and Apache Parque for persistence. I think for anybody who's really familiar with the nuts and bolts of our backend and our TSI and our, our time series merged Trees, this is a big break from that, you know, arrow on the sort of in MI side and then Par K in the on disk side. >>It, it allows us to, to present, you know, a unified set of APIs for those really fast real time inquiries that we talked about, as well as for very large, you know, historical sort of bulk data archives in that PARQUE format, which is also cool because there's an entire ecosystem sort of popping up around Parque in terms of the machine learning community, you know, and getting that all to work, we had to glue it together with aero flight. That's sort of what we're using as our, our RPC component. You know, it handles the orchestration and the, the transportation of the Coer data. Now we're moving to like a true Coer database model for this, this version of the engine, you know, and it removes a lot of overhead for us in terms of having to manage all that serialization, the deserialization, and, you know, to that again, like blurring that line between real time and historical data. It's, you know, it's, it's highly optimized for both streaming micro batch and then batches, but true streaming as well. >>Yeah. Again, I mean, it's funny you mentioned Rust. It is, it's been around for a long time, but it's popularity is, is you know, really starting to hit that steep part of the S-curve. And, and we're gonna dig into to more of that, but give us any, is there anything else that we should know about Bryan? Give us the last word? >>Well, I mean, I think first I'd like everybody sort of watching just to like take a look at what we're offering in terms of early access in beta programs. I mean, if, if, if you wanna participate or if you wanna work sort of in terms of early access with the, with the new engine, please reach out to the team. I'm sure you know, there's a lot of communications going out and you know, it'll be highly featured on our, our website, you know, but reach out to the team, believe it or not, like we have a lot more going on than just the new engine. And so there are also other programs, things we're, we're offering to customers in terms of the user interface, data collection and things like that. And, you know, if you're a customer of ours and you have a sales team, a commercial team that you work with, you can reach out to them and see what you can get access to because we can flip a lot of stuff on, especially in cloud through feature flags. >>But if there's something new that you wanna try out, we'd just love to hear from you. And then, you know, our goal would be that as we give you access to all of these new cool features that, you know, you would give us continuous feedback on these products and services, not only like what you need today, but then what you'll need tomorrow to, to sort of build the next versions of your business. Because you know, the whole database, the ecosystem as it expands out into to, you know, this vertically oriented stack of cloud services and enterprise databases and edge databases, you know, it's gonna be what we all make it together, not just, you know, those of us who were employed by Influx db. And then finally I would just say please, like watch in ICE in Tim's sessions, like these are two of our best and brightest, They're totally brilliant, completely pragmatic, and they are most of all customer obsessed, which is amazing. And there's no better takes, like honestly on the, the sort of technical details of this, then there's, especially when it comes to like the value that these investments will, will bring to our customers and our communities. So encourage you to, to, you know, pay more attention to them than you did to me, for sure. >>Brian Gilmore, great stuff. Really appreciate your time. Thank you. >>Yeah, thanks Dave. It was awesome. Look forward to it. >>Yeah, me too. Looking forward to see how the, the community actually applies these new innovations and goes, goes beyond just the historical into the real time really hot area. As Brian said in a moment, I'll be right back with Anna East dos Georgio to dig into the critical aspects of key open source components of the Influx DB engine, including Rust, Arrow, Parque, data fusion. Keep it right there. You don't wanna miss this >>Time series Data is everywhere. The number of sensors, systems and applications generating time series data increases every day. All these data sources producing so much data can cause analysis paralysis. Influx DB is an entire platform designed with everything you need to quickly build applications that generate value from time series data influx. DB Cloud is a serverless solution, which means you don't need to buy or manage your own servers. There's no need to worry about provisioning because you only pay for what you use. Influx DB Cloud is fully managed so you get the newest features and enhancements as they're added to the platform's code base. It also means you can spend time building solutions and delivering value to your users instead of wasting time and effort managing something else. Influx TVB Cloud offers a range of security features to protect your data, multiple layers of redundancy ensure you don't lose any data access controls ensure that only the people who should see your data can see it. >>And encryption protects your data at rest and in transit between any of our regions or cloud providers. InfluxDB uses a single API across the entire platform suite so you can build on open source, deploy to the cloud and then then easily query data in the cloud at the edge or on prem using the same scripts. And InfluxDB is schemaless automatically adjusting to changes in the shape of your data without requiring changes in your application. Logic. InfluxDB Cloud is production ready from day one. All it needs is your data and your imagination. Get started today@influxdata.com slash cloud. >>Okay, we're back. I'm Dave Valante with a Cube and you're watching evolving Influx DB into the smart data platform made possible by influx data. Anna ETOs Georgio is here, she's a developer advocate for influx data and we're gonna dig into the rationale and value contribution behind several open source technologies that Influx DB is leveraging to increase the granularity of time series analysis analysis and bring the world of data into real-time analytics and is welcome to the program. Thanks for coming on. >>Hi, thank you so much. It's a pleasure to be here. >>Oh, you're very welcome. Okay, so IX is being touted as this next gen open source core for Influx db. And my understanding is that it leverages in memory of course for speed. It's a kilo store, so it gives you a compression efficiency, it's gonna give you faster query speeds, you store files and object storage, so you got very cost effective approach. Are these the salient points on the platform? I know there are probably dozens of other features, but what are the high level value points that people should understand? >>Sure, that's a great question. So some of the main requirements that IOx is trying to achieve and some of the most impressive ones to me, the first one is that it aims to have no limits on cardinality and also allow you to write any kind of event data that you want, whether that's live tag or a field. It also wants to deliver the best in class performance on analytics queries. In addition to our already well served metrics queries, we also wanna have operator control over memory usage. So you should be able to define how much memory is used for buffering caching and query processing. Some other really important parts is the ability to have bulk data export and import super useful. Also broader ecosystem compatibility where possible we aim to use and embrace emerging standards in the data analytics ecosystem and have compatibility with things like sql, Python, and maybe even pandas in the future. >>Okay, so lot there. Now we talked to Brian about how you're using Rust and which is not a new programming language and of course we had some drama around Rust during the pandemic with the Mozilla layoffs, but the formation of the Rust Foundation really addressed any of those concerns. You got big guns like Amazon and Google and Microsoft throwing their collective weights behind it. It's really, the adoption is really starting to get steep on the S-curve. So lots of platforms, lots of adoption with rust, but why rust as an alternative to say c plus plus for example? >>Sure, that's a great question. So Russ was chosen because of his exceptional performance and reliability. So while Russ is synt tactically similar to c plus plus and it has similar performance, it also compiles to a native code like c plus plus. But unlike c plus plus, it also has much better memory safety. So memory safety is protection against bugs or security vulnerabilities that lead to excessive memory usage or memory leaks. And rust achieves this memory safety due to its like innovative type system. Additionally, it doesn't allow for dangling pointers. And dangling pointers are the main classes of errors that lead to exploitable security vulnerabilities in languages like c plus plus. So Russ like helps meet that requirement of having no limits on ality, for example, because it's, we're also using the Russ implementation of Apache Arrow and this control over memory and also Russ Russ's packaging system called crates IO offers everything that you need out of the box to have features like AY and a weight to fix race conditions, to protection against buffering overflows and to ensure thread safe async cashing structures as well. So essentially it's just like has all the control, all the fine grain control, you need to take advantage of memory and all your resources as well as possible so that you can handle those really, really high ity use cases. >>Yeah, and the more I learn about the, the new engine and, and the platform IOCs et cetera, you know, you, you see things like, you know, the old days not even to even today you do a lot of garbage collection in these, in these systems and there's an inverse, you know, impact relative to performance. So it looks like you really, you know, the community is modernizing the platform, but I wanna talk about Apache Arrow for a moment. It it's designed to address the constraints that are associated with analyzing large data sets. We, we know that, but please explain why, what, what is Arrow and and what does it bring to Influx db? >>Sure, yeah. So Arrow is a, a framework for defining in memory calmer data. And so much of the efficiency and performance of IOx comes from taking advantage of calmer data structures. And I will, if you don't mind, take a moment to kind of of illustrate why column or data structures are so valuable. Let's pretend that we are gathering field data about the temperature in our room and also maybe the temperature of our stove. And in our table we have those two temperature values as well as maybe a measurement value, timestamp value, maybe some other tag values that describe what room and what house, et cetera we're getting this data from. And so you can picture this table where we have like two rows with the two temperature values for both our room and the stove. Well usually our room temperature is regulated so those values don't change very often. >>So when you have calm oriented st calm oriented storage, essentially you take each row, each column and group it together. And so if that's the case and you're just taking temperature values from the room and a lot of those temperature values are the same, then you'll, you might be able to imagine how equal values will then enable each other and when they neighbor each other in the storage format, this provides a really perfect opportunity for cheap compression. And then this cheap compression enables high cardinality use cases. It also enables for faster scan rates. So if you wanna define like the men and max value of the temperature in the room across a thousand different points, you only have to get those a thousand different points in order to answer that question and you have those immediately available to you. But let's contrast this with a row oriented storage solution instead so that we can understand better the benefits of calmer oriented storage. >>So if you had a row oriented storage, you'd first have to look at every field like the temperature in, in the room and the temperature of the stove. You'd have to go across every tag value that maybe describes where the room is located or what model the stove is. And every timestamp you'd then have to pluck out that one temperature value that you want at that one time stamp and do that for every single row. So you're scanning across a ton more data and that's why Rowe Oriented doesn't provide the same efficiency as calmer and Apache Arrow is in memory calmer data, commoner data fit framework. So that's where a lot of the advantages come >>From. Okay. So you basically described like a traditional database, a row approach, but I've seen like a lot of traditional database say, okay, now we've got, we can handle colo format versus what you're talking about is really, you know, kind of native i, is it not as effective? Is the, is the foreman not as effective because it's largely a, a bolt on? Can you, can you like elucidate on that front? >>Yeah, it's, it's not as effective because you have more expensive compression and because you can't scan across the values as quickly. And so those are, that's pretty much the main reasons why, why RO row oriented storage isn't as efficient as calm, calmer oriented storage. Yeah. >>Got it. So let's talk about Arrow Data Fusion. What is data fusion? I know it's written in Rust, but what does it bring to the table here? >>Sure. So it's an extensible query execution framework and it uses Arrow as it's in memory format. So the way that it helps in influx DB IOCs is that okay, it's great if you can write unlimited amount of cardinality into influx Cbis, but if you don't have a query engine that can successfully query that data, then I don't know how much value it is for you. So Data fusion helps enable the, the query process and transformation of that data. It also has a PANDAS API so that you could take advantage of PANDAS data frames as well and all of the machine learning tools associated with Pandas. >>Okay. You're also leveraging Par K in the platform cause we heard a lot about Par K in the middle of the last decade cuz as a storage format to improve on Hadoop column stores. What are you doing with Parque and why is it important? >>Sure. So parque is the column oriented durable file format. So it's important because it'll enable bulk import, bulk export, it has compatibility with Python and Pandas, so it supports a broader ecosystem. Par K files also take very little disc disc space and they're faster to scan because again, they're column oriented in particular, I think PAR K files are like 16 times cheaper than CSV files, just as kind of a point of reference. And so that's essentially a lot of the, the benefits of par k. >>Got it. Very popular. So and he's, what exactly is influx data focusing on as a committer to these projects? What is your focus? What's the value that you're bringing to the community? >>Sure. So Influx DB first has contributed a lot of different, different things to the Apache ecosystem. For example, they contribute an implementation of Apache Arrow and go and that will support clearing with flux. Also, there has been a quite a few contributions to data fusion for things like memory optimization and supportive additional SQL features like support for timestamp, arithmetic and support for exist clauses and support for memory control. So yeah, Influx has contributed a a lot to the Apache ecosystem and continues to do so. And I think kind of the idea here is that if you can improve these upstream projects and then the long term strategy here is that the more you contribute and build those up, then the more you will perpetuate that cycle of improvement and the more we will invest in our own project as well. So it's just that kind of symbiotic relationship and appreciation of the open source community. >>Yeah. Got it. You got that virtuous cycle going, the people call the flywheel. Give us your last thoughts and kind of summarize, you know, where what, what the big takeaways are from your perspective. >>So I think the big takeaway is that influx data is doing a lot of really exciting things with Influx DB IOx and I really encourage, if you are interested in learning more about the technologies that Influx is leveraging to produce IOCs, the challenges associated with it and all of the hard work questions and you just wanna learn more, then I would encourage you to go to the monthly Tech talks and community office hours and they are on every second Wednesday of the month at 8:30 AM Pacific time. There's also a community forums and a community Slack channel look for the influx DDB unders IAC channel specifically to learn more about how to join those office hours and those monthly tech tech talks as well as ask any questions they have about iacs, what to expect and what you'd like to learn more about. I as a developer advocate, I wanna answer your questions. So if there's a particular technology or stack that you wanna dive deeper into and want more explanation about how INFLUX DB leverages it to build IOCs, I will be really excited to produce content on that topic for you. >>Yeah, that's awesome. You guys have a really rich community, collaborate with your peers, solve problems, and, and you guys super responsive, so really appreciate that. All right, thank you so much Anise for explaining all this open source stuff to the audience and why it's important to the future of data. >>Thank you. I really appreciate it. >>All right, you're very welcome. Okay, stay right there and in a moment I'll be back with Tim Yoakum, he's the director of engineering for Influx Data and we're gonna talk about how you update a SAS engine while the plane is flying at 30,000 feet. You don't wanna miss this. >>I'm really glad that we went with InfluxDB Cloud for our hosting because it has saved us a ton of time. It's helped us move faster, it's saved us money. And also InfluxDB has good support. My name's Alex Nada. I am CTO at Noble nine. Noble Nine is a platform to measure and manage service level objectives, which is a great way of measuring the reliability of your systems. You can essentially think of an slo, the product we're providing to our customers as a bunch of time series. So we need a way to store that data and the corresponding time series that are related to those. The main reason that we settled on InfluxDB as we were shopping around is that InfluxDB has a very flexible query language and as a general purpose time series database, it basically had the set of features we were looking for. >>As our platform has grown, we found InfluxDB Cloud to be a really scalable solution. We can quickly iterate on new features and functionality because Influx Cloud is entirely managed, it probably saved us at least a full additional person on our team. We also have the option of running InfluxDB Enterprise, which gives us the ability to even host off the cloud or in a private cloud if that's preferred by a customer. Influx data has been really flexible in adapting to the hosting requirements that we have. They listened to the challenges we were facing and they helped us solve it. As we've continued to grow, I'm really happy we have influx data by our side. >>Okay, we're back with Tim Yokum, who is the director of engineering at Influx Data. Tim, welcome. Good to see you. >>Good to see you. Thanks for having me. >>You're really welcome. Listen, we've been covering open source software in the cube for more than a decade, and we've kind of watched the innovation from the big data ecosystem. The cloud has been being built out on open source, mobile, social platforms, key databases, and of course influx DB and influx data has been a big consumer and contributor of open source software. So my question to you is, where have you seen the biggest bang for the buck from open source software? >>So yeah, you know, influx really, we thrive at the intersection of commercial services and open, so open source software. So OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service from our core storage engine technologies to web services temping engines. Our, our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants and like you've mentioned, even better, we contribute a lot back to the projects that we use as well as our own product influx db. >>You know, but I gotta ask you, Tim, because one of the challenge that that we've seen in particular, you saw this in the heyday of Hadoop, the, the innovations come so fast and furious and as a software company you gotta place bets, you gotta, you know, commit people and sometimes those bets can be risky and not pay off well, how have you managed this challenge? >>Oh, it moves fast. Yeah, that, that's a benefit though because it, the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we, what we tend to do is, is we fail fast and fail often. We try a lot of things. You know, you look at Kubernetes for example, that ecosystem is driven by thousands of intelligent developers, engineers, builders, they're adding value every day. So we have to really keep up with that. And as the stack changes, we, we try different technologies, we try different methods, and at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's, it's something that we just do every day. >>So we have a survey partner down in New York City called Enterprise Technology Research etr, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes is one of the areas that has kind of, it's been off the charts and seen the most significant adoption and velocity particularly, you know, along with cloud. But, but really Kubernetes is just, you know, still up until the right consistently even with, you know, the macro headwinds and all, all of the stuff that we're sick of talking about. But, so what are you doing with Kubernetes in the platform? >>Yeah, it, it's really central to our ability to run the product. When we first started out, we were just on AWS and, and the way we were running was, was a little bit like containers junior. Now we're running Kubernetes everywhere at aws, Azure, Google Cloud. It allows us to have a consistent experience across three different cloud providers and we can manage that in code so our developers can focus on delivering services, not trying to learn the intricacies of Amazon, Azure, and Google and figure out how to deliver services on those three clouds with all of their differences. >>Just to follow up on that, is it, no. So I presume it's sounds like there's a PAs layer there to allow you guys to have a consistent experience across clouds and out to the edge, you know, wherever is that, is that correct? >>Yeah, so we've basically built more or less platform engineering, This is the new hot phrase, you know, it, it's, Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on and they only have to learn one way of deploying their application, managing their application. And so that, that just gets all of the underlying infrastructure out of the way and, and lets them focus on delivering influx cloud. >>Yeah, and I know I'm taking a little bit of a tangent, but is that, that, I'll call it a PAs layer if I can use that term. Is that, are there specific attributes to Influx db or is it kind of just generally off the shelf paths? You know, are there, is, is there any purpose built capability there that, that is, is value add or is it pretty much generic? >>So we really build, we, we look at things through, with a build versus buy through a, a build versus by lens. Some things we want to leverage cloud provider services, for instance, Postgres databases for metadata, perhaps we'll get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can, can deliver on that has consistency that is, is all generated from code that we can as a, as an SRE group, as an ops team, that we can manage with very few people really, and we can stamp out clusters across multiple regions and in no time. >>So how, so sometimes you build, sometimes you buy it. How do you make those decisions and and what does that mean for the, for the platform and for customers? >>Yeah, so what we're doing is, it's like everybody else will do, we're we're looking for trade offs that make sense. You know, we really want to protect our customers data. So we look for services that support our own software with the most uptime, reliability, and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team. And of course for customers you don't even see that, but we don't want to try to reinvent the wheel, like I had mentioned with SQL data stores for metadata, perhaps let's build on top of what of these three large cloud providers have already perfected. And we can then focus on our platform engineering and we can have our developers then focus on the influx data, software, influx, cloud software. >>So take it to the customer level, what does it mean for them? What's the value that they're gonna get out of all these innovations that we've been been talking about today and what can they expect in the future? >>So first of all, people who use the OSS product are really gonna be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you, but then you want to scale up. We have some 270 terabytes of data across, over 4 billion series keys that people have stored. So there's a proven ability to scale now in terms of the open source, open source software and how we've developed the platform. You're getting highly available high cardinality time series platform. We manage it and, and really as, as I mentioned earlier, we can keep up with the state of the art. We keep reinventing, we keep deploying things in real time. We deploy to our platform every day repeatedly all the time. And it's that continuous deployment that allows us to continue testing things in flight, rolling things out that change new features, better ways of doing deployments, safer ways of doing deployments. >>All of that happens behind the scenes. And like we had mentioned earlier, Kubernetes, I mean that, that allows us to get that done. We couldn't do it without having that platform as a, as a base layer for us to then put our software on. So we, we iterate quickly. When you're on the, the Influx cloud platform, you really are able to, to take advantage of new features immediately. We roll things out every day and as those things go into production, you have, you have the ability to, to use them. And so in the end we want you to focus on getting actual insights from your data instead of running infrastructure, you know, let, let us do that for you. So, >>And that makes sense, but so is the, is the, are the innovations that we're talking about in the evolution of Influx db, do, do you see that as sort of a natural evolution for existing customers? I, is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >>Yeah, it really is it, it's a little bit of both. Any engineer will say, well, it depends. So cloud native technologies are, are really the hot thing. Iot, industrial iot especially, people want to just shove tons of data out there and be able to do queries immediately and they don't wanna manage infrastructure. What we've started to see are people that use the cloud service as their, their data store backbone and then they use edge computing with R OSS product to ingest data from say, multiple production lines and downsample that data, send the rest of that data off influx cloud where the heavy processing takes place. So really us being in all the different clouds and iterating on that and being in all sorts of different regions allows for people to really get out of the, the business of man trying to manage that big data, have us take care of that. And of course as we change the platform end users benefit from that immediately. And, >>And so obviously taking away a lot of the heavy lifting for the infrastructure, would you say the same thing about security, especially as you go out to IOT and the Edge? How should we be thinking about the value that you bring from a security perspective? >>Yeah, we take, we take security super seriously. It, it's built into our dna. We do a lot of work to ensure that our platform is secure, that the data we store is, is kept private. It's of course always a concern. You see in the news all the time, companies being compromised, you know, that's something that you can have an entire team working on, which we do to make sure that the data that you have, whether it's in transit, whether it's at rest, is always kept secure, is only viewable by you. You know, you look at things like software, bill of materials, if you're running this yourself, you have to go vet all sorts of different pieces of software. And we do that, you know, as we use new tools. That's something that, that's just part of our jobs to make sure that the platform that we're running it has, has fully vetted software and, and with open source especially, that's a lot of work. And so it's, it's definitely new territory. Supply chain attacks are, are definitely happening at a higher clip than they used to, but that is, that is really just part of a day in the, the life for folks like us that are, are building platforms. >>Yeah, and that's key. I mean especially when you start getting into the, the, you know, we talk about IOT and the operations technologies, the engineers running the, that infrastructure, you know, historically, as you know, Tim, they, they would air gap everything. That's how they kept it safe. But that's not feasible anymore. Everything's >>That >>Connected now, right? And so you've gotta have a partner that is again, take away that heavy lifting to r and d so you can focus on some of the other activities. Right. Give us the, the last word and the, the key takeaways from your perspective. >>Well, you know, from my perspective I see it as, as a a two lane approach with, with influx, with Anytime series data, you know, you've got a lot of stuff that you're gonna run on-prem, what you had mentioned, air gaping. Sure there's plenty of need for that, but at the end of the day, people that don't want to run big data centers, people that want torus their data to, to a company that's, that's got a full platform set up for them that they can build on, send that data over to the cloud, the cloud is not going away. I think more hybrid approach is, is where the future lives and that's what we're prepared for. >>Tim, really appreciate you coming to the program. Great stuff. Good to see you. >>Thanks very much. Appreciate it. >>Okay, in a moment I'll be back to wrap up. Today's session, you're watching The Cube. >>Are you looking for some help getting started with InfluxDB Telegraph or Flux Check >>Out Influx DB University >>Where you can find our entire catalog of free training that will help you make the most of your time series data >>Get >>Started for free@influxdbu.com. >>We'll see you in class. >>Okay, so we heard today from three experts on time series and data, how the Influx DB platform is evolving to support new ways of analyzing large data sets very efficiently and effectively in real time. And we learned that key open source components like Apache Arrow and the Rust Programming environment Data fusion par K are being leveraged to support realtime data analytics at scale. We also learned about the contributions in importance of open source software and how the Influx DB community is evolving the platform with minimal disruption to support new workloads, new use cases, and the future of realtime data analytics. Now remember these sessions, they're all available on demand. You can go to the cube.net to find those. Don't forget to check out silicon angle.com for all the news related to things enterprise and emerging tech. And you should also check out influx data.com. There you can learn about the company's products. You'll find developer resources like free courses. You could join the developer community and work with your peers to learn and solve problems. And there are plenty of other resources around use cases and customer stories on the website. This is Dave Valante. Thank you for watching Evolving Influx DB into the smart data platform, made possible by influx data and brought to you by the Cube, your leader in enterprise and emerging tech coverage.

>>This past May, The Cube in collaboration with Influx data shared with you the latest innovations in Time series databases. We talked at length about why a purpose built time series database for many use cases, was a superior alternative to general purpose databases trying to do the same thing. Now, you may, you may remember the time series data is any data that's stamped in time, and if it's stamped, it can be analyzed historically. And when we introduced the concept to the community, we talked about how in theory, those time slices could be taken, you know, every hour, every minute, every second, you know, down to the millisecond and how the world was moving toward realtime or near realtime data analysis to support physical infrastructure like sensors and other devices and IOT equipment. A time series databases have had to evolve to efficiently support realtime data in emerging use cases in iot T and other use cases. >>And to do that, new architectural innovations have to be brought to bear. As is often the case, open source software is the linchpin to those innovations. Hello and welcome to Evolving Influx DB into the smart Data platform, made possible by influx data and produced by the Cube. My name is Dave Valante and I'll be your host today. Now in this program we're going to dig pretty deep into what's happening with Time series data generally, and specifically how Influx DB is evolving to support new workloads and demands and data, and specifically around data analytics use cases in real time. Now, first we're gonna hear from Brian Gilmore, who is the director of IOT and emerging technologies at Influx Data. And we're gonna talk about the continued evolution of Influx DB and the new capabilities enabled by open source generally and specific tools. And in this program you're gonna hear a lot about things like Rust, implementation of Apache Arrow, the use of par k and tooling such as data fusion, which powering a new engine for Influx db. >>Now, these innovations, they evolve the idea of time series analysis by dramatically increasing the granularity of time series data by compressing the historical time slices, if you will, from, for example, minutes down to milliseconds. And at the same time, enabling real time analytics with an architecture that can process data much faster and much more efficiently. Now, after Brian, we're gonna hear from Anna East Dos Georgio, who is a developer advocate at In Flux Data. And we're gonna get into the why of these open source capabilities and how they contribute to the evolution of the Influx DB platform. And then we're gonna close the program with Tim Yokum, he's the director of engineering at Influx Data, and he's gonna explain how the Influx DB community actually evolved the data engine in mid-flight and which decisions went into the innovations that are coming to the market. Thank you for being here. We hope you enjoy the program. Let's get started. Okay, we're kicking things off with Brian Gilmore. He's the director of i t and emerging Technology at Influx State of Bryan. Welcome to the program. Thanks for coming on. >>Thanks Dave. Great to be here. I appreciate the time. >>Hey, explain why Influx db, you know, needs a new engine. Was there something wrong with the current engine? What's going on there? >>No, no, not at all. I mean, I think it's, for us, it's been about staying ahead of the market. I think, you know, if we think about what our customers are coming to us sort of with now, you know, related to requests like sql, you know, query support, things like that, we have to figure out a way to, to execute those for them in a way that will scale long term. And then we also, we wanna make sure we're innovating, we're sort of staying ahead of the market as well and sort of anticipating those future needs. So, you know, this is really a, a transparent change for our customers. I mean, I think we'll be adding new capabilities over time that sort of leverage this new engine, but you know, initially the customers who are using us are gonna see just great improvements in performance, you know, especially those that are working at the top end of the, of the workload scale, you know, the massive data volumes and things like that. >>Yeah, and we're gonna get into that today and the architecture and the like, but what was the catalyst for the enhancements? I mean, when and how did this all come about? >>Well, I mean, like three years ago we were primarily on premises, right? I mean, I think we had our open source, we had an enterprise product, you know, and, and sort of shifting that technology, especially the open source code base to a service basis where we were hosting it through, you know, multiple cloud providers. That was, that was, that was a long journey I guess, you know, phase one was, you know, we wanted to host enterprise for our customers, so we sort of created a service that we just managed and ran our enterprise product for them. You know, phase two of this cloud effort was to, to optimize for like multi-tenant, multi-cloud, be able to, to host it in a truly like sass manner where we could use, you know, some type of customer activity or consumption as the, the pricing vector, you know, And, and that was sort of the birth of the, of the real first influx DB cloud, you know, which has been really successful. >>We've seen, I think like 60,000 people sign up and we've got tons and tons of, of both enterprises as well as like new companies, developers, and of course a lot of home hobbyists and enthusiasts who are using out on a, on a daily basis, you know, and having that sort of big pool of, of very diverse and very customers to chat with as they're using the product, as they're giving us feedback, et cetera, has has, you know, pointed us in a really good direction in terms of making sure we're continuously improving that and then also making these big leaps as we're doing with this, with this new engine. >>Right. So you've called it a transparent change for customers, so I'm presuming it's non-disruptive, but I really wanna understand how much of a pivot this is and what, what does it take to make that shift from, you know, time series, you know, specialist to real time analytics and being able to support both? >>Yeah, I mean, it's much more of an evolution, I think, than like a shift or a pivot. You know, time series data is always gonna be fundamental and sort of the basis of the solutions that we offer our customers, and then also the ones that they're building on the sort of raw APIs of our platform themselves. You know, the time series market is one that we've worked diligently to lead. I mean, I think when it comes to like metrics, especially like sensor data and app and infrastructure metrics, if we're being honest though, I think our, our user base is well aware that the way we were architected was much more towards those sort of like backwards looking historical type analytics, which are key for troubleshooting and making sure you don't, you know, run into the same problem twice. But, you know, we had to ask ourselves like, what can we do to like better handle those queries from a performance and a, and a, you know, a time to response on the queries, and can we get that to the point where the results sets are coming back so quickly from the time of query that we can like limit that window down to minutes and then seconds. >>And now with this new engine, we're really starting to talk about a query window that could be like returning results in, in, you know, milliseconds of time since it hit the, the, the ingest queue. And that's, that's really getting to the point where as your data is available, you can use it and you can query it, you can visualize it, and you can do all those sort of magical things with it, you know? And I think getting all of that to a place where we're saying like, yes to the customer on, you know, all of the, the real time queries, the, the multiple language query support, but, you know, it was hard, but we're now at a spot where we can start introducing that to, you know, a a limited number of customers, strategic customers and strategic availability zones to start. But you know, everybody over time. >>So you're basically going from what happened to in, you can still do that obviously, but to what's happening now in the moment? >>Yeah, yeah. I mean if you think about time, it's always sort of past, right? I mean, like in the moment right now, whether you're talking about like a millisecond ago or a minute ago, you know, that's, that's pretty much right now, I think for most people, especially in these use cases where you have other sort of components of latency induced by the, by the underlying data collection, the architecture, the infrastructure, the, you know, the, the devices and you know, the sort of highly distributed nature of all of this. So yeah, I mean, getting, getting a customer or a user to be able to use the data as soon as it is available is what we're after here. >>I always thought, you know, real, I always thought of real time as before you lose the customer, but now in this context, maybe it's before the machine blows up. >>Yeah, it's, it's, I mean it is operationally or operational real time is different, you know, and that's one of the things that really triggered us to know that we were, we were heading in the right direction, is just how many sort of operational customers we have. You know, everything from like aerospace and defense. We've got companies monitoring satellites, we've got tons of industrial users, users using us as a processes storing on the plant floor, you know, and, and if we can satisfy their sort of demands for like real time historical perspective, that's awesome. I think what we're gonna do here is we're gonna start to like edge into the real time that they're used to in terms of, you know, the millisecond response times that they expect of their control systems, certainly not their, their historians and databases. >>I, is this available, these innovations to influx DB cloud customers only who can access this capability? >>Yeah. I mean commercially and today, yes. You know, I think we want to emphasize that's a, for now our goal is to get our latest and greatest and our best to everybody over time. Of course. You know, one of the things we had to do here was like we double down on sort of our, our commitment to open source and availability. So like anybody today can take a look at the, the libraries in on our GitHub and, you know, can ex inspect it and even can try to, you know, implement or execute some of it themselves in their own infrastructure. You know, we are, we're committed to bringing our sort of latest and greatest to our cloud customers first for a couple of reasons. Number one, you know, there are big workloads and they have high expectations of us. I think number two, it also gives us the opportunity to monitor a little bit more closely how it's working, how they're using it, like how the system itself is performing. >>And so just, you know, being careful, maybe a little cautious in terms of, of, of how big we go with this right away, just sort of both limits, you know, the risk of, of, you know, any issues that can come with new software rollouts. We haven't seen anything so far, but also it does give us the opportunity to have like meaningful conversations with a small group of users who are using the products, but once we get through that and they give us two thumbs up on it, it'll be like, open the gates and let everybody in. It's gonna be exciting time for the whole ecosystem. >>Yeah, that makes a lot of sense. And you can do some experimentation and, you know, using the cloud resources. Let's dig into some of the architectural and technical innovations that are gonna help deliver on this vision. What, what should we know there? >>Well, I mean, I think foundationally we built the, the new core on Rust. You know, this is a new very sort of popular systems language, you know, it's extremely efficient, but it's also built for speed and memory safety, which goes back to that us being able to like deliver it in a way that is, you know, something we can inspect very closely, but then also rely on the fact that it's going to behave well. And if it does find error conditions, I mean we, we've loved working with Go and, you know, a lot of our libraries will continue to, to be sort of implemented in Go, but you know, when it came to this particular new engine, you know, that power performance and stability rust was critical. On top of that, like, we've also integrated Apache Arrow and Apache Parque for persistence. I think for anybody who's really familiar with the nuts and bolts of our backend and our TSI and our, our time series merged Trees, this is a big break from that, you know, arrow on the sort of in MI side and then Par K in the on disk side. >>It, it allows us to, to present, you know, a unified set of APIs for those really fast real time inquiries that we talked about, as well as for very large, you know, historical sort of bulk data archives in that PARQUE format, which is also cool because there's an entire ecosystem sort of popping up around Parque in terms of the machine learning community, you know, and getting that all to work, we had to glue it together with aero flight. That's sort of what we're using as our, our RPC component. You know, it handles the orchestration and the, the transportation of the Coer data. Now we're moving to like a true Coer database model for this, this version of the engine, you know, and it removes a lot of overhead for us in terms of having to manage all that serialization, the deserialization, and, you know, to that again, like blurring that line between real time and historical data. It's, you know, it's, it's highly optimized for both streaming micro batch and then batches, but true streaming as well. >>Yeah. Again, I mean, it's funny you mentioned Rust. It is, it's been around for a long time, but it's popularity is, is you know, really starting to hit that steep part of the S-curve. And, and we're gonna dig into to more of that, but give us any, is there anything else that we should know about Bryan? Give us the last word? >>Well, I mean, I think first I'd like everybody sort of watching just to like take a look at what we're offering in terms of early access in beta programs. I mean, if, if, if you wanna participate or if you wanna work sort of in terms of early access with the, with the new engine, please reach out to the team. I'm sure you know, there's a lot of communications going out and you know, it'll be highly featured on our, our website, you know, but reach out to the team, believe it or not, like we have a lot more going on than just the new engine. And so there are also other programs, things we're, we're offering to customers in terms of the user interface, data collection and things like that. And, you know, if you're a customer of ours and you have a sales team, a commercial team that you work with, you can reach out to them and see what you can get access to because we can flip a lot of stuff on, especially in cloud through feature flags. >>But if there's something new that you wanna try out, we'd just love to hear from you. And then, you know, our goal would be that as we give you access to all of these new cool features that, you know, you would give us continuous feedback on these products and services, not only like what you need today, but then what you'll need tomorrow to, to sort of build the next versions of your business. Because you know, the whole database, the ecosystem as it expands out into to, you know, this vertically oriented stack of cloud services and enterprise databases and edge databases, you know, it's gonna be what we all make it together, not just, you know, those of us who were employed by Influx db. And then finally I would just say please, like watch in ICE in Tim's sessions, like these are two of our best and brightest, They're totally brilliant, completely pragmatic, and they are most of all customer obsessed, which is amazing. And there's no better takes, like honestly on the, the sort of technical details of this, then there's, especially when it comes to like the value that these investments will, will bring to our customers and our communities. So encourage you to, to, you know, pay more attention to them than you did to me, for sure. >>Brian Gilmore, great stuff. Really appreciate your time. Thank you. >>Yeah, thanks Dave. It was awesome. Look forward to it. >>Yeah, me too. Looking forward to see how the, the community actually applies these new innovations and goes, goes beyond just the historical into the real time really hot area. As Brian said in a moment, I'll be right back with Anna East dos Georgio to dig into the critical aspects of key open source components of the Influx DB engine, including Rust, Arrow, Parque, data fusion. Keep it right there. You don't wanna miss this >>Time series Data is everywhere. The number of sensors, systems and applications generating time series data increases every day. All these data sources producing so much data can cause analysis paralysis. Influx DB is an entire platform designed with everything you need to quickly build applications that generate value from time series data influx. DB Cloud is a serverless solution, which means you don't need to buy or manage your own servers. There's no need to worry about provisioning because you only pay for what you use. Influx DB Cloud is fully managed so you get the newest features and enhancements as they're added to the platform's code base. It also means you can spend time building solutions and delivering value to your users instead of wasting time and effort managing something else. Influx TVB Cloud offers a range of security features to protect your data, multiple layers of redundancy ensure you don't lose any data access controls ensure that only the people who should see your data can see it. >>And encryption protects your data at rest and in transit between any of our regions or cloud providers. InfluxDB uses a single API across the entire platform suite so you can build on open source, deploy to the cloud and then then easily query data in the cloud at the edge or on prem using the same scripts. And InfluxDB is schemaless automatically adjusting to changes in the shape of your data without requiring changes in your application. Logic. InfluxDB Cloud is production ready from day one. All it needs is your data and your imagination. Get started today@influxdata.com slash cloud. >>Okay, we're back. I'm Dave Valante with a Cube and you're watching evolving Influx DB into the smart data platform made possible by influx data. Anna ETOs Georgio is here, she's a developer advocate for influx data and we're gonna dig into the rationale and value contribution behind several open source technologies that Influx DB is leveraging to increase the granularity of time series analysis analysis and bring the world of data into real-time analytics and is welcome to the program. Thanks for coming on. >>Hi, thank you so much. It's a pleasure to be here. >>Oh, you're very welcome. Okay, so IX is being touted as this next gen open source core for Influx db. And my understanding is that it leverages in memory of course for speed. It's a kilo store, so it gives you a compression efficiency, it's gonna give you faster query speeds, you store files and object storage, so you got very cost effective approach. Are these the salient points on the platform? I know there are probably dozens of other features, but what are the high level value points that people should understand? >>Sure, that's a great question. So some of the main requirements that IOx is trying to achieve and some of the most impressive ones to me, the first one is that it aims to have no limits on cardinality and also allow you to write any kind of event data that you want, whether that's live tag or a field. It also wants to deliver the best in class performance on analytics queries. In addition to our already well served metrics queries, we also wanna have operator control over memory usage. So you should be able to define how much memory is used for buffering caching and query processing. Some other really important parts is the ability to have bulk data export and import super useful. Also broader ecosystem compatibility where possible we aim to use and embrace emerging standards in the data analytics ecosystem and have compatibility with things like sql, Python, and maybe even pandas in the future. >>Okay, so lot there. Now we talked to Brian about how you're using Rust and which is not a new programming language and of course we had some drama around Rust during the pandemic with the Mozilla layoffs, but the formation of the Rust Foundation really addressed any of those concerns. You got big guns like Amazon and Google and Microsoft throwing their collective weights behind it. It's really, the adoption is really starting to get steep on the S-curve. So lots of platforms, lots of adoption with rust, but why rust as an alternative to say c plus plus for example? >>Sure, that's a great question. So Russ was chosen because of his exceptional performance and reliability. So while Russ is synt tactically similar to c plus plus and it has similar performance, it also compiles to a native code like c plus plus. But unlike c plus plus, it also has much better memory safety. So memory safety is protection against bugs or security vulnerabilities that lead to excessive memory usage or memory leaks. And rust achieves this memory safety due to its like innovative type system. Additionally, it doesn't allow for dangling pointers. And dangling pointers are the main classes of errors that lead to exploitable security vulnerabilities in languages like c plus plus. So Russ like helps meet that requirement of having no limits on ality, for example, because it's, we're also using the Russ implementation of Apache Arrow and this control over memory and also Russ Russ's packaging system called crates IO offers everything that you need out of the box to have features like AY and a weight to fix race conditions, to protection against buffering overflows and to ensure thread safe async cashing structures as well. So essentially it's just like has all the control, all the fine grain control, you need to take advantage of memory and all your resources as well as possible so that you can handle those really, really high ity use cases. >>Yeah, and the more I learn about the, the new engine and, and the platform IOCs et cetera, you know, you, you see things like, you know, the old days not even to even today you do a lot of garbage collection in these, in these systems and there's an inverse, you know, impact relative to performance. So it looks like you really, you know, the community is modernizing the platform, but I wanna talk about Apache Arrow for a moment. It it's designed to address the constraints that are associated with analyzing large data sets. We, we know that, but please explain why, what, what is Arrow and and what does it bring to Influx db? >>Sure, yeah. So Arrow is a, a framework for defining in memory calmer data. And so much of the efficiency and performance of IOx comes from taking advantage of calmer data structures. And I will, if you don't mind, take a moment to kind of of illustrate why column or data structures are so valuable. Let's pretend that we are gathering field data about the temperature in our room and also maybe the temperature of our stove. And in our table we have those two temperature values as well as maybe a measurement value, timestamp value, maybe some other tag values that describe what room and what house, et cetera we're getting this data from. And so you can picture this table where we have like two rows with the two temperature values for both our room and the stove. Well usually our room temperature is regulated so those values don't change very often. >>So when you have calm oriented st calm oriented storage, essentially you take each row, each column and group it together. And so if that's the case and you're just taking temperature values from the room and a lot of those temperature values are the same, then you'll, you might be able to imagine how equal values will then enable each other and when they neighbor each other in the storage format, this provides a really perfect opportunity for cheap compression. And then this cheap compression enables high cardinality use cases. It also enables for faster scan rates. So if you wanna define like the men and max value of the temperature in the room across a thousand different points, you only have to get those a thousand different points in order to answer that question and you have those immediately available to you. But let's contrast this with a row oriented storage solution instead so that we can understand better the benefits of calmer oriented storage. >>So if you had a row oriented storage, you'd first have to look at every field like the temperature in, in the room and the temperature of the stove. You'd have to go across every tag value that maybe describes where the room is located or what model the stove is. And every timestamp you'd then have to pluck out that one temperature value that you want at that one time stamp and do that for every single row. So you're scanning across a ton more data and that's why Rowe Oriented doesn't provide the same efficiency as calmer and Apache Arrow is in memory calmer data, commoner data fit framework. So that's where a lot of the advantages come >>From. Okay. So you basically described like a traditional database, a row approach, but I've seen like a lot of traditional database say, okay, now we've got, we can handle colo format versus what you're talking about is really, you know, kind of native i, is it not as effective? Is the, is the foreman not as effective because it's largely a, a bolt on? Can you, can you like elucidate on that front? >>Yeah, it's, it's not as effective because you have more expensive compression and because you can't scan across the values as quickly. And so those are, that's pretty much the main reasons why, why RO row oriented storage isn't as efficient as calm, calmer oriented storage. Yeah. >>Got it. So let's talk about Arrow Data Fusion. What is data fusion? I know it's written in Rust, but what does it bring to the table here? >>Sure. So it's an extensible query execution framework and it uses Arrow as it's in memory format. So the way that it helps in influx DB IOCs is that okay, it's great if you can write unlimited amount of cardinality into influx Cbis, but if you don't have a query engine that can successfully query that data, then I don't know how much value it is for you. So Data fusion helps enable the, the query process and transformation of that data. It also has a PANDAS API so that you could take advantage of PANDAS data frames as well and all of the machine learning tools associated with Pandas. >>Okay. You're also leveraging Par K in the platform cause we heard a lot about Par K in the middle of the last decade cuz as a storage format to improve on Hadoop column stores. What are you doing with Parque and why is it important? >>Sure. So parque is the column oriented durable file format. So it's important because it'll enable bulk import, bulk export, it has compatibility with Python and Pandas, so it supports a broader ecosystem. Par K files also take very little disc disc space and they're faster to scan because again, they're column oriented in particular, I think PAR K files are like 16 times cheaper than CSV files, just as kind of a point of reference. And so that's essentially a lot of the, the benefits of par k. >>Got it. Very popular. So and he's, what exactly is influx data focusing on as a committer to these projects? What is your focus? What's the value that you're bringing to the community? >>Sure. So Influx DB first has contributed a lot of different, different things to the Apache ecosystem. For example, they contribute an implementation of Apache Arrow and go and that will support clearing with flux. Also, there has been a quite a few contributions to data fusion for things like memory optimization and supportive additional SQL features like support for timestamp, arithmetic and support for exist clauses and support for memory control. So yeah, Influx has contributed a a lot to the Apache ecosystem and continues to do so. And I think kind of the idea here is that if you can improve these upstream projects and then the long term strategy here is that the more you contribute and build those up, then the more you will perpetuate that cycle of improvement and the more we will invest in our own project as well. So it's just that kind of symbiotic relationship and appreciation of the open source community. >>Yeah. Got it. You got that virtuous cycle going, the people call the flywheel. Give us your last thoughts and kind of summarize, you know, where what, what the big takeaways are from your perspective. >>So I think the big takeaway is that influx data is doing a lot of really exciting things with Influx DB IOx and I really encourage, if you are interested in learning more about the technologies that Influx is leveraging to produce IOCs, the challenges associated with it and all of the hard work questions and you just wanna learn more, then I would encourage you to go to the monthly Tech talks and community office hours and they are on every second Wednesday of the month at 8:30 AM Pacific time. There's also a community forums and a community Slack channel look for the influx DDB unders IAC channel specifically to learn more about how to join those office hours and those monthly tech tech talks as well as ask any questions they have about iacs, what to expect and what you'd like to learn more about. I as a developer advocate, I wanna answer your questions. So if there's a particular technology or stack that you wanna dive deeper into and want more explanation about how INFLUX DB leverages it to build IOCs, I will be really excited to produce content on that topic for you. >>Yeah, that's awesome. You guys have a really rich community, collaborate with your peers, solve problems, and, and you guys super responsive, so really appreciate that. All right, thank you so much Anise for explaining all this open source stuff to the audience and why it's important to the future of data. >>Thank you. I really appreciate it. >>All right, you're very welcome. Okay, stay right there and in a moment I'll be back with Tim Yoakum, he's the director of engineering for Influx Data and we're gonna talk about how you update a SAS engine while the plane is flying at 30,000 feet. You don't wanna miss this. >>I'm really glad that we went with InfluxDB Cloud for our hosting because it has saved us a ton of time. It's helped us move faster, it's saved us money. And also InfluxDB has good support. My name's Alex Nada. I am CTO at Noble nine. Noble Nine is a platform to measure and manage service level objectives, which is a great way of measuring the reliability of your systems. You can essentially think of an slo, the product we're providing to our customers as a bunch of time series. So we need a way to store that data and the corresponding time series that are related to those. The main reason that we settled on InfluxDB as we were shopping around is that InfluxDB has a very flexible query language and as a general purpose time series database, it basically had the set of features we were looking for. >>As our platform has grown, we found InfluxDB Cloud to be a really scalable solution. We can quickly iterate on new features and functionality because Influx Cloud is entirely managed, it probably saved us at least a full additional person on our team. We also have the option of running InfluxDB Enterprise, which gives us the ability to even host off the cloud or in a private cloud if that's preferred by a customer. Influx data has been really flexible in adapting to the hosting requirements that we have. They listened to the challenges we were facing and they helped us solve it. As we've continued to grow, I'm really happy we have influx data by our side. >>Okay, we're back with Tim Yokum, who is the director of engineering at Influx Data. Tim, welcome. Good to see you. >>Good to see you. Thanks for having me. >>You're really welcome. Listen, we've been covering open source software in the cube for more than a decade, and we've kind of watched the innovation from the big data ecosystem. The cloud has been being built out on open source, mobile, social platforms, key databases, and of course influx DB and influx data has been a big consumer and contributor of open source software. So my question to you is, where have you seen the biggest bang for the buck from open source software? >>So yeah, you know, influx really, we thrive at the intersection of commercial services and open, so open source software. So OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service from our core storage engine technologies to web services temping engines. Our, our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants and like you've mentioned, even better, we contribute a lot back to the projects that we use as well as our own product influx db. >>You know, but I gotta ask you, Tim, because one of the challenge that that we've seen in particular, you saw this in the heyday of Hadoop, the, the innovations come so fast and furious and as a software company you gotta place bets, you gotta, you know, commit people and sometimes those bets can be risky and not pay off well, how have you managed this challenge? >>Oh, it moves fast. Yeah, that, that's a benefit though because it, the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we, what we tend to do is, is we fail fast and fail often. We try a lot of things. You know, you look at Kubernetes for example, that ecosystem is driven by thousands of intelligent developers, engineers, builders, they're adding value every day. So we have to really keep up with that. And as the stack changes, we, we try different technologies, we try different methods, and at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's, it's something that we just do every day. >>So we have a survey partner down in New York City called Enterprise Technology Research etr, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes is one of the areas that has kind of, it's been off the charts and seen the most significant adoption and velocity particularly, you know, along with cloud. But, but really Kubernetes is just, you know, still up until the right consistently even with, you know, the macro headwinds and all, all of the stuff that we're sick of talking about. But, so what are you doing with Kubernetes in the platform? >>Yeah, it, it's really central to our ability to run the product. When we first started out, we were just on AWS and, and the way we were running was, was a little bit like containers junior. Now we're running Kubernetes everywhere at aws, Azure, Google Cloud. It allows us to have a consistent experience across three different cloud providers and we can manage that in code so our developers can focus on delivering services, not trying to learn the intricacies of Amazon, Azure, and Google and figure out how to deliver services on those three clouds with all of their differences. >>Just to follow up on that, is it, no. So I presume it's sounds like there's a PAs layer there to allow you guys to have a consistent experience across clouds and out to the edge, you know, wherever is that, is that correct? >>Yeah, so we've basically built more or less platform engineering, This is the new hot phrase, you know, it, it's, Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on and they only have to learn one way of deploying their application, managing their application. And so that, that just gets all of the underlying infrastructure out of the way and, and lets them focus on delivering influx cloud. >>Yeah, and I know I'm taking a little bit of a tangent, but is that, that, I'll call it a PAs layer if I can use that term. Is that, are there specific attributes to Influx db or is it kind of just generally off the shelf paths? You know, are there, is, is there any purpose built capability there that, that is, is value add or is it pretty much generic? >>So we really build, we, we look at things through, with a build versus buy through a, a build versus by lens. Some things we want to leverage cloud provider services, for instance, Postgres databases for metadata, perhaps we'll get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can, can deliver on that has consistency that is, is all generated from code that we can as a, as an SRE group, as an ops team, that we can manage with very few people really, and we can stamp out clusters across multiple regions and in no time. >>So how, so sometimes you build, sometimes you buy it. How do you make those decisions and and what does that mean for the, for the platform and for customers? >>Yeah, so what we're doing is, it's like everybody else will do, we're we're looking for trade offs that make sense. You know, we really want to protect our customers data. So we look for services that support our own software with the most uptime, reliability, and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team. And of course for customers you don't even see that, but we don't want to try to reinvent the wheel, like I had mentioned with SQL data stores for metadata, perhaps let's build on top of what of these three large cloud providers have already perfected. And we can then focus on our platform engineering and we can have our developers then focus on the influx data, software, influx, cloud software. >>So take it to the customer level, what does it mean for them? What's the value that they're gonna get out of all these innovations that we've been been talking about today and what can they expect in the future? >>So first of all, people who use the OSS product are really gonna be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you, but then you want to scale up. We have some 270 terabytes of data across, over 4 billion series keys that people have stored. So there's a proven ability to scale now in terms of the open source, open source software and how we've developed the platform. You're getting highly available high cardinality time series platform. We manage it and, and really as, as I mentioned earlier, we can keep up with the state of the art. We keep reinventing, we keep deploying things in real time. We deploy to our platform every day repeatedly all the time. And it's that continuous deployment that allows us to continue testing things in flight, rolling things out that change new features, better ways of doing deployments, safer ways of doing deployments. >>All of that happens behind the scenes. And like we had mentioned earlier, Kubernetes, I mean that, that allows us to get that done. We couldn't do it without having that platform as a, as a base layer for us to then put our software on. So we, we iterate quickly. When you're on the, the Influx cloud platform, you really are able to, to take advantage of new features immediately. We roll things out every day and as those things go into production, you have, you have the ability to, to use them. And so in the end we want you to focus on getting actual insights from your data instead of running infrastructure, you know, let, let us do that for you. So, >>And that makes sense, but so is the, is the, are the innovations that we're talking about in the evolution of Influx db, do, do you see that as sort of a natural evolution for existing customers? I, is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >>Yeah, it really is it, it's a little bit of both. Any engineer will say, well, it depends. So cloud native technologies are, are really the hot thing. Iot, industrial iot especially, people want to just shove tons of data out there and be able to do queries immediately and they don't wanna manage infrastructure. What we've started to see are people that use the cloud service as their, their data store backbone and then they use edge computing with R OSS product to ingest data from say, multiple production lines and downsample that data, send the rest of that data off influx cloud where the heavy processing takes place. So really us being in all the different clouds and iterating on that and being in all sorts of different regions allows for people to really get out of the, the business of man trying to manage that big data, have us take care of that. And of course as we change the platform end users benefit from that immediately. And, >>And so obviously taking away a lot of the heavy lifting for the infrastructure, would you say the same thing about security, especially as you go out to IOT and the Edge? How should we be thinking about the value that you bring from a security perspective? >>Yeah, we take, we take security super seriously. It, it's built into our dna. We do a lot of work to ensure that our platform is secure, that the data we store is, is kept private. It's of course always a concern. You see in the news all the time, companies being compromised, you know, that's something that you can have an entire team working on, which we do to make sure that the data that you have, whether it's in transit, whether it's at rest, is always kept secure, is only viewable by you. You know, you look at things like software, bill of materials, if you're running this yourself, you have to go vet all sorts of different pieces of software. And we do that, you know, as we use new tools. That's something that, that's just part of our jobs to make sure that the platform that we're running it has, has fully vetted software and, and with open source especially, that's a lot of work. And so it's, it's definitely new territory. Supply chain attacks are, are definitely happening at a higher clip than they used to, but that is, that is really just part of a day in the, the life for folks like us that are, are building platforms. >>Yeah, and that's key. I mean especially when you start getting into the, the, you know, we talk about IOT and the operations technologies, the engineers running the, that infrastructure, you know, historically, as you know, Tim, they, they would air gap everything. That's how they kept it safe. But that's not feasible anymore. Everything's >>That >>Connected now, right? And so you've gotta have a partner that is again, take away that heavy lifting to r and d so you can focus on some of the other activities. Right. Give us the, the last word and the, the key takeaways from your perspective. >>Well, you know, from my perspective I see it as, as a a two lane approach with, with influx, with Anytime series data, you know, you've got a lot of stuff that you're gonna run on-prem, what you had mentioned, air gaping. Sure there's plenty of need for that, but at the end of the day, people that don't want to run big data centers, people that want torus their data to, to a company that's, that's got a full platform set up for them that they can build on, send that data over to the cloud, the cloud is not going away. I think more hybrid approach is, is where the future lives and that's what we're prepared for. >>Tim, really appreciate you coming to the program. Great stuff. Good to see you. >>Thanks very much. Appreciate it. >>Okay, in a moment I'll be back to wrap up. Today's session, you're watching The Cube. >>Are you looking for some help getting started with InfluxDB Telegraph or Flux Check >>Out Influx DB University >>Where you can find our entire catalog of free training that will help you make the most of your time series data >>Get >>Started for free@influxdbu.com. >>We'll see you in class. >>Okay, so we heard today from three experts on time series and data, how the Influx DB platform is evolving to support new ways of analyzing large data sets very efficiently and effectively in real time. And we learned that key open source components like Apache Arrow and the Rust Programming environment Data fusion par K are being leveraged to support realtime data analytics at scale. We also learned about the contributions in importance of open source software and how the Influx DB community is evolving the platform with minimal disruption to support new workloads, new use cases, and the future of realtime data analytics. Now remember these sessions, they're all available on demand. You can go to the cube.net to find those. Don't forget to check out silicon angle.com for all the news related to things enterprise and emerging tech. And you should also check out influx data.com. There you can learn about the company's products. You'll find developer resources like free courses. You could join the developer community and work with your peers to learn and solve problems. And there are plenty of other resources around use cases and customer stories on the website. This is Dave Valante. Thank you for watching Evolving Influx DB into the smart data platform, made possible by influx data and brought to you by the Cube, your leader in enterprise and emerging tech coverage.

(upbeat intro music) >> Good afternoon, fellow tech nerds. My name is Savannah Peterson, coming to you from theCube's Remote Studio here in Motown, Detroit, Michigan where we are at KubeCon. John, this is our 12th interview of the day. How are you feeling? >> I'm feeling fresh as the first interview. (Savannah laughs) As always. >> That delivery really implied a level of freshness. >> Let's go! No, this is only Day 1. In three days, reinvent. We go hardcore. These are great events. We get so much great content. The conversations are amazing. The guests are awesome. They're technical, they're smart, and they're making the difference in the future. So, this next segment about Scale MySQL should be awesome. >> I am very excited to introduce our next guest who actually has a Twitter handle that I think most people, at least of my gender in this industry would love to have. She is @ATechGirl. So you can go ahead and tweet her and tell her how great this interview is while we're live. Please welcome Deepthi Sigireddi. Thank you so much for being here with us. >> Thank you for having me. >> You're feeding us in. You've got two talks you're giving while we're here. >> Yes, yes. So tomorrow we will be talking about VTR, myself and one of the other maintainers of Vitess and on Friday we have the Vitess Maintainer Talk. All graduated projects get a maintainer talk. >> Wow, so you are like KubeCon VIP celebrity. >> Well, I hope so. >> Well, you're a maintainer and technical lead, also software engineer at the PlanetScale. But talk about the graduation process where that means to the project and the people involved. >> So Vitess graduated in 2019 and there are strict criteria for graduation and you don't just have to meet the minimum, you sort of have to over perform on the graduation criteria. Some of which are like there must be at least two large production deploys and people from those companies have to go in front of the CNCF committee that approves these things and say that, "Yes, this project is critical to our business." >> A lot of peer review, a lot of deployment success. >> Yes. >> Good consistency in the code. >> Deepthi: Community diversity. >> All that. >> All those things. >> Talk about the importance of this project. What is the top story that people should know about around the project? Why it exists, why it's important, why it's relevant, why it's cool. How would you answer that? >> So MySQL is now 30 years old and yet they are still- >> Makes me feel a little sidebar. (Deepthi laughs) Yeah. >> And yet even though there are many other newer databases, it continues to be used at many of the largest internet scale companies. And some of them, for example, Slack, GitHub, Square, they have grown to a level where they could not have if they had tried to do it with Vanilla MySQL that they started with, and the only reason they are where they are is Vitess. So that is I think the number one thing people should know about Vitess. >> And the origination story on notes say "Came from YouTube." >> Yes. So the way Vitess started was that YouTube was having problems with their MySQL deployment and they got tired of dealing with the site being down. So the founders of Vitess decided that they had to do something about it and they started building Vitess which started as a pretty small, relatively code-based with limited features, and over time they built charting and all of the other things that we have today. >> Well, this is exciting Savannah because we've seen this industry. Like with Facebook, when they started, everyone built their own stuff. MySQL was a great- >> Oh gosh, and everyone wanted to build it their way, reinventing the wheel. >> And MySQL was great. And then as it kind of broke when it grew, it got retrofitted. So, it was constantly being scaled up to the point where now you guys, if I get this right, said, "Hey, we're going to work on this. We're going to make it next-gen." So it's kind of like next-gen MySQL. Almost. >> Yes, yes. I would say that's pretty accurate, yeah. So there are still large companies which run their own MySQL and they have scaled it in their own way, but Vitess happens to be an open source way of scaling MySQL that people can adopt without having to build all of their own tooling around it. >> Speaking of that and growing, you just announced a new version today. >> Yes, yes. >> Tell us about that. >> The focus in this version was to make Vitess easier to use and to deploy. So in the past, there was one glaring gap in Vitess which was that Vitess did not automatically detect and repair MySQL level failures. With this release, we've actually closed that gap. And what that means for people using Vitess is that they will actually spend less time dealing with outages manually, or less human intervention, More automated recovery is what it means. The other thing we've released today is a new web UI. Vitess had a very old web UI, ugly, hard to maintain. Nobody liked it. But it was functional, except we couldn't add anything new to it because it was so old. So, the backend functionality kept advancing but the front end was kind of frozen. Now we have a next generation UI to which in upcoming releases we can add more and more functionality. >> So, it's extensible. They add things in. >> Deepthi: Oh yes, of course. Yeah. >> Awesome. What's the biggest thing that you like about the new situation? Is it more contributors are on board the UI? What's the fresh new impact that's happening in the community? What's getting you excited about with the current project? And the UI's great 'cause usability is important. >> Deepthi: Right. >> Scalability is important. >> I think Vitess solved the scalability problem way early and only now we are really grappling with the usability problem. So the hope and the desire is to make Vitess autopilot so that you reduce human intervention to a minimum once you deploy it. Obviously, you have to go through the process of deploying it. But once you've deployed it, it should just run itself. >> Runs at scale. So, the scale's huge? >> Deepthi: Yes. >> How many contributors are involved in the project? Can you give some numbers? Do you have any handy that you can speak to? >> Right. So, CNCF actually tracks these statistics for all the projects and we consolidated some numbers for the last two full calendar years, 2020 and 2021. We had over 400 contributors and 200 plus of them contributed code and the others contributed documentation issues, website changes, and things like that. So that gives- >> How about downloads? Download's good? >> Oh, okay. So we started publishing the current official Vitess Docker Image in 2018. And by October of 2020, we had about 3.8 million downloads. And by August of 2021, we had 5.2 million. And today, we have had over 10 million downloads- >> Wow! >> Of the main image. >> Starting to see a minute of that hockey stick that we all like to see. Seems like you're very clearly a community-first leader and it seems like that's in the PlanetScale and the test's DNA. Is that how the whole company culture views it? Would you say it's community-first business? >> PlanetScale is very much committed to Vitess as an open source project and to serving the Vitess community. So as part of my role at PlanetScale, some of the things I do are helping new contributors whether they are from PlanetScale or from outside PlanetScale. A number of PlanetScale engineers who don't work full-time on Vitess still contribute bug fixes and features to Vitess. We spend a significant amount of our energy helping users in our community Slack. The releases we do are mainly for the benefit of the community and PlanetScale is making those releases because for Planet Scale... Within PlanetScale, we actually do separate releases versus the public ones. >> One of the things that's coming up here at the show is deploying on Kubernetes. How does that look like? Everyone wants ease of use. Are you guys easy to use? >> Yes, yes. So PlanetScale also open sourced a Kubernetes operator for Vitess that people outside PlanetScale are using to run their production deployments of Vitess. Prior to that, there were Vitess users who actually built their own Kubernetes deployments of Vitess and they are still running those, but new users and new adopters of Vitess tend to use the Kubernetes operator that we are publishing. >> And you guys are the managed service for Vitess for the people that that's the business model for PlanetScale. >> Correct. So PlanetScale has a serverless database on demand which is built on Vitess. So if someone's starting something new and they just need a database, you sign up. It takes 30 seconds to get a database. Connect to it and start doing things with it. Versus if you are a large enterprise and you have a huge database deployment, you can migrate to PlanetScale, import all of your existing data, cut over with minimal downtime and then go, and then PlanetScale manages that. >> And why would they do that? What's the use case for that? Save time new development team or refactoring? >> Save time not being able to hire people with the skills to run it in-house. Not wanting to invest engineering resources in what businesses think is not their core competency. They want to focus on their business value. >> So, this database is a service in their whatever they're doing without adding more costs. >> Right. >> And speed. Okay, cool. How's that going? >> It's going well. >> Any feedback from customers in terms of why that there are any benefit statements you seek popping out? What are the big... What's the big aha when they... When people realize what they have here, what's the aha moment for them? Do they go, "Wow, this is awesome. It's so easy. Push a button. Migrate." Or is it... >> All of those. And people have actually seen cost savings when they've migrated from Amazon RDS to PlanetScale and we have testimonials from people who've said that, "It was so easy to use PlanetScale. Why would we try to do it ourselves?" >> It's the best thing a customer could say, right? We're all about being painkillers and solving some sort of problem. I think that that's a great opportunity to let you show off some of your customers. So, who is receiving this benefit? 'Cause I know PlanetScale specifically is for a certain style of business. >> Hmm. We have a list of customers on the website. >> Savannah: I was going to say you have a really- >> John: She's a software engineer. She's not marketing. >> You did sexy. >> You're doing a great job as much as marketing. >> So the reason I am bringing this up is because it's clear this is a solution for companies like Square, SoundCloud, Etsy, Jordan, and other exciting brands. So when you're talking about companies at scale, these companies are very much at scale, which is awesome. >> Yeah. >> What's next? What do you guys see the future for the project? >> I think we talked about that a little bit already. So, usability is a big thing. We did the new UI. It's not complete, right? Because over the last four years we've built more features into the backend which you can't yet access from the UI. So we want to be able for people to use things like online schema changes which is a big feature of Vitess. Doing schema changes without downtime from the UI. So, schema management from the UI. Vitess has something called VReplication which is the core technology that enables charting. And right now you can from the UI monitor your charting status, but you can't actually start charting from the UI. So more of the administrative functions we want to enable from the UI. >> John: Awesome. >> Last question. What are you personally most excited about this week being here with our wonderful community? >> I always enjoy being at KubeCon. This is my fifth or sixth in-person and I've done a couple of virtual ones. >> Savannah: Awesome. >> Because of the energy, because you get to meet people in person whom previously you've only met in Slack or maybe in a monthly community Zoom calls. We always have people come to our project booth. We have a project booth here for Vitess. People come to the company booth. PlanetScale has a booth. People come to our talks, ask questions. We end up having design discussions, architecture discussions. We get feedback on what is important to the people who show up here. That always informs what we do with the project in future releases. >> Perfect answer. I already mentioned that you can get a hold and in touch with Deepthi through her wonderful Twitter handle. Is there any other website or anything you want to shout out here before I do our close? >> vitess.io. V-I-T-E-S-S dot I-O is the Vitess website and planetscale.com is the PlanetScale website. >> Deepthi Sigireddi, thank you so much for being on the show with us today. John, thanks for keeping me company as always. >> You're welcome. >> And thank all of you for tuning into theCUBE. We will be here in Detroit, Michigan all week live from KubeCon and we hope to see you there. (gentle upbeat music)

(upbeat music) >> Okay, we're back with Tim Yoakum, who is the Director of Engineering at Influx Data. Tim, welcome. Good to see you. >> Good to see you. Thanks for having me. >> You're really welcome. Listen, we've been covering open source software on the Cube for more than a decade, and we've kind of watched the innovation from the big data ecosystem, the cloud is being built out on open source, mobile social platforms, key databases, and of course Influx DB, and Influx Data has been a big consumer and contributor of open source software. So my question to you is where have you seen the biggest bang for the buck from open source software? >> So, yeah, you know, Influx, really, we thrive at the intersection of commercial services and open source software. So OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service, from our core storage engine technologies to web services, templating engines. Our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants. And like you've mentioned, even better, we contribute a lot back to the projects that we use as well as our own product, Influx DB. >> You know, but I got to ask you, Tim, because one of the challenge that we've seen, in particular, you saw this in the heyday of Hadoop. The innovations come so fast and furious, and as a software company, you got to place bets, you got to, you know, commit people, and sometimes those bets can be risky and not pay off. How have you managed this challenge? >> Oh, it moves fast, yeah. That's a benefit though, because the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we tend to do is we fail fast and fail often. We try a lot of things. You know, you look at Kubernetes for example. That ecosystem is driven by thousands of intelligent developers, engineers, builders. They're adding value every day. So we have to really keep up with that. And as the stack changes, we try different technologies, we try different methods, and at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's something that we just do every day. >> So we have a survey partner down in New York City called Enterprise Technology Research, ETR, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes, is one of the areas that has kind of, it's been off the charts and seen the most significant adoption and velocity, particularly, you know, along with cloud. But really Kubernetes is just, you know, still up and to the right consistently, even with, you know the macro headwinds and all of the other stuff that we're sick of talking about. So what are you doing with Kubernetes in the platform? >> Yeah, it's really central to our ability to run the product. When we first started out, we were just on AWS, and the way we were running was a little bit like containers junior. Now we're running Kubernetes everywhere, at AWS, Azure, Google Cloud. It allows us to have a consistent experience across three different cloud providers, and we can manage that in code. So our developers can focus on delivering services, not trying to learn the intricacies of Amazon, Azure, and Google, and figure out how to deliver services on those three clouds with all of their differences. >> Just a follow up on that, is it, now, so I presume it sounds like there's a PaaS layer there to allow you guys to have a consistent experience across clouds and up to the edge, you know, wherever. Is that, is that correct? >> Yeah, so we've basically built, more or less, platform engineering. This is the new hot phrase. You know, Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on, and they only have to learn one way of deploying their application, managing their application. And so that just gets all of the underlying infrastructure out of the way and lets them focus on delivering Influx Cloud. >> Yeah, and I know I'm taking a little bit of a tangent, but is that, I'll call it a PaaS layer if I can use that term, are there specific attributes to Influx DB, or is it kind of just generally off the shelf PaaS? You know, is there any purpose built capability there that is value add, or is it pretty much generic? >> So we really build, we look at things with a build versus buy, through a build versus buy lens. Some things we want to leverage, cloud provider services for instance, Postgres databases for metadata perhaps, get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can deliver on, that has consistency, that is all generated from code that we can, as an SRE group, as an ops team, that we can manage with very few people really, and we can stamp out clusters across multiple regions in no time. >> So how, so sometimes you build, sometimes you buy it. How do you make those decisions, and what does that mean for the platform and for customers? >> Yeah, so what we're doing is, it's like everybody else will do. We're looking for trade offs that make sense. You know, we really want to protect our customers' data. So we look for services that support our own software with the most uptime, reliability, and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team. And of course for customers, you don't even see that, but we don't want to try to reinvent the wheel. Like I had had mentioned with SQL data storage for metadata perhaps. Let's build on top of what these three large cloud providers have already perfected, and we can then focus on our platform engineering, and we can have our developers then focus on the Influx Data software, Influx Cloud software. >> So take it to the customer level. What does it mean for them? What's the value that they're going to get out of all these innovations that we've been been talking about today? And what can they expect in the future? >> So first of all, people who use the OSS product are really going to be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you. But then you want to scale up. We have some 270 terabytes of data across over 4 billion series keys that people have stored. So there's a proven ability to scale. Now, in terms of the open source software, and how we've developed the platform, you're getting highly available, high cardinality time series platform. We manage it, and really as I mentioned earlier, we can keep up with the state of the art. We keep reinventing. We keep deploying things in real time. We deploy to our platform every day repeatedly, all the time. And it's that continuous deployment that allows us to continue testing things in flight, rolling things out that change, new features, better ways of doing deployments, safer ways of doing deployments. All of that happens behind the scenes. And we had mentioned earlier Kubernetes, I mean that allows us to get that done. We couldn't do it without having that platform as a base layer for us to then put our software on. So we iterate quickly. When you're on the Influx Cloud platform, you really are able to take advantage of new features immediately. We roll things out every day. And as those things go into production, you have the ability to use them. And so in the end, we want you to focus on getting actionable insights from your data instead of running infrastructure. You know, let us do that for you. >> And that makes sense, but so is the, are the innovations that we're talking about in the evolution of Influx DB, do you see that as sort of a natural evolution for existing customers? Is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >> Yeah, it really is. It's a little bit of both. Any engineer will say, well, it depends. So cloud native technologies are really the hot thing. IoT, industrial IoT especially, people want to just shove tons of data out there and be able to do queries immediately, and they don't want to manage infrastructure. What we've started to see are people that use the cloud service as their data store backbone, and then they use edge computing with our OSS product to ingest data from say multiple production lines and down-sample that data, send the rest of that data off to Influx Cloud where the heavy processing takes place. So really us being in all the different clouds and iterating on that, and being in all sorts of different regions allows for people to really get out of the business of trying to manage that big data, have us take care of that. And of course, as we change the platform, end users benefit from that immediately. >> And so obviously, taking away a lot of the heavy lifting for the infrastructure, would you say the same thing about security, especially as you go out to IoT and the edge? How should we be thinking about the value that you bring from a security perspective? >> Yeah, we take security super seriously. It's built into our DNA. We do a lot of work to ensure that our platform is secure, that the data we store is kept private. It's of course always a concern. You see in the news all the time companies being compromised. You know, that's something that you can have an entire team working on, which we do, to make sure that the data that you have, whether it's in transit, whether it's at rest, is always kept secure, is only viewable by you. You look at things like software bill of materials. If you're running this yourself, you have to go vet all sorts of different pieces of software. And we do that, you know, as we use new tools. That's something that's just part of our jobs, to make sure that the platform that we're running has fully vetted software. And with open source especially, that's a lot of work. And so it's definitely new territory. Supply chain attacks are definitely happening at a higher clip than they used to. But that is really just part of a day in the life for folks like us that are building platforms. >> Yeah, and that's key. I mean, especially when you start getting into the, you know, we talk about IoT and the operations technologies, the engineers running that infrastructure. You know, historically, as you know, Tim, they would air gap everything. That's how they kept it safe. But that's not feasible anymore. Everything's >> Can't do that. >> connected now, right? And so you've got to have a partner that is, again, take away that heavy lifting to R and D so you can focus on some of the other activities. All right. Give us the last word and the key takeaways from your perspective. >> Well, you know, from my perspective, I see it as a a two lane approach. With Influx, with any any time series data, you know, you've got a lot of stuff that you're going to run on-prem. What you mentioned, air gaping, sure there's plenty of need for that, but at the end of the day, people that don't want to run big data centers, people that want to entrust their data to a company that's got a full platform set up for them that they can build on, send that data over to the cloud. The cloud is not going away. I think a more hybrid approach is where the future lives, and that's what we're prepared for. >> Tim, really appreciate you coming to the program. Great stuff. Good to see you. >> Thanks very much. Appreciate it. >> Okay, in a moment, I'll be back to wrap up today's session. You're watching the Cube. (gentle music)

(soft music) >> Hey, welcome back to theCUBE's coverage from Miami of IFS Unleashed 2022, Lisa Martin here with you. We've had great conversations today with IFS execs, customers, partners. Our ecosystem is quite robust and quite strong. And we've had some alumni on, I've got another alumni who's back with me, Michael Ouissi, the group's COO of IFS. Michael, welcome back to theCUBE. >> Thanks for having us, my pleasure. >> It's great to be back in-person. >> Absolutely. >> It was great to walk into the keynote this morning and see a full room. I was talking with Darren Roos, your CEO earlier this morning and I said, it must have felt great to walk out on stage and actually see a sea of people and customers and partners who want to engage and get that relationship with IFS just turbocharged. >> Absolutely, I mean, it's been three years, we haven't had this buzz, this energy, and the opportunity to actually see all our customers and also show our customers who we are, how we are evolving and how we're becoming a different company over the past four years. >> And it's impressive what IFS has done in that timeframe. All the conversations I've had today, really reflect the strategy, the strong strategy and vision that this company has. But I was looking at some of the financials and saw that your first half of 2022, which ended in June, there was tremendous growth. ARR up 33%, I think they're recurring revenue is in the 70 percentile now. Lot of new customers, a lot of of trust that existing customers are showing to the company. >> Yeah, absolutely. Look, and I think the secret sauce is that we have focused on where our strengths are, we haven't gone astray, we haven't tried to actually capture growth in any other vertical. We are really very religious about where we're going and there, where we are going, we are going deep and we really are trying to be the best version of ourselves for our customers and for those customers' business transformation needs. >> Talk a little bit about that vertical specialization. It's something that we don't see very often but throughout all of my conversations today with your executives, IFS executives, with customers, with partners, that domain expertise, really the granularity of the domain expertise is really resonant that IFS has achieved that in those five key verticals in which you have such specialization. >> Yeah, look, I mean, I would love to take credit for having been the person who has done that, but IFS has over the past 35 years, really had this very strong focus. But what actually was important when you try to double a business in the space of four years, not to be tempted to go away from that but actually double down on exactly that and see the opportunity in those verticals and make sure that our customers actually are getting the attention and the functionality they deserve. >> Let's talk about customers. Over 10,000 customers right now. I was also in the keynote this morning where Christian Peterson was sharing that, in its first 18 months, IFS Cloud has over 400,000 users. So the growth is tremendous. The customer loyalty is ostensible in those verticals. Talk about customers and their influence on the company, the direction the technology goes, the evolution, that kind of stuff. >> Yeah, I mean, look, as I said, we are all about the depth of the functionality and that means that we need to listen to our customers, We need to listen what's going on in the industries. We also need to not just listen but we need to think forward. >> Yeah. >> We need to have some thought leadership on what we think is going to emerge and then test that with our customers again. So our customers are at the core of everything we do. When we engage with a customer, we start with trying to understand their business in depth. We've got our own methodology around that and we don't just try to push technology onto them, but we are trying to understand what are their business drivers and then actually try to apply technology to what enables them to deliver on those business transformation objectives they've got. >> What are some of the changes or the waves that you've seen, especially the last couple of years during the pandemic when we saw so many customers pivot, we need to transform digitally to stay alive, and then those that did that well enough to be competitive and to thrive, talk to me about some of the changes as the group's COO that you've seen. >> Yeah, so when you go back, I mean, there's two types of transformation, business and digital transformation but they are the same thing, they're just a different side of the coin. And when I talk about business transformation, what we're seeing a lot is, and there's this big buzzword overtization out there, but customers going service and customers trying to build an end to end business that is more viable, more sustainable, more successful in how they develop great moments of service for their customers, that is something we are seeing a lot. And during this business transformation, digital transformation has become a means to that end. And that is something where customers have matured a lot, where in the past we have seen a lot of the IOT, AI, machine learning, cloud, everything was a means or a purpose in itself and that has changed. It's now become actually a means to an end. It's become a means to actually deliver a business transformation and a business outcome that is meaningful for their customers. >> Has to be meaningful for their customers. I love how IFS talks about enabling your customers to deliver those moments of service. And when we think of, in our consumer lives, many of us flew here, and you think about what's the moment of service for an airline? Well, it's being able to get on that plan on time, have it leave on time and meet my expectations as a demanding consumer. But regardless if we're talking about aerospace, energy, manufacturing, engineering, the customers on the other end expect to have an integrated seamless experience that's not fragmented, that is able to deliver moments of service that then help drive up their revenue. So what IFS is doing is so embedded in what your customers are able to deliver to their customers. >> Yeah, absolutely. And look, if you look at all the things that have to come together to actually have a plane taken off at the right point in time or if you take any other examples, but there's so many things that need to go right. Crew scheduling, you need to have the right crew at the right point in time. You need to have them actually with the right experience to fly the right plane. You need to have airplane maintenance going right to have the plane available at the right point in time and no technical failures and so on and so forth. And we look at that as between customers, the people, and the assets that an organization has, you need to coordinate between all those dimensions in everything you do to make sure that this one moment of service where your plane takes off on time, you actually catch your connecting flight at the other end, that this actually is being delivered. And that's what drives us, that's what customers are driving into our product development, into how we embed AI, machine learning and so on in our technology to make it relevant to exactly that moment of service. >> That's what we as those consumers want. We want relevance, we want personalization, we want that relationship to know who we are and how to serve us best. Let's dig into the Jotun case study. He was going to join us, our CEO was going to join us, couldn't make it. Talk to me a little bit about Jotun, what type of business is it and then let's kind of start unpacking how they're leveraging IFS technology. >> Yeah, so Jotun is the seventh largest paints and coatings manufacturer in the world. And they've got obviously a home decoration part of the business, but they've got an industrial part of the business where one large part of the business is also a marines part. So they actually provide paints, coating, for all sorts of large ships and it's quite astonishing what you learn about that customer. I mean, we are now partnering with them for more than 20 years, so we are very intimate with that customer obviously. But when you see all of a sudden, three, four years ago, they started going onto a journey where they looked at apart from paint and coating, what actually can I provide to my customer in the marine industry to actually make their business more efficient, to actually make it easier for them to get a ship from A to B in an efficient way, in a timely way and so on. And they developed something called Hull Skating Solutions and those Hull Skating Solutions are integrating all sorts of weather data, all sorts of other data and provide them to the marine companies that actually then help them drive this... Well, actually get this ship in a more efficient way from A to B. And at the same time, also where there's predictions as to when you need to clean that ship, and they've got Hull Skating Solutions, which then actually clean the ship automatically as well. So it's quite an astonishing thing for a paints and coating manufacturer to then think about what do I need to know about my customer's business to provide that additional service to my customer? Great solution and great way of dealing with or delivering that great moment of service to their customers. >> Absolutely, the evolution of that business from paint manufacturing into the marine industry is not a stretch based on how you described it, but it's very innovative. How is IFS enabling them to do that and do it well? >> Well, one, they went on a modernization program for all their factories for all these kinds of things that they need to integrate then deliver to their customers. And we are in the central part in being that agile partner that actually delivers those technology solutions that enable them to, well, first of all think about that service, provide that service to their customers and make sure that they run a very efficient, very integrated version of IFS and can actually harmonize globally to make sure that wherever the customer is, they can deliver on that promise. >> Fantastic, let's talk a little bit about from your team's perspective, the go to market. We talked about the five verticals in which IFS specializes energy, aerospace and defense, engineering, manufacturing and there's one I'm missing. >> Utilities. >> Utilities, of course. >> Yeah. >> In terms of the domain expertise, are there vertical teams that are focused? I imagine that there are, talk to me a little bit about that specialization from that lens. So obviously, I mean, there are so many dimensions. There's our sales teams, there's our pre-sales teams, there's our industry teams which actually are working with the customers on receiving their feedback, on actually providing thought leadership and then organizing the feedback loop into our development teams who are providing these solutions then that hopefully our customers will cherish. So we are very specialized in that respect. We are driving the industry specialization. We've got a complete aerospace and defense business unit. We are in the market unit, specializing in the industries where we work in the various different territories with just those industry teams. We've got specialization in the pre-sales teams. So we take that really deep down and very seriously to make sure that whenever we talk to a customer, we also have the understanding and we have also got the curiosity to understand more of the customer's business, and that is something that is part of the IFS DNA. >> It's a differentiating part of IFS' DNA that not only having the domain expertise, and a lot of people talk about, well, we got to meet the customer where they are, wherever they are digitally, wherever they are in business transformation. But you're actually talking the customer's language. >> Yeah. >> By industry, which I would imagine really helps to not only solidify that relationship, but you actually get to really do a double click and get much more tightly connected with the customers and the outcomes that they're wanting to achieve so that those moments of service happen. >> Well, that's so true. And actually this is not just while we are selling to the customers, but it's actually throughout the whole life cycle of this application and the technology in Jotun's case more than two decades. And we've got a lot of customers who are actually that long with us because we don't run away once we've implemented a solution, but we actually stay close to it because first of all, we want to learn from our customers continuously. We want to actually give to our customers also what we are learning outside of the conversations we have with these customers. And we make sure that these customers continuously evolve how they think about their business, how they think about the application of our technology and then in turn, we can actually develop technology again, for their use cases. >> It's a flywheel. >> It's a complete flywheel and that creates loyalty. >> Yeah. >> That actually creates the longstanding relationships we have with many, many of our customers, yeah. >> I was speaking with a number of your executives, Marni Martin was here and we were talking about brand recognition and the loyalty, but that intimate customer knowledge that IFS really works hard to gain with its customers. 'Cause as consumers, we bleed into our business lives and we have very little tolerance, very little patients. I think that was one of the things in COVID that went away. People were just not tolerating this rapid change and we had no choice. But I don't know that patience is going to come back at the level in which we experienced it before COVID. So customers expect businesses and brands to know them and help anticipate what's next for me, how do I get there? And it sounds to me like IFS has really nailed that from a customer relationship perspective. >> As I said, I mean it's really part of our DNA and we try to preserve that culture while we're doubling our business and hopefully, doubling our business in the next three years again, because that is really the secret sauce to being that successful, and not only with our existing customers, but also with the net new customers. And we are driving almost 50% of our revenue, which is very, very much a benchmark in the industry from net new customers that we're winning while we're actually keeping or staying close to our existing customers and try to apply that knowledge to our net new customers. >> Yeah. >> But it's something that we absolutely have to preserve to be as successful as we've been in the past four years, also in the next four years. >> So coming off a great first half in the summer, when I teased Darren, "Any nuggets you want to say?" He said financials for Q3 are coming out in the next couple of weeks. And I said, I imagine that trajectory is up and to the right. >> Yeah. >> What are some of the things, Michael, that excite you for where you've seen this company go in your time there and the rocket ship that it seems to be on today? >> Yeah, look, I mean, what's amazing to me is... And if I look back, I joined four and a half years ago, and only the first one and a half years were under normal circumstances. >> Right. >> The other three years were a major pandemic, now a major war and recession and we've got all sorts of economic and macroeconomic headwinds. And what what impresses me about the company, about our customers, about our employees is the resilience we've got to just carry on with what we're doing. And I mean, I don't give too much away when I say we had a pretty good Q3 as well, and we are looking forward to a really good 2022 as a full year, and there are no excuses that actually the organization makes, it has just taken along. And we are facing the economic headwinds and we are going through that time hugely successful. And I'm very optimistic about the year and about 2023 as much. >> Fantastic, it's kind of hard to believe that calendar year 2023 is literally around the corner. But Michael, it's been great having you on theCUBE. Thank you for coming back, talking about what's going on at IFS from the overall COO's perspective, the customer synergies that IFS has, the work that you do to really get granular in those industries, it's impressive and congratulations on the success. We'll have to have you back next year to talk about what else is new. >> Thank you very much, Lisa. >> All right, my pleasure. >> Thank you. >> For Michael Ouissi, I'm Lisa Martin, you're watching theCUBE's coverage live from Miami on the show floor of IFS Unleashed. We'll be back with our final guest in just a minute. (soft music)

>> theCUBE Presents UiPath FORWARD 5. Brought to you by UiPath. >> We're back in Las Vegas live. You're watching theCUBE's coverage of FORWARD 5 UiPath's customer event. My name is Dave Vellante. I'm here with David Nicholson. Our third Dave Espinoza is here, Director of Transformation at Cushman & Wakefield. And Marshall Sied is also here. He's the co-founder of Ashling Partners. Guys, thanks for coming on theCUBE. >> Thanks for having us. >> We know Cushman & Wakefield, huge real estate firm. We'll come back to that, wanted to dig into some of the industry trends. But Marshall, what is Ashling Partners all about? >> Great question, Dave. So Ashling Partners was founded with modern automation and continuous improvement in mind. So a lot of us used to implement large ERP systems, accounting transaction systems. We viewed RPA and broader intelligent automation as kind of the wave of the future. So everything we do has continuous process improvement and automation in mind together. So we don't want to decouple, we want bring those together in an agile way. >> It's interesting, Rob Enslin this morning on the stage was talking about the waves of industry tech that used ERP was where he started and you know, et cetera, internet and now automation. He's sort of drawing that analogy. It's interesting that you're seeing the same pattern. >> David: Were were you fist bumping in the back of the room? >> Marshall: Absolutely. >> Well, I mean there's a lot of opportunity there. A lot of money to be made on both ends. Dave, talk about your firm. What's going on in the industry specifically? You joined sort of as we're exiting the isolation economy. Right? So what's happening in the industry now? I mean, real estate has been up and down and, you know, wild ride, you know, with COVID. What are the big trends in the industry that are informing your automation strategy. >> And actually I joined probably like right in the middle of the isolation economy. So it was a really interesting time to like to, I'm sure for most people also onboarding into groups. But coming on Cushman, you know, Cushman itself is an organization that formed predominantly through acquisition and through merger, right? So three large companies came together. And so a lot of the times the sort of headaches and the opportunities that we find are probably no different than other legacy organizations have when they're merging three companies together, right? So lots of disparate process, lots of paper, lots of process that isn't really very standardized. And so really it's a lot about us trying to make sure that we're continuing to double down on really that continuous process improvement but also bringing technology, lots of different types of technologies to bear to solve different problems throughout the organization. >> Well is the pandemic a catalyst for the automation initiative? Or actually you guys started before that I think, Marshall started about 2018. But was it like a rocket booster during the pandemic or was it more sort of steady state? >> I think it was actually a little bit of both Dave. 'Cause the reality is there was already top down executive support at Cushman pre-pandemic. So Cushman was already moving on this in a big way and they had executive sponsorship across the C-suite. Pandemic came, never a good time for a pandemic, but it came at a decent time for Cushman because they were prepared. They had the foundation of governance, everything you need in a large enterprise to run a program. They had that in place so they were able to kind of just put kerosene on the fire when the pandemic hit with certain automation candidates. >> Because I often said that pre-pandemic, you know, digital transformation was kind of this buzzword. A lot of firms were sort of giving it lip service. But it sounds like Cushman actually had started down the digital transformation path and then obviously everybody was accelerated. If you weren't digital business, you were out of business. But but how tightly aligned, 'cause we heard this in the keynotes today, I'd like to test it. How tightly aligned is automation and digital transformation at Cushman. >> They're pretty synonymous really for us, right? So like it is really about bringing different types of technologies, whether it's like NLP. The other really interesting thing that we were talking about the keynote, right? There's just so much that is going into the UiPath platform that is enabling us and enabling the things that we want to do across the organization, right? So like natural language processing, document understanding, you know, cloud based items. Like there's just so much that we can leverage and it's really about that continuous process improvement. It's trying to make sure that we're aligning ourselves to the strategy that the organization is absolutely pushing, but making sure that we're doing it in smart ways, right? And that we're empowering our employees as we do it, right? So it's not just very top down from a COE, it's also very bottoms up, very citizen-led throughout the organization. >> So I think of this as a strategic initiative that happens over time. But how does Ashling, and Marshall, how do you engage with Cushman? Do you engage on a project by project basis? Do you have sort of a long term strategic arc that you're working to? >> Absolutely. >> How does that work? >> No, that's a great question. So we started project based, so we were a part of the co-establishment of the intelligent automation COE. So very outcome driven, top down approach as Dave mentioned. But we also had a wider aperture than just RPA. It was broader end to end automation experiences that was project based. We had so much kind of quantifiable evidence at that point that we wanted to go bigger with the program. Over time we matured into more of an agile DevOps methodology with the Cushman team. And Dave should certainly speak about the size of the Cushman team and how that's evolved over time, but- >> Because the two of you are in a partnership in terms of proving out the ROI of what you're doing. >> Oh, absolutely. >> Right? >> Marshall: Every day, every day. We all have numbers we got to hit, right? And that's just the reality of it. But in order to do that, you know, agile DevOps approach where you're, you know, releasing every two weeks into production, you need a dedicated team that has like a longer term roadmap that is coinciding with the Cushman objective. So that's what we have in place today, something we call build as a service and mROC. So kind of think of that as as plan, build, and then run. We're infused. You have to be infused with your clients if you're going to run an agile DevOps program. >> Is automation more self-funding? Marshall, I want to draw on your experience with ERP. Is automation more self-funding than other technology initiatives? And if so, why or if not, why not? >> It is, and it's a double edged sword actually. We talk about this all the time at Ashling. We've never worked in an enterprise technology space where there's more accountability to value delivered because it's so quantifiable and measurable. So every time a transaction runs you can measure- >> Dave: How are we doing? >> Exactly, I mean the ERP days, nobody questioned. They just, they thought we just have to move to S/4HANA, we just have to move to Oracle. >> We'll let you know in a couple years. >> That's it, yeah. >> I mean the stuff that we just saw earlier from Javier Castellanos, right, from Orange. It is very much like each transaction has a value associated to it. Each part of that transaction has a value associated to it. We're constantly monitoring the numbers of looking at our performance, right? There's very real value associated to maintaining business as usual for the 50 plus automations that we have in production, right? So like the business is really counting on us to maintain and to make sure that we're continuing to perform. But also that we're continuing to work with them to find additional value and additional opportunities, right? To make sure that we are saving money and finding dollars- >> But it's dropping hard dollars to the bottom line, right, that are quantifiable to your point. But what's the governor, what's the barrier to your ability to absorb whether it's new automation? Is it just expertise, talent, or you bandwidth? Is it the prioritization exercise and thinking intelligently about, you know not- >> Dave: All of that. >> So how do you, I guess you guys work together, but take us through that a little bit. >> I mean, we're constantly refining our approach. So we were just talking about our DevOps approach. You know, we started with I think maybe five or six different teams based on specific service lines. We modulated that recently to go to two teams, right? One specific to build and one specific to enhance. So we're constantly looking for and building new automations throughout the organization. And then also looking for incremental value to enhance the automations that we've got out there, right? So making them better, faster, making them more resilient so resolving technical debt, doing a lot of different things to make sure that we're as stable as we possibly can be. But it's not only that, it's really like making sure like we're just as pinched by everybody else in terms of like the great resignation and looking for talent. I think everybody here is basically looking for the exact same talent. And so it's really making sure that we have interesting work, we're doing interesting work, we're making people feel valued, and we're bringing value throughout the business. >> So I remember Bobby Patrick called me when he joined UiPath. He goes, "You're not going to believe what I'm doing now. You got to get on this train." And so I started looking to it and we actually downloaded, you know, the package and started playing with it. And we tried to do it with the competitors, we, you know, we couldn't. It was like call for pricing kind of thing. We're like, well that's interesting. But what we saw was my perspective, this bottoms up adoption. And I know there was top down as well. But then, I remember I was in the meeting when they announced the sort of process gold acquisition and then started, I said, "Okay, they're going for platform now." And then Microsoft came into the market like, okay, they got to differentiate there. Now you're seeing everybody, all the software companies think they should own every dollar that's ever spent on software. So SAP's doing it and ServiceNow. And so Marshall, from your perspective, how has this platform evolved? And then Dave, to the extent you can talk about it, how is that platform adoption taking shape within the organization? I mean, platforms are much more complicated than products and they require integration. How is UiPath doing there? >> I think they're doing fantastic in that category. If you think about, and it's been a natural evolution. They're not fighting inertia, they're following challenges of their clients, right? So RPA obviously came onto the scene hot, everybody understands the business rule driven automation value. Easy to, you know, make a quantifiable, tangible evidence with RPA. But exceptions happen in a business and upstream processes break that, you know, cause challenges with downstream automations. So what do you do? You have to go upstream. You have to have more automations, you have to have process discovery, process mining with process gold. You need to have the ability to have a better user experience interface, which we've definitely incorporated into Cushman when we didn't get adoption with certain automations that we like. You build low-code apps. People want that consumerization of technology in the enterprise and that allows them to adopt more of the automation which triggers the robots and then you report analytics on it. So that expansion's been pretty natural with UiPath and I think the next acquisition they just made with Re:infer's really interesting, 'cause now you're going even more upstream with communication mining, turning that into structure data that you potentially could automate or analyze so it's been natural. It's truly the only platform that we've encountered that can do all of this at this point. >> So a couple things there. You know, one is the nuance of adoptions, not just the function of the potential savings or, you know, revenue production or productivity. It's, you know, the experience because you got to have a great UI. And then what are you going to do with Re:infer? I don't know if you guys are adopting Re:infer but what do you see as the potential. Marshall and Dave, if you guys have visibility on it? >> I know we've talked about it Dave so I mean the potential's huge. I think it's going to be more of a question of change management for each organization just to feel comfortable with that. But I mean, think about all of the communication and the semi and unstructured data in an organization that comes, you know, via Slacks, Teams, emails. It's huge and it's significant if you can figure out the right identifiers that you want to trigger for your business. And then figure out is that something downstream we can automate or can we just analyze and make our business more effective, more efficient, or provide a better experience. So I think it's huge. We don't know how big this is yet, but we know that it's something that, I mean, think about Cushman, get brokers all day long that are communicating with clients and third parties. So it could be extremely significant. >> Sounds like a potential to eliminate email hell, but. >> Marshall: Heard those promises before. >> Maybe that's like the paperless office eventually. >> Well in our organizations, like 50, 40 to 50,000 people, you know, globally, right? And there are definitely service lines within our organization where probably it doesn't make sense for us to leverage UiPath and provide them the, you know, studio and low code, no code automation tools. But a lot of this NLP stuff and a lot of the content mining and the communication mining stuff, really has the ability for us to be able to sort of pinpoint opportunities at levels that we couldn't possibly do it before. So it was really very exciting to see the stuff that we were in there. I think when you start your organization, a lot of times you're a hammer looking for a nail, right? And you need to quickly move away from that. And so I think a lot of the stuff that UiPath is introducing, a lot of the stuff that they're bringing into their platform, really helps us to be moving away from that sort of orientation. >> Well when you think of this in terms of CI/CD, you know, people maybe have a better understanding of sort of the life cycles and, you know, the iteration calendar. Can you give us an example of something that went from an idea, something like, "Hey, I think we might be able to automate this process" through "Okay, yeah, let's do it." You try it, at some point there's sort of quality testing involved to make sure that it's achieving that we want to do. Can you give us an example of a process that you've gone through? And then how long do those things usually take? Are we talking weeks, months? What are we talking about from idea to establishing that, "Yeah, this is something we want to keep in place." >> Dave: We always want to make it faster. So we're especially always trying to find ways, especially upfront parts of the process. So a lot of the analysis, requirements gathering, you know, stuff that's not actual building. We want to make sure that we're shrinking that as much as possible, that we're also being comprehensive so that we're not building something that doesn't meet someone's needs, right? Or that just completely misses the mark. But I mean, invoice processing is a good example. We do that internally. Obviously, we have corporate accounting. We also do that on behalf of clients. And so a lot of times, you know, we're bringing some of the internal processes, we're using the technologies for document understanding, optical character reading, and machine learning. And we're doing that on behalf of clients, but we're also doing that internally. So to be able to use some of those processes and automations, sort of client facing plus internally, are big changes. Big changes for us. But I think the other thing too is like, we're always trying to make it faster and better. I think that's one of those also processes where we put something in place and we're constantly looking to enhance it, make it better based on the process that's out here. >> And you're applying automation to that upfront piece, the planning phase? Is that right? Or? >> Yeah, yeah, so a lot of it is about sort of the work that we do on behalf of clients. And there are teams who are specifically tasked to accounts. And so we're looking to find ways to make it easier for those accounts to get their bills paid, to get visibility into, you know, accounts payable, accounts receivable, their full end to end accounts lifecycle. And so yeah, we're doing that directly on behalf of clients and then we're doing that internally. >> How about the why UiPath question. Marshall, I think I heard you say that you're pretty much exclusively UiPath as your automation partner. Why? Why not play the field? Why UiPath? >> So I think it started in like 2017, 2018 for Ashling. We did an analysis of kind of an outside in of what, at that point was the big three of RPA, the vision and the roadmap and the open platform architecture of UiPath and just the self-awareness that, "Hey, we need to operate with other technologies in order for our clients to get the most value from automation." That was really the main reason, outside of the fact that we like working with UiPath, but it was just that complete vision of a platform as opposed to a tool. We felt like everybody else was more of a pointed tool and then UiPath had this platform approach and it was going to be necessary to go end to end like we all are trying to achieve. >> And UiPath continues to deepen that, right? They continues to support us with tons of new technology- >> How so? Can you be specific? >> I mean, when we're talking about document understanding, I mean, we're trying to leverage that for manual handwritten time sheets. We're also using it for, you know, Chronos integration, right? So like there's a lot of stuff that we're using it for and we can go to a single shop, right? To be able to do it, a single platform from a scalability and a supportability perspective, it's also a big game changer for us, right? As you start, you want to be able to scale, but you can't spend a ton of money supporting, you know, a hundred different platforms. You really got to invest and be smart about it. And UiPath for us was a really smart play. >> Are you budget limited relative, you're competing with other initiatives within the organization? Where's the funding come from? Is it from the business? Is it from IT? Is it a combination? >> It had been centrally funded and we are now moving into a different model. So we are constantly looking at, you know, the justification of value, speed to value, and proving it out to our business partners from all service lines and within all different functions of the organization. So we're at an interesting inflection point, but I think we also have a really good background that we're building on. >> I've been saying it all day, I've said it for years, at the UiPath events that they are awesome about putting customers on theCUBE and we love to hear from the customer stories because we get to sort of map what we hear in the keynotes and then test it, right, in the real world. And I also really love the fact that Marshall, UiPath always brings implementation partners so we can get the expertise and you have a wider observation space. So guys, thanks so much for coming on theCUBE and thanks for sharing your stories and good luck in the future. >> Thanks for having us. >> Appreciate it guys. >> Very welcome. >> Thank you. >> All right, keep it right there. Dave Nicholson and Dave Vellante live from Las Vegas UiPath FORWARD 5. We'll be right back right after this short break.

>>Hey everyone. Welcome back to Las Vegas. This is the Cube's live coverage of day. One of snowflake summit 22 fourth annual. We're very happy to be here. A lot of people here, Lisa Martin with Dave Valante, David's always great to be at these events with you, but me. This one is shot out of the cannon from day one, data, data, data, data. That's what you heard of here. First, we have two guests joining us next, please. Welcome Matthew Scalian. Who's an alumni of the cube CEO and founder of Matillion and Jer staying chief data architect and global head of data engineering from Western union. Welcome gentlemen. Thank >>You. Great to be here. >>We're gonna unpack the Western union story in a second. I love that, but Matthew, I wanted to start with you, give the audience who might not be familiar with Matillion an overview, your vision, your differentiators, your joint value statement with snowflake, >>Of course. Well, first of all, thank you for having me on the cube. Again, Matillion S mission is to make the world's data useful, and we do that by providing a technology platform that allows our customers to load transform, synchronize, and orchestrate data on the snowflake data cloud. And on, on the cloud in general, we've been doing that for a number of years. We're co headquartered in the UK and the us, hence my dat accents. And we work with all sorts of companies, commercial scale, large end enterprises, particularly including of course, I'm delighted to say our friends at Western union. So that's why we're here today. >>And we're gonna talk about that in a second, but I wanna understand what's new with the data integration platform from Matillion perspective, lots of stuff coming out, give us an overview. >>Yeah, of course, it's been a really busy year and it's great to be here at snowflake summit to be able to share some of what we've been working on. You know, the Matillion platform is all about making our customers as productive as possible in terms of time to value insight on that analytics, data science, AI projects, like get you to value faster. And so the more technology we can put in the platform and the easier we can make it to use, the better we can achieve that goal. So this year we've, we've shipped a product that we call MDL 2.0, that's enterprise focused, exquisitely, easy to use batch data pipelines. So customers can load data even more simply into the snowflake data cloud, very excitingly we've also launched Matillion CDC. And so this is an industry first cloud native writer, head log based change data capture. >>I haven't come up with a shorter way of saying that, but, and surprise customers need this technology and it's been around for years, but mostly pre-cloud technology. That's been repurposed for the cloud. And so Matillion has rebuilt that concept for the cloud. And we launched that earlier this year. And of course we've continued to build out the core Matillion ETL platform that today over a thousand joint snowflake Matillion customers use, including Western union, of course we've been adding features there such as universal connectivity. And so a challenge that all data integration vendors have is having the right connectors for their source systems. Universal connectivity allows you to connect to any source system without writing code point and click. We shape that as well. So it's been a busy year, >>Was really simple. Sorry. I love that. He said that and it also sounded great with your accent. I didn't wanna >>Thank you. Excellent. Javier, talk about your role at Western union in, in what you've seen in terms of the evolution of the, the data stack. >>So in the last few years, well, a little bit of Western union, a 70 or 170 year old company, pretty much everybody knows what Western union is, right? Driving an interesting synergy from what Matthew says, when data moves money moves, that's what we do when he moves the da, he moves the data. We move the money. That's the synergy between, you know, us and the organization that support us from data move perspective. So what I've seen in the last few years is obviously a shift towards the cloud, but, you know, within the cloud itself, obviously there's a lot of players as well. And we as customers have always been wishing to have a short, smaller footprint of data so that the movement becomes a little lesser. You know, interestingly enough, in this conference, I've heard some very interesting stuff, which kind of helping me to bring that footprint down to a manageable number, to be more governed, to be more, you know, effective in terms of delivering more end results for my customers as well. >>So Matillion has been a great partner for us from our cloud adoption perspective. During the COVID times, we were a re we are a, you know, multi-channel organization. We have retail stores as well, our digital presence, but people just couldn't go to the retail stores. So we had to find ways to accelerate our adoption, make sure our systems are scaling and making sure that we are delivering the same experience to our customers. And that's where, you know, tools like Matillion came in and really, really partnered up with us to kind of bring it up to the level. >>So talk specifically about the stack evolution. Cause I have this sort of theory that everybody talks about injecting data and, and machine intelligence and AI and machine learning into apps. But the application development stack is like totally separate from the, the data analytics and the data pipeline stack. And the database is somewhere over here as well. How is that evolving? Are those worlds coming together? >>Some part of those words are coming together, but where I still see the difference is your heavy lifting will still happen on the data stack. You cannot have that heavy lifting on the app because if once the apps becomes heavy, you'll have trouble communicating with, with, with the organizations. You know, you need to be as lean as possible in the front end and make sure things are curated. Things are available on demand as soon as possible. And that's why you see all these API driven applications are doing really, really well because they're delivering those results back to the, the leaner applications much faster. So I'm a big proponent of, yes, it can be hybrid, but the majority of the heavy lifting still needs to happen down at the data layer, which is where I think snowflake plays a really good role >>In APIs are the connective tissue >>APIs connections. Yes. >>Also I think, you know, in terms of the, the data stack, there's another parallel that you can draw from applications, right? So technology is when they're new, we tend to do things in a granular way. We write a lot of code. We do a lot of sticking of things together with plasters and sticky tape. And it's the purview of high end engineers and people enthusiastic about that to get started. Then the business starts to see the value in this stuff, and we need to move a lot faster. And technology solutions come in and this is what the, the data cloud is all about, right? The technology getting out of the way and allowing people to focus on higher order problems of innovating around analytics, data applications, AI, machine learning, you know, that's also where Matillion sit as well as other companies in this modern enterprise data stack is technology vendors are coming in allowing organizations to move faster and have high levels of productivity. So I think that's a good parallel to application development. >>And's just follow up on that. When you think about data prep and you know, all the focus on data quality, you've got a data team, you know, in the data pipeline, a very specialized, maybe even hyper specialized data engineers, quality engineers, data, quality engineers, data analysts, data scientist, but they, and they serve a lot of different business lines. They don't necessarily have the business, they don't have the business context typically. So it's kind of this back and forth. Do you see that changing in your organization or, or the are the lines of business taking more responsibility for the data and, and addressing that problem? It's, >>It's like you die by thousand paper cuts or you just die. Right? That's the kind >>Of, right, >>Because if I say it's, it's good to be federated, it comes with its own flaws. But if I say, if it's good to be decentralized, then I'm the, the guy to choke, right? And in my role, I'm the guy to choke. So I've selectively tried to be a pseudo federated organization, where do I do have folks reporting into our organization, but they sit close to the line of business because the business understands data better. We are working with them hand in glove. We have dedicated teams that support them. And our problem is we are also regional. We are 200 countries. So the regional needs are very different than our us needs. Majority of the organizations that you probably end up talking to have like very us focused, 50 per more than 50% of our revenue is international. So we do, we are dealing with people who are international, their needs for data, their needs for quality and their needs for the, the delivery of those analytics and the data is completely different. And so we have to be a little bit more closer to the business than traditionally. Some, some organizations feel that they need >>To, is there need for the underlying infrastructure and the operational details that as diverse, or is that something that you bring standardization to the, >>So the best part about this, the cloud that happened to us is exactly that, because at one point of time, I had infrastructure in one country. I had another infrastructure sitting in another country, regional teams, making different different decisions of bringing in different tools. Now I can standardize. I will say, Matillion is our standard for doing ETL work. If this is the use case, but then it gets deployed across the geographies because the cloud helps us or the cloud platform helps us to manage it. Sitting down here. I have three centers around the world, you know, Costa Rica, India, and the us. I can manage 24 7 sitting here. No >>Problem. So the underlying our infrastructure is, is global, but the data needs are dealt with locally. Yep. >>One of the pav question, I was just thinking JVE is super well positioned funds for you, which is around that business domain knowledge versus technical expertise. Cause again, early in technology journeys tend, things tend to be very technical and therefore only high end engineers can do it, but high end engineers are scar. Right? Right. And, and also, I mean, we survey our hundreds of large enterprise customers and they tell us they spend two thirds of their time doing stuff they don't really want to do like reinventing the wheel, basic data movement and the low order staff. And so if you can make those people more productive and allow them to focus on higher value problems, but also bring pseudo technical people into it. Overall, the business can go a lot faster. And the way you do that is by making it easier. That's why Matillion is a low code NOCO platform, but Jer and Western union are doing this right. I >>Mean, I can't compete with AWS and Google to hire people. So I need to find people who are smart to figure the products that we have to make them work. I don't want them to spend time on infrastructure, Adam, I don't want them to spend time on trying to manage platforms. I want them to deliver the data, deliver the results to the business so that they can build and serve their customers better. So it's a little bit of a different approach, different mindset. I used to be in consulting for 17 years. I thought I knew it all, but it changed overnight when I own all of these systems. And I'm like, I need to be a little bit more smarter than this. I need to be more proactive and figure out what my business needs rather than what just from a technology needs. It's more what the business needs and how I can deliver that needs to them. So simple analogy, you know, I can build the best architecture in the world. It's gonna cost me an arm and leg, but I can't drive it because the pipeline is not there. So I can have a Ferrari, but I can't drive it. It's still capped at 80, 80 miles an hour. So rather than spend, rather than building one Ferrari, let me have 10 Toyotas or 10 Fs, which will go further along and do better for my cus my, for my customers. >>So how do you see this whole, we hearing about the data cloud. We hear about the marketplace, data products now, application development inside the data cloud. How do you see that affecting not so much the productivity of the data teams. I don't wanna necessarily say, but the product, the value that, that customers like you can get out >>Data. So data is moving closer to the business. That's the value I see, because you are injecting the business and you're injecting the application much more closer to the data because it, in the past, it was days and days of, you know, churn the data to actually clear results. Now the data has moved much closer. So I have a much faster turnaround time. The business can adapt and actually react much, much faster. It took us like 16 to 30 days to deliver, you know, data for marketing. Now I can turn it down in four hours. If I see something happening, I'll give you an example. The war in Ukraine happened. Let is shut down operations in Russia. Ukraine is cash swamp. There's no cash in Ukraine. We have cash. We roll out campaign, $0 money, transferred to Ukraine within four hours of the world going on. That's the impact that we have >>Massive impact. That's huge, especially with such a macro challenge going on, on the, in, in the world. Thank you so much for sharing the Matillion snowflake partnership story, how it's helping Western union really transform into a data company. We love hearing stories of organizations that are 170 years old that have always really been technology focused, but to see it come to life so quickly is pretty powerful. Guys. Thank you so much for your time. Thanks >>Guys. Thank you, having it. Thank >>You >>For Dave Velante and our guests. I'm Lisa Martin. You're watching the cubes live coverage of snowflake summit 22 live from Las Vegas. Stick around. We'll be back after a short break.

>>Hey everyone. Welcome to this cube conversation featuring branch. I'm your host. Lisa Martin, my guest joining me today is Mike nav Bosnia, the VP of sales at branch. Michael. Welcome to the cube. Great to have you here. >>Thanks Lisa. Really good to be here. >>So talk to us about branch, give the audience an overview of the technology, the mission of the company. What is it that you guys do? >>Yeah, certainly. Uh, thank you for the opportunity. Um, so we are founded in 2014 and the mission is to create a more open connected and relevant digital ecosystem. And of course that's very kind of top level. And so what does that mean in terms like how do we do that? Uh, we do that in two ways. We have two, two large products. One is our mobile linking platform and this is, this is like specifically the, the thing that people click on. So you might think of like a hyperlink. We, uh, think about branch links. We want every link in the world to be a branch link. And, and why, like, why would that be helpful? Two reasons. Number one is it's gonna give the user the best experience, the most relevant experience, the fastest experience. And we're very kind of passionate about those delightful user experiences. And we'll talk more about the importance of those, um, as we go on. And then the second reason is we provide, um, great accuracy and great data in measurement. And so second product is our mobile measurement platform or measurement partnership that enables marketers to help understand what parts of their marketing are working as they buy for consumer attention and buy for consumer dollars. Um, so yeah, that's, uh, that's the mission and kind of when we were founded >>That consumer experience these days just seems to be more and more critical because one of the things that has waned thin the last two years is patients on the, on the hand of, I think all of us at some point, right? So being able to help brands deliver a seamless frictionless customer experience is table stakes for businesses in any organization. Talk to me in founded in 2014, lots of change in evolution of the business of the technology and of course of the world, since then, how has life changed for mobile modern marketers? What are some of the key challenges that they have that they come to a branch and say help us fix these? >>Yeah, that's a, that's a, that's the question right. Is, is if you, if you zoom out, if you zoom out and take just the 10,000 foot view, uh, and go back in time, like marketing was certainly simpler, right? And with each new platform creates new opportunities for marketers to reach their consumers in new ways, but also new complexity to master those and also prioritize which ones are marketers going to invest in, versus which ones are they not going to invest in. And today the, the platform that is, is, you know, the top of the heap here of course, is the mobile phone. It's where the attention is the, the insights, the data that are out there, your audience is more than well aware of, of those things. And so these are where the eyeballs are, but within the mobile phone, you have a whole host of wall gardens and new ones pop up all the time. >>The latest kind of biggest has been TikTok, but you can kind of go backwards from there and you can also go forward from where we stand today. That is not gonna be the last one. And each of these are platforms in of themselves for marketers to go reach their consumers. So two challenges for marketers. Number one, how do you reach your consumer in those places and also ensure a, a consistent, amazing brand experience. Cause this all kind of started with you mentioning the importance of that user experience. And when we're talking about mobile phone, tens of seconds matter, honestly, hundreds of seconds matter. And, and there's, there's, you know, data and studies that show that you get delays or you get a little bit of friction and your conversion rate will, will plummet. And so branch is that linking infrastructure to ensure that regardless of the platform you're trying to reach your consumer on, which is getting more and more complex and there more and more of them that you can trust, you're gonna get the best user experience without having to dedicate a ton of engineering resources. Uh, and then second that you're gonna have insights. You're gonna have the best available insights to how those campaigns, how those endeavors are performing to help you then prioritize and make informed decisions for your next set of campaigns. >>And that's so important as we've seen marketing evolve so much in recent years to become really a science. So being able to deliver those insights to organizations, I imagine across any industry on how campaigns are performing, where they're losing people, how they can facilitate conversions faster with less friction is, is a competitive advantage for any business, right? >>Yeah, hundred percent. >>Talk to me about, gimme a customer example, like walk me through a customer, any industry, one that you think really articulates your value and, and kind of walk me through that experience. If I'm engaging with this brand on my mobile phone, maybe my laptop, um, different devices, how, how does all that work together to be able to deliver that seamless experience to the consumer? >>Yeah. I love that you mentioned different devices. Um, that one's, that one's huge. Um, so yeah, let's talk through a customer example. Uh I'll, I'll, I'll just suffice to say that this is, um, a customer that, uh, does, you know, uh, sends music, uh, to, to, you know, tens of millions, hundreds of millions of phones worldwide. And, um, they were using actually, uh, a competitive platform in the marketplace and they cared very deeply about having a delightful user experience in every single channel that they could have it in. And they wanted to see if, if branch was a stronger user experience and to do this on the left hand side, you have all the different places you might wanna reach your consumers. And so let's think about some of those. Maybe let's think about it in the music industry. Let's say I've got a great playlist that I know you love Lisa. >>And I, I share it with you and let's say, I share it via text message and you click on it. What is that user experience like? Let's say I share it on my Instagram feed and you click on it. What is that user experience like? Let's say I send it to you in an email. These are all different platforms that you could click on this link. And this music platform wants you to have the best possible user experience. Now over on the right hand side, let's talk about all the different devices and technology you could interact with that link on your iPhone, but maybe you're not an iPhone user. Maybe you are interacting with that on a Samsung. Maybe you're on an older version of Android. All of these things actually matter because, because in the deep technicals of how these links work and how these walled gardens operate, um, they're making changes and all of those changes can cause breakage. >>Okay, this was all the background. Now the actual story. So head-to-head test one of my favorite, most unique companies that, that illustrates the importance of user experience out there is a company called applause. Applause literally, um, puts together a user panel of hundreds, if not thousands of users with all these different phone makeup, because they recognize that it's really hard to do this type of testing in the wild. If you're just a brand like, are you gonna have hundreds of different phones and lots of different setups in your lab? So they do this for you with a user panel and they put branch links head to head with the competitor link in all of these different spaces. And they said, we want our panel to click on link a and then write down specifically, how long did it take? And they actually have like a timer. >>Um, did it, you get the expected outcome? Did it take you to the place that you expected? And just generally other things about that experience and when rated head to head, they put it in green, yellow and red buckets. Branch was getting a green rating over 85% of the time. And the competitor was getting a green rating under 20% of the time. And in that difference for this music company was downstream metrics that really mattered to them such as consumption of the media user happiness conversion to free trials and conversion to paid trials. And so by having that, that better foundation, better user experience, there was massive ROI that over the course of this six month test, we, we proved out and then, you know, initiated a multi-year partnership. >>That's a significant difference, 85% to less than 20 when you're in customer conversations. What are some of the key differentiators that you talk about when you're talking about and why its of the competitors out there? >>Certainly we start there, right? So like we, we care most about that user experience, right? So if you, when we, when we get over to the measurement side, which, which I hope we get to, um, measurement is all about telling you did the conversion happen and where should you give credit to? Right. And the conversion could be an event, could be streaming. A song could be a purchase, whatever, whatever a conversion is for you, but conversions don't happen if you don't have a strong user experience, you know? And so you can't measure a conversion that didn't take place. And so in terms of our differentiator, we start with that user experience. And so we talk about within the mobile ecosystem, we've identified 6,000 edge cases. Um, these are Instagram builds on a certain cell phone, maybe an older operating system. So 6,000 cases that you as a marketer should care about, but you don't necessarily want your engineering team spending time staying up to date on all of those. >>And if one of them changes, if one of 'em breaks, the big ones that are out there that people will be familiar with, of course, is we're May 25th right now on June 6th, apple will have their developer conference and they do have a history of announcing some changes there that then cause engineering teams to go running. You want branch to be that partner to, to, to know that we will run faster than anybody else and ensure that you're ahead of the pack for whatever those changes may be to ensure that that solid customer user experience that you could build upon. And then over on the measurement side, we're gonna give you best in class insights, uh, because one we're giving you better conversions, but two, we have a best in class fraud platform, we have best in class data to increase yours. We have very high accuracy across 700 ad networks. Um, and we're gonna shield you from these systematic disruptions that happen in the digital space. >>So we talked about the mobile linking plant from the MFP. Let's now talk about the, uh, mobile measurement program. The MMP give because measurement is so critical for organizations to be able to understand, see that data and act on it in real time. How does branch help? >>Yes, certainly. So on the mobile measurement platform side, um, generally when people think about this and they talk about this, they, they, they're largely talking about paid ads and, and we think paid ads are, are very important. And we do, we, we do talk about that quite a bit. And so with that, you are spending money with a lot of the big networks. So Google, Facebook, apple, et cetera. And we enable you to, to get an insight into which network was truly the last touch, because when you're dealing with self attributing networks, they tend to all take credit for them. So, Hey, yeah, Facebook, we saw this user Google. We also saw this user and they, they both take credit. And so we give you some insight into where was that touchpoint in kind of a series of touchpoints to enable you to like assign credit as you see fit, uh, for future decisions. >>And then beyond the self attributing networks, there's hundreds of other networks that you should be testing like you should consider to be testing. Cuz like, to me, this is the, the competitive advantage for marketers is the ability to find valuable users where your competition is not. And in general, if you are, you know, one big retailer and another big retailer, you're both spending on the same keywords on Google or the same things on Facebook. But if you could find some kind of niche networks for your audience and branch is able enables you to one test that with confidence and two, the smaller networks tend to, you know, have maybe a little bit more susceptible to some fraud and so have confidence that there is gonna be fraud blocking, should it pop up? Um, you know, that is gonna increase yours and increase your, your decision making over time. >>That it, the technology sense. Fascinating. I wish we had more time. I would love to dig in this deeper, but you've done a great job of articulating the value of branch. What it is that you guys do, uh, the value in it for customers in many industries. I love the music example. Thank you so much, Mike, for joining me today and sharing these insights into branch and the website is branch.io. >>Yes, that's correct. >>All right, folks can go there for more information. Awesome, Mike. Thanks. Thanks so much for your time. >>Thank you. >>Lisas. I'm Lisa Martin, you watching this.

we're back at vemma in 2022 we're here at the aria hotel in las vegas this is thecube's continuous coverage we're day two welcome to the cxo session we have ceo cto cso chief strategy officer brett diamond is the ceo justin jardina is the cto and dante orsini is the chief strategy officer for 11 11 systems recently named i guess today the impact cloud service provider of the year congratulations guys welcome thank you welcome back to the cube great to see you again thank you great likewise so okay brett let's start with you tell give us the overview of 11 1111 uh your focus area talk about the the the island acquisition what that what that's all about give us the setup yeah so we started 11-11 uh really with a focus on taking the three core pillars of our business which are cloud connectivity and security bring them together into one platform allowing a much easier way for our customers and our partners to procure those three solution sets through a single company and really focus on uh the three main drivers of the business uh which you know have a litany of other services associated with them under each platform okay so so justin cloud connectivity and security they all dramatically changed in march of 2020 everybody had to go to the cloud the rather rethink the network had a secure remote worker so what did you see from a from a cto's perspective what changed and how did 11 respond sure so early on when we built our cloud even back into 2008 we really focused on enterprise great features one of which being uh very flexible in the networking so we found early on was that we would be able to architect solutions for customers that were dipping their toe in the cloud and set ourselves apart from some of the vendors at the time so if you fast forward from 2008 until today we still see that as a main component for iaz and draz and the ability to start taking into some of the things brett talked about where customers may need a point-to-point circuit to offload data connectivity to us or develop sd-wan and multi-cloud solutions to connect to their resources in the cloud in my opinion it's just the natural progression of what we set out to do in 2008 and to couple that with the security um if you think about what that opens up from a security landscape now you have multiple clouds you have different ingress and egress points you have different people accessing workloads in each one of these clouds so the idea or our idea is that we can layer a comprehensive security solution over this new multi-cloud networking world and then provide visibility and manageability to our customer base so what does that mean specifically for your customers because i mean we saw obviously a rapid move toward endpoint um cloud security uh identity access you know people really started thinking rethinking that as opposed to trying to just you know build a moat around the castle right um what does that mean for for your customer you take care of all that you partner with whomever you need to partner in the ecosystem and then you provide the managed service how does that work right it does and that's a great analogy you know we have a picture of a hamburger in our office exploded with all the components and they say a good security policy is all the pieces and it's really synonymous with what you said so to answer your question yes we have all that baked in the platform we can offer managed services around it but we also give the consumer the ability to access that data whether it's a ui or api so dante i know you talk to a lot of customers all you do is watch the stock market go like this and like that you say okay the pandemic drove all these but but when you talk to csos and customers a lot of things are changing permanently first of all they were forced to march to digital when previously they were like we'll get there i mean a lot of customers were let's face it i mean some were serious about it but many weren't now if you're not a digital business you're out of business what have you seen when you talk to customers in terms of the permanence of some of these changes what are they telling you well i think we go through this for ourselves right the business continues to grow you've got tons of people that are working remotely and that are going to continue to work remotely right as much as we'd like to offer up hybrid workspace and things like that some folks are like hey i've worked it out i'm working out great from home right and also i think what justin was saying also is we've seen time go on that operating environment has gotten much more complex you've got stuff in the data center stuff it's somebody's you know endpoint you've got various different public clouds different sas services right that's why it's been phenomenal to work with veeam because we can protect that data regardless of where it exists but when you start to look at some of the managed security services that we're talking about we're helping those csos you get better visibility better control and take proactive action against the infrastructure um when we look at threat mitigation and how to actually respond when when something does happen right and i think that's the key because there's no shortage of great security vendors right but how do you tie it all together into a single solution right with a vendor that you can actually partner with to help secure the environment while you go focus on the things they're more strategic to the business i was talking to jim mercer at um red hat summit last week he's an idc analyst and he said we did a survey i think it was last summer and we asked customers to your point about there's no shortage of security tools how do you want to buy your security and you know do you want you know best to breed bespoke tools and you sort of put it together or do you kind of want your platform provider to do it now surprisingly they said platform provider the the problem is that's aspirational for a lot of platforms providers so they've got to look to a managed service provider so brett talk about the the island acquisition what green cloud is how that all fits together so we acquired island and green cloud last year and the reality is that the people at both of those companies and the technology is what drove us to making those acquisitions they were the foundational pieces to eleven eleven uh obviously the things that justin has been able to create from an automation and innovation perspective uh at the company is transforming this business in a litany of different ways as well so those two acquisitions allow us at this point to take a cloud environment on a geographic footprint not only throughout the us but globally uh have a security product that was given to us from from the green cloud acquisition of cascade and add-on connectivity to allow us to have all three platforms in one all three pillars so i like 11 11 11 is near and dear to my heart i am so where'd the name come from uh everybody asked me this question i think five times a day so uh growing up as a kid everyone in my family would always say 11 11 make a wish whenever you'd see it on the clock and uh during coven we were coming up with a new name for the business my daughter looked at the microwave said dad it's 11 11. make a wish the reality was though i had no idea why i'd been doing it for all that time and when you look up kind of the background origination derivation of the word uh it means the time of day when everything's in line um and when things are complex especially with running all the different businesses that we have aligning them so that they're working together it seemed like a perfect man when i had the big corner office at idc i had my staff meetings at 11 11. because the universe was aligned and then the other thing was nobody could forget the time so they gave him 11 minutes to be there now you'll see it all the time even when you don't want to so justin we've been talking a lot about ransomware and and not just backup but recovery my friend fred moore who you know coined the phrase backup is one thing recovery is everything and recovery time network speeds and and the like are critical especially when you're thinking cloud how are you architecting recovery for your clients maybe you could dig into that a little bit sure so it's really a multitude of things you know you mentioned ransomware seeing the ransomware landscape evolve over time especially in our business with backup and dr it's very singular you know people protecting against host nodes now we're seeing ransomware be able to get into an environment land and expand actually delete backups target backup vendors so the ransomware point i guess um trying to battle that is a multi-step process right you need to think about how data flows into the organization from a security perspective from a networking perspective you need to think about how your workloads are protected and then when you think about backups i know we're at veeam vmon now talking about veeam there's a multitude of ways to protect that data whether it's retention whether it's immutability air gapping data so while i know we focus a lot sometimes on protecting data it's really that hamburg analogy where the sum of the parts make up the protection so how do you provide services i mean you say okay you want immutability there's a there's a line item for that um you want faster or you know low rpo fast rto how does that all work for as a customer what what am i buying from you is it just a managed service we'll take care of everything platinum gold silver or is it if if you don't mind so i'm glad you asked that question because this is something that's very unique about us years ago his team actually built the ip because we were scaling at such an incredible rate globally through all our joint partners with veeam that how do we take all the intelligence that we have in his team and all of our solution architects and scale it so they actually developed a tool called catalyst and it's a pre-sales tool it's an application you download it you install it it basically takes a snapshot of your environment you start to manipulate the data what are you trying to do dave are you trying to protect that data are you backing up to us are you trying to replicate for dr purposes um you know what are you doing for production or maybe it's a migration it analyzes the network it analyzes all your infrastructure it helps the ses know immediately if we're a feasible solution based on what you are trying to do so nobody in the space is doing this and that's been a huge key to our growth because the channel community as well as the customer they're working with real data so we can get past all the garbage and get right to what's important for them for the outcome yeah that's huge who do you guys sell to is it is it more mid-sized businesses that maybe don't have the large teams is it larger enterprises who want to complement to their business is it both well i would say with the two acquisitions that we made the go-to-market sales strategies and the clientele were very different when you look at green cloud they're selling predominantly wholesale through msps and those msps are mostly selling to smbs right so we covered that smb market for the most part through our acquisition of green cloud island on the other hand was more focused on selling direct inbound through vars through the channel mid enterprise big enterprise so really those two acquisitions outside of the ip that we got from the systems we have every single go-to-market sale strategy and we're aligned from smb all the way up to the fortune 500. i heard a stat a couple months ago that that less than 50 of enterprises have a sock it blew me away and you know even small businesses need one they may not be able to afford but certainly a medium size or larger business should have some kind of sock is it does that stat jive with what you're seeing in the marketplace 100 if that's true the need for a managed service like this is just it's going to explode it is exploding yeah i mean 100 right there is zero unemployment in the cyberspace right just north america alone there's about a million or so folks in that space and right now you've got about 600 000 open wrecks just in north america right so earlier we talked about no shortage of tools right but the shortage of head count is a significant challenge big time right most importantly the people that you do have on staff they've got alert fatigue from the tools that they do have that's why you're seeing this massive insurgence in the managed security services provider lack of talent is number one challenge for csos that's what they'll tell you and there's no end in sight to that and it's you know another tool and and it's amazing because you see security companies popping up all the time billion dollar evaluations i mean lacework did a billion dollar raise and so so there's no shortage of funding now maybe that'll change you know with the market but i wanted to turn our attention to the keynotes this morning you guys got some serious love up on stage um there was a demo uh it was a pretty pretty cool demo fast recovery very very tight rpo as i recall it was i think four minutes of data loss is that right was that the right knit stat i was happy it wasn't zero data loss because there's really you know no such thing uh but so you got to feel good about that tell us about um how that all came about your relationship with with veeam who wants to take it sure i can i can take a step at it so one of the or two of the things that i'm um most excited about at least with this vmon is our team was able to work with veeam on that demo and what that demo was showing was some cdp-based features for cloud providers so we're really happy to see that and the reason why we're happy to see that is that with the veeam platform it's now given the customers the ability to do things like snapshot replication cdp replication on-prem backup cloud backup immutability air gap the list goes on and on and in our opinion having a singular software vendor that can provide all that through you know with a cloud provider on prem or not is really like the icing on the cake so for us it's very exciting to see that and then also coupled with a lot of the innovation that veeam's doing in the sas space right so again having that umbrella product that can cover all those use cases i'll tell you if you guys can get a that was a very cool demo if we can get a youtube of that that that demo i'll make sure we put it in the the show notes and uh of this video or maybe pop it into one of the blogs that we write about it um so so how you guys feel i mean this is a new chapter for you very cool with a couple of acquisitions that are now the main mainspring of your strategy so the first veeam on in a couple years so what's the vibe been like for you what's the nighttime activity the customer interaction i know you guys are running a lot of the back end demos so you're everywhere what's the what's the vibe like at veeamon and how does it feel to be back look at that one at dante as far as yeah you got a lot of experience here yeah let me loose on this one dave i'm like so excited about this right it's been it's been far too long to get face to face again and um veeam always does it right and i think that uh for years we've been back-ending like all the hands-on lab infrastructure here but forget about that i think the part that's really exciting is getting face-to-face with such a great team right we have phenomenal architects that we work with at veeam day in and day out they put up with us pushing them pushing and pushing them and together we've been able to create a lot of magic together right but i think it's you can't replace the human interaction that we've all been starving for for the last two years but the vibe's always fantastic at veeam if you're going to be around tonight i'll be looking forward to enjoying some of that veeam love with you at the after party yeah that's well famous after parties we'll see if that culture continues i have a feeling it will um brett where do you want to take 11 11. a new new phase in all of your careers you got a great crew out here it looks like i i love that you're all out and uh make some noise here people let's hear it all right let's see you this is the biggest audience we've had all week where do you want to take 11 11. i think you know if uh if you look at what we've done so far in the short six months since the acquisitions of green cloud and ireland obviously the integration is a key piece we're going to be laser focused on growing organically across those three pillars we've got to put more capital and resources into the incredible ip like i said earlier that just and his team have created on those front ends the user experience but you know we made two large acquisitions obviously mna is a is a key piece for us we're going to be diligent and we're probably going to be very aggressive on that front as well to be able to grow this business into the global leader of cloud connectivity and security and i think we've really hit a void in the industry that's been looking for this for a very long time and we want to be the first ones to be able to collaborate and combine those three into one when the when the cloud started to hit the steep part of the s-curve kind of early part of the last decade people thought oh wow these managed service providers are toast the exact opposite happened it created such a tailwind and need for consistent services and integration and managed services we've seen it all across the stack so guys wish you best of luck congratulations on the acquisitions thank you uh hope to have you back soon yeah thank you around the block all right keep it right there everybody dave vellante for the cube's coverage of veeamon 2022 we'll be right back after this short break

(pleasant music) >> We're back at Veeamon 2022. We're here at the Aria hotel in Las Vegas. This is theCube's continuous coverage. We're in day two. Welcome to the CXO session. We have CEO, CTO, CSO, chief strategy officer. Brett Diamond is the CEO, Justin Giardina is the CTO, and Dante Orsini is the chief strategy officer for 11:11 Systems recently named, I guess today, the impact cloud service provider of the year. Congratulations, guys. Welcome to theCube. Welcome back to theCube. Great to see you again. >> Thank you. >> Great. >> Likewise. >> Thanks for having us. Okay, Brett, let's start with you. Give us the overview of 11:11, your focus area, talk about the Island acquisition, what that's all about, give us the setup. >> Yeah, so we started 11:11, really, with a focus on taking the three core pillars of our business, which are cloud, connectivity, and security, bring them together into one platform, allowing a much easier way for our customers and our partners to procure those three solution sets through a single company and really focus on the three main drivers of the business, which, you know, have a litany of other services associated with them under each platform. >> Okay, so Justin, cloud connectivity and security, they all dramatically changed in March of 2020. Everybody had to go to the cloud, had to rethink the network, had to secure remote workers. So what did you see, from a CTO's perspective, what changed and how did 11:11 respond? >> Sure, so early on, when we built our cloud, even back into 2008, we really focused on enterprise grade features, one of which being very flexible in the networking. So we found early on was that we would be able to architect solutions for customers that were dipping their toe in the cloud and set ourselves apart from some of the vendors at the time. So if you fast forward from 2008 until today, we still see that as a main component for IaaS and DRaaS and the ability to start taking into some of the things Brett talked about, where customers may need a point to point circuit to offload data connectivity to us, or develop SD-WAN and multi-cloud solutions to connect to their resources in the cloud. In my opinion, it's just the natural progression of what we set out to do in 2008. And to couple that with the security, if you think about what that opens up from a security landscape, now you have multiple clouds, you have different ingress and egress points, you have different people accessing workloads in each one of these clouds, so the idea or our idea is that we can layer a comprehensive security solution over this new multi-cloud networking world and then provide visibility and manageability to our customer base. >> So what does that mean specifically for your customers? Because, I mean, we saw obviously a rapid move toward end point, cloud security, identity access. You know, people really started rethinking that as opposed to trying to just, you know, build a moat around the castle. >> Right. >> What does that mean for your customer? You take care of all that? You partner with whomever you need to partner in the ecosystem and then you provide the managed service? How does that work? >> Right. It does and that's a great analogy. You know, we have a picture of a hamburger in our office, exploded with all the components and they say, a good security policy has all the pieces and it's really synonymous with what you said. So to answer your question, yes. We have all that baked in the platform. We can offer managed services around it, but we also give the consumer the ability to access that data, whether it's a UI or API. >> So Dante, I know you talked to a lot of customers. All you do is watch the stock market go like this and like that and you say, okay, the pandemic drove all these, but when you talk to CISOs and customers, a lot of things are changing permanently. First of all, they were forced to march to digital when previously, they were like, eh, we'll get there. I mean, a lot of customers were. Let's face it. I mean, some were serious about it, but many weren't. Now, if you're not a digital business, you're out of business. What have you seen when you talk to customers in terms of the permanence of some of these changes? What are they telling you? >> Well, I think, you know, we go through this ourselves, right? The business continues to grow. You've got tons of people that are working remotely and they are going to continue to work remotely, right? As much as we'd like to offer up hybrid workspace and things like that, some folks are like, hey, I've worked it out. I'm working out great from home, right? And also, I think what Justin was saying also is, as we've seen time go on, that operating environment has gotten much more complex. You've got stuff in the data center, stuff in somebody's, you know, endpoint, you've got various different public clouds, different SAS services, right? That's why it's been phenomenal to work with Veeam because we can protect that data regardless of where it exists. But when you start to look at some of the managed security services that we're talking about, we're helping those CSOs, you know, get better visibility, better control, and take proactive action against the infrastructure when we look at threat mitigation and how to actually respond when something does happen, right? And I think that's the key because there's no shortage of great security vendors, right? But how do you tie it all together into a single solution, right, with a vendor that you can actually partner with to help secure the environment while you go focus on the things that are more strategic to the business? >> I was talking to Jim Mercer at Red Hat Summit last week. He's an IDC analyst and we did a survey, I think it was last summer, and we asked customers to your point about, there's no shortage of security tools. How do you want to buy your security? And, you know, do you want, you know, best to breed bespoke tools and you sort of put it together or do you kind of want your platform provider to do it? Now surprisingly, they said platform provider. The problem is, that's aspirational for a lot of platform providers, so they got to look to a managed service provider. So Brett, talk about the Island acquisition, what Green Cloud is, how that all fits together. >> So we acquired Island and Green Cloud last year and the reality is, the people at both of those companies and the technology is what drove us to making those acquisitions. They were the foundational pieces to 11:11. Obviously, the things that Justin has been able to create from an automation and innovation perspective at the company is transforming this business in a litany of different ways, as well. So, those two acquisitions allow us at this point to take a cloud environment on a geographic footprint, not only throughout the US but globally, have a security product that was given to us from the Green Cloud acquisition of Cascade, and add on connectivity to allow us to have all three platforms in one, all three pillars in one. >> So I like 11:11. 11:11 is near and dear to my heart. So where'd the name come from? >> Everybody asked me this question, I think, five times a day. So growing up as a kid, everyone in my family would always say 11:11 make a wish whenever you'd see it on the clock. And during COVID, we were coming up with a new name for the business. My daughter looked at the microwave, said, dad, it's 11:11, make a wish. The reality was though, I had no idea why I'd been doing it for all that time and when you look up kind of the background origination, derivation of the word, it means the time of day when everything's in line and when things are complex, especially with running all the different businesses that we have, aligning them so that they're working together, it seemed like the perfect thing >> So when I had the big corner office at IDC, I had my staff meetings at 11:11. >> Yep. >> Because the universe was aligned and then the other thing was, nobody could forget the time. So they gave me 11 minutes to be there, so they were never late. >> And now you'll see it all the time, even when you don't want to. (chuckles) >> So Justin, we've been talking a lot about ransomware and not just backup, but recovery. My friend, Fred Moore, who, you know, coined the phrase backup is one thing, recovery is everything, and recovery time, network speeds and the like are critical, especially when you're thinking cloud. How are you architecting recovery for your clients? Maybe you could dig into that a little bit. >> Sure. So it's really a multitude of things. You know, you mention ransomware. Seeing the ransomware landscape evolve over time, especially in our business with backup NDR, is very singular, you know, people protecting against host nodes. Now we're seeing ransomware be able to get into an environment, land and expand, actually delete backups, target backup vendors. So the ransomware point, I guess, trying to battle that is a multi-step process, right? You need to think about how data flows into the organization from a security perspective, from a networking perspective, you need to think about how your workloads are protected, and then when you think about backups, I know we're at Veeamon now talking about Veeam, there's a multitude of ways to protect that data, whether it's retention, whether it's immutability, air gapping data. So, while I know we focus a lot sometimes on protecting data, it's really that hamburger analogy where the sum of the parts make up the protection. >> So how do you provide services? I mean, do you say, okay, do you want immutability? There's a line item for that. You want low RPO, fast RTO? How does that all work as a customer? What am I buying from you? Is it just a managed service? We'll take care of everything, platinum, gold, silver, or is it? >> If you don't mind, so I'm glad you asked that question because this is something that's very unique about us. Years ago, his team actually built the IP because we were scaling at such an incredible rate globally through all our joint partners with Veeam that, how do we take all the intelligence that we have and his team and all of our solution architects and scale it? So they actually developed a tool called Catalyst, and it's a pre-sales tool. It's an application. You download it, you install it. It basically takes a snapshot of your environment. You start to manipulate the data. What are you trying to do, Dave? Are you trying to protect that data? Are you backing up to us? Are you trying to replicate it for DR purposes? You know, what are you doing for production, or maybe it's a migration? It analyzes the network. It analyzes all your infrastructure. It helps the SEs know immediately if we're a feasible solution based on what you are trying to do. So, nobody in the space is doing this and that's been a huge key to our growth because the channel community, as well as the customer, they're working with real data. So we can get past all the garbage, you get right to what's important for them for the outcome. >> Yeah, that's huge. Who do you guys sell to? Is it more mid-size businesses that maybe don't have the large teams? Is it larger enterprises who want to compliment to their business? Is it both? >> Well, I would say with the two acquisitions that we made to go to market sales strategies and the clientele were very different, when you look at Green Cloud, they're selling predominantly wholesale through MSPs and those MSPs are mostly selling to SMBs, right? So we covered that SMB market for the most part through our acquisition of Green Cloud. Island, on the other hand, was more focused on selling direct, inbound, through VARs through the channel, mid-enterprise, big enterprise. So really, those two acquisitions outside of the IP that we got from the systems, we have every single go to market sales strategy and we're aligned from SMB all the way up to the Fortune 500. >> I heard a stat a couple months ago that less than 50% of enterprises have a SAQ. That blew me away. And, you know, even small businesses need one. They may not be able to afford, but there's certainly a medium size or a larger business should have some kind of SAQ. Does that stat jive with what you're seeing in the marketplace? >> A hundred percent. >> If that's true, the need for a managed service like this, it's going to explode. It is exploding, I mean. >> Yeah, I mean, a hundred percent, right? There is zero unemployment in the cyberspace, right? Just North America alone, there's about a million or so folks in that space and right now you've got about 600,000 open recs just in North America, right? So earlier, we talked about no shortage of tools, right? But the shortage of headcount is a significant challenge, big time, right? Most importantly, the people that you do have on staff, they've got alert fatigue from the tools that they do have. That's why you're seeing this massive surgence in the managed security services provider. >> Lack of talent is number one challenge for CISOs. That's what they'll tell you and there's no end in sight to that. And it's, you know, another tool and it's amazing 'cause you see security companies popping up all the time. I mean, billion dollar valuations, I mean, Lacework did a billion dollar raise. And so, there's no shortage of funding. Now, maybe that'll change, you know, with the market but I wanted to turn our attention to the keynotes this morning. You guys got some serious love up on stage. There was a demo. It was a pretty cool demo, fast recovery, very tight RPO, as I recall. It was, I think, four minutes of, of data loss? Is that right? Is that the right stat? I was happy it wasn't zero data loss 'cause there's really, you know, no such thing, but so you got to feel good about that. Tell us about how that all came about, your relationship with Veeam. Who wants to take it? >> Sure, I can take a stab at it. So two of the things that I'm most excited about, at least with this Veeamon, is our team was able to work with Veeam on that demo, and what that demo was showing was some CDP based features for cloud providers. So we're really happy to see that and the reason why we're happy to see that is that with the Veeam platform, it's now given the customers the ability to do things like snapshot replication, CDP replication, on-prem backup, cloud backup, immutability air gap, the list goes on and on. And in our opinion, having a singular software vendor that can provide all that, you know, with a cloud provider on-prem or not is really like, the icing on the cake. So for us, it's very exciting to see that, and then also coupled with a lot of the innovation that's Veeam's doing in the SAS space, right? So again, having that umbrella product that can cover all those use cases. >> I'll tell you, that was a very cool demo. If you can get a YouTube of that demo, I'll make sure we put it in the show notes of this video or maybe pop it into one of the blogs that we write about it. So, how do you guys feel? I mean, this is a new chapter for you. Very cool, with a couple of acquisitions that are now the main spring of your strategy, so the first Veeamon in a couple years. So what's the vibe been like for you? What's the nighttime activity, the customer interaction? I know you guys are running a lot of the backend demos, so you're everywhere. What's the vibe like at Veeamon and how does it feel to be back? >> I'll give that one to Dante as far as the vibes, so far. >> Yeah, yeah, you got a lot of experience. >> Yeah, let me loose on this one, Dave. I'm like, so excited about this, right? It's been far too long to get face to face again and Veeam always does it right. And I think that for years, we've been back ending like, all the hands on lab infrastructure here, but forget about that. I think the part that's really exciting is getting face to face with such a great team, right? We have phenomenal architects that we work with at Veeam day in and day out. They put up with us, pushing them, pushing them, pushing them and together, we've been able to create a lot of magic together, right? But I think you can't replace the human interaction that we've all been starving for, for the last two years. But the vibe's always fantastic at Veeam. If you're going to be around tonight, I'll be looking forward to enjoying some of that Veeam love with you at the after party. >> Yeah, well, famous after parties. We'll see if that culture continues. I have a feeling it will. Brett, where do you want to take 11:11? New phase in all of your careers. You got a great crew out here, it looks like. I love that you're all out and, make some noise here, people. Let's hear it! (audience cheering) You see, this is the biggest audience we've had all week. Where do you want to take 11:11? >> I think, you know, if you look at what we've done so far in the short six months since the acquisitions of Green Cloud and Island, obviously the integration is a key piece. We're going to be laser focused on growing organically across those three pillars. We've got to put more capital and resources into the incredible IP, like I said earlier, that Justin and his team have created on those front ends, the user experience. But, you know, we made two large acquisitions, obviously M and A is a key piece for us. We're going to be diligent and we're probably going to be very aggressive on that front as well, to be able to grow this business into the global leader of cloud connectivity and security. And I think we've really hit a void in the industry that's been looking for this for a very long time and we want to be the first ones to be able to collaborate and combine those three into one. >> When the cloud started to hit the steep part of the S-curve, kind of early part of last decade, people thought, oh wow, these managed service providers are toast. The exact opposite happened. It created such a tailwind and need for consistent services and integration and managed services. We've seen it all across the stacks. So guys, wish you best of luck. Congratulations on the acquisitions, >> Thank you. >> And hope to have you back soon. >> Absolutely, thanks for having us. >> All right, keep it right there everybody. Dave Vellante for theCube's coverage of Veeamon 2022. We'll be right back after this short break. (pleasant music)

(upbeat music) >> Despite its 70 to $80 billion total available market, computer storage is like a small town, everybody knows everybody else. We say in the storage world, there are a hundred people, and 99 seats. Infinidat is a company that was founded in 2011 by storage legend, Moshe Yanai. The company is known for building products with rock solid availability, simplicity, and a passion for white glove service, and client satisfaction. Company went through a leadership change recently, in early this year, appointed industry vet, Phil Bullinger, as CEO. It's making more moves, bringing on longtime storage sales exec, Richard Bradbury, to run EMEA, and APJ Go-To-Market. And just recently appointed marketing maven, Eric Hertzog to be CMO. Hertzog has worked at numerous companies, ranging from startups that were acquired, two stints at IBM, and is SVP of product marketing and management at Storage Powerhouse, EMC, among others. Hertzog has been named CMO of the year as an OnCon Icon, and top 100 influencer in big data, AI, and also hybrid cloud, along with yours truly, if I may say so. Joining me today, is the newly minted CMO of Infinidat, Mr.Eric Hertzog. Good to see you, Eric, thanks for coming on. >> Dave, thank you very much. You know, we love being on theCUBE, and I am of course sporting my Infinidat logo wear already, even though I've only been on the job for two weeks. >> Dude, no Hawaiian shirt, okay. That's a pretty buttoned up company. >> Well, next time, I'll have a Hawaiian shirt, don't worry. >> Okay, so give us the backstory, how did this all come about? you know Phil, my 99 seat joke, but, how did it come about? Tell us that story. >> So, I have known Phil since the late 90s, when he was a VP at LSA of Engineering, and he had... I was working at a company called Milax, which was acquired by IBM. And we were doing a product for HP, and he was providing the subsystem, and we were providing the fiber to fiber, and fiber to SCSI array controllers back in the day. So I met him then, we kept in touch for years. And then when I was a senior VP at EMC, he started originally as VP of engineering for the EMC Isilon team. And then he became the general manager. So, while I didn't work for him, I worked with him, A, at LSA, and then again at EMC. So I just happened to congratulate him about some award he won, and he said "Hey Herzog, "we should talk, I have a CMO opening". So literally happened over LinkedIn discussion, where I reached out to him, and congratulate him, he said "Hey, I need a CMO, let's talk". So, the whole thing took about three weeks in all honesty. And that included interviewing with other members of his exec staff. >> That's awesome, that's right, he was running the Isilon division for awhile at the EMC. >> Right. >> You guys were there, and of course, you talk about Milax, LSA, there was a period of time where, you guys were making subsystems for everybody. So, you sort of saw the whole landscape. So, you got some serious storage history and chops. So, I want to ask you what attracted you to Infinidat. I mean, obviously they're a leader in the magic quadrant. We know about InfiniBox, and the petabyte scale, and the low latency, what are the... When you look at the market, you obviously you see it, you talk to everybody. What were the trends that were driving your decision to join Infinidat? >> Well, a couple of things. First of all, as you know, and you guys have talked about it on theCUBE, most CIOs don't know anything about storage, other than they know a guy got to spend money on it. So the Infinidat message of optimizing applications, workloads, and use cases with 100% guaranteed availability, unmatched reliability, the set and forget ease of use, which obviously AIOps is driving that, and overall IT operations management was very attractive. And then on top of that, the reality is, when you do that consolidation, which Infinidat can do, because of the performance that it has, you can dramatically free up rack, stack, power, floor, and operational manpower by literally getting rid of, tons and tons of arrays. There's one customer that they have, you actually... I found out when I got here, they took out a hundred arrays from EMC Hitachi. And that company now has 20 InfiniBoxes, and InfiniBox SSAs running the exact same workloads that used to be, well over a hundred subsystems from the other players. So, that's got a performance angle, a CapEx and OPEX angle, and then even a clean energy angle because reducing Watson slots. So, lots of different advantages there. And then I think from just a pure marketing perspective, as someone has said, they're the best kept secret to the storage industry. And so you need to, if you will, amp up the message, get it out. They've expanded the portfolio with the InfiniBox SSA, the InfiniGuard product, which is really optimized, not only as the PBA for backup perspective, and it works with all the backup vendors, but also, has an incredible play on data and cyber resilience with their capability of local logical air gapping, remote logical air gapping, and creating a clean room, if you will, a vault, so that you can then recover their review for malware ransomware before you do a full recovery. So it's got the right solutions, just that most people didn't know who they were. So, between the relationship with Phil, and the real opportunity that this company could skyrocket. In fact, we have 35 job openings right now, right now. >> Wow, okay, so yeah, I think it was Duplessy called them the best kept secret, he's not the only one. And so that brings us to you, and your mission because it's true, it is the best kept secret. You're a leader in the Gartner magic quadrant, but I mean, if you're not a leader in a Gartner magic quadrant, you're kind of nobody in storage. And so, but you got chops and block storage. You talked about the consolidation story, and I've talked to many folks in Infinidat about that. Ken Steinhardt rest his soul, Dr. Rico, good business friend, about, you know... So, that play and how you handle the whole blast radius. And that's always a great discussion, and Infinidat has proven that it can operate at very very high performance, low latency, petabyte scale. So how do you get the word out? What's your mission? >> Well, so we're going to do a couple of things. We're going to be very, very tied to the channel as you know, EMC, Dell EMC, and these are articles that have been in CRN, and other channel publications is pulling back from the channel, letting go of channel managers, and there's been a lot of conflict. So, we're going to embrace the channel. We already do well over 90% of our business within general globally. So, we're doing that. In fact, I am meeting, personally, next week with five different CEOs of channel partners. Of which, only one of them is doing business with Infinidat now. So, we want to expand our channel, and leverage the channel, take advantage of these changes in the channel. We are going to be increasing our presence in the public relations area. The work we do with all the industry analysts, not just in North America, but in Europe as well, and Asia. We're going to amp up, of course, our social media effort, both of us, of course, having been named some of the best social media guys in the world the last couple of years. So, we're going to open that up. And then, obviously, increase our demand generation activities as well. So, we're going to make sure that we leverage what we do, and deliver that message to the world. Deliver it to the partner base, so the partners can take advantage, and make good margin and revenue, but delivering products that really meet the needs of the customers while saving them dramatically on CapEx and OPEX. So, the partner wins, and the end user wins. And that's the best scenario you can do when you're leveraging the channel to help you grow your business. >> So you're not only just the marketing guy, I mean, you know product, you ran product management at very senior levels. So, you could... You're like a walking spec sheet, John Farrier says you could just rattle it off. Already impressed that how much you know about Infinidat, but when you joined EMC, it was almost like, there was too many products, right? When you joined IBM, even though it had a big portfolio, it's like it didn't have enough relevant products. And you had to sort of deal with that. How do you feel about the product portfolio at Infinidat? >> Well, for us, it's right in the perfect niche. Enterprise class, AI based software defined storage technologies that happens run on a hybrid array, an all flash array, has a variant that's really tuned towards modern data protection, including data and cyber resilience. So, with those three elements of the portfolio, which by the way, all have a common architecture. So while there are three different solutions, all common architecture. So if you know how to use the InfiniBox, you can easily use an InfiniGuard. You got an InfiniGuard, you can easily use an InfiniBox SSA. So the capability of doing that, helps reduce operational manpower and hence, of course, OPEX. So the story is strong technically, the story has a strong business tie in. So part of the thing you have to do in marketing these days. Yeah, we both been around. So you could just talk about IOPS, and latency, and bandwidth. And if the people didn't... If the CIO didn't know what that meant, so what? But the world has changed on the expenditure of infrastructure. If you don't have seamless integration with hybrid cloud, virtual environments and containers, which Infinidat can do all that, then you're not relevant from a CIO perspective. And obviously with many workloads moving to the cloud, you've got to have this infrastructure that supports core edge and cloud, the virtualization layer, and of course, the container layer across a hybrid environment. And we can do that with all three of these solutions. Yet, with a common underlying software defined storage architecture. So it makes the technical story very powerful. Then you turn that into business benefit, CapEX, OPEX, the operational manpower, unmatched availability, which is obviously a big deal these days, unmatched performance, everybody wants their SAP workload or their Oracle or Mongo Cassandra to be, instantaneous from the app perspective. Excuse me. And we can do that. And that's the kind of thing that... My job is to translate that from that technical value into the business value, that can be appreciated by the CIO, by the CSO, by the VP of software development, who then says to VP of industry, that Infinidat stuff, we actually need that for our SAP workload, or wow, for our overall corporate cybersecurity strategy, the CSO says, the key element of the storage part of that overall corporate cybersecurity strategy are those Infinidat guys with their great cyber and data resilience. And that's the kind of thing that my job, and my team's job to work on to get the market to understand and appreciate that business value that the underlying technology delivers. >> So the other thing, the interesting thing about Infinidat. This was always a source of spirited discussions over the years with business friends from Infinidat was the company figured out a way, it was formed in 2011, and at the time the strategy perfectly reasonable to say, okay, let's build a better box. And the way they approached that from a cost standpoint was you were able to get the most out of spinning disk. Everybody else was moving to flash, of course, floyers work a big flash, all flash data center, etc, etc. But Infinidat with its memory cache and its architecture, and its algorithms was able to figure out how to magically get equivalent or better performance in an all flash array out of a system that had a lot of spinning disks, which is I think unique. I mean, I know it's unique, very rare anyway. And so that was kind of interesting, but at the time it made sense, to go after a big market with a better mouse trap. Now, if I were starting a company today, I might take a different approach, I might try to build, a storage cloud or something like that. Or if I had a huge install base that I was trying to protect, and maybe go into that. But so what's the strategy? You still got huge share gain potentials for on-prem is that the vector? You mentioned hybrid cloud, what's the cloud strategy? Maybe you could summarize your thoughts on that? >> Sure, so the cloud strategy, is first of all, seamless integration to hybrid cloud environments. For example, we support Outpost as an example. Second thing, you'd be surprised at the number of cloud providers that actually use us as their backend, either for their primary storage, or for their secondary storage. So, we've got some of the largest hyperscalers in the world. For example, one of the Telcos has 150 Infiniboxes, InfiniBox SSAS and InfiniGuards. 150 running one of the largest Telcos on the planet. And a huge percentage of that is their corporate cloud effort where they're going in and saying, don't use Amazon or Azure, why don't you use us the giant Telco? So we've got that angle. We've got a ton of mid-sized cloud providers all over the world that their backup is our servers, or their primary storage that they offer is built on top of Infiniboxes or InfiniBox SSA. So, the cloud strategy is one to arm the hyperscalers, both big, medium, and small with what they need to provide the right end user services with the right outside SLAs. And the second thing is to have that hybrid cloud integration capability. For example, when I talked about InfiniGuard, we can do air gapping locally to give almost instantaneous recovery, but at the same time, if there's an earthquake in California or a tornado in Kansas City, or a tsunami in Singapore, you've got to have that remote air gapping capability, which InfiniGuard can do. Which of course, is essentially that logical air gap remote is basically a cloud strategy. So, we can do all of that. That's why it has a cloud strategy play. And again we have a number of public references in the cloud, US signal and others, where they talk about why they use the InfiniBox, and our technologies to offer their storage cloud services based on our platform. >> Okay, so I got to ask you, so you've mentioned earthquakes, a lot of earthquakes in California, dangerous place to live, US headquarters is in Waltham, we're going to pry you out of the Golden State? >> Let's see, I was born at Stanford hospital where my parents met when they were going there. I've never lived anywhere, but here. And of course, remember when I was working for EMC, I flew out every week, and I sort of lived at that Milford Courtyard Marriott. So I'll be out a lot, but I will not be moving, I'm a Silicon Valley guy, just like that old book, the Silicon Valley Guy from the old days, that's me. >> Yeah, the hotels in Waltham are a little better, but... So, what's your priority? Last question. What's the priority first 100 days? Where's your focus? >> Number one priority is team assessment and integration of the team across the other teams. One of the things I noticed about Infinidat, which is a little unusual, is there sometimes are silos and having done seven other small companies and startups, in a startup or a small company, you usually don't see that silo-ness, So we have to break down those walls. And by the way, we've been incredibly successful, even with the silos, imagine if everybody realized that business is a team sport. And so, we're going to do that, and do heavy levels of integration. We've already started to do an incredible outreach program to the press and to partners. We won a couple awards recently, we're up for two more awards in Europe, the SDC Awards, and one of the channel publications is going to give us an award next week. So yeah, we're amping up that sort of thing that we can leverage and extend. Both in the short term, but also, of course, across a longer term strategy. So, those are the things we're going to do first, and yeah, we're going to be rolling into, of course, 2022. So we've got a lot of work we're doing, as I mentioned, I'm meeting, five partners, CEOs, and only one of them is doing business with us now. So we want to get those partners to kick off January with us presenting at their sales kickoff, going "We are going with Infinidat "as one of our strong storage providers". So, we're doing all that upfront work in the first 100 days, so we can kick off Q1 with a real bang. >> Love the channel story, and you're a good guy to do that. And you mentioned the silos, correct me if I'm wrong, but Infinidat does a lot of business in overseas. A lot of business in Europe, obviously the affinity to the engineering, a lot of the engineering work that's going on in Israel, but that's by its very nature, stovepipe. Most startups start in the US, big market NFL cities, and then sort of go overseas. It's almost like Infinidat sort of simultaneously grew it's overseas business, and it's US business. >> Well, and we've got customers everywhere. We've got them in South Africa, all over Europe, Middle East. We have six very large customers in India, and a number of large customers in Japan. So we have a sales team all over the world. As you mentioned, our white glove service includes not only our field systems engineers, but we have a professional services group. We've actually written custom software for several customers. In fact, I was on the forecast meeting earlier today, and one of the comments that was made for someone who's going to give us a PO. So, the sales guy was saying, part of the reason we're getting the PO is we did some professional services work last quarter, and the CIO called and said, I can't believe it. And what CIO calls up a storage company these days, but the CIO called him and said "I can't believe the work you did. We're going to buy some more stuff this quarter". So that white glove service, our technical account managers to go along with the field sales SEs and this professional service is pretty unusual in a small company to have that level of, as you mentioned yourself, white glove service, when the company is so small. And that's been a real hidden gem for this company, and will continue to be so. >> Well, Eric, congratulations on the appointment, the new role, excited to see what you do, and how you craft the story, the strategy. And we've been following Infinidat since, sort of day zero and I really wish you the best. >> Great, well, thank you very much. Always appreciate theCUBE. And trust me, Dave, next time I will have my famous Hawaiian shirt. >> Ah, I can't wait. All right, thanks to Eric, and thank you for watching everybody. This is Dave Vellante for theCUBE, and we'll see you next time. (bright upbeat music)